A Massively Parallel Reservoir Simulator for Large Scale Reservoir Simulation

Doğru, Ali H.; Li, K.G.; Sunaidi, H.A.; Habiballah, W.A.; Fung, Larry S.K.; Alzamil, Nour; Shin, Dongwon; McDonald, A.E.; Srivastava, Nimita

doi:10.2118/51886-ms

Cited by 30 publications

(5 citation statements)

References 15 publications

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“…Because of the demand for large-scale reservoir simulations in the petroleum industry, there exist several commercial and in-house simulators that are able to take advantage of parallel computing platforms. Examples include the Saudi Aramco POWERS [19][20][21] and GigaPOWERS [22] simulators, which are able to run simulations on reservoir grids with billions of cells.…”

Section: Related Workmentioning

confidence: 99%

On the impact of heterogeneity-aware mesh partitioning and non-contributing computation removal on parallel reservoir simulations

2021

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Parallel computations have become standard practice for simulating the complicated multi-phase flow in a petroleum reservoir. Increasingly sophisticated numerical techniques have been developed in this context. During the chase of algorithmic superiority, however, there is a risk of forgetting the ultimate goal, namely, to efficiently simulate real-world reservoirs on realistic parallel hardware platforms. In this paper, we quantitatively analyse the negative performance impact caused by non-contributing computations that are associated with the “ghost computational cells” per subdomain, which is an insufficiently studied subject in parallel reservoir simulation. We also show how these non-contributing computations can be avoided by reordering the computational cells of each subdomain, such that the ghost cells are grouped together. Moreover, we propose a new graph-edge weighting scheme that can improve the mesh partitioning quality, aiming at a balance between handling the heterogeneity of geological properties and restricting the communication overhead. To put the study in a realistic setting, we enhance the open-source Flow simulator from the OPM framework, and provide comparisons with industrial-standard simulators for real-world reservoir models.

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Section: Related Workmentioning

confidence: 99%

On the impact of heterogeneity-aware mesh partitioning and non-contributing computation removal on parallel reservoir simulations

2021

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“…SAGD process with 756 well pairs is simulated. The grid has a dimension of 60 × 220 × 85 and size of 20 f t × 10 f t × 1 f t. All wells are horizontal wells along x direction, if the index of y direction of a grid block equals to 3,7,11,15,19,23,27,31,35,39,43,47,51,55,59,63,67,71,75,79,83,87,91,95,99,103,107,111,115,119,123,127,131,135,139,143,147,151,155,159,163,167,171,175,179,183,187,191,195,199,203,207,211, or 215, and the index of z direction equals to 4,10,16,…”

Section: Numerical Performancementioning

confidence: 99%

“…Killough [33] reviewed the parallel reservoir models and parallel computing technologies. Saudi Aramco developed new-generation massively-parallel reservoir simulator [34][35][36][37]. Zhang et al developed a scalable general-purpose platform for parallel adaptive finite element methods and adaptive finite volume methods [38,39], which was applied to reservoir simulations [40].…”

Section: Introductionmentioning

confidence: 99%

Development of a Scalable Thermal Reservoir Simulator on Distributed-Memory Parallel Computers

Liu

Chen

Guo

et al. 2021

Fluids

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Reservoir simulation is to solve a set of fluid flow equations through porous media, which are partial differential equations from the petroleum engineering industry and described by Darcy’s law. This paper introduces the model, numerical methods, algorithms and parallel implementation of a thermal reservoir simulator that is designed for numerical simulations of a thermal reservoir with multiple components in three-dimensional domain using distributed-memory parallel computers. Its full mathematical model is introduced with correlations for important properties and well modeling. Efficient numerical methods (discretization scheme, matrix decoupling methods, and preconditioners), parallel computing technologies, and implementation details are presented. The numerical methods applied in this paper are suitable for large-scale thermal reservoir simulations with dozens of thousands of CPU cores (MPI processes), which are efficient and scalable. The simulator is designed for giant models with billions or even trillions of grid blocks using hundreds of thousands of CPUs, which is our main focus. The validation part is compared with CMG STARS, which is one of the most popular and mature commercial thermal simulators. Numerical experiments show that our results match commercial simulators, which confirms the correctness of our methods and implementations. SAGD simulation with 7406 well pairs is also presented to study the effectiveness of our numerical methods. Scalability testings demonstrate that our simulator can handle giant models with billions of grid blocks using 100,800 CPU cores and the simulator has good scalability.

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“…Details of mathematical formulation used in POWERS are given in Ref. 10 and the implementation on parallel computing platforms is discussed in Ref. 12-13. POWERS and GAP have been loosely coupled at the sand face in the reservoir.…”

Section: Coupled Simulation Workflowmentioning

confidence: 99%

“…As expected, loose couplings are faster and are generally sufficient if interface conditions between the reservoir and the surface system do not change significantly between synchronization intervals. We chose Saudi Aramco's in-house simulator POWERS 10 , which is used routinely to simulate giant reservoirs in Saudi Arabia, and the commercial surface network simulator General Allocation Package (GAP 11 ), which is capable of providing optimized flow rates within user specified constraints. POWERS is highly parallel and optimized to run on large parallel computing platforms 12,13 .…”

Section: Introductionmentioning

confidence: 99%

Coupled Facility and Reservoir Simulations to Optimize Strategies for a Mature Field

2011

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It is important to employ a good production injection strategy to optimize hydrocarbon recovery from a field. Reservoir constraints on the surface facility change as the field matures. It may be economical to revise the surface facility configurations rather than retaining the initial design of the surface facility to maintain the target production level of the field as reservoir conditions change. If reservoir pressure is not sufficient to maintain natural flow, there may be need for artificial lift mechanisms to keep the well flowing. Careful analysis of interdependence of the surface facility constraints and reservoir conditions are important in designing good quality production injection strategies for these circumstances. Coupled facility and reservoir simulations allow production optimization and determination of the impact of injection or disposal policies on reservoir management. Sometimes there are oscillations in computed production rates, which may be as a result from inaccurate treatment of a coupling algorithm, well management rules, optimization techniques, etc. Excessive fluctuations make the solution impractical to implement. In this paper, we examine the cause of well rate fluctuations in coupled simulations. We were able to keep oscillation levels at a very low level in our simulations by using a small coupling interval and by revising well management rules. We made case studies with reconfiguration of surface facility designs in two large fields to examine if those designs were capable of meeting the required production targets as the reservoir conditions change with time. Surface facility models were built using a commercially available software, which were coupled to Saudi Aramco's in-house reservoir simulator, POWERS. We examine scenarios where some facilities could be eliminated to reduce cost while maintaining required production target. We study the impact of reconfiguring the surface network and examine how surface constraints might change the overall production rate.

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A Massively Parallel Reservoir Simulator for Large Scale Reservoir Simulation

Abstract: This paper was prepared for presentation at the 1999 SPE Reservoir Simulation Symposium held in Houston, Texas, 14-17 February 1999.

Cited by 30 publications

References 15 publications

On the impact of heterogeneity-aware mesh partitioning and non-contributing computation removal on parallel reservoir simulations

On the impact of heterogeneity-aware mesh partitioning and non-contributing computation removal on parallel reservoir simulations

Development of a Scalable Thermal Reservoir Simulator on Distributed-Memory Parallel Computers

Coupled Facility and Reservoir Simulations to Optimize Strategies for a Mature Field

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