Thank you Elizabeth. Good morning, everyone, both here in the room and so forth. Thank you, Lonnie, for that reminder. So good morning and really good morning. Welcome. We appreciate everybody that could join us here in the room and and online today. We think we have a very interesting and should be insightful meeting today. So as many of you know, this committee is one of several standing committees under the Board of Earth Science and Resources and this committee is the locus of all the activities of the academies related to energy and mineral resources and that includes ranges from the full life cycle of their exploration, characterization, production and recovery use, recycling, reclamation, regulation and stewardship. So the whole range. So the committee has existed for about 30 years and has been fortunate to have the support from several federal agencies and those include the DOE Geothermal Technologies Office, the DOE Office of Fossil Energy and that's both the Oil and Gas and the Coal Technologies Office and the National Institute for Occupational Safety and Health Mining Program. As a non-profit organization with a congressional academies, a congressional charter, the academy serves in a unique function in the nation's dialogue which brings expert scientific and technical information and advice into the policy and decision-making arena. In addition to the annual support of the committee's work from those agencies I mentioned, the committee couldn't function without our members who are seated here at the table with me and they're all experts that are selected by the national academies to serve and we all, committee members all serve as a volunteer in addition to their other normal routine activities and businesses. So for this meeting today, so the committee works together on planning these meetings and today I'd particularly like to acknowledge our three moderators today, David Spears, Bridget Ailing and Joel Renner who have kindly spent many hours planning the meeting and have agreed to serve as our moderators today. So the committee works with the national academy staff to identify and main an awareness of specific energy and mineral resources issues, whether addressing the subsurface characterization and management of resources or surface manifestations and legacy of their extraction or training and education of the workforce associated with the resources. The committee hosts, we typically have two meetings a year and in addition we try to then build off those meetings with some webinars or other activities and then we also work on building other projects such workshops around tables or national academies, consensus studies. The meeting today grew out of interest the committee had to focus on some advances and challenges within the geothermal energy sector. And in discussions with the geothermal technology, the DOEs checked geothermal to office, we worked on the scoping of the meeting and agreed that the strength of our committee could offer was to convene a meeting around several challenges that different industry sectors, geothermal, oil and gas and mining have in common when working to characterize and manage the subsurface. Three things we identified will each be addressed by a separate panel of experts today who will present their perspectives from across these three sectors with the idea of sharing common experience, novel solutions and a view toward future advances in areas of progress. Sue Ham who directs DOEs, geothermal technology office will be kicking off the meeting with her keynote remarks about geothermal energy and research, giving us a baseline to see the value across the sectorial and the sectional conversations. I would and these meetings are one of the richness they have is the interaction and input from everyone who participates in the meeting today. So everybody that's here should be considered themselves not an observer but a participant and so the panels are designed to leave a very significant amount of time for discussion and input in the meeting. So I mentioned the national candidates function in terms of groups like this committee which is a convening body and our ad hoc committees that conduct consensus studies like some of you, there are some copies of the consensus studies out in the hallway and but the academy works as a service to the nation on with these and dates back to 1863 and it also recognizes the nation's top engineers, scientists and medical health professionals with the National Academy of Science, National Academy of Engineering and the National Academy of Medicine. We're fortunate that this meeting was scheduled to coincide with the end of the meeting of the National Academy of Engineers here in Washington and a number of members of the NAE and specifically the energy resources engineering section of the NAE have stayed an additional day so they could be with us and participate in our meeting. So I'd like to recognize all of the NAE members that are in attendance today and some of which are on our committee and on our board but so everybody that's an NAE member if you just raise your hand, welcome, special welcome to the NAE members. And co-chairing this meeting with me is the chair of NAE section 11 which is the energy resources engineering section, Dr. Lynn Orr and many of you know Lynn was at the Department of Energy a few years ago and I actually was at the Department of Energy a few years before that and so I think that one of the things and this is that I think is evidenced here today that people don't always have the perception with what you see in the media today but that two members of two different administrations that were controlled by two different political parties can sit up here together and have a very constructive and useful but I was going to add that that Elizabeth must have been worried. So with that I'll turn this over to Lynn to make some additional opening comments. I'm not sure I can follow that. So it is a pleasure to be here and as far as I can tell I must have at least three hats here. One is the chair of section 11. That's a temporary position. We rotate the leadership of section 11, the energy resources engineering and it's largely connected with the subsurface and the earth sciences and the way fluids move around in the subsurface and the way we use the subservice in lots of ways. We do have a responsibility to serve what Jim called a unique function which is to provide advice to the nation and the way that's done is through the National Research Council in a variety of ways. I personally have participated I think in most of the elements of that process, whether it comes from participating in studies or chairing a few of them, being a reviewer on many of the reports and then at the Department of Energy being on the other side of the process of receiving the reports and I guess that job was under secretary of science and energy at DOE and there were things that could be done under the sort of ages of the NRC that were hard for us to do within DOE and that provided an independent view of what went on and the potential research agendas for the nation that was extremely valuable. I'll give you one sort of humorous example. We had a deep interest in the whole energy efficiency area and at least part of that has to do with how we pesky humans make decisions about how we use energy but the Congress in its wisdom had prohibited us from doing anything that any sort of social science associated with this because I won't speculate on motives but in any case they thought that we weren't the right folks to do that. So of course we didn't do any social science. We did some decision science which was to try to understand how humans make decisions about energy but we were able to partially support a study of all of those aspects of energy use that could be done by the National Research Council in a way that was complied with what Congress wanted us to do and helped us think about how to organize the energy efficiency programs. That was one of many, many places where the advice from the independent groups that the NRC put together was valuable to those of us who were in office. So with that I'll just say that I've also spent most of my career thinking about how fluids move around in the subsurface so I'm personally interested in practically everything that we'll talk about today. I'll say thank you to all of you for participating in this program. Thank you to the members of section 11 of the National Academy of Engineering. There's about, I don't know, 10 or 11 who doesn't have us here and that's a reflection of our interest in the topic of the day. So thank you all for being here and let's get started. Okay. Thank you, Lynn. So with that we'll get underway and let me introduce Sue Ham. Sue is the Office Director of the Geothermal Technology Office which is in the Energy Efficiency and Renewable Energy Office at the Department of Energy. Before DOE she's had been in significant positions at the National Science Foundation and the Department of Homeland Security. So with that I'll turn it over to Sue. Her more complete and detailed bio is available in your packet. Good morning everyone. Is this loud enough? Okay. So I just want to say how thrilled I am to be here. Thank you for inviting me. Subsurface is obviously absolutely critical to geothermal and geothermal research. This is a fantastic opportunity for us to hear from all of you and really learn from others around. I'm personally excited to hear the panels, the questions, et cetera. So I just want to point out that we actually have two staff members from our office here. We have Zach Frone who is an ORISE fellow in our office and Doug Blankenship back there. Doug, can you wave? Thank you. Who is on loan to us from San Diego. We also have a number of our PIs that we fund in the audience and I'm sure they're going to identify themselves as the day goes on. I don't want to name them all. Okay. So I'm going to take, I don't know, 20 minutes or so to go through our program and why we're doing what we're doing. But with a long presentation it's really hard to know what the speaker really wants you to remember. So I want to start up front with, I'm going to stop in a couple of places and talk about sort of future R&D directions and that's really what I want this group to think about. We're going to go through a lot of stuff, but that's really the fundamental pieces that I want you to think about throughout the day and take home with you. Okay.  Why do we care about geothermal? I'm sure many in the room already know that. Let's just go over that. Why is the geothermal technology office exist? What is our mission? What are we doing? I'm going to spend some time talking about the results of our recent, relatively recent GeoVision report which came out in May. And then I'm going to go through some of our programs and talk just, it's not going to be all of our programs, but some of the major ones, maybe. All right. What am I doing around Remy? Towards you. Oh, okay. So why geothermal? So beneath our feet lies this vast resource, right? And it's relatively untapped. Geothermal is always on. It's secure and flexible. It provides base load power. It's also, you can also, it's also dispatchable in addition to being base load, creates thousands of energy sector jobs. And when you combine both power generation and direct use, heating and cooling, it's an everywhere solution. So that's why geothermal is really important for the United States. Trying one more time. All right, Remy, I give up. There we go. Thank you. All right. I'm just going to say next. We said we weren't going to do that, but I guess we're going to. So this is a map at about 10 kilometers depth of heat across the United States. It does not include Alaska and Hawaii. And what you can see is that for the most part, when you're talking about the highest of temperatures, that's the purple, you're really looking in the western half of the United States. There is, however, heat at depth everywhere. And that's what we're going to be looking to tap. Current installed capacity is actually an old slide. It's somewhere between 3.9 and 4 gigawatts now. Undiscovered hydrothermal. So we're going to talk a little bit about this when you have a hydrothermal system. That's where you have heat and permeability in the subsurface and a geothermal brine running around the subsurface. You have the complete system already for you. That's a hydrothermal system. If you have something like a geyser or a fumarole or hot springs, then you know that that's there. But if they don't have a surface expression, then that's what's called an undiscovered or hidden hydrothermal system. And the USGS has estimated that there's about 30 gigawatts of undiscovered hydrothermal resources in the United States. So it's left to be tapped. We're going to talk about enhanced geothermal systems. So I talked about the three pieces that make up a hydrothermal system. If you are missing either permeability in the subsurface or a geothermal brine in the subsurface or both, you can add those. And that's what's called an enhanced geothermal system. And the western USGS potential is 500 gigawatts. If you look at the entire US, you're up at 2.3 terawatts. Okay, can I try this again? All right, so based on that enormous resource, what is a geothermal technology office doing and why? So if you look at where geothermal sits, a couple of slides are going to be very government-like, and I somewhat apologize for that, but that's how we think. So geothermal sits inside the Office of Energy Efficiency and Renewable Energy. We sit inside the deputy assistant secretary's sector for renewable power. Within renewable power, there's geothermal, water, wind energy, solar energy, and then grid modernization. So we're part of that. And the three main priorities for EERE right now are energy affordability, energy integration, and energy storage. With the GTO programs, we work on all three, but really our focus tends to be on affordability and storage. Great, so let's look at what it takes. This is when you're talking about geothermal power. So right now I'm not talking about direct use as much. Really focusing on geothermal power generation and to get from pre-survey, which is all the way on the left, to operations and maintenance of a power plant on the right, what we're looking at here is risks and cost. So the color, the dark, the heavy black line with the color underneath is really looking at the risk. And you can see that the risk is very high in the upfront stages because you're thinking about the subsurface, and we don't know. It's really hard to see in the subsurface and understand what's there. And so the risk tends to be very high. Where our costs tend to increase is when you get to drilling, can you hit next? When you get to drilling in the test drilling and in the drilling phases, that's where our costs tend to skyrocket. And so what we do is we are looking to support research in these key areas, drilling, success probability, new technologies. What we're really looking to do is reduce the cost and the risk to help, it's really looking to reduce that early stage and make it accessible for industry to pick up and get these plants online. Okay. Wouldn't be a government presentation if we didn't actually have a budget slide. So one of the reasons that I put this in in particular is to look at the very large growth that we've seen since FY 15, we started about $55 million. Next. So for FY 20, the President's request was $28 million. The house mark next is $90 million. And the Senate mark is a whopping $115 million. If you look at the Senate mark at $115 compared to the FY 15 number of $55 million, that's a pretty large potential increase. We anticipate that the actual FY 20 budget will come out somewhere between $90 and $115, just still going to be a pretty big increase. That gives