Basin simulation for complex geological settings

Transcription

1 Énergies renouvelables Production éco-responsable Transports innovants Procédés éco-efficients Ressources durables Basin simulation for complex geological settings Towards a realistic modeling P. Havé*, I. Faille, F. Willien IFP Energies nouvelles * pascal.have@ifpen.fr

2 What is «Basin simulation»? (1/2) Improving subsoil knowledge by modeling its geological history Modeling from the creation of the basin to know its present state Qualitative and quantitative information about fluids in the porous media Reducing risks and costs of the oil exploration Where are hydrocarbons? How much oil is available in a trap? Is there any risk to drill in an abnormally high pressure area? 2

3 What is «Basin simulation»? (2/2) Sediment deposition Typical geological scales Time: From 10 to 400 MY Length : 100 km Depth : 10 km Burying - Compaction Temperature increase Highly heterogeneous media : sand, clay... Cracking expulsion - migration Trapping into oil and gas fields 3

4 Existing approaches : «simple geometry» Structured grids Conforming mesh with vertical pillars Allows degenerated hexahedra Parallel 3D code Does not allow complex tectonic deformations E.g. : fault displacements Structured grid with degenerated hexahedra Multi structured blocks Sequential 2D code Difficult to extend in 3D Multi blocks mesh 4

5 Why «Complex geological settings»? «Simple geometry» areas are well known «Complex geological» areas are promising To push back peak oil Recent discoveries in unexpected areas Complex areas are difficult to understand without modelling World production forecasts 5

6 Examples of complex geological settings (1/2) «simple» «complex» Extensive setting HW Cutoff of 2.3 Ma Horizon NE Compressive setting 6

7 Examples of complex geological settings (2/2) Faults have an important impact on flow paths Discontinuous model Can juxtapose stratigraphically distinct layers «Fault zone» : thin area around faults Can define new barriers or shorten migration path Jourde et al. (2002) 7 Fault network Huge impact on pressure field Berg and Skar(2006)

8 The challenge of «Complex» A short research to market timing 2006 : first prototype 2012 : first commercial product New 4D meshes mixing 3D (media matrix) and 2D areas (faults) Improved physics modeling A wide range of geometric alterations Fault flow : across and along New schemes For Stress, Darcy and Thermal models Performance To address accurately new hardware architectures 8

9 A short research to market timing (1/2) The choice of a C++ Framework : Arcane Co-developed since 2006 with CEA/DAM Provide low level services I/O, parallelism and network communications Parallel data management : Partitioning, load-balancing, checkpoint/restart... Ensure good performance on parallel clusters Tested with > 16k cores and > 10 9 cells Domain decomposition parallelism : MPI, threads or hybrid of both Task parallelism : to process a flow of (in)dependant small tasks Plug-in architecture for sharing or extending base services Mesh, Timeloop... Numerics, Physics... Arcane Startup Data set & mesh building Application initialization compute-loop Application exit Arcane Completion 9

10 A short research to market timing (2/2) The choice of a C++ Framework : Arcane Speed up industrialization process Debugging tools (TotalView integration, HYbrid Online Debugger for Arcane), performance tracking, trace facilities... High level approach : abstract interface, embedded containers, C# binding Supports Linux and Windows platforms Extended for business features in ArcGeoSim project Provide common facilities for research and commercial IFPEN products (CO 2 sequestration, Enhanced Oil Recovery simulator...) People focussed on their skills or or Physics modeling Numerical analysis Computer Science Specific Modules Application Numerics Schemes Solvers Algorithms Geometry CPG Surface SubMesh AMR Arcane Core Specific Services Parallelism Load Balancing Mesh Module/Service Mng I/O Variables Integrated in a pre/post-processing environment : Open Flow Business MultiPhaseFlow ReactiveTransport Wells Physics Thermodynamics Hydrodynamics Chemistry Application ArcGeoSim 10

