Improving the Performance of MARS Reservoir Simulator on Cray-2 Supercomputer

Li, K.G.; Doğru, Ali H.; McDonald, A.E.; Merchant, A.R.; Al-Mulhem, Abdulrahman A.; AlRuwaili, Saleh B.; Sobh, Nahil; Al-Sunaidi, H.A.

doi:10.2118/29856-ms

Cited by 9 publications

(3 citation statements)

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“…Reservoir simulations have been studied for decades by researchers, and various techniques have been developed to model new recovery processes and to accelerate computer simulations, including new reservoir models and numerical methods [27,28] , nonlinear methods [23,28] , linear solvers and preconditioner techniques [17,11,12,13,14,15] , and parallel computing [1,2] . Shiralkar and his collaborators [4] developed a parallel simulator, FALCON, using FORTRAN 90 and high performance FORTRAN (HPF), which could run on a variety of computing platforms, such as Cray T3D and T3E, SGI Origin 2000, Thinking Machines CM5 and IBM RS6000.…”

Section: Introductionmentioning

confidence: 99%

A Parallel Simulator for Massive Reservoir Models Utilizing Distributed-Memory Parallel Systems

Liu,

Shen,

Chen

et al. 2017

Preprint

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This paper presents our work on developing parallel computational methods for two-phase flow on modern parallel computers, where techniques for linear solvers and nonlinear methods are studied and the standard and inexact Newton methods are investigated. A multi-stage preconditioner for two-phase flow is applied and advanced matrix processing strategies are studied. A local reordering method is developed to speed the solution of linear systems. Numerical experiments show that these computational methods are effective and scalable, and are capable of computing large-scale reservoir simulation problems using thousands of CPU cores on parallel computers. The nonlinear techniques, preconditioner and matrix processing strategies can also be applied to three-phase black oil, compositional and thermal models.

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Section: Introductionmentioning

confidence: 99%

A Parallel Simulator for Massive Reservoir Models Utilizing Distributed-Memory Parallel Systems

Liu,

Shen,

Chen

et al. 2017

Preprint

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“…Parallel computing techniques were also adopted in the petroleum industry . Rutledge et al , implemented a parallel compositional simulator on massive single instruction, multiple data computers using the IMPES method.…”

Section: Introductionmentioning

confidence: 99%

A family of constrained pressure residual preconditioners for parallel reservoir simulations

Liu

Wang

Chen

2015

Numerical Linear Algebra App

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Summary Large‐scale reservoir simulations are extremely time‐consuming because of the solution of large‐scale linear systems arising from the Newton or Newton–Raphson iterations. The problem becomes even worse when highly heterogeneous geological models are employed. This paper introduces a family of multi‐stage preconditioners for parallel black oil simulations, which are based on the famous constrained pressure residual preconditioner. Numerical experiments demonstrate that our preconditioners are robust, efficient, and scalable. Copyright © 2015 John Wiley & Sons, Ltd.

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“…There has been considerable effort in developing and applying parallel computing techniques in reservoir simulation since 1980s (Chien and Northrup 1993;Chien et al 1997;Killough and Bhogeswara 1991;Killough et al 1997;Li et al 1995;Parashar et al 1997;Rame and Delshad 1995;Rutledge et al 1992;Scott et al 1987;Shiralkar et al 1997;Wheeler and Smith 1990). Black oil model (Rutledge et al 1992;Wheeler and Smith 1990), compositional model (Chien et al 1997;Dogru et al 2002;Killough and Bhogeswara 1991), chemical flooding model (Rame and Delshad 1995) and dual porosity dual permeability model (Al-Shaalan et al 2003) has been numerically solved using different paradigms of parallel simulation, including shared memory, distributed memory, and GPGPUs (Dogru et al 2013) with structured grids and unstructured grids (Fung and Dogru 2008b).…”

Section: Introductionmentioning

confidence: 99%

On Robust and Efficient Parallel Reservoir Simulation on Tianhe-2

Guan¹,

Qiao

Zhang

et al. 2015

Day 3 Wed, September 16, 2015

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Parallel reservoir simulators are now widely used with availability of super computers. Modern massively parallel supercomputers demonstrate great power for simulating large-scale reservoir models. However, improving scalability and efficiency for fully implicit methods on emerging parallel architectures is still challenging. In this paper, we present a robust discretization together with a parallel linear solver algorithm; and we explore the parallel implementation on the world's fastest supercomputer Tianhe-2.Starting with a general compositional model, we focus on the black oil model and developed Parallel eXtension Framework for parallelizing the serial simulator. A parallel preconditioner based on fast auxiliary space preconditioning (FASP) is applied to solve the Jacobian system arising from the fully implicit discretization. The parallel simulator was validated using large-scale black oil benchmark problems, for which parallel scalabilities were tested. Giant reservoir models with over 100 million grid blocks have been simulated within a few minutes, and test the strong scalability of AMG solver with 1 billion unknown. We also demonstrate the parallelization and acceleration using Intel Xeon Phi coprocessors. In the end, the efficiency of the parallel simulator is illustrated by a giant reservoir using up to 10,000 cores, for which the CPU and communication time are summarized for the linear and nonlinear algorithms.

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Improving the Performance of MARS Reservoir Simulator on Cray-2 Supercomputer

Abstract: The computational efficiency of a simulator-MARS-that is heavily used ..._m ..i-ni{iaantl.,

Cited by 9 publications

References 1 publication

A Parallel Simulator for Massive Reservoir Models Utilizing Distributed-Memory Parallel Systems

A Parallel Simulator for Massive Reservoir Models Utilizing Distributed-Memory Parallel Systems

A family of constrained pressure residual preconditioners for parallel reservoir simulations

On Robust and Efficient Parallel Reservoir Simulation on Tianhe-2

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