us a lot of room to do a lot of really great research. Next. Okay. The Office of Energy Efficiency and Renewable Energy has put out a number of vision studies. There was a sunshot vision, a wind vision, a hydro vision. And in the geothermal office, we really wanted to follow on. We really wanted to follow the other offices. We saw a need for a study of this magnitude and the scale to more accurately assess the impact of geothermal in America's energy future. And we really wanted to include a comprehensive look at how innovation and innovative technologies would impact it and how non-electric applications, the direct use would also impact that picture. And so what we did is we looked at, we sort of started with a fundamental question. If everything went right, given where things are now, given what the barriers to deployment are, given what exists now in technology and what could exist in technology, what level of deployment would be possible by 2050? And given that level of deployment, what would be the economic impacts, what would be the environmental impacts of those deployment levels on the United States? Next. So the geovision was not just our office. There were about 120 to 150 people involved in the creation of the geovision document. It's a product of years of rigorous research and analysis with contributions from a broad range of participants. And we really had industry, academia, national laboratories, federal agencies. You name it, we had them involve public utilities. And this was a really great document. And I highly recommend that anyone take a look at least if you don't want to read all 200 pages of it and I can understand why someone would not want to read all 200 pages of it. Read the executive summary. You can find it. I'm pretty sure we have the link in just a few slides. Go ahead. Next slide. So the main results from the geovision study showed, this is what the analysis showed, that optimized permitting, so just reminding the permitting, could cut the timeline. Remember I talked about those stages of our plant that you could cut the timeline in half with streamlined permitting and that would lead to a doubling of geothermal development to 13 gigawatts by about 2050 versus the business as usual. So what that says is that with absolutely no increases in technology, no advances in technology, nothing. If we just work on the streamlined permitting, we would double the size of the industry. Direct use could increase by orders of magnitude as well. There's currently 21 geothermal district heating installations in the United States and what the analysis shows is that with the appropriate advances, let's just leave it that way, we could get up to 17,500. In addition for backyard geothermal, which is what a lot of people think about when you're, so ground source heat pumps, geothermal heat pumps, it's what people think of when you say geothermal. Currently two million installations in the United States and the analysis shows you could go to 28 million by 2050. That's a huge number. The really, the big money number though is that with advanced technologies with technology improvements and the bringing online of enhanced geothermal systems as I talked about before where you're adding either water or permeability to the subsurface, definitely it could reach 60 gigawatts by 2050. So that's a pretty impressive number. So what do you need in order to get to that 60 gigawatts? Next slide, please. Technology innovation is therefore going to be absolutely essential. It improves our understanding of the subsurface, helps us reduce risk, and accelerates growth of domestic geothermal power. Next slide. So at the last chapter of the GeoVision document is our GeoVision roadmap. And what we looked at, remember I said that we started with okay if everything went right, well then the question becomes what all has to become right? And we have these four action areas, I'm just going to read them to you because I know they're a little hard to see on the slide. Action area one is really, that's really the advances in exploration and achieve key technology advancements. Action area two is optimizing regulatory processes. That's really where you're going to get that big jump to 13 gigawatts. Action area three, optimize revenue and market structures. Action area four, improve collaboration, education, and outreach. All of these four action areas are really aimed at getting to these three key objectives. Increase access to geothermal resources, reduce costs, and improve economics for geothermal projects, and improve education and outreach. So I said I was going to stop for just a couple of seconds in two places during the talk. This is one of them. So I would like to call your attention again to this document. This is the roadmap chapter five of the GeoVision document. It's, I don't know, 20 or 30 pages. This is really going to help define where the geothermal industry and where the Geothermal Technology Office needs to go over the next five to 10 years. So if you're looking for where are the big research gains to have, I would recommend taking a look at this. You can find the GeoVision document at www.energy.gov. So again, I really highly recommend the executive summary. You can skip the letter from the director. I pretty much said everything you need to hear from there. But the executive summary and the roadmap, which is chapter five. Next slide. I'm going to quickly go through the four action areas and just point out a number of the programs in the Geothermal Technology Office where we are already doing some of the work that you see in these action areas. And then after that, we're going to go through a couple of them in detail. So the first is the Frontier Observatory for Research in Geothermal Energy. We've got Play Fairway, Jim Falz is here. Efficient drilling for Geothermal Energy Edge. We've got CoLab, Waterless Stimulation, Zonal Isolation, Subsurface Stress and Law Circulation and Machine Learning Exploration. So a lot of these, this is really where the GTO intersects with the GeoVision. We do a little bit in action areas two, three and four, and we're going to see some of that. But this is really the key technology advances and that's really where our emphasis is. Next slide. Action area two is optimized in those regulatory processes. We're working with the Bureau of Land Management Department of Interior to try to figure out where can we help make some of that streamlining happen. We're working with Forest Service. A lot of the land that has geothermal resources on it is either BLM land or Forest Service land. We're looking to do some collaboration with state and local governments. In fact, I'm actually talking with the Connecticut State Government next week, I think, that we're going to do a webinar looking at GeoVision and the Northeast, right? Because if you think back to what that map looked like, all the high temperature was over in the west. And so how do you really think about using geothermal resources in the Northeast? And that can be a challenge. It's doable, but it is a challenge. And then we're really looking to collaborate with the Department of Defense. The military installations may be on some really interesting lands in terms of geothermal resources. And one of the things that the military really wants to do is they want to be able to have their own power if and when they need it. And so we're talking to them about how can we collaborate, how can we make sure that we are able to harness geothermal resources in a way that makes sense for military installations. Next slide. Optimizing revenue and market structures, one of the things that is just absolutely critically important when you think about geothermal. Geothermal is not the cheapest renewable energy out there. We all know that, right? Solar is at what? Two or three cents per kilowatt hour. And geothermal is at, you know, seven when you're talking about a hydrothermal system. But if you're talking about EGS, it's significantly more. So you really need to think about what is it that geothermal brings to the table. And when we talked about it at the very first slide, we talked about how it's secure and flexible and reliable, base load, et cetera. All those things have value. It can also help stabilize the grid. Things like that. And all those things have value. But right now, when people think about renewable power, they only think in terms of a levelized cost of electricity. So we're working with others in EERE on something called Beyond LCOE, which is looking at how do you value some of these other elements, these other benefits that any one of the power technologies could bring to bear. We look at critical materials, right? So some geothermal brines are pretty heavy in lithium or other critical materials that we want to try and harness. How do you bring those out in an economically viable way? We have something called Advanced Energy Storage Initiative. I'm going to have a slide on that a little later. So I'll move on. Okay, next slide. Obviously, we're identifying plans for regular updates on the geovision roadmap. We're working on a multi-year program plan, which is the next step after this roadmap, right? The roadmap is not specific to the Geothermal Technologies Office. It's really for the entire geothermal industry stakeholder base. And so our multi-year program plan, which Doug is working very actively on, is looking at what are the next steps for GTO in these areas. We also have a number of international collaborations. We have one with New Zealand. We have the Collaboration Geothermica, which is with the European Union Nations, and that is a lab call on our side to see how can our lab folks collaborate with folks in the European Union to share information, share data, share facilities, those kinds of things. I already talked about the military bases. Next slide. Okay, so I'm going to go a little bit more into detail in some of our programs. Next slide, please. Our biggest program is this Frontier Observatory for Research in Geothermal Energy. Can I get a show of hands? Who's heard of FORGE? Okay, so about two-thirds. Great. So the idea behind FORGE is that we're looking to design and test a breakthrough approach developing large-scale, economically sustainable EGS reservoir. So what does that actually mean? I talked in the beginning about hydrothermal being where these three things already exist, heat, water permeability. When you don't have all three of them, you need to create them. But it's actually not that simple. You just can't just go down to the subsurface, create some fractures, throw in some water, so the idea behind FORGE is we started with a number of potential sites. We're down to a final site. What can we do to make sure that we could make the technologies? How can we test various technologies and get a large EGS reservoir that is maintainable, sustainable over time? And so right now we are in the process of just about to launch phase three. Phases one and two are really getting the site ready to go, making sure we had the right site. And phase three is a five-year phase three. And on each year about half of the money will go for the team that is operating the site for characterization and drilling. And the other half is going to go for solicitations that go out to the entire geothermal stakeholder community for R&D. Next. Did somebody have a question or something? Okay. I'll just keep going. So one thing that's very important is understanding where we want to go with the Forge R&D. And so we did a Forge roadmap that was stakeholder based. The Science and Technology Policy Institute which is an FFRDC run out of the Institute for Defense Analysis supports the White House but also does many other studies with other parts of the government. And we worked with STIPI to figure out where do we want to go with Forge R&D. So the roadmap is really a detailed outline of the recommended R&D activities for the site in Utah. It's a plan for understanding the key mechanisms controlling EGS success. And it had input from EGS experts across academia, industry, government and national labs. And really what we were looking for were what are the critical research areas that would allow us to create an EGS reservoir and then repeat it across the country. So the three areas are stimulation planning and design, fracture control and reservoir management. And all three of these obviously are subsurface and really very critical to what we're going to be talking about today. And the website for the roadmap is listed here. It's another great thing to read. And I said I wanted to stop two places to talk about future R&D directions. This is the second of those places. So first is roadmap, second is the Forge roadmap. Geovision roadmap and the Forge roadmap. So I highly recommend that as you get a chance to take a look at those two documents. Okay, next slide. If you've got really expensive wells drilled on the Forge site and you want to test technologies and you don't know what's going to happen, one of your concerns is that you don't necessarily want to test dangerous technologies and I mean dangerous in the sense that they might break a well on your super expensive Forge site. And so what we have is something called wells of opportunity. This has gotten a lot of support from Congress already. And the idea here is where can we use abandoned wells, idle wells, less critical wells to test some of these technologies. And what you see here on this slide is going from the left, which are the least invasive to the right, which are the most invasive, highest risk types of activities that you could try in a well. Right now we have a request for information out looking for input on wells and sites that could be put to use for this. So as you're thinking, especially oil and gas folks, think about what kinds of wells might be useful for this. We will have money to bring these wells up to the standards that we might need. And the RFI is listed over here on the right. You do have to go into the exchange to actually give a response to this RFI and we hope to hear from any of you. Next slide. EGS CoLab. So the EGS CoLab is in a mine in South Dakota. How many people have heard of a home stake mine in South Dakota? Biggest, great, almost everybody. Biggest gold mine in the United States at one point, and now being used mainly for physics experiments.  