Demonstration of grid-enabled ensemble Kalman Filter data assimilation methodology for reservoir characterization

ABSTRACT

Ensemble Kalman filter data assimilation methodology is a popular approach for hydrocarbon reservoir simulations in energy exploration. In this approach, an ensemble of geological models and production data of oil fields is used to forecast the dynamic response of oil wells. The Schlumberger ECLIPSE software is used for these simulations. Since models in the ensemble do not communicate, message-passing implementation is a good choice. Each model checks out an ECLIPSE license and therefore, parallelizability of reservoir simulations depends on the number licenses available. We have Grid-enabled the ensemble Kalman filter data assimilation methodology for the TIGRE Grid computing environment. By pooling the licenses and computing resources across the collaborating institutions using GridWay metascheduler and TIGRE environment, the computational accuracy can be increased while reducing the simulation runtime. In this paper, we provide an account of our efforts in Grid-enabling the ensemble Kalman Filter data assimilation methodology. Potential benefits of this approach, observations and lessons learned will be discussed.

REFERENCES

• 1: Ian Foster , Carl Kesselman, The grid: blueprint for a new computing infrastructure, Morgan Kaufmann Publishers Inc., San Francisco, CA, 1998
• 2: TIGRE Portal: http://tigreportal.hipcat.net
• 3: Vadapalli, R. Sill, A., Dooley, R., Murray, M., Luo, P., Kim, T., Huang, M., Thyagaraja, K., and Chaffin, D. 2007. Demonstration of TIGRE environment for Grid enabled/suitable applications. 8^th IEEE/ACM Int. Conf. on Grid Computing, Sept 19--21, Austin
• 4: The High Performance Computing across Texas Consortium http://www.hipcat.net
• 5: Pordes, R. Petravick, D. Kramer, B. Olson, D. Livny, M. Roy, A. Avery, P. Blackburn, K. Wenaus, T. Würthwein, F. Foster, I. Gardner, R. Wilde, M. Blatecky, A. McGee, J. and Quick, R. 2007. The Open Science Grid, J. Phys Conf Series http://www.iop.org/EJ/abstract/1742-6596/78/1/012057 and http://www.opensciencegrid.org
• 6: Daniel A. Reed, Grids, the TeraGrid, and Beyond, Computer, v.36 n.1, p.62-68, January 2003 [doi>10.1109/MC.2003.1160057]
• 7: Geir Evensen, Data Assimilation: The Ensemble Kalman Filter, Springer-Verlag New York, Inc., Secaucus, NJ, 2006
• 8: J. Herrera , E. Huedo , R. S. Montero , I. M. Llorente, Porting of scientific applications to Grid Computing on GridWay, Scientific Programming, v.13 n.4, p.317-331, October 2005
• 9: Avery, P. and Foster, I. 2001. The GriPhyN project: Towards petascale virtual data grids, technical report GriPhyN-2001-15 and http://vdt.cs.wisc.edu
• 10: The PacMan documentation and installation guide http://physics.bu.edu/pacman/htmls
• 11: Caskey, P. Murray, M. Perez, J. and Sill, A. 2007. Case studies in identify management for virtual organizations, EDUCAUSE Southwest Reg. Conf., Feb 21--23, Austin, TX. http://www.educause.edu/ir/library/pdf/SWR07058.pdf
• 12: The Grid User Management System (GUMS) https://www.racf.bnl.gov/Facility/GUMS/index.html
• 13: Thomas, M. and Boisseau, J. 2003. Building grid computing portals: The NPACI grid portal toolkit, Grid computing: making the global infrastructure a reality, Chapter 28, Berman, F. Fox, G. Thomas, M. Boisseau, J. and Hey, T. (eds), John Wiley and Sons, Ltd, Chichester
• 14: Open Ticket Request System http://otrs.org
• 15: The MoinMoin Wiki Engine http://moinmoin.wikiwikiweb.de
• 16: Vasco, D. W. Yoon, S. and Datta-Gupta, A. 1999. Integrating dynamic data into high resolution reservoir models using streamline-based analytic sensitivity coefficients, Society of Petroleum Engineers (SPE) Journal, 4 (4).
• 17: Emanuel, A. S. and Milliken, W. J. 1998. History matching finite difference models with 3D streamlines, SPE 49000, Proc of the Annual Technical Conf and Exhibition, Sept 27--30, New Orleans, LA.
• 18: Nævdal, G. Johnsen, L. M. Aanonsen, S. I. and Vefring, E. H. 2003. Reservoir monitoring and Continuous Model Updating using Ensemble Kalman Filter, SPE 84372, Proc of the Annual Technical Conf and Exhibition, Oct 5--8, Denver, CO.
• 19: Jafarpour B. and McLaughlin, D. B. 2007. History matching with an ensemble Kalman filