Obtaining capillary pressure curves from resistivity measurements in low-permeability sandstone
The increasing global demand for energy necessitates exploring and developing low-quality prospects, e.g., low-permeability reservoirs, which contain substantial hydrocarbon resources and have the potential to fill the gap in the energy markets. Typically, modeling fluid flow using reservoir simulat...
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| Format: | Article |
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Elsevier B.V.
2023
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| Online Access: | http://scholars.utp.edu.my/id/eprint/34135/ https://www.scopus.com/inward/record.uri?eid=2-s2.0-85143690237&doi=10.1016%2fj.petrol.2022.111297&partnerID=40&md5=89908de2abceff76500655203eb7cd49 |
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| Summary: | The increasing global demand for energy necessitates exploring and developing low-quality prospects, e.g., low-permeability reservoirs, which contain substantial hydrocarbon resources and have the potential to fill the gap in the energy markets. Typically, modeling fluid flow using reservoir simulators requires capillary pressure curves as an input. Nonetheless, laboratory capillary pressure measurements in low-permeability samples are time-consuming and challenging. On the contrary, resistivity measurements are easier to perform in the laboratory and offer a different prospect for obtaining capillary pressure curves. This paper proposes a new approach for obtaining capillary pressure curves from resistivity measurement in low-permeability sandstone using fractal theory and genetic algorithm. First, the fractal pore system is characterized as tortuous square and triangular capillaries to account for angular pores. Afterward, the drainage process is simulated to develop an innovative electrical resistivity model in fully and partially saturated porous media. Next, the genetic algorithm matches laboratory-measured resistivity data and obtains the developed model parameters. Afterward, the matched parameters are adopted in the drainage capillary pressure model to generate capillary pressure curves. The proposed model's reliability is verified by analyzing the prediction results of eighteen sandstone core samples. Furthermore, the developed model performance is compared with different models from the literature, and the results indicated its superiority in predicting capillary pressure curves. © 2022 Elsevier B.V. |
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