So what we've done, this is a the idea behind EGS CoLab was to try things at a smaller range and test some of the things that we would be eventually doing at FORGE. So with these and Doug again is a co-PI on this. If you the idea is to go into the drift, the well drift with, I don't know, 50 or 100 meters and try to observe so you've got boreholes and they're full of monitoring. Try to observe fractures happening in real time. And that's what we were able to do with experiment one. We're just about to start experiment two. So experiment one was really just a straight fracture and experiment two will include some shear in it as well and the experiment two should start sometime Doug next in the next few months. Okay, thanks Doug. Alright, next slide. Play fair way analysis. So Jim can speak to this one exceedingly well. The play fair way analysis is an idea we adapted from oil and gas where you're taking various data sets and combining them to see where would it be more likely that you might find a geothermal resource. And we started with 11 sites, ended up doing drilling at these final phase three confirmation drilling and what we're finding is that these are working out pretty well. That we're trying to find so again they were looking for these hidden systems. I don't think I said that. So hidden systems, combining data sets like gravity and magnetic all sorts of stuff to try to see where might you find a resource. And what we've been able to find with confirmation drilling in phase three is that you actually do get elevated temperatures where some of these combined data sets are suggesting that you should see them. So it's very exciting. Okay, next slide. I mentioned when we were talking about about getting from the beginning to the end that drilling is really expensive. So obviously one of the things we want to do is put a lot of money into drilling research. Drilling can account for up to 50% of that cost to get to geothermal full plant. So we are now funding 10 projects for a total of $14.5 million and we're looking to reduce delays in drilling operations. We're looking for innovative drilling technologies and we also want to accelerate technology transfer from lab to the real world. So these are getting started and you have the awardees down here on the bottom right and we'll see. I'll have more information on this in six months to a year as to where we are with these. Next slide please. Machine learning for geothermal energy is a super exciting area for us. Machine learning is a huge buzzword for geothermal engineering. Drilling in oil and gas has been using machine learning for years and we really want to try and make this work for geothermal energy. One of the issues for geothermal is that we don't have the data. We just don't have as much subsurface data as the oil and gas industry does. And so we're trying to identify what would we actually need to understand? What would be the data acquisition targets? What could be some new signatures for detecting those hidden geothermal systems? We want to minimize power production, understanding what's going on at your plant and your reservoir monitoring and then we want to improve prediction and detection of trouble events, right? You want to be able to use a machine to see things that we as humans don't see as quickly or as well. So another 10 awards for $5.5 million in funding. These are actually small awards. They're phase one we will be doing. We'll be down selecting to a couple of them for a phase two and putting additional money into it. Something that's really important, obviously, and those who know the subsurface know this, right, is that you need to understand the state of stress. And that is not a simple thing to understand in the subsurface. That along with lost circulation, so I'm sure most of you know what lost circulation is, but it's the idea where you're trying to... What we're looking at is trying to minimize the impact of lost circulation events where your mud disappears while you're drilling. Because that we want to we want to continue to reduce the drilling costs while improving efficiency. And so we have up to $7 million in funding that's available. This is 2019 funding, and those proposals are now under review. Next slide. I talked about the fact that we were really focused on storage, and this is our assistant secretary, Daniel Simmons, talking about how important storage is, and I'm sure we all agree that storage is critically important. Within the geothermal technologies office, we're really looking at this in three separate ways. We're looking at deep direct use as a way to think about storage, bi-directional energy storage, and flexible generation. And with all of these we have six deep direct use awards that have been going since 2017. We will be putting out another funding opportunity announcement to look at the next stage of those types of awards. And then we have lab projects in bi-directional energy storage and flexible generation, and likely we will have additional awards into the future in this area. This is just a really critical piece to understand how can geothermal contribute to storage of energy. It's going to be a big deal as we move forward. Next slide. One of the things that I promised my team is that everywhere I go I will ask for reviewers. If you are interested in serving as a mayor reviewer for us, please contact us at this web email address. Actually, if anything you want to talk to us about you can use this address. You can always email me, but doe.geothermal at ee.doe.gov is looked at several times a day by our staff to make sure that we are answering anything that comes in from the community. And then our website is energy.gov slash eere slash geothermal. And I just want to say thank you so much for your kind attention during this. And I don't know if I'm taking questions OK. Thank you Sue. So just we will have some time for some questions and discussion. And I would just ask folks to just you can always if you have a card you can put it up so we know or you can, you know, motion that you want to ask a question please use your mics. And we want to make sure that we have questions we'll do we'll get to those as well. And I would also say that there are folks in this audience who are much bigger experts on particular areas than I am so I may be turning to them if anyone asks me a question I don't quite exactly know the answer to. Yes, I'm Christine the Economist. My question is just with 60 gigawatts that's a lot. So it seems like most of this is quite far from the market. What's the plan to get the power to where it would be used? OK. So there's sort of two pieces to that question. The first 60 gigawatts is a lot. Actually what I should have said is that analysis shows that that would be 8.5% of national generation by 2050. So right now geothermal provides 0.4% of national generation so going to 8.5 is quite a lot. OK. So the question of a lot of it is far away and it's very expensive. And so one of the ideas with EGS is can you do EGS in a way that is safe closer to population centers? You're not going to do it right smack in the city we've seen what happens when you do that. You can end up with a lot of induced seismicity. So the US geothermal industry is very careful and the researchers are very careful about following induced seismicity protocols and making sure that we are not putting anyone or anything at risk. So the question is how much transmission costs? Was it a million dollars a mile or something like that? So that does add to the cost of what the eventual LCOE will be. So it's true. But the idea is with EGS to get closer to population centers because you aren't necessarily required to be at the risk zone of the West United States. Right. Well we're demonstrating in the middle of Utah and it's not near anything. But the idea is when you demonstrate there, can you make sure that you don't have induced seismicity issues and then try to move a little closer to population centers? Great question. I had a quick question. You had a figure up there where you had risk on the Y axis and time on the X axis. I was just wondering how you were defining risk in that. Is it cost or? Well really it's how likely are you to hit a resource so that if you're in the exploration stage you don't exactly know, right? So if you're talking about oil and gas and you're looking at seismic reflection you can really see the resource when you're looking at seismic reflection in geothermal you can't see it. And so the risk comes in with how likely is it that you're going to be able to hit a resource exactly where you think it is. And we're trying to bring that down. We're trying to say okay let's narrow it. Jeffrey? I'll repeat your question. Go ahead. Oh there we go. Okay. Jeff Yaris with Case Western. I'm going to answer the first part of the question I think because you just said it which is well placement seems to be important. So how extensive are the subsurface earth models that you're building to reduce the uncertainty around well placement? The Forge project is doing a massive amount of that kind of modeling. We don't actually fund modeling just for random places. And so I think some of the projects do it and some of them don't. That's not an area where we particularly are focused with. It's not an area that we are currently focused on. How do you make those earth models better? So the well placement itself is it done based on very broad parameters or are you trying to You know, let me turn this to Jim. Jim, do you want to talk for just a minute about how you did it in your play fairway? There we go. Yeah. So there's a number of parameters that we take into account in multiple geologic geophysical parameters to model both the surface and the subsurface. And then we try to use the most sophisticated 3D modeling programs and so on such as EarthVision and there's others. And really to and then we we take, Sue mentioned the play fairway program. So that's not only estimating the probability of a resource on the surface but where in the subsurface that resource might be. So actually a play fairway that's three-dimensional. Okay. So I don't know Earth modeling has been a specific focus of a program but many of the programs like the play fairway program have gotten into some pretty sophisticated Earth modeling. If that makes sense. Thank you. There's another question up here. Ken Woodley, Condor Consulting. You mentioned one of your first point, your first point I think was enhanced permitting. Are those places that would be developed irregardless but you've cited a figure of a significant resource available if enhanced permitting worked out? And I just thought well okay is it a question of time because sometimes those we've well in the mining we've seen for pebble for instance. Very difficult getting all the stakeholders lined up and the government is now trying to expedite that but these can be thorny issues that go out for some time and so a guarantee that you're actually going to see this increased resource is sort of like if you get a third of it you're probably doing well and you comment about what you thought that would give us because it was the first point that you mentioned. Right it's a big point because to us it's a somewhat easy fix right it just relies on the government maybe changing some of its rules which exists for a reason, I'm not saying they don't but when you're doing geothermal you go back for NEPA testing you have to go back for NEPA documentation six or seven times in the process of getting to a project if you're doing oil and gas it's something like one of the concepts is if it's very expensive to go back for NEPA there's a lot of time involved and so if we can reduce the number of times that a geothermal project has to go back for NEPA you are then reducing the cost reducing the risk and increasing the probability of getting to a resource is that what you're Yeah no thank you good luck Actually there are some bills in congress that are putting forward categorical exclusions that are similar to oil and gas for geothermal we'll see if they go through but they're there Yes Well kind of a pardon me, Tom Craffer with USGS but before I worked with USGS I was in the state of Alaska and I know of one instance in the state of Alaska and this is kind of a continuation of the permitting theme where there was a company that was seeking to drill some geothermal exploration wells near Mount Spur which is an active volcano in Alaska and because of the lack of infrastructure they were having to rely upon a very expensive helicopter supported drilling operation and eventually they gave up because they were being required to deal with the drill cuttings as hazardous waste and they had to collect and bag and transport to an approved disposal facility all of those drill cuttings and to kill the project so I think there's maybe another component to the permitting there that ought to be considered and that's these kinds of issues in relation to the drilling Actually that really helps bring up one point which is that when you talk to BLM one of the concerns is that depending on whether you're in Alaska or Nevada or Illinois or depending on really where you are you can get a very different level of expertise in the BLM office and I'm assuming that BLM is working very hard to address so that if X is required in Nevada the same X would be required in Alaska and they're really trying to get to that In this case it wasn't on BLM land so I think there's the EPA can have a role in this as well That's very fair Yeah I guess I didn't catch how this EGS differentiates from previous efforts towards EGS Could you comment on that? Sure so there were a number of EGS demonstrations that were done in 2014 and those were sort of at the 5 megawatt or less level and what we're really looking for is more at the 50 megawatt level so this is bigger reservoir bigger team a lot more money right so that when you are talking about $35 million a year for 7 years approximately you can really get much farther than you could with a few million dollars and a random we've got a lot of experts working on this we have not only the team at Utah we also have the science and technology analysis team which is made up of a whole bunch of experts that are helping sort of guide that science as well and there's just a lot more concentration of the entire geothermal community on this one project to make it a success we have a lot of interest from some of our members on eastern demonstrations of EGS so I'm wondering what do you see as the timeframe for that and are you doing any work specifically on eastern areas like the West Virginia hotspot or anything So in terms of the eastern part of the United States I think where we're going to see enhanced geothermal systems technologies show up is in deep direct use type areas because in order to make deep direct use viable even on the east coast you're going to need some of those technologies as well and I would say the timeline for that we have of our you mentioned West Virginia we also have an upstate New York project on deep direct use so we have two of them already looking at those and sort of the feasibility and the question really becomes is it feasible and that's not even necessarily a technology question but more of an economic question I mean it combines right because if it's cheaper to get down and do these technologies that's going to bring down the cost and make it more feasible those feasibility studies should be coming in this fall and we'll know a little bit more then alright I've hit my time thank you all so much for your attention I really appreciate it thank you Susan so what we're going to do now we're going to transition directly into our first panel and we will so I'll turn it over to David Spears and he's going to go until 11am some of you have a little air on your agenda but we have a break at 11 and David I'll let you take it over okay good morning I'm David Spears I'm a member of the committee on our three sources and this is our first panel it's on managing uncertainty in the subsurface and we have three eminent panelists here on my far right is Ken witherley who is a consultant nowadays has his own consulting company Condor consulting but Ken has a long history in the mining industry he was worked for BHP for many years by the way the complete bios are in your handout beginning on page five but Ken worked for many years for BHP Minerals as a geophysicist and since then he's had a technology based consulting company so we have strong expertise from the mineral sector and then in the center we've got Colin Williams who's currently at the United States Geological Survey in Menlo Park where he directs the geology minerals energy and geophysics science center otherwise known as GMEG but before that you were chief of geothermal resource investigations the earthquake science center almost also in Menlo Park so Colin has a long and strong background in geothermal energy and then immediately to my right is Jeffrey Yaras who has currently is currently at Case Western Reserve University but has a long history in the oil and gas industry over 42 years with companies such as Amaco and Marathon and now Ken is basically an earth modeling specialist and so I think we've got a good round panel here with representation from oil and gas geothermal and mining and I think we're going to start