435137 Enhancing the Predictive Capability of the Pore-Scale Multiphase Fluid Transport in Unconventional Reservoirs: A Molecular Dynamics Simulation Approach

Tuesday, November 10, 2015: 10:35 AM
252A/B (Salt Palace Convention Center)
Gorakh Pawar, Mining Engineering, University of Utah, Salt Lake City, UT and Ilija Miskovic, The University of Utah, Salt Lake City, UT

A predictive understanding of the complex pore-scale multiphase fluid transport in unconventional reservoirs is crucial in optimizing the hydrocarbon recovery from these low-mobility reservoirs and understanding the water uptake into the reservoir formations. Currently used methods for assessment of the pore-scale processes, including numerical reservoir modeling and experimental studies, are unable to capture the details of the pore-scale multiphase fluid flow in unconventional reservoirs adequately. Here we present a molecular dynamics (MD) approach for the most-detailed pore-scale fluid flow characterization in shales. The process of enhanced gas recovery at the reservoir conditions is investigated by simulating the injection of water into methane-saturated shale nanopore. The pore sizes ranging from 2 nm to 7 nm are used for the analysis. All simulations are run for the period of 1 ns, and relevant transport properties are evaluated.

A correlation between self-diffusion coefficient of water is established for different pore sizes. Further, the methane recovery and the water uptake in the shale nanopore is evaluated for various water injection pressures. It was observed that the self-diffusion coefficient of water increases initially with increased in pore size  up to 4 nm but reduces with further increase in the pore size, suggesting the role of surface forces on the fluid transport due to shale-fluid interactions. Further, it was seen that the methane recovery rates increases with increase in the water injection pressure. Finally, it was observed that the water uptake increases with increase in the shale nanopore size.

The present study demonstrates the capability of the MD in modeling the most detailed fluid transport processes in shale reservoirs. Furthermore, by establishing a correlation between fluid properties over different pore sizes, this study provides a baseline for development of new simulation tools that can significantly improve our predictive capabilities necessary for optimization of process-level parameters. Finally, it enables the detailed characterization of the water uptake into the reservoir formation that is crucial to estimate the significant amount of water loss during the hydraulic fracturing process.

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