A New Approach to Limited Compositional Simulation: Direct Solution of the Phase Equilibrium Equations

1987 ◽  
Vol 2 (04) ◽  
pp. 703-712
Author(s):  
Tak Sing Lo ◽  
Gary K. Youngren
Keyword(s):  
Phase Equilibrium ◽  
Direct Solution ◽  
Compositional Simulation ◽  
Equilibrium Equations ◽  
New Approach

Three-Phase Equilibrium Calculations for Compositional Simulation

2007 ◽  
Author(s):  
Abbas Firoozabadi ◽  
Kjetil Braathen Haugen ◽  
Lixin Sun
Keyword(s):  
Phase Equilibrium ◽  
Compositional Simulation ◽  
Three Phase ◽  
Equilibrium Calculations

Efficient Phase Equilibrium Calculation for Compositional Simulation: The Direct Reduced Flash

2007 ◽  
Vol 25 (3) ◽  
pp. 315-342 ◽  
Author(s):  
D. V. Nichita ◽  
D. Broseta ◽  
J. -C. de Hemptinne ◽  
V. Lachet
Keyword(s):  
Phase Equilibrium ◽  
Compositional Simulation ◽  
Equilibrium Calculation

A New Approach to Load Balance for Parallel/Compositional Simulation Based on Reservoir-Model Overdecomposition

SPE Journal ◽  
2013 ◽  
Vol 19 (02) ◽  
pp. 304-315 ◽  
Author(s):  
Yuhe Wang ◽  
John E. Killough
Keyword(s):  
Dynamic Load ◽  
Execution Time ◽  
Static Load ◽  
Computational Cost ◽  
Hydrocarbon Composition ◽  
Reservoir Model ◽  
Compositional Simulation ◽  
New Approach ◽  
Load Imbalance ◽  
Load Balancer

Summary The quest for efficient and scalable parallel reservoir simulators has been evolving with the advancement of high-performance computing architectures. Among the various challenges of efficiency and scalability, load imbalance is a major obstacle that has not been fully addressed and solved. The causes of load imbalance in parallel reservoir simulation are both static and dynamic. Robust graph-partitioning algorithms are capable of handling static load imbalance by decomposing the underlying reservoir geometry to distribute a roughly equal load to each processor. However, these loads that are determined by a static load balancer seldom remain unchanged as the simulation proceeds in time. This so-called dynamic imbalance can be exacerbated further in parallel compositional simulations. The flash calculations for equations of state (EOSs) in complex compositional simulations not only can consume more than half of the total execution time but also are difficult to balance merely by a static load balancer. The computational cost of flash calculations in each gridblock heavily depends on the dynamic data such as pressure, temperature, and hydrocarbon composition. Thus, any static assignment of gridblocks may lead to dynamic load imbalance in unpredictable manners. A dynamic load balancer can often provide solutions for this difficulty. However, traditional techniques are inflexible and tedious to implement in legacy reservoir simulators. In this paper, we present a new approach to address dynamic load imbalance in parallel compositional simulation. It overdecomposes the reservoir model to assign each processor a bundle of subdomains. Processors treat these bundles of subdomains as virtual processes or user-level migratable threads that can be dynamically migrated across processors in the run-time system. This technique is shown to be capable of achieving better overlap between computation and communication for cache efficiency. We use this approach in a legacy reservoir simulator and demonstrate a reduction in the execution time of parallel compositional simulations while requiring minimal changes to the source code. Finally, it is shown that domain overdecomposition, together with a load balancer, can improve speedup from 29.27 to 62.38 on 64 physical processors for a realistic simulation problem.

Rapid Flash Calculations for Compositional Simulation

2006 ◽  
Vol 9 (05) ◽  
pp. 521-529 ◽  
Author(s):  
Yinghui Li ◽  
Russell T. Johns
Keyword(s):  
Computation Time ◽  
Binary Interaction ◽  
Computational Time ◽  
Compositional Simulation ◽  
New Approach ◽  
Number Of Components ◽  
Black Oil ◽  
Reduced Parameters ◽  
Fluid Characterization ◽  
Flash Calculation

Summary The computational time for conventional flash calculations increases significantly with the number of components, making it impractical for use in many fine-grid compositional simulations and other applications. Previous research to increase flash-calculation speed has been limited to those with zero binary interaction parameters (BIPs) or approximate methods based on an eigenvalue analysis of the binary interaction matrix. Practical flash calculations, however, nearly always have some nonzero BIPs. Further, the accuracy and speed of the eigenvalue methods varies depending on the choice and number of the dominant eigenvalues. This paper presents a new and simple method for significantly increasing the speed of flash calculations for any number of nonzero BIPs. The approach requires the solution of up to six reduced parameters regardless of fluid complexity or the number of components and is based on decomposing the BIPs into two parameters using a simple quadratic expression. The new approach is exact in that the equilibrium-phase compositions for the same BIPs are identical to those with the conventional flash calculation; no eigenvalue analysis is required. Further, the new approach eliminates the Rachford-Rice procedure (1952) and is more robust than the conventional flash-calculation procedure. We demonstrate the new approach for several example fluids and show that speedup by a factor of approximately 3 to 20 is obtained over conventional flash calculations, depending on the number of components. Introduction Gas injection into oil reservoirs results in complex interactions of flow with phase behavior that often are not modeled accurately by black-oil simulation. This is especially true for miscible or nearly miscible floods in which significant mass transfer occurs between the hydrocarbon phases. Such floods are best modeled by compositional simulation. A significant disadvantage of compositional simulation, however, is that it is much more computationally intensive than black-oil simulation. The primary reason for the increased computational time is the result of solving repeated flash calculations with cubic equations of state (EOS). Research has shown that EOS flash calculations can occupy 50 to 70% of total computational time in compositional simulations (Stenby and Wang 1993; Chang 1990). This is also true for other applications, such as multiphase flow in pipelines. The use of fewer pseudocomponents can reduce the flash computation time, but fewer components results in less accuracy (Hong 1982; Liu 2001; Egwuenu et al. 2005). This is especially true in multicontact miscible displacements, in which miscibility is developed by a combined condensing/vaporizing drive process (Zick 1986; Johns et al. 1993; Egwuenu et al. 2005). Fluid characterization by pseudocomponent models can be improved by tuning to the analytical minimum miscibility enrichment or minimum miscibility pressure (Johns et al. 1994), but those models still require significant computational time, even for fewer pseudocomponents. Another way to reduce computation time is to reduce the number of gridblocks. With coarse grids, however, numerical dispersion is large, which may cloud the results (Solano et al. 2001). Ideally, fine grids should be used that better match the level of dispersion found at the field scale. More recently, methods have been examined to find reduced parameters for flash calculations. Michelsen (1982a, 1982b, 1986) significantly increased flash-calculation speed by finding three reduced parameters, regardless of the number of components. His method, however, assumes zero BIPs, which is too restrictive for real fluid characterization. Michelsen also gave a practical method for stability calculations using the tangent plane distance (TPD) (Michelsen 1982b).

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