with Colin right? You ready? So I'll get started while the slides are coming up try to save a little time I should mention that I promised Elizabeth I would have 10 slides I actually have 15 so we're at 50% uncertainty already but we're trying to bring that down and I'm going to talk fast anyway one of those just a title slide so it doesn't really count but I'm Colin Williams I'm the USGS David introduced me mostly I'm going to try to speak to the work that many other people have done at least touch on it both within the USGS and in particular outside the USGS highlight a few issues related to uncertainty and subsurface data and also just briefly mentioned that we are in the process of moving and I'm no longer officially in Menlo Park but in Moffitt Field which is 8 miles to the south where we're co-located with the NASA Ames Research Center see if this works next please I'll just do the Susan pioneered the way here so I'll have a very brief introduction talk a little bit about challenges in geothermal energy from the perspective of assessments resources assessments like we have done in USGS exploration and resource management of course where the common themes are in the context of natural hydrothermal systems and also enhanced or engineered geothermal systems or EGS as Susan introduced it and ideally just important topics and possible future directions for research next so geothermal systems happen in a wide variety of environments these are a couple of classic images one from Marshall Reed a former colleague illustrating what's conceived as a simple fault-hosted warm water circulation system this might be an idealization of basin boundary fault in the basin and range where Jim of course is the expert and would draw a much more complicated section and we'll get to that and the other from Henley and Ellis back in the early 80's kind of a cross section through a volcanic system magmatics hosted geothermal systems tend to be at least the natural hydrothermal ones tend to be the best place to find high temperature and large power potential but diverse environment of course you've got high temperatures and alteration focused in the center of the volcano but because of fluid pathways especially if there's a ring of faulting or groundwater flow down the volcanic edifice you can have hot water and hot springs way out on the distal end of course the common elements here are there's certain fundamental common elements fluid and heat flow being the main one trying to understand those fluid flow pathways typically there's a cap rocker seal because cold groundwater is the enemy of hydrothermal systems and sealing away that cold groundwater is shallow groundwater is important and of course being able to classify these systems in a geologic context with examples like the play fairway work being prominent is invaluable tool next can you go back yes surface manifestation so it's worth mentioning Susan touched on this a little bit that in geothermal of course it's not unlike oil and gas in that it helps a lot if there are surface manifestations and much of the early geothermal development and many of the largest geothermal fields developed both in the United States and around the world were found because there were hot springs or other you know steaming ground other thermal manifestations obvious hydrothermal alteration and that was the low hanging fruit just as if for example you look at a map of oil seeps in California and a map of all the oil fields that were discovered in the early part of the 20th century they pretty much overlay and just as the oil and gas and mineral resource communities have had to move beyond that to finding systems under cover or systems without obvious surface manifestations the same as true for geothermal that the frontier for exploration right now is in these blind hydrothermal systems where or at least ones for which the surface manifestations are indirect or complex indicator of the subsurface next then of course Susan already talked about this but in the context of EGS we want to be sure to note that EGS is a much broader resource it relates to being able to exploit the high temperatures that are ubiquitous at depth in the earth and it involves a broad range of stimulation potential mechanical thermal and or chemical and can be at a site like this where you're presumably creating a hydrothermal reservoir in a rock that was previously low in permeability and not part of an active hydrothermal system to working on the margins or within existing geothermal reservoirs and I think based on one of the questions that came in earlier that's another advantage that's worth pointing out to the DOE FORGE project is that many of the earlier EGS demonstration projects earlier this decade were involved working in or on the margins of existing geothermal fields and there are limits to what an operator will let you do in producing geothermal field and having a dedicated test site is a great step forward next. So some of the challenges and here I want to try to emphasize challenges that in some ways are at least partly common to natural hydrothermal systems and also EGS well of course you need to find high temperature right you've got to find predominantly high temperatures relatively shallow depths geothermal is where where those high temperatures come up in the near surface which of course within the high temperature halos when you can identify them typically the permeability is a much smaller volume and predicting where that high permeability is a real challenge even when you have a good the distribution of temperature and part of big reason for that is because most systems in the United States are fracture dominated in terms of the permeability which means there are dramatic variations spatially in permeability and predicting it is not just a geologic problem but a geomechanical problem of course and much of the exploration and the technologies to characterize the subsurface focus on cap rock and reservoir rock properties as do many other fields but one of them and again Susan alluded to this is because we're basically looking at water and hot water in the subsurface tends to look a lot like warm water we don't have the physical properties that necessarily come out of say looking at gas or petroleum versus water that you do in the petroleum field with EGS we're moving from an environment in which he transport is predominantly convective to one that is predominantly conductive so understanding the subsurface temperatures generally takes a somewhat different approach rock properties are also the key and the research projects are the way in which we're moving ahead and better understanding how factors like lithology pre-existing permeability and situ stress etc affect the viability of EGS projects and the other challenges of course since the EGS is broadly defined as a resource as opposed to narrowly focused in particular locations we have to be able to work consistently skills especially from the assessment perspective from the continental down to the local and be consistent it's been alluded to already but one thing that's definitely true with geothermal is their sparse data and limited resources and the important question obviously here is how will these challenges evolve and what carries across as we move from a geothermal community that's predominantly based on exploiting natural hydrothermal systems to one that's based on EGS next and here I'll just highlight that things are complicated no big surprise so this is a cross-section idealized based on a study of the Brady's geothermal field that my colleague Drew Seiler at the USGS worked on predominantly worked on this though I want to give credit with Jim Falls when Drew was at the University of Nevada Reno and it's highlighting in this great basin hydrothermal system context all the geologic factors that contribute to and affect fluid flow system there are many geological factors related to variations in mythology and structure and then of course the mechanical factors like the dilation on these active or recently active faults their slip tendency how that interacts with the thickness of various units what's the inherent orientation character permeability in these units Drew and his colleagues looked at a lot of these things in Brady's partly because Brady's has been operating for a while there are a number of wells in the subsurface they were able to make three comprehensive 3D geologic map and or should say model and analyze it in terms of synthetic wells that penetrate the surface and highlighted that dilation tendency in these faults in particular and coulomb shear stress change had a significant effect on which wells tended to be permeable but again we often in geothermal don't have access to the kind of data that allows for this sort of analysis which is absolutely key next this is a few slides I borrowed from Bill Cumming who's a consultant geophysicist quite successful in the geothermal regime he focuses primarily on magnetoteluric systems and in magmatic setting takes advantage of the fact that he and others that the alteration patterns of created as a halo around these hydrothermal systems in magmatic settings lead to very different resistivity characters and in particular this shows the idealized cap of lower temperature Smectite clay rich alteration above higher temperature reservoir where there's higher temperature Illite alteration and the higher resistivity associated with that reservoir next and the fact that you can see this in actual systems this is his section through geothermal field which is located at medicine lake volcano in Northeastern California and the reds highlight that low resistivity clay cap over the reservoir there which is very important because in these volcanic environments you get active shallow groundwater flow through the younger more permeable volcanic which are the very dark blues the Smectite fills the pore spaces and seals off the underlying hydrothermal reservoir which is again somewhat higher in resistivity with the higher temperature alteration the tricky thing here is that while the empty surveys do a great job in highlighting zones of potential it does turn out that in these environments it's individual faults and fracture systems that are again the conveyance of the high permeability for geothermal reservoirs and it takes additional techniques to actually target those next and then just reiterating for EGS we're trying to work across these larger scales and down to the local scale and there's a different challenge in the context of estimating in particular subsurface temperature and rock properties. Next. We need to develop better and more comprehensive 3D models of the subsurface this is just an example from a few years back in the vicinity of Biowawa, Nevada where through inversion of various geophysical data sets in particular gravity and magnetics combined with some drilling results from the nearby geothermal system geophysicists were able to tease out the 3D geometries on various important components there, Paleozoic rocks that have been intruded by much later Granitic rocks and then the intrusive characteristic of the northern Nevada Rift. In an EGS setting each of these would have different physical properties probably different temperatures at different depths because of their different thermal conductivity and being able to understand how to exploit this geology is very important but also often with these subsurface maps we don't tend to have a very good idea of what the uncertainty is. Next. And this question came up earlier and this is another one of Drew's slides but I tried to put from the related paper everybody's name on it because this is essentially a cross-section through the Fallon Forge 3D model that Doug Blankenship and Jim Falls and Bridget and many others worked on and it shows how the cross-section the geological understanding from the top to the bottom evolved from phase one to phase two B through a variety of efforts geophysical data acquisition a new well that was drilled and studied a lot of analysis of existing data in greater detail and you can see the lithology higher resolution the lithology is popping up in the subsurface the interesting thing and the reason I wanted to highlight this here is not to go into the details of how the model evolved but to note that one of the things that this group did that I think is in the geothermal context pretty pioneering is to note the uncertainties associated with their model and those are the little boxes in the lower right of each of the cross-sections which show the log of the distance from each model pixel to the relevant data sets that constrain those observations and you can see through the analysis and the new drilling how the data density improved tremendously and being able to carry these kinds of analyses into other settings and quantify them is very important. Next and the last one in the CGS context but perhaps most important is similar analysis something that we worked on a few years back is how to characterize your uncertainties in crustal temperature you often see in talking about EGS and geothermal you see maps like on the left of heat flow this is just a map of heat flow in the western United States of course reds are hot high heat flow blues are low heat flow and the right is a model based on this data set of the estimated temperature at 6 km and again you see that it looks a lot like the heat flow map but to get to that map on the right involves a lot of analysis it involves estimates of where there's predominantly conductive heat transport where convection or convection is influencing the shallow heat flow measurements what are the uncertainties on those heat flow measurements the spatial variation in the coverage of those heat flow measurements which are all the dots on the map you can see there's high densities in some locations very low densities and others estimating the thermal properties of the crust at depth with EGS we're obviously going to in many cases much greater depth than traditional hydrothermal systems. Next and by going through as well as we could what the quantitative uncertainties were we said that even in the best case at this kind of regional scale our estimates of temperature are only good on the order of plus or minus 20% but are highly variable depending on local crustal structure and data availability and quality and noted that we need to make progress in quantifying the uncertainties of these heat flow measurements there are a lot in the literature that do not have uncertainties associated with them we need additional measurements we need consistent scaling of models from local to regional and continental dimensions better constraints on thermal properties and the last one which is most relevant here is improved approaches to uncertainty analysis finally last slide I think so just to summarize I think as I look across having been involved with geothermal for a few decades now it's definitely made significant advances in integrating diverse data sets as Jim mentioned and I think it's worth mentioning that the 3D data sets that Jim refers to whether play fairway or Fallon Forge or a few other cases that we've been involved with DOE support has been key that many of the geothermal companies are operating on shoe string and some of them do this kind of analysis and some of them don't so developing these 3D models has been important we're still at the early stages of quantifying the uncertainties associated with those models and we need to learn a lot more especially as we move into the EGS context and I think this came up in Seuss talk and I'm glad it did but I think there's no substitute for drilling and when holes are drilled because many of these companies are operating on limited budgets they're not necessarily collecting all the data that they could or it isn't necessarily