A Next-Generation Parallel Reservoir Simulator for Giant Reservoirs

Doğru, Ali H.; Fung, Larry S.K.; Middya, Usuf; Al-Shaalan, Tareq M.; Pita, Jorge A.; Hemanthkumar, Kesavalu; Su, H.J.; Tan, James C.T.; Hoy, H.; Dreiman, W.T.; Hahn, W. A.; Alharbi, Rawan; Alyoubi, Ahmad; Al-Zamel, Nabil; Mezghani, M.; Almani, Tameem

doi:10.3997/2214-4609-pdb.170.spe119272

Cited by 38 publications

(4 citation statements)

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“…CPR restricts the full system residual to the pressure part (which has been shown to affect the convergence most negatively by Behie and Vinsome [4]) and solves it approximately, then, applies the pressure solution to constrain the residual on the full system. Its robustness and efficiency have been demonstrated in many industry-standard reservoir simulators such as Schlumberger's ECLIPSE [5] and Saudi Aramco's GigaPOWERS [6]. GigaPOWERS is the first simulator capable of handling over billion-cell models and its code has been used a baseline for this paper.…”

Section: Introductionmentioning

confidence: 99%

Performance Assessment of Hybrid Parallelism for Large-Scale Reservoir Simulation on Multi- and Many-core Architectures

AlOnazi

Rogowski

Al-Zawawi

et al. 2018

2018 IEEE High Performance Extreme Computing Conference (HPEC)

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Two trends are reshaping the landscape of petroleum reservoir simulators, one architecturally and one application driven: an increasing number of cores per node and increasing computational intensity arising from higher fidelity physics at each cell. Implicit algebraic solvers being the dominant kernels, we present hybrid MPI and OpenMP implementations of the linear solver of GigaPOWERS, a full-scale real-world massively parallel simulator for black oil and composition models. We also evaluate the impact of explicit communication and computation overlap by including the halo exchange in the task-dependency graph. We analyze the performance of these modifications across multi-and many-core architectures, i.e., Intel Haswell, Skylake, and Knights Landing, using a variety of synthetic and real-world models. The hybrid approach results in up to 50% reduction of time to solution on a 16 million-cell SPE10-like model on Skylake whereas on a smaller, 1 million-cell, model on Haswell and Knights Landing both implementations achieve very similar performance. In the real-world reservoir simulations, the hybrid parallelism has reduced communication volume, memory consumption, and improved load balancing.

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Section: Introductionmentioning

confidence: 99%

Performance Assessment of Hybrid Parallelism for Large-Scale Reservoir Simulation on Multi- and Many-core Architectures

AlOnazi

Rogowski

Al-Zawawi

et al. 2018

2018 IEEE High Performance Extreme Computing Conference (HPEC)

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“…Waterflooding technique is the oldest assisted recovery method and it remains as the most common method used to sweep the oil that was not produced by natural pressure, and to keep the oil pressure when this has declined due to reservoir conditions (Latil, 1980).On the other hand, due to the growing need in the oil industry to make faster and more efficient calculations to simulate the recovery conditions before, during and after the production life of a reservoir, it is necessary to test new computational techniques that reduce the run time of the numerical simulators. Several investigations have been carried out to improve the run time of the reservoir simulators (Killough et al, 1991;Shiralkar et al, 1998;Ma and Chen, 2004;Dogru et al, 2009). Most of these papers have been developed using distributed computing.…”

Section: Introductionmentioning

confidence: 99%

A Graphic Processing Unit (GPU) based implementation of an incompressible two-phase flow model in porous media

Teja-Juárez

Cruz

2018

GeofInt

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En este trabajo se presenta una estrategia de paralelización de un simulador completamente implícito para la solución numérica del modelo de flujo bifásico incompresible en medios porosos usando unidades de procesamiento gráfico (GPU, por sus siglas en inglés). El modelo matemático está basado en las ecuaciones de conservación de masa para las fases agua y aceite. Se utiliza la formulación PresiónSaturación para simplificar el modelo numérico. La técnica de Volumen Finito y el método de Newton-Raphson se usan para discretizar y linealizar las ecuaciones diferenciales parciales, respectivamente. Se propone la construcción del Jacobiano directamente en la GPU, lo que reduce la información que debe intercambiarse entre la CPU (Unidad Central de Procesamiento CPU, por sus siglas en inglés) y la GPU. El simulador utiliza bibliotecas que ya incluyen los métodos del subespacio de Krylov para resolver sistemas de ecuaciones lineales. Se comparan los resultados de tres problemas de referencia utilizando diferentes tamaños de malla. También se evalúa el rendimiento del código numérico desarrollado. Los resultados de la GPU versus CPU indican que el simulador numérico alcanzó hasta 22x de aceleración para construir el Jacobiano y 3x de aceleración para ejecutar el código numérico completo usando la paralelización GPU.

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“…However, this approach is often limited by available computing power. Even with recent advances in parallel computing, the most powerful reservoir simulators are only just entering the regime of billion-cell models [17,34]. Finer meshes allow the CFD solution to capture features such as saturation fronts, gas breakthroughs and regions of trapped oil, all of which contribute to the performance of the reservoir.…”

Section: Introductionmentioning

confidence: 99%

A space-time adaptive method for reservoir flows: formulation and one-dimensional application

et al. 2017

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This paper presents a space-time adaptive framework for solving porous media flow problems, with specific application to reservoir simulation. A fully unstructured mesh discretization of space and time is used instead of a conventional time-marching approach. A space-time discontinuous Galerkin finite element method is employed to achieve a high-order discretization on the anisotropic, unstructured meshes. Anisotropic mesh adaptation is performed to reduce the error of a specified output of interest, by using a posteriori error estimates from the dual weighted residual method to drive a metric-based mesh optimization algorithm. The spacetime adaptive method is tested on a one-dimensional two-phase flow problem, and is found to be more efficient in terms of computational cost (degrees-of-freedom and total runtime) required to achieve a specified output error level, when compared to a conventional firstorder time-marching finite volume method and the spacetime discontinuous Galerkin method on structured meshes. Keywords unstructured space-time methods • anisotropic mesh adaptation • discontinuous Galerkin • high-order • two-phase flow This research was supported through a Research Agreement with Saudi Aramco, a Founding Member of the MIT Energy Initiative (http://mitei.mit.edu/), with technical monitors Dr. Ali Dogru and Dr. Nicholas Burgess.

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A Next-Generation Parallel Reservoir Simulator for Giant Reservoirs

Cited by 38 publications

References 0 publications

Performance Assessment of Hybrid Parallelism for Large-Scale Reservoir Simulation on Multi- and Many-core Architectures

Performance Assessment of Hybrid Parallelism for Large-Scale Reservoir Simulation on Multi- and Many-core Architectures

A Graphic Processing Unit (GPU) based implementation of an incompressible two-phase flow model in porous media

A space-time adaptive method for reservoir flows: formulation and one-dimensional application

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