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Rapid Computation Of Permeability From Micro-CT Images On GPGPUsNormal access

Authors: F.O. Alpak and M. Araya-Polo
Event name: ECMOR XVI - 16th European Conference on the Mathematics of Oil Recovery
Session: ECMOR XVI Poster Session 2
Publication date: 03 September 2018
DOI: 10.3997/2214-4609.201802184
Organisations: EAGE
Language: English
Info: Extended abstract, PDF ( 1.99Mb )
Price: € 20

Summary:
Digital rock physics (DRP) is a rapidly evolving technology targeting fast turnaround times for repeatable core analysis and multi-physics simulation of rock properties. We develop a rapid and scalable distributed-parallel single-phase pore-scale flow simulator for permeability estimation on real 3D pore-scale micro-CT images using a novel variant of the lattice Boltzmann method (LBM). The LBM code implementation is designed to take maximum advantage of distributed computing on multiple general-purpose graphics processing units (GPGPUs). We describe and extensively test the distributed parallel implementation of an innovative LBM algorithm for simulating flow in pore-scale media based on the multiple-relaxation-time (MRT) model. The novel contributions of this work are (1) integration of mathematical and high-performance computing components together with a highly optimized implementation and (2) quantitative results with the resulting simulator in terms of robustness, accuracy, and computational efficiency for a variety of flow geometries including various types of real rock images. We report on extensive tests with the simulator in terms of accuracy and provide near-ideal distributed parallel scalability results on large pore-scale image volumes that were largely computationally inaccessible prior to our implementation. Permeability estimation results are provided on large 3D binary microstructures including real rocks from various sandstone and carbonate formations. We quantify the scalability behavior of the distributed parallel implementation of MRT-LBM as a function of model type/size and the number of utilized new-generation NVIDIA V100 GPGPUs for a panoply of permeability estimation problems.


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