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Core samples were collected from three wells, one onshore and two offshore, from Qatar’s Upper Jurassic Arab D reservoir. The samples were subjected to multiproxy petrographic and chemical analyses to identify their micro- and nanoporosity types and understand their evolution and destruction. Based on the petrographic and petrophysical properties of studied rocks, the Arab D succession was divided into seven rock types. Primary microporosity includes intergranular and interplanar, while secondary types include vuggy, intercrystalline, moldic, dissolution, pyrite displacement, microfracture, and microbial boring. Primary micropores were found mainly between the micrite grains in the lime mudstone facies, between the grains or the plates of clay minerals. Secondary micropores result from open and closed diagenetic systems. The open diagenetic system led to the development of dissolution and moldic micropores, while the closed system created pyrite displacement and boring porosity. Mechanical stress due to crystal growth or displacement generated microfractures. Micropores were destroyed either by cementation, clay minerals growth, dolomitization, or microbial pustular overgrowth. Microporosity was important in quantity and varied in nature in the mud-supported rocks. They are similar to macropores in grain-supported sediments but of less importance. The complex lithology of the studied rocks has significantly influenced the development and destruction of the porosity system of the Arab Formation.

Tight and unconventional reservoirs such as shales are rich in clay minerals that give rise to several fluid-rock interactions. The effect of such fluid-rock interactions is manifested at multiscales. The fluid-rock interactions induce changes in various physical responses of the rock, which is termed as multiphysics. An underlying property that influences the multiphysics process is wettability which has remained a conundrum for shale researchers. This chapter provides a detailed perspective on shale wettability in the context of fluid-rock interactions. Pore structural alteration induced by fluid-rock interactions is also discussed specifically from the standpoint of recent advances using digital techniques. The chapter also presents recent developments in explaining the role of pore sizes in causing configurational diffusion of water and oil in shales. Lastly, multiphysics constitutive modeling to predict shale rock responses is discussed. Specifically, new developments regarding the incorporation of sorptive fluid-rock interaction in constitutive models are presented. 2023 Elsevier B.V. The authors would like to acknowledge the support of the Qatar National Research Fund (a member of the Qatar Foundation) through Grant # NPRP12S-0305-190235 and NPRP11S-1228-170138. The authors, particularly M.A.Q.S, H.R., and K.R., also acknowledge the support of the Australian Research Council (ARC) through the Discovery Project Grant (DP200102517). The findings achieved herein are solely the responsibility of the authors. Scopus

SummaryShale, which has pores as small as 10 nm, is economically viable for hydrocarbon recovery when it is fractured. Although the fracture toughness dictates the required energy for the improvement, the existing techniques are not suitable for characterization at scales smaller than 1 cm. Developing practical methods for characterization is crucial because fractures can contribute to an accessible pore volume at different scales. This study proposes a conceptual model to characterize the anisotropic fracture toughness of shale using nanoindentations on a sub-1-cm scale. The conceptual model reveals the complexities of characterizing shales and explains why induced fractures differ from those observed in more-homogeneous media, such as fused silica. Samples from the Wolfcamp Formation were tested using Berkovich and cube-corner tips, and the interpreted fracture toughness values are promising. The conceptual model is the first application of the effective-medium theory for fracture toughness characterization using nanoindentation. In addition, it can quantify fracture toughness variations when using small samples, such as drill cuttings.

Capillary pressure plays an essential role in controlling multiphase flow in porous media and is often difficult to be estimated at subsurface conditions. The Leverett capillary pressure function J provides a convenient tool to address this shortcoming; however, its performance remains poor where there is a large scatter in the scaled data. Our aim, therefore, was to reduce the gaps between J curves and to develop a method that allows accurate scaling of capillary pressure. We developed two mathematical expressions based on permeability and porosity values of 214 rock samples taken from North America and the Middle East. Using the values as grouping features, we used pattern-recognition algorithms in machine learning to cluster the original data into different groups. In each wetting phase saturation, we were able to quantify the gaps between the J curves by determining the ratio of the maximum J to the minimum J. Graphical maps were developed to identify the corresponding group for a new rock sample after which the capillary pressure is estimated using the average J curve of the identified group and the permeability and porosity values of the rock sample. This method also provides better performance than the flow zone indicator (FZI) approach. The proposed technique was validated on six rock types and has successfully generated average capillary pressure curves that capture the trends and values of the experimentally measured data by mercury injection. Moreover, the proposed methodology in this study provides an advanced and a machine-learning-oriented approach for rock typing. In this paper, we provide a reliable and easy-to-use method for capillary pressure estimation in the absence of experimentally measured data by mercury injection. Copyright 2022 Society of Petroleum Engineers We would like to acknowledge the support of Qatar National Research Fund (a member of Qatar Foundation) through Grant # NPRP11S-1228-170138. The findings achieved herein are solely the responsibility of the authors. Scopus