finding its way into the public domain and so projects like the one that Sue mentioned of working with holes of opportunity or Idle Wells is really important and I think leveraging what the industry is doing could be a cost effective role for government and that's it thank you Colin if you have questions please hold them till the end of the panel here write them down if you have to and now we're going to bring up Ken witherley good morning everybody I think one of my first men being from Vancouver not a lot of geothermal around there but I spent some time in Reno and I remember there was a spot about 150 miles east of Reno along the road there was a bathtub with warm water in it so I saw a manifestation of geothermal I believe I'm not sure if that bathtub is still there but it was useful the topic of the theme we're calling it managing uncertainty in the subsurface data ducker told us that if you if you can't measure it you can't manage it and I would say by and large the mining industry that I've worked for for almost a century doesn't really do a great job of defining uncertainty in part there's reasons for that one of the things that many mineral deposits unfortunately are quite unique and so what are brothers in the oil and gas sisters in the oil and gas and geothermal businesses probably have as more generic geological model whereas each mine is often very different and so special knowledge has to be built up around that actual deposit and when special knowledge is created it can be applied obviously to that deposit but companies tend to have very little motivation to share that information either within their own organizations or put that out into public in the exploration part of the business so that's the downstream in the exploration part of the business where I've spent most of my life I thought about this and there are some people certainly engaged in more rigorous mathematical approaches to trying to define uncertainty but by and large the industry has relied on experience it's basically the knowledge you develop working in mineral systems as we call them now is to try and make the best guess as to what's going on because we simply haven't over the years acquired sufficient petrophysical data calibration information to do a quantitative assessment of these things it's night and day compared to what the oil industry does in system characterization and we're too late now many of the sites which we would have liked to examine have simply passed this by so I'm going to show you some images and talk some about mostly focusing on the downstream side because I think that's where the money comes from and that's often where society sees the biggest impact so with Remy's blessing it's the top button right one on the right magic so scale dependent targeting this comes out of a presentation a colleague made that shows where we have our information and to some degree the certainty of that information we begin an exploration program really on the far left this could be this could be global state geological terrain and then as we move further and further down moving over to the right we put a lot more time and money into prediction and so we reduce uncertainty moving from the left to the right but it costs us a great deal of money to put that information into play and you can see the relative scales there and so I spent most of my time to the left of that red arrow but the mining business the extractive side spends most of their time at the consequences of the successful outcome of looking for deposits on the right hand side so the degree of uncertainty is reduced but it comes at a high cost I mean the very same things that Colin mentioned the drilling, Susan very expensive and we rely very very heavily on that information and in part as I said earlier most mining deposits are fairly unique and they require probably a lot more information to basically be able to figure out the proper metallurgy rock stability issues issues of fluid flow in and around the deposits all of this has to be monitored for the life of the mine and afterwards these things, these big holes that we create in the ground don't go away very very comfortably so some idea of the deposits, critical some ideas that were put out by a colleague he used to work for Newcrest and they've pioneered the development of large scale underground copper deposits in the state of New South Wales in Australia and he put some points out he's an SEG special lecturer about seven, eight years ago, Dan Woods' name so I've just put down some of his points and used some of his figures because I think showing these you get some idea where in the mining industry we're going to have to focus in getting better control of the uncertainty because as deposits go deeper it's probably going to have a larger footprint underground even if it is underground and there's going to be more challenges from how to manage that so mass mining he calls it these are constrained economically it's always running up against barriers because what we produce in our country is not typically unique we're always competing against sometimes the same companies who are mining here in the US are also mining overseas and it's up to them to make a return to their shareholders not just keep a good balance sheet for their domestic production where are we currently working with underground depths to 300 to 2 kilometers and that's in part it's a bit of an iffy thing it depends on somewhat on the local conditions some environments like in the Sudbury Basin they're pushing down 3 kilometers at Kid Creek in Canada and other places it's difficult to go beyond a kilometer just because of rock conditions future underground deposits I think we're thinking maybe or Dan was thinking maybe a 3 kilometer limit part of this has to do with gradients as well some of you have probably heard of the resolution deposit show of hands who you've heard of resolution there you go one of the things they're dealing with at resolution is ultra high temperatures probably requiring some sort of autonomous mining equipment but really having to design equipment at this point probably for one deposit in the whole world but it's a very very attractive deposit Rio Tinto is spending a huge amount of time and effort on autonomous mining trucks in the Pilbara the idea they will eventually be able to bring that technology to places like resolution open pits at one and a half kilometer deep hole that is definitely a pretty scary thought a number of you probably saw what happened at Bingham about three years ago where they had a it was not unexpected but still a fairly disruptive slump coming in from the north face and cost them quite a bit of money to fix that up the sorts of beasts that we're actually finding now and we'll probably see in the future these are cross-sectional views as if you were down in the earth these are very very large operations as Dan says we're going to have to get much better if we're going to reduce the overall footprint on the environment to knowing everything about what that cube is actually doing over time we have to have four dimensional models of these in this one in the bottom right I'll just expand on that notice the base scale 6.6 kilometers and that's just where the deposit is so they're taking a chunk of earth going down approximately three to four kilometers and have cube that's probably going to be 10 by 10 and all of that material by and large or it'll actually be changed in some way there'll be a lot of fluids flowing through there a lot of things happening that somebody's going to have to take accountability for so we need to reduce the uncertainty we need to be able to define what's going to happen before we actually start mining something like this on the geological side this is just the results of follow up on a workshop that I attended last month in Perth there's a very clever group of people at what they call the center for exploration targeting largely focused on the upside exploration side of things for 3D modeling and that's one of the things we probably need to see more interaction between the people the bright people on the exploration side communicating more with the miners that would be very very helpful for our business and you can see in this example when they're asked this is a questionnaire I've circled the one here and we're talking about mine dimensions of under a kilometer well that deposit in Mongolia is far bigger and if we have a 10 meter resolution we are talking very very large data sets very large data sets will be created for models of this so we're going to have to work hard to get control of this information otherwise there'll be blowback at a number of levels that will be ultimately probably damage the social license of the operation if we don't get it right and this is what these blowbacks can look like this was called unexpected subsidence of Ridgeway about 500 meters below that was a block caving operation my understanding is they knew this was going to happen they just didn't know when and unfortunately there was a loss of life attributable to this so this is the sort of consequences these mines of the future they potentially have obviously if it's an open pit you can guard the perimeter but these underground block caving operations are they going to be what the future is about for mining particularly in built up areas so we are uncertainty far better and define it that's it thank you thank you Ken and then we will finish up with Jeffrey Yaras I'm not sure whether the uncertainty here is greater with respect to advancement of the slides or whether or not I can get through my eight slides in 10 or 12 minutes so what's that there okay so I'm a little bit more in the weeds on the earth modeling side here looking at the uncertainty in fairly good detail around geological reservoirs and just as a matter of interest the scale of the models that we build today used to cover 5, 6 square kilometers those were fairly typical but today we're closer to 2,000 kilometer models or somewhere in the north of 2 million cubic cubic kilometers in size so the earth models have become quite large and the purpose of course is to really measure uncertainty that's what we really do that's our job and to move these models downstream to engineers to dynamic simulation or for drilling or for completion so with that in mind what I'm going to do is talk a little bit about the definition behind what I perceived to be uncertainty at least in the petroleum arena and then I'll talk a little bit about the sources of uncertainty in general and then I'll talk about our wishlist what we'd like to do with respect to our models and then actually what we do do in practice with some of the pitfalls that we have and I'll give you some examples of that so I'd like to start off with this definition that is kind of well known in our industry particularly from what I refer to as the three Johns John Harbaugh John Dubton and John Davis who really were some of the earlier pioneers in risk assessment and modeling of the subsurface and sadly John Harbaugh recently passed away so we owe him a debt of gratitude in the work that he and the others have done and their definition really was there's an inadequate awareness of the differences of the geological features as they are perceived and as they exist in reality and I would add to that that represented by the data available to describe them so we often don't have all the data that we would like and hence it's the idea of having a probabilistic model set in some kind of a probabilistic framework is really the way we approach this what we'd like to do theoretically of course is have all the possible outcomes of all possible values across all possible scenarios but that's really an impossibility we really can't do that so from a pragmatic point of view we put this into some kind of a probabilistic framework that we frame and we test uncertainty against that model and the real engine under the hood, the real work course here is the geostatistical methods that were developed very early on by Danny Krieg and George Matrone back in the late 50s and early 60s and that of course really originated in the mining industry and the petroleum industry has leveraged that as well and has taken it to slightly different directions in many cases than the mining industry has so we use something called conditional simulation and that's the geostatistical approach to a really reducing uncertainty so the reality too is that we live with the uncertainty assessment today that it's necessarily the models that we produce are necessarily constrained so we know we're not going to capture everything we're going to do the best job we can with the models that we create and we'll test against those models so that's basically the overview of that some of the sources of uncertainty that we have are the inherent randomness in nature there's a limited understanding of the phenomena we're trying to study we have measurement errors we have incomplete measurements of the phenomena that we're trying to measure and there are lots of interpretation differences so I really agree with Ken in the sense that our experience which is something I'm really worried about today in terms of losing that with the younger folks that are coming into the industry and not having the older folks available to impart that wisdom but the experience is still a huge important area and my focus has been more on the mathematical side so I've kind of got both of these things going on the conceptual models, our experience are hugely important and I see that something's wrong even though the math worked and the computer programmed in crash it doesn't mean that it's right so we've got to be very careful about that and I think one of the more important aspects of this is really to produce enough of what we would call realizations enough different models that we capture the unexpected contributions it's not the stuff that we expect to happen we kind of all get that what we expect to happen and the idea of capturing that entire probability distribution is really important so we want to get the extremes and that's something that we really lack and don't do well in our industry at least not well enough these unmeasurable phenomena are another thing if something we totally didn't expect at all to happen then it actually happens and how do we capture that in the conventional reservoirs plastic and carbonate reservoirs we've established a long history of experience so we kind of know where the uncertainties lie and the magnitude of those uncertainties so things like structure is really the first and the highest amount of uncertainty you want to add a little bit more reservoir to your reservoir quality rock to your model it's not going to be by increasing the spatial range on your variegram for example in the geostatistical world it's going to be the structure add more structure there's a lot of uncertainty around it and certainly room to do that and then that's followed by the stratigraphic relationships we have to pin down the stratigraphic relationships then generally the facies or rock types and then finally the petrophysical properties play an important role so we've kind of established that and that's generally the rule today with the unconventional things are kind of upside now we don't quite know really what facies are in these shale reservoirs we don't quite understand the rock types they're complex certainly we refer to them as shales but they're not really shales they're all sorts of things so what we kind of think is that the stratigraphy in terms of not only the chronostratigraphy that we're kind of used to or lithostratigraphic stratigraphy that they could override any of that so that's a huge part of the uncertainty that we need to capture and the rock types themselves whether they're clay, silica, carbonate, organics