11 Workflow Temis Flow V3 11

12 Workflow Temis Flow V3 gocad / Kine3D Powered by Code Aster Powered by Open Flow Eclipse based environment ArcTem // ArcTem pre-processing processing Mesh validation Data preparation 12

13 Unstructured mesh in ArcGeoSim CPG with degenerated hexahedra Evolutive Mesh : kinematic driven geometry Faults with 3D dynamic co-refinement AMR (2010) Voronoï approach IXM Format (v4 - XDMF like) Sub-meshes (mesh view) 1D and 2D variants 13

14 New meshes : kinematic driven geometry (4D) Mesh increments given at each geological age Increment types: Fault = sliding surface Sediment deposition : new cells appear and grow Compaction and kinematic deformation : nodes move Sliding along faults : non conforming mesh and surface co-refinement Erosion : cells disappear or may change their type Computation mesh is interpolated between two ages 14

15 15 Improved physics and robust numerics (1/5) Compaction and fluid flow coupling Compaction is the engine of the fluid flow Coupled equations Mass conservation, Darcy law Vertical mechanic equilibrium Elasto-plastic rheology Finite volume schemes Implicit formulation Unknowns Cell-centered Pressure (over-pressure) Node-centered Vertical Constraint Cell-centered Porosity Challenges Robust FV schemes for «div K» operator on very messy mesh No more vertical pillar Faults K u K LGR σ n K σ u L L Fault

16 Improved physics and robust numerics : Faults (2/5) Faults A fault is defined as a relation between 2 surfaces The interactions between these two surfaces have to be computed at each time step and take into account gaps, overlaps and fault intersections (Node Face and Face Face correlations) Across fault flow Fault properties associated to each face Flux through juxtaposed faces 16

17 Very permeable media Improved physics : Faults (3/5) Across fault flow An academic test case Very impermeable media Increased water speed due to connected permeable layers 17

18 Improved physics : Faults (4/5) Along fault flow Flow parallel to the fault Flow in a thin part of the medium (damaged zone) Modeled using a surface flow on fault surfaces requires Extended conservation equations New pressure unknowns to discretize Opposite flow surfaces connected through an across fault flow Implemented using sub-mesh concept which defines a part of a mesh (here codim 1) as a true mesh. Each mesh or sub-mesh has its own connectivity. 18

19 40km Improved physics (5/5) 10km Synthetic example 8 layers : sand and shale 8 faults 7km Overpressure and water velocity 19

20 40km Improved physics (5/5) 10km Synthetic example 8 layers : sand and shale 8 faults 7km Velocity along fault surfaces 20

21 Performance (1/3) The target... comparable performances with legacy code on simple geometry and able to support complex geometry weak scalability to aim our customers optimized for 8-32 cores ready for more However, performances are a key element of the strategy of that product. 21

22 Performance (2/3) On simple geometry... Reference legacy code Simple geometry, complex physics, 10 years old optimized code New product Complex geometry young physics Visco ArcTem (best of 3 runs) v7062 # procs Durée (h:m:s) Durée (s) Scalabilité Efficacité Durée (h) Durée (s) Scalabilité Efficacité vs Visco 1 09:24: ,0 100% 11, ,0 100% +26% 4 02:37: ,6 90% 3, ,9 97% +16% 8 01:39: ,7 71% 1, ,2 88% +1% 16 00:59: ,5 59% 1, ,3 70% +6% 32 00:36: ,6 49% 0, ,8 58% +6% 64 00:24: ,0 36% 0, ,3 50% -9% 22 An overhead due to complex data structures but More scalable Major performance improvement will come from an improvement of the linear solver scalability.

23 Performance (3/3) And more... Dynamic partitioning facilities Dynamic fault aware partitioning: Zoom on two sub-domains (own + ghost) Allows to address a wider range of solvers (including GPU) Tested up to 2048 cores (robustness test) 23

24 Énergies renouvelables Production éco-responsable Transports innovants Procédés éco-efficients Ressources durables