VISUALISATION A GRANDE ECHELLE (GIGAMODEL RESERVOIR, SISMIQUE, DRP) Bruno Conche (Total)

Transcription

1 VISUALISATION A GRANDE ECHELLE (GIGAMODEL RESERVOIR, SISMIQUE, DRP) Bruno Conche (Total)

2 TOTAL EXPLORATION-PRODUCTION CONTEXT Increase of simulation data results size Huge data visualization in several E&P domains: - Seismic Cubes (Pré/Post-stack) many TB - Reservoir grids GigaCells, many attributes & time steps - DRP experiments - Points clouds / LIDAR data Limits of conventional Tools used to QC data New technologies & approaches for visualization Take profit of using HPC resources Parallel Rendering Remote visualization solutions New algorithms & methodology - MultiResolution - Data compression (uncompression on flight)

3 PARALLEL RENDERING USING HPC RESOURCES PV server on Pangea ComputeNodes Lustre SSH Or VNC client PV client on Pangea Login Node TCP/IP Each CU node render a subdomain of the grid Implementation of Paraview in Pangea (MPI, LSF), MultiCPU rendering DOMAIN DECOMPOSITION IS THE KEY POINT 3

4 PARAVIEW PLUGIN FOR RESERVOIR GIGAGRID active cells (10%), 54 properties, 26 time steps - Data Conversion ECLIPSE HDF5 (performed on fatnode pangea) - Run Paraview On Pangea : 128 rangs MPI, 2 process / nodes, dataset sur Lustre (workrd) Reservoir Simulator Rendering Refresh Rate:15 sec between 2 time steps 3 sec between 2 props at same time step Eclipse format Parallel hdf5 LOAD (*) 11 min RENDER 11 sec (*) LOAD: Read/Convert Zcorn + compute grid connections + Partionning (PARMETIS) + properties loading Save as PVTK file 35 sec Re read from PVTK file 25 sec

5 OTHER FIELD OF USE FOR PARALLEL RENDERING Digital Rock Physics: IsoVolume with Paraview Seismic PostStack Visualization with Paraview Visualization of Huge Reservoir Grid with VisIt (Paraview alternative) implemented on HPC pangea cluster

6 VOLUMIC RENDERING SOLUTIONS FOR HUGE VOXET INDEX NVIDIA library : Ray casting, Multi GPU ; Integrated with INTviewer & Paraview for end-user Intel OSPray: Ray casting, CPU multithread + AVX; Integrated with INTviewer & Paraview for end-user

7 UNCOMPRESSION ON FLIGHT FOR SEISMIC VISUALIZATION HueSpace Library evaluation: JPEG2000 like compression / Bricked data format / Data requested on demand Efficient Visualization of 600 GB of post-stack data Navigation in arbitrary directions Efficient Visualization of 2 TB of pre-stack data Comparison / Quality Check Tool

8 Error L2 ( %) COMPRESSION PERFORMANCE EVALUATION ,5 0,25 0,125 0,0625 0, Compression Ratio L2error = SQRT ( [(x - xref)*(x-xref)]) / SQRT (( [xref*xref]) expressed in % L2_seam L2_B32shot_30Hz L2_B32shot_45Hz L2_stackUY L2_stackBR_sismage L2_DIABA_zof7cdpline L2_DIABA_zcdplineof7 L2_COLgathers Quality Check on different types of dataset Quality evaluation : need to define relevant metrics Performance measurements throughputs: MB/sec on CPU MB/sec on GPU

9 GIGAGRID VISUALIZATION COMPONENT Developed with INT Collaboration with CMR Institute (visu algo expertise + methodology ) Multi-Resolution approach (GoogleMap like) Dedicated data structure (based on octrees) Target visualization on Workstation (Sismage/CIG, INTviewer) Octree multi-resolution data structure Visualization of cells grid Property Filtering IJK Filtering

10 REMOTE VISUALIZATION AT TOTAL Necessary to avoid data transfert Remote Desktop Nice DCV deployed in production mode: - Commercial support - Security - Resources management (Engine Frame) NoMachine: - OpenSource solution - Experimented in Houston Research Center NoMachine Nice DCV

11 IN-SITU VISUALIZATION : A NEW PARADIGM Evolution of the simulation context: - Size of simulation results increasing - Classic approach found its limits Computation Results on Disk DataTransfer Visualisation on Workstation - Impossible to store results of each time steps of simulation - BUT need to QC the intermediate steps of simulation & have a better control of the simulations Need to introduce new paradigm In-Situ IN-SITU approach (with data reduction Classical approach (bottleneck stockage)

12 IN-SITU APPROACH BASIC CONCEPTS Include during the computation run, some visualization or analytical processus to for QC on flight of the simulation (need to dedicate some computation nodes) Introduce some data reduction process (ex: iso contour extraction, images) that allows to perform (after end of simulation (à posteriori) a QC visualization of the simulations results (with reconstruction techniques)

13 ACTION PLAN AROUND IN-SITU VISUALIZATION Acquires experience on the subject Evaluate some frameworks (Paraview/Catalyst, VisIt/libsim,.. ) Initiate collaborations (industry, academic) experience exchanges (ex Avido PROJECT) Plan to have PHD (mid 2016) First domains targeted: - Reservoir simulation (Priority 1) - Wave propagation (wave fronts, progressive contribution of shots to final image) - P2

14 THANKS FOR YOUR ATTENTION QUESTIONS?