Understanding O/G Shale Reservoir Tortuosity by Imaging Characterizations

Abstract

A shale reservoir rock sample has been imaged successfully at 40X (millimeter scale), 400X (micrometer scale), and 4000X (nanometer scale). All captured images have been processed with morphological approach utilizing big data for porosity with pore size distribution as well as tortuosity. 1D, 2D and 3D pre-logic models are developed. And heterogeneity post-logic models are also developed. Nano pores are dominated in shale rock; as a result, the tortuous paths recognized are very complex yet very hopeful for many production scenarios. The prepared shale rock samples in the form of rock fragments will be imaged and characterized for porosity morphology, pore size distributions, and tortuosity in 2D format utilizing SEM-BSE imaging techniques. The generated images will be quantified using pre-defined logic (10-classes of pore ranges, pore counts, pore frequency percent, and pore area). The data generated will be used to estimate tortuosity. Tortuosity investigations are set for different magnifications X40-millimeter scale, X400-micrometer scale, and X4000-nanometer scale, yielding the total formation/ sample experiments to become 3 magnifications X 1 sample = 3 experiment suites to ensure tortuosity representations for all shale pore magnification. The overall objective is to increase shale reservoir knowledge and awareness of imaging characterizations that inherits increasingly sophisticated and unconventional technologies, which make the production of unconventional resources faster, accurate, and economically efficient. Another objective is to justify the exploitation of organically rich unconventional Oil and Gas (O&G) shale reservoirs that were always ignored by operators seeking easier production and faster returns on investments, as potential sources of significant natural gas and liquid reserves. The final objective is to introduce a reliable method to quantify tortuosity for unconventional reservoirs that seeks new physics in order to advance stimulation, advance reservoir characterization, and advance recovery efficiencies and production improvement.