that's probably one of the higher levels of uncertainty that we have to deal with and then the geochemical or geomechanical processes that they go on so that part is really important and a little figure that you see in the bottom right hand corner I captured that from Gross from 2009 it just shows the overprint of the mechanical stratigraphy on top of the litho or chronostratigraphy so it's quite complex and it's something that we don't model very well today and it's really one of the sources of uncertainty that we have and have to do a better job capturing should I give up Remy here oh there we go I guess you did that so let's talk about what we do in practice we tend to really oversimplify our models that we build at least in the petroleum industry and the reason is complexity leads to increased CPU time which leads to increased dollars and everybody's under the hammer of time the drilling schedule is not going to change and you've got so much time to do your project so you cut back one of which is the structural or the stratigraphic complexity the other thing that we don't do, we should do is we run too few realizations in the probabilistic framework we don't capture the extremes and believe it or not those extremes become really important in trying to mitigate cost expenditures so we really want to be able to take the advantage of our computing systems today and our performance computing and parallel processing to try and run the realizations as much as we can to capture as much of the uncertainty as possible we run scenarios at the expense of realizations and make a subtle distinction between the two terms so a scenario is kind of your best guess and you could say well you know I think the high side the medium side and the low side would be these scenarios and they may be different but the real systems that are similar but you choose them and John Davis years ago showed that human beings tend to pick scenarios that are much closer to the mean and not the extremes so we kind of fall prey to that problem so we really want to run the stochastic realizations to try and help us capture those extremes and the other thing that we do is often tend to spend more time on variable sensitivity than we do in capturing the uncertainty and those two terms on a practical level on a day to day basis is often confused by our modelers they tend to say well I ran realizations I ran those things but what they're really doing is variable sensitivity so the variable sensitivity is not going to change from realization to realization right so you really need to do both and that's important if you run a single realization you have no idea where you are on that cumulative ability distribution function and to know where you are you really have to map it all out so we have a couple of examples there's what I call the hand-picked example and that's where someone says here are my three scenarios and for the reasons I just explained that's not really a good idea to do the other way people will work is they'll say it's what I call the one one and many they're going to run one realization for each of the structure and the facies and then they're going to do multiple realizations on the petrophysical properties which have the lowest degree of uncertainty and sensitivity in our model generally so that's kind of an issue but it saves time another way to do it is to run many structural realizations and then run one of each of the rock types and the petrophysical properties and again that saves time and it captures the greatest uncertainty which is the structure generally in conventional reservoirs but doesn't really capture the rest of the uncertainty that could end up being very important and then the last one is what I call the one one one which is you just choose one realization of each and you focus on variable sensitivity that's one of the things that's more common in the industry to do and I don't think that's really the right thing to do and the little example that I have off on the right there gives you an idea of why it's a problem right if I say I want to run a probabilistic sense and then for each one of those I want to run a hundred realizations of the stratigraphic relationships you're up to 10,000 realizations if I want to run a hundred realization of each of those 10,000 for the facies or rock types then I'm up to a million realizations and then finally the petrophysical properties each will increase that thing to over a hundred million realizations and really even now with the HBC the high performance computing systems that just isn't really going to cut it people aren't going to waste the time to do that but maybe that's something that we can accomplish in the future or we can mitigate that by finding simpler ways to capture the extremes on those realizations and cover all the properties that are necessary so that's kind of one of the issues that we face so this next one I like this example I think you'll appreciate this this came from the University of Houston with my students in my class last year looking at the uncertainty in a reservoir model this is the static model that's going to go to the reservoir engineer on the left you've got the probability distribution curve which gives you the plethora of realizations and ranked and then on the right where it was in video mode was showing all the different possible from the most conservative to the most extreme and if you really got a sense of it it was changing quite a bit so there's a great deal of uncertainty in terms of this reservoir model if you just pick p50 you might be in danger not understanding what could happen on the extreme so what we like to do with uncertainty is say well I'm not going to give you all 100 or 1000 realizations because my reservoir engineer would not be happy with that that's a lot of work to do and particularly when I tell them that each realization consists of something like 50 or 100 million nodes that just isn't going to happen but they might take three they might take that p10 they might take the p50 and they might take the p90 so you bracket the uncertainty and then of course we could discuss upscaling and whatnot which may also lead to some additional uncertainty but that's practice in the industry so we want to bracket that uncertainty and this way get a sense of what we could have and what we have to be concerned about and what are most likely cases the other thing that I think is important is really in this slide and that is all too often we tend to run these deterministic models which is on a far right so that's a that's creaking which is the geostatistical approach but it could be any kind of interpolation algorithm it gives you this static model which is a single result and it shows the distribution in this case of a porosity in this particular field and then I show you the recoverable hydrocarbons of the base of the figure but if you do a co-simulation you integrate more than one variable say two you know porosity impermeability or some secondary variable or seismic data for example a tertiary variable if you need to you get a much more detailed solution and you can see that in the middle figure it's more homogeneous it gives you solutions that increase in this case the recoverable hydrocarbons and the image on the right is even better because you've now done it in a stochastic matter so the first two images are static they give you single solutions but the last image involves a co-simulation as opposed to co-creaking and it looks at all possible realizations 200 or 1000 whatever you've run so those images that you see show the degree of change that takes place in the inner well space and then the resulting probability curves on the right kind of summarize that the blue curve would be the one with best recoverables based on the better measurement of uncertainty and the black curve would be the middle one which is co-simulation or co-creaking and then the little red dot that you see there is simply the result of co-creaking itself so we really encourage the idea of a stochastic framework in order to assess the uncertainty the last one I want to show again I'll point to the University of Houston where I was teaching last year and this is one of my students who just presented this at the International Association of Mathematical Geosciences a few weeks ago at Penn State and this is kind of one of those unexpected uncertainties it's kind of one of those things that you think you'd know but maybe you don't or you forget and that has to do with missing data right missing values and sparse data so one of the things that I think Susan alluded to earlier in her talk was that the petroleum industry has a lot more data well that may be true in many ways but when it comes to the unconventionals we're not spending the money on drilling the wells logging the wells or evaluating the wells so you have all these horizontal wells all over the place with almost no information and the little information that might be there is proprietary so you just don't get to evaluate it properly so how do you manage uncertainty in that context and what the figure here shows particularly on the right are the different patterns that come up with missing values your petrophysicist is going to know this but the modeler may not and the little patterns that you see there indicate where missing values occur and the green zone the green area that you see this little stair step pattern is really at the base of the well because we stack our tools right so at the bottom of the well you might get your gamma ray but you might not get your neutron and as a consequence you get this funny pattern then if you're looking to fill in that data because of an interesting part of the formation you're going to need to subset it and look for well to have that information so that you can then use machine learning an appropriate way of looking at with machine learning and filling or predicting or imputing those values the blue values are randomly random issues or outliers for example the yellow or gold strip that you see there is just a completely missing log it wasn't available to the public or it wasn't available because it was never run and then the blue area at the bottom is where the hole was drilled deep but it wasn't logged that deep so by categorizing these things and finding similar wells in your area that have this information you can begin to impute or predict those values properly on the left you can see the result of missing values often leads to sparse data so here's something out of the Permian on the left you can see the distribution of those wells and then on the top if you try to krig it you don't get a very or do some kind of a simple algorithm to interpolate the data you don't get a very good solution so it's it's pretty broad in the solution if you do a conditional simulation what might look noisier look more heterogeneous but it's really no better you really need to add a secondary variable what are you going to do if you don't have seismic how do you manage that right so one suggestion is that you do basin modeling and that's a volume based model uses finite volume modeling you distribute the properties you use it as a secondary variable and you fill in the data and then reduce the uncertainty it'd be just like using seismic if you had it but you don't have it so there's ways we can mitigate these things but it's important to think about that and how you're going to manage that so at the end of that if you look at on the left again you see the basin model is on the upper figure on the left there and the lower figure is the minimized uncertainty version where we integrated the well data with a physics based model in order to get the proper spatial distributions of the properties of interest alright so about done here so just a few pondering things that we can be thinking about I think that one of the solutions that we'll have in terms of uncertainty is really the use of machine learning and big data analytics of course high performance computing there's no question that that's going to play a very important role for the future and using it properly is important so we want to make sure we don't lose the physics and the insight of these folks when we do that you don't want to just throw stuff in a neural net and say here's the answer you really want to make sure that you've captured the proper physics and chemistry to get the right solutions looking at maximum diversity realizations maybe there's a way we can shortcut the number of realizations we have by looking at maximum diversity so we can pinpoint the end members of those distributions in terms of dynamic simulation those are generally based on best estimate models a single solution how do we integrate multiple realizations into the dynamic simulator so that we can not just choose two or three or even one how can we integrate hundreds and look at the uncertainty in dynamic simulation can we use proxy modeling that's another popular thing to look at where we use machine learning to run the first few time steps on a simulation and then use machine learning to complete it reduction of nonlinear responses from data sparsity, diverse realizations and upscaling is another thing to consider and then in terms of also with respect to simulation dynamic simulation in unconventional reservoirs modeling the impact of natural fractures that's a huge deal what is the impact of a hydraulic fracture into a naturally fractured system I think that's where everybody's really looking to try and figure out when and where it's important the use of non-darcy flow equations in our simulation particularly in unconventional reservoirs is it important, is it not important sometimes yes, sometimes no what's the effect of a stimulated reservoir volume how do we model that so that's an important piece the reduction of uncertainty through unstructured grids or grid list topologies I think that's something that we can be looking at and then finally the last thing I'll mention is well placement which is really what we're all about modeling earth models, building earth models well placement how do we pass that information to a completion and then ultimately from production just because you have a great frack job or a completion job doesn't mean you're going to get really good production if you drill it well in the wrong place the best completion job isn't going to help you very much so we want to have good well placement minimize the uncertainty for that and then there's a whole level of minimization of uncertainty with respect to the completion methods themselves in terms of what components are used and how much of or how little of those components are needed to have effective effective work so that's it, that's all I have to say and I'll turn it back over to the chair okay Jeffrey, thank you let's move immediately to questions from the audience Jeff and Anna Colin and Jeffrey you both spoke to the importance of natural fractures to in shales and in hydrothermal systems what is the technology applications for identifying that and what's the state of the art currently so we rely a lot at least in the work I'm familiar with we rely a lot on borehole image logs and in trying to understand the state of stress and from that and knowing something about the structure surface geology trying to predict where the open fractures would be out of the population of fractures when you look at the entire population of fractures tends to be quite large and quite diverse in their orientations and their character but how about pre-drill I mean drilling's expensive pre-drill that's where Jim comes in having the geologic mapping and the structure pinned down as well as you can in advance through the combination of geologic mapping geophysics I think has proven to be critical because it's those structures that define where the fault intersections are and