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High performance computing for Darcy compositional single phase fluid flow simulations L.Agélas, I.Faille, S.Wolf, S.Réquena Institut Français du Pétrole.

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Presentation on theme: "High performance computing for Darcy compositional single phase fluid flow simulations L.Agélas, I.Faille, S.Wolf, S.Réquena Institut Français du Pétrole."— Presentation transcript:

1 High performance computing for Darcy compositional single phase fluid flow simulations L.Agélas, I.Faille, S.Wolf, S.Réquena Institut Français du Pétrole Abstract The compositional description of flow through heterogeneous porous media is of primary interest to many applications such as basin modeling. The flow equations that we consider model a Darcy compositional single phase migration in a porous media. Our interest is to predict the pressure, the saturation and the fluid composition. Darcy fluid flow simulations on nowadays million-cells and highly heterogeneous basin models are tremendously CPU-time consuming. To make Darcy flow simulation tractable, different numerical techniques have been studied to improve the solution of the non linear system on parallel computers. Real case : the time period is 250 My, the size of the block is 101 km x 65 km x 8.7 km refined on a 180x180x29 grid (0.94M cells). The simulation is a full darcy compositional single phase migration with twelve components run with a thermal gradient. The number of unknowns is 11.3 M. The test was performed on a 64 AMD Opteron 2.2 Ghz Infiniband cluster with 64 procs. The CPU time is 15h. Overnight runs can be expected with more processors. Difficulty : solve a large non linear system of size, number of cells multiplied by (2 + number of mobile components) Lithology distribution Tranformation ratio (layers = 3, 7, 9, 12, 20) Oil saturation (layers = 11, 13, 15, 21) Mass conservation of the water phase Mass conservation of each component Generalised Darcy law, α = (w,o) proc 3 proc 2 proc 1 monoprocessor To cope with simulations of millions cells : The global domain is split among the y dimension. Each processor owns a private subdomain. All the inter-processors communications are handled by MPI calls. To save cpu-time : We use the under relaxation technique to maintain a good convergence of the Newton algorithm. We combine two finite volume schemes : the one explicit in composition and the other one implicit in composition. For null saturations, the compositions are undefined. A good initialization is important to keep a good convergence. Improvements and results

2 We considerably speed up the Darcy compositional single phase fluid flow simulations. The new numerical techniques considerably improve the convergence of the Newton algorithm both in terms of robustness and CPU time enabling the efficient simulations of millions cells models on parallel computers. Contact name : Leo Agelas (leo.agelas@ifp.fr) Some compositions (c2,c14+Csat,c14+aroU,NSO) at layer 21 Fluid properties Api gravityGor solution Pressure Temperature very heavy oil Condensate gas 10 ° API 22,3 ° 31,1°45 ° heavy oilmedium oil light oil Gas volume liberated at Surf Cond. GOR ------------------------------------------ Oil Volume Surf Cond. Huile Gaz casesize of gridblock number of unknowns Long time period Cpu time previous versionCpu time current version Berkine section SWNE149 x 3981354510 My6h43mn2h12mn Berkine section NS160 x 50112000510 My23h17mn (until the event 48)10h37mn Some cpu time performances obtained on real cases 2D with 1 proc (16 components) Conclusion Here are the results of Api gravity, Gor solution and Number of phases obtained with a PVT flash EOS calculation in postprocessing for layers 3, 4, 5, 6, 13, 14 Number of phases 1 for only the water phase 2 for two phases water and oil 3 for three phases water/oil/gas 4 for two phases water and gas


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