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Pore Type Characterization and Classification in Carbonate Reservoirs


Pore space geometry affects permeability and water saturation, becoming an important aspect of reservoir characterization. Existing pore space classifications for carbonate reservoirs include some genetic, geometrical and petrophysical aspects, but the influence of diagenesis in the pore system is poorly described. The purpose of this study is to develop a new pore classification applied to carbonate rocks that encompasses pore geometry, pore connectivity and the influence of diagenesis in the pore system by generating a quantitative result in order to identify and map reservoir flow units and diagenetic trends. This new classification is based on features observed in thin sections and hand samples, being a fast and less expensive method to evaluate porosity characteristics. Pore geometry data come from image analysis of scanned thin sections. Area, perimeter, maximum elongation and minimum width of the pores are measured. These data are used as input in an equation, and a numerical result gives information about the pore complexity and roughness. Pore connectivity data come from the definition of pore types, pore size distribution, patchiness (spatial distribution of pores), and characteristics of cementation, dolomitization and dissolution processes. Giving values for each of these textural characteristics, a numerical result also is generated through an equation, which gives information about pore connectivity. The influence of diagenesis in the pore system is evaluated through the analysis of pore types, cement textures, characteristics of dissolution (if fabric selective or not), and dolomitization, combined with the intensity of each of these processes. The diagenetic parameter is calculated similarly to the connectivity parameter, but the numerical value for each textural characteristic is different, so it gives information about diagenesis instead of connectivity. The final result is a two axis graph (pore geometry versus pore connectivity) with diagenetic data superimposed in color. This graph shows, for each sample, if the pores have simple or complex geometry, low or high connectivity, and their degree of diagenetic influence. This information helps to define petrophysical rock types and evaluate the role of diagenesis in enhancing or reducing reservoir quality. It can also be displayed as maps, so variations in the pore system geometry can be visualized in space and lateral diagenetic trends can be defined.