the favorable permeability and I don't know if Jim wants to add anything to that I could say more I'll cover it with a few slides later but basically we've characterized what some of the most favorable settings are and then gotten into the devils and the details why those particular settings are more conducive for fluid flow and then had good people like with the USGS modeling slip and dilation tendency so I'll add my two cents let me know if I'm getting too down into the weeds there but there are really three components that we need to look at for the natural fractures and one as Colin just mentioned borehole images are critical for us to have so if we have a borehole image we know exactly where those fractures are in the borehole and we know the number of fracture sets which is important the other part of that is the use of seismic data where we can look at seismic attributes and if you peel down into the seismic and you look at the smallest type of fractures that you can model from some attribute you can think of those then as fracture swarms or the likelihood of a fracture occurring so that would be our secondary data so I mentioned in the presentation that we have this ability to do co-simulation so we want to use this idea of co-simulation where we know that the data are pinned at the borehole images we know that that exists we use the fracture of the seismic attributes as a secondary variable and then we use the stochastic geostatistics to propagate the fractures in space and there's a third variable that can be used you can integrate multiple tertiary or multiple variables into the co-simulation process which could be gravity or magnetics or fractured density maps or even a hand-drawn map to make sure we're incorporating experience but obviously the biggest issue we have unlike mapping fractures on the surface we can't see them so that is the issue so we want to do multiple realizations then of these fractures and we want to make sure that we have the fracture attributes distributed not just the presence of the fracture but stochastic versions of the fracture aperture and the fillings of the fracture so we actually have that software to do that in the industry and it's quite complex and the last thing I'll mention on that is that we have to be more attentive to the complex effective stress field it's not a single value every time you hit a natural fracture or your near a natural fracture the effective stress field changes so we've taken approach using something called material point method which allows us to map the effective stress which now becomes a component in terms of how you orient your horizontal wells and then the kind of fracture completion methods that you might use and then the impact of those hydraulic fractures on that natural fracture system so that's the workflow so to speak question from the far end table down there my quick comment is everything you said in addition to that when I worked basins for fractures the key thing that I found most effective like in the montan basins or whatever you're working is the anisonic stress states first thing you want to do is understand the anisonic stress states for the area that you're working in you hit a strike slip regime or you're in a first fault regime understanding the anisonic stress state that you're dealing with first and then look across the basin and look at the different fracture sets and things near the wearable and then looking for fractured intensities in different areas but the anisonic stress state for that region is probably a good starting point can I make a comment here sure go ahead John you're right on and I think that when we're actually building a model of subsurface that includes natural fractures we we would start from the basin scale because the physics would take place at that scale dictate what's going to happen at every other scale you'd run into trouble if you just try to do the local area without understanding the bigger picture so it's really important to take in that basin scale model and drill it down to your area and you can inherit that information at every scale so you're correct Lynn so that last question anticipated mine a little bit I wanted to try to back up and think about this the overall question of what are we trying to know and how can we reduce the uncertainty and it seems to me that maybe one way to think about that is to ask something about the length scales that matter for a particular process so I'll pick a simple example because the harder ones are too hard but suppose you're thinking about the temperature distribution then there's some length scale associated with the underlying regional gradient there's some length scale associated with conduction there's some length scale associated with convection maybe through fractures and so I wonder if in thinking about a general problem can we gain anything by stepping back and asking which length scales matter maybe they're all there all the variability is on scales that are so small that we can't ever resolve that that might be one of the things that could happen but it also could be that the combination of drilling and other remote sensing might give us information that helps band the uncertainties in a particular area you can think about variability and permeability where which really matters the extremes dominate all the flow stuff that's different from something that has a big conductive smoothing so adding some physics to that process and then the last piece of it seems to me to be about sensing length scales so asking ourselves what under what circumstances can we do some sort of measurement that has a length scale appropriate to whatever we're trying to do now maybe this is all obvious to all the experts in the field that probably is but so I wonder if you could just comment on whether there's a fruitful path here or we already followed that pathway as far as it'll go I think you're absolutely right one of the when I referred probably a bit incoherently to working across these multiple scales for mapping subsurface temperature in the upper crust if you take for example thermal conductivity I would kill for a three-dimensional geologic map of the United States to a depth of 10 kilometers at scales of even a few kilometers in spatial resolution one of the real challenges we have is we often have very good information in a few local places we have what we think is pretty good information at the scales of tens to hundreds of kilometers and what we think are relatively good generic crystal properties but that that middle scale the middle scale that matters and then in some cases the very local scale where we don't have a lot of data we need we need things that the appropriate length scale that we don't have and probably are attainable by bringing together multiple datasets and working on them with at least in my case the thermal model in mind there's not more much more that I can add to that but I would say that there are two things that I would just simply state one is first of all your question is totally relevant and right on and the fact that that's really where a lot of research is being done today to determine these appropriate scales and one of the most important scales that we're not really understanding very well at all is the effect at the nano scale so flow at the nano scale and the impact of how hydrocarbons make it out in our business how the hydrocarbons make it out of the source rock into the surrounding shale so to speak at that nano scale and we're not going to understand how to model hydraulic fracturing and its relationship to natural fractures until we get that scale down there are others but I think that's the key there is we're trying to figure out the best scales I'm afraid we haven't exhausted the topic but we've exhausted the time we had available Jim would you say we need to move on at this point? I think we have one or two more questions since we have some interest and then we'll take a break. I think this should be a pretty quick question again Tom Crawford with the USGS I know that on the mineral side of things there's a real issue with preservation and accessibility to data and more often than not it's not the first company that explores an occurrence that actually defines an economic deposit it's maybe multiple companies down the line and in the geothermal world I'm wondering if that's typically the case and if so what about the preservation of that data from the original companies and the accessibility to that information down the line I know it's a big problem on the mineral side I'm wondering about geothermal it is a big problem it varies somewhat by state some state as you know the federal government doesn't require samples or data to be provided but some states in Nevada as one example do a fairly good job but basically it's the same as the minerals world the one if I could say benefit in a way from the fact that the geothermal industry is a small industry is most people know each other and they know who has what in their garage or what data trades happened with what companies 10 or 20 or 30 years ago the DOE has done I think a fantastic job of in two ways one in capturing a lot of the gray literature and a lot of the data that's out there in the public domain but in obscure places and also something that they didn't used to do but they have done in recent years is require that anything that they're helping to fund make sure that the data from that experiment come into the public domain okay Jim yeah okay join me in thanking our first panel this morning okay we're gonna we'll take a break we're gonna stay on schedule which means to return by 1115 okay so we already have ten minutes thank you is going to is chairing our next panel so let Joel I'm gonna turn it over to you well we have three speakers for this session I'll briefly go through their biographies a bit before we get started uh Jim Falls is going to lead off the session Jim is director of the matter of your minds and geology structural geologist primarily structural deformation uh he also recently has been well not so recently more than ten years now he's been involved in geothermal energy so he's our first speaker uh Azadeh I is our second speaker she'll be talking about uh geomechanical aspects of things and that's mainly what she works on with the itasca consulting group been working primarily on uh fractured rock and its mechanical numerical or mechanical aspects of rock doing numerical modeling and developing technologies looking both geothermal oil and gas and mining and our third speaker was on the first panel so I won't uh say any more about him but if you want to find out more you of course read their bibliographies in our report Jim I'll turn it over to you right uh thanks very much I'm gonna talk a little bit about some of the strengths as we've been able to make primarily in Nevada looking at some of the geothermal systems they are modeling them and and really kind of trying to define where we have hidden blind geothermal resources of significance so I'm gonna start here I actually have a laser pointer my kids say this is so 90s dad you know they're 20 something but anyways but basically there's a shot of McGinnis Hills and about the actual sort of center of Nevada and it's now the largest producing geothermal system in Nevada 165 megawatts is the latest from ORMAT as of a few days ago in terms of what three relatively new power plants all built in the past five years are producing there and so this is an amazing system it's a blind system no hot springs or steam vents here at all and it's now been developed into the largest system in Nevada and so I'll talk a little bit about these kinds of systems in the region because we think there's many more of them and just to acknowledge the significant support we have received from the geothermal technologies office at DOE which has funded most of this research over the past several years see if this actually works there we go so just real quick a quick summary this region the Great Basin region produces nearly a gigawatt well at least in terms of nameplate capacity of power plants typical systems produce anywhere from 10 or even under to as much as a couple of hundred maybe a few hundred megawatts I think at one time at COSO produce that much and and just so we're all on the same page one megawatt is enough energy for about 750 to a thousand homes so as others have mentioned Colin and others this region has vast more potential than this I think some of the estimates have been 30 gigawatts I actually think it's much much more than that especially when you consider that most of the conventional resources are blind or hidden and this is what we've been doing the past several years this is just geothermal production in Nevada and you can see there's a significant climb in terms of production in Nevada in the past ten years and the opening up of several additional new power plants which are shown by the purple stars on this map here alright so we know that this region is under crustal extension and of course crustal extension brings warmer parts of the lithosphere up closer to the surface and so the primary reason for the significant geothermal activity in this region is high geothermal gradient not necessarily magnetism magnetism is really isolated to a couple of small parts of this region and not a factor at least we don't think it's a factor in most of the geothermal activity in the region so the crust is pulling part we have lots of faults lots of active faults nice conduits pathways to bring hot water back up quickly to the surface to essentially exploitable levels so the secret is bringing these pathways and using the geologic and geophysical techniques to figure out where they are at depth so this is a typical geothermal reservoir this is just a simple version if you will portrayal fractured rocks as mentioned earlier that fracture permeability is the key to geothermal activity in this region and so that's a simple view but the devil is in the details and this is a nice 3D model that Drew Seiler has generated for the Brady's geothermal system that was mentioned earlier Drew is with the USGS now and so lots of complexity and so on to understand sort of where those sweet spots are in terms of fluid flow at depth so basically you know we need geothermal production wells injection wells etc and of course these are always at much deeper levels than any of the geothermal aquifers and we want to re-inject of course the water into back into the system to keep fluid loss at a minimum so we have a great region undergoing crustal extension high geothermal gradient you think it would be easy but it's not necessarily easy to develop a geothermal system there are a number of challenges one that I'll focus on meaning we don't have any surface hot springs or steam vents so finding sufficient permeability at depth is key and it's actually more important than finding temperature we have high temperature in this region the key is where do we have permeability at depth so any challenge creates an opportunity and the opportunities we have is we have lots of great techniques to characterize the favorable settings for the known systems in this region on that for about 15 years now a lot of innovative geologic and geophysical techniques to apply to that both in terms of characterizing on the surface and then after you've characterized going after similar systems based on subsurface data maybe in other regions we have lots of great software techniques now to develop 3D conceptual models and this is all culminated for some of us anyways over about the past 5 years in a DOE funded project the play fairway project that I'll describe in a little bit of detail here so this is just to portray the main challenge these are just a couple of cross sections and most of the fluid flow at least the geothermal fluid