Techniques of High Performance Reservoir Simulation for Unconventional Challenges

The quest to improve the performance of reservoir simulators has been evolving with the newly encountered challenges of modeling more complex recovery mechanisms and related phenomena. Reservoir subsidence, fracturing and fault reactivation etc. require coupled flow and poroelastic simulation. These features, in turn, bring a heavy burden on linear solvers. The booming unconventional plays such as shale/tight oil in North America demand reservoir simulation techniques to handle more physics (or more hypotheses). This dissertation deals with three aspects in improving the performance of reservoir simulation toward these unconventional challenges. Compositional simulation is often required for many reservoir studies with complex recovery mechanisms such as gas inject. But, it is time consuming and its parallelization often suffers sever load imbalance problems. In the first section, a novel approach based on domain over-decomposition is investigated and implemented to improve the parallel performance of compositional simulation. For a realistic reservoir case, it is shown the speedup is improved from 29.27 to 62.38 on 64 processors using this technique. Another critical part that determines the performance of a reservoir simulator is the linear solver. In the second section, a new type of linear solver based the combinatorial multilevel method (CML) is introduced and investigated for several reservoir simulation applications. The results show CML has better scalability and performance empirically and is well-suited for coupled poroelastic problems. These results also suggest that CML might be a promising way of precondition for flow simulation with and without coupled poroelastic calculations. In order to handle unconventional petroleum fluid properties for tight oil, the third section incorporates a simulator with extended vapor-liquid equilibrium calculations to consider the capillarity effect caused by the dynamic nanopore properties. The enhanced simulator can correctly capture the pressure dependent impact of the nanopore on rock and fluid properties. It is shown inclusion of these enhanced physics in simulation will lead to significant improvements in field operation decision-making and greatly enhance the reliability of recovery predictions

Doctor of Philosophy

dissertationShale resources provide a tremendous opportunity for a long-term viable energy source, but the lower hydrocarbon recovery rates are hindering the economic development of shale reservoirs. One of the main reasons for the lower hydrocarbon recovery rates is the inadequate understanding of the fate of various injected fluids and the recovered hydrocarbons during various stages of exploration and production. As Darcy's law is limited in describing the multiphase fluid transport in shale, a comprehensive simulation framework is necessary, enabling the replication of the nanometer and subnanometer pores found in organic and inorganic matrices, and the simulation of the multiphase fluid flow in these nanopores, thus improving the comprehension of the pore-scale fluid transport process in shale reservoirs. A molecular dynamics simulation-based framework is developed in present research to address the above-defined challenges. The applications of various open-source molecular modeling tools are integrated to develop molecular pore structures found in the organic and inorganic matrices. An application of the general-purpose DREIDING force field is extended to simulate the kerogen. A gas-liquid (methane and water) transport is simulated in nanopores confined in the organic and inorganic matrices, and various dynamic transport properties of fluids (subjected to confinement) are determined to gain the qualitative and the quantitative understanding of the fluid flow. The present research provides a powerful molecular dynamics simulation-based framework that will enable the development of more complex models of nanoporous shale structures and address numerous challenges encountered in hydrocarbon recovery from shale reservoirs

Supercomputing Frontiers

This open access book constitutes the refereed proceedings of the 6th Asian Supercomputing Conference, SCFA 2020, which was planned to be held in February 2020, but unfortunately, the physical conference was cancelled due to the COVID-19 pandemic. The 8 full papers presented in this book were carefully reviewed and selected from 22 submissions. They cover a range of topics including file systems, memory hierarchy, HPC cloud platform, container image configuration workflow, large-scale applications, and scheduling

A Multi-Core Numerical Framework for Characterizing Flow in Oil Reservoirs

Presented at the SCS Spring Simulation Multi-Conference – SpringSim 2011, April 4-7, 2011 – Boston, USA Awarded Best Paper in the 19th High Performance Computing Symposium and Best Overall Paper at SpringSim 2011.This paper presents a numerical framework that enables scalable, parallel execution of engineering simulations on multi-core, shared memory architectures. Distribution of the simulations is done by selective hash-tabling of the model domain which spatially decomposes it into a number of orthogonal computational tasks. These tasks, the size of which is critical to optimal cache blocking and consequently performance, are then distributed for execution to multiple threads using the previously presented task management algorithm, H-Dispatch. Two numerical methods, smoothed particle hydrodynamics (SPH) and the lattice Boltzmann method (LBM), are discussed in the present work, although the framework is general enough to be used with any explicit time integration scheme. The implementation of both SPH and the LBM within the parallel framework is outlined, and the performance of each is presented in terms of speed-up and efficiency. On the 24-core server used in this research, near linear scalability was achieved for both numerical methods with utilization efficiencies up to 95%. To close, the framework is employed to simulate fluid flow in a porous rock specimen, which is of broad geophysical significance, particularly in enhanced oil recovery