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This work applies the pore network modeling methodology, a widely used technique for simulating multiphase flow in porous media. A case study was designed to estimate key petrophysical parameters such as porosity, permeability, relative permeabilities, tortuosity, capillary pressure, and effective diffusivity in porous media generated using OpenPNM, based on data obtained from SEM images of sedimentary rocks from the Chicontepec paleochannel.
The numerical experiment simulated two immiscible fluids under imbibition and drainage scenarios, reproducing conditions representative of displacement processes in reservoirs. For geometric characterization, ImageJ was used for quantitative image analysis, calculating pore and throat size distribution, diameter, and surface area. In parallel, displacement tests were conducted at the Petroleum Engineering Laboratory of UANL to obtain porosity and permeability of rock samples, aiming to validate the numerical results.
The results show strong consistency with experimental data and values reported in the literature, confirming the model’s ability to reproduce multiphase flow phenomena in complex porous media. This methodology provides a robust tool for digital petrophysical characterization, with direct applications in the oil industry, particularly for the evaluation and optimization of unconventional reservoirs.
| References | Pore Network Modeling Framework in Python — OpenPNM 3.5.0.Dev2 documentation. (s. f.). OpenPNM. https://openpnm.org/. C.G. Aguilar-Madera, J.V. Flores-Cano, V. Matías-Pérez, J.A. Briones-Carrillo, F. Velasco-Tapia, “Computing the permeability and Forchheimer tensor of porous rocks via closure problems and digital images, Advances in Water Resources”, Volume 142, 2020, 103616, ISSN 0309-1708, https://doi.org/10.1016/j.advwatres.2020.103616. |
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| Country | Nuevo León, México |
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