flow in this region is controlled by faults the fluids come up along the faults but then they commonly hit permeable layers and leak out and maybe the hot springs are several kilometers away from the upwelling at depth so if you drill over here you're in for a surprise because the temperature is actually going to go down with depth so how do we sort of focus back into finding those sweet spots if you will where the geothermal upwellings are actually occurring and then this is actually what we think is the most common case the fluids come up along faults leak out into permeable layers on the surface and the adjacent basins and really never see the light of day so how do we find those systems that have absolutely no reflection at the surface we know that 40% of the known systems in this region are actually blind and just about all of those have been discovered accidentally through agricultural wells or mineral wells that have found hot water and then many of those have been later developed into geothermal power plants so we estimated about three quarters of the resources are blind and so then you have a significant sort of exploration risk in finding these systems and developing them and so again you need high quality geologic geophysical data in order to have a successful exploration program so this is what we started doing now about 15 years ago culminated in a major DOE funded project in the early part of this decade and we started characterizing the structural settings the sort of fault patterns that are conducive to geothermal activity in this region by looking at the known systems so there's about 450 known systems we were able to catalog about 250 of them and we found that these four fault patterns controlled nearly 90% of the systems fault terminations where faults break up into multiple splays fault stepovers fault intersections and areas that we call accommodation zones where there's multiple faults intersecting one another and dying out and terminating as well so most then of the known systems are on rather they're on young faults paternity faults that accommodate the regional extension but less conspicuous faults not the major range bounding faults and the higher temperature systems actually all of the higher temperature systems occur along or near faults they're less than 750,000 years old so we found similar findings in other parts of the world and fundamentally though you need detailed geologic maps and of course we have a lot of techniques now that help to sort of facilitate the production of geologic maps like LiDAR but we also need good subsurface data then to find these systems at depth so just real quick most of you probably know what LiDAR is but we need to produce good geologic maps and realize that only about 20% of this region is mapped in sufficient detail like this and then but today we can expedite that mapping if we have the funds to acquire LiDAR and so this is just a view of an area of forested area as you sort of climb up into the sierras and then we'll reveal what that area really looks like with LiDAR high resolution topographic imaging and you can see a little stuff over here in a normal fault system and this is the kind of area that we might explore for a blind geothermal system so LiDAR is very important in moving forward and oops we went too far back one more please there we go so and then of course subsurface geophysical methods to elucidate what we have in the subsurface and of course gravity is very important noting lateral contrast in the density of rocks faults at depth magnetic data is very important might indicate altered rocks at depth, geothermal systems commonly correspond to mag lows magnetotoleric data very important basically mapping electrical resistivity at depth and geothermal systems commonly correspond to areas of low resistivity due to the alteration at depth or fluid saturation and seismic reflection data really sort of mapping the subsurface at depth and noting some of those favorable fault patterns if you will at depth so that we can go after some of these blind geothermal systems the problem is where do we have these kind of data in a particular region or in this region and most of this region lacks that kind of detail data that we need but nonetheless we sort of started combining the geophysical methods and the geologic methods to develop a geothermal potential map part of the play fairway program this started in 2014 phase 1 was then producing a geothermal potential map there we go for that box in Nevada about 96,000 square kilometers one third of Nevada we then did detailed studies of some of the promising areas within that box and then finished just finishing up the third phase where we did drilling of two of the most promising areas so this is our Great Basin Transact Nevada Transact again a high heat flow abundant quaternary faults and we had the advantage in this particular box of having a number of benchmarks that we could gauge against including 14 geothermal power plants and 34 areas where we knew the temperature was 130C or above so these were some of the parameters we used the parameters shown in red were what we used in creating that initial geothermal potential map all of these parameters were ultimately used in some of the detailed study areas and you can see on a regional basis we lacked a lot of the critical geophysical data sets to really understand geothermal potential but of course we did the best we could and then on a more local scale than commonly we have to acquire these data sets shown in blue so a huge challenge is basically availability of data and then an additional challenge is once you have all those data sets how do you combine that into something meaningful to actually evaluate geothermal potential and I purposely made this small because I don't have time to talk about it but basically we combined a number of those parameters about 10 parameters into evaluating regional scale permeability, local scale permeability and something we called intermediate permeability and then we combined permeability with heat to develop a play fairway map of the region a term that we stole from the oil industry and the warm colors indicate areas of higher geothermal potential cool colors lower potential and then from this we studied five areas in detail one of which I'll describe now and that's a place called Southern Gabs Valley which is sort of in basically West Central Nevada oops there we go this is very sensitive there we go so this is Southeast Gabs Valley and this is a new discovery we found a new blind geothermal system there have been absolutely no geothermal exploration in this region a master's student of mine did much of this work Jason Craig he should get significant credit but first we noticed that there was a favorable structural setting in this area there were active fault zones and so we went in and looked at it in a little bit more detail and there was a branch in the area we found warm ag wells we then did geothermometry that was promising then did a two meter temperature probe into this area and then we spent the money on additional geophysics I should say most of the geophysics was done by the USGS crew headed by Jonathan Glenn so we did detailed gravity detailed mag and detailed magnetotelurics we found then a sort of gravity anomaly intersecting gravity gradients indicating intersecting faults at depth of mag low indicating altered rocks at depth and a low resistivity anomaly indicating either altered rocks, clay cap or possibly this saturated fluid flow at depth all of these anomalies are co-located indicating the potential for a blind geothermal system so then that led to the third phase where we drilled this about a year ago, June of 2018 and right where we expected to find the system we did 124C at about 150 meters depth it's about a two or three kilometer long system that's probably viable for something maybe on the order of a 20 or 30 megawatt power plant so we've confirmed if you will a blind geothermal system in this area and I would say our methodology is guarded lead verified we did do a second system another system and another location in Nevada a place called Granite Springs Valley so we feel pretty good about this especially since there was nothing here initially not even any indicator of geothermal activity at the surface not so different than finding hydrocarbons in most of the world so and I just want to compare phase one and phase two results real quick this is phase one it's a blob okay we knew there was a favorable structural setting and then phase two then when we did additional geologic work and especially the geophysical work the basin blossoms with data if you will in terms of understanding where the most favorable setting might be within that initial blob in other words we're vectoring into the most promising area the area that has the highest probability of a geothermal system we drilled it and we found one so this is what most of the region is like in terms of availability of data and this is where we want to get if eventually we can have detailed gravity MAG MT geologic work that covers most of the region alright so conclusion it's a great region lots of favorable settings for geothermal activity a favorable tectonic setting vast geothermal resources I think far greater than the 30 gigawatts that are estimated nearly 90% of the known systems occur in four types of fault patterns and the main challenges are finding sufficient permeability at depth in those blind systems but you can have a systematic workflow where you're combining geologic and geophysical data to essentially develop 3D geologic maps and then reduce the risk of where you ultimately drill plus you can combine that with a new generation of geothermal potential maps that are combining multiple parameters that play fairway analysis approach and we think there are many more McGinnis-Fills than to be developed in the region we're now beginning to apply machine learning techniques to take this to the next level but again the major challenge is availability of data through most of this region so thanks very much thank you Jim we'll hold the questions until after the three speakers has the date today I'm going to talk about fracture network engineering and the role of numerical modeling in engineering of subsurface problems basically we have come to an understanding that fracture network and pre-existing fractures are important to many of the industries that are important for us including hydraulic fracturing in hydrocarbon reservoirs enhanced geothermal systems block cave mining, radioactive based storage and also CO2 sequestration for example we now know that the hydraulic fracturing in shale gas is very complex these hydraulic fractures are not planar surfaces they interact with pre-existing fractures which results in very complex geometries and fracture network engineering is the engineering of rock masses such that we get the desired performance and this performance can be different from one industry to another with the extensive use of numerical modeling and also correlation with field observations such as micro seismic or seismic data so why fracture network engineering is so challenging in different industries to my view it comes from two different reasons or there are two contributing factors one is the complex mechanisms so we are dealing with very complicated mechanical behavior coupled usually with hydraulic behavior and sometimes with thermal and chemical responses and this gives rise to a very complex engineering behavior but then also we are dealing with uncertainty and this uncertainty is coming from different reasons one is the lack of access to subsurface the other one is the heterogeneity we are dealing with rock masses that are heterogeneous at different scales from micro to like kilometer scale and finally there is a significant presence of discontinuous surfaces such as pre-existing fractures so this picture here tries to show schematically what fracture is we tend to rely on field observation one of the most important one would be micro seismic data analyze these data and then feed them to different type of numerical modeling at different scales and use these numerical modeling to gain insight into field characteristics for example what are the status of stresses what is the fracture properties but also to gain a better understanding of the mechanical behavior for example how hydraulic fractures are formed and how they interact with pre-existing fractures and use this understanding both in terms of field characterization and also in terms of mechanical behavior and feed it back to the model in real time to improve our field characterization and also improve our design and operation so this graph here tends to show the project life cycle and how traction network engineering fits in usually the project life cycle starts with resource targeting site characterization coming up with the design criteria and it's through this design process that numerical modeling traditionally come into play and traditionally numerical modeling has been extensively used as a validation tool eventually we come up with an engineer design and some sort of field observation sometimes when there's a deviation in response, in expected response we again rely on numerical modeling to gain a better understanding of what went wrong but in the workflow that we are advocating for numerical modeling is ubiquitous through the life cycle of the project so we use numerical models at all including microscale, laboratory scale, borehole regional and reservoir scale to again use these information and numerical modeling to gain a better understanding of the data constraint uncertainty and then continuously update these models which are multi-scale but coupled meaning that all of these models eventually need to conform to one set of data and that by itself is very important in constraining the uncertainty and use this process and continuously feed to our site characterization to design and to operation so what are the characteristics of these numerical models first what we are advocating for is coupled geomechanical and micro seismic modeling basically we are using micro seismic modeling as a way to calibrate our geomechanical model but then also we are advocating for the use of this continuum modeling so basically in plain words that means that discrete fractures are important in these systems fractures and their individual results in mechanisms that cannot be captured with traditional continuum models such as finite element or finite difference and therefore explicit representation of these fractures into geomechanical model are important for subsurface engineering then these models must be physically based basically mechanical, thermal, hydraulic and chemical processes need to be formulated explicitly in these models and finally there is a coupled model that produces synthetic micro seismicity and by synthetic micro seismicity I mean being able to predict, slip on these fractures and translate that to individual events with magnitude their time, location and eventually coming up with a micro seismic cloud so here I have one example that we applied this approach to underground mining field study and here hydraulic fracturing was used as a way to precondition the mine basically coming up with a method to reduce induced seismicity as a result of mining operation so here what they do was that there were a number of boreholes and they inject into these boreholes sequentially in different stages with the purpose of creating hydraulic fracturing and thus changing the state of stress and then using this precondition formation and subsequently do the mining excavation so we started with a borehole model and we modeled the process of injection into each of those individual boreholes we captured the synthetic micro seismicity and then we used this