28 Geoscience and Hydrogeology in the AI Era: From Predictive Models to Real-Time Applications (Posters)

This session offers a unique platform to showcase advancements in Artificial Intelligence (AI), Machine Learning (ML), and physics-informed methodologies, focusing on topics in hydrogeology, subsurface flow and transport, real-time geophysical inversion, critical minerals, and energy applications.

Sunday, 19 October 2025
8:00 AM - 5:30 PM
HBGCC, Hall 1

Stochastic Modeling and Pore Scale Simulation of Fluid Flow for Permeability Predictions in Carbonates

Paper number: 28-6
Program: Technical Sessions
Time: 8:00 AM – 8:00 AM

Authors

Abstract

Carbonate reservoirs comprise the world's major share of hydrocarbon reserves. The geometrically complex pore structures of carbonates are highly heterogeneous, which makes it difficult to predict the flow properties by using traditional methods that usually fail to capture the intricate heterogeneities at the pore level. Therefore, pore-scale modeling is essential in understanding the flow and transport properties of carbonate rocks. One of the widely used techniques in pore-scale modeling is using micro-CT imaging techniques to construct 3D images, which provide a visual representation of pore microstructures. In this work, we incorporate 3D images generated using high-resolution micro-CT images, numerical simulations, and data-driven approaches to predict the permeability of carbonates rocks. By using porosity and pore size distribution data obtained from Micro-CT images, we use a stochastic modeling approach to generate several pore microstructures of the same porosity with different pore connectivity to overcome the limitations of traditional techniques. This approach is validated by comparing experimental permeability data with pore-scale simulations conducted on both generated pore microstructures and 3D images reconstructed from stacked micro-CT slices, using the computational fluid dynamics software Star-CCM+. Four carbonate samples are used to validate the proposed stochastic modeling approach. The preliminary results show close porosity and permeability values for the experimental and simulated approaches. In the future, we expect to develop this modeling approach for two-phase flow, which will be beneficial in a broad range of geoscience applications like gas sequestration, groundwater exploration, and environmental protection.

Geological Society of America Abstracts with Programs. Vol. 57, No. 6

doi: 10.1130/abs/2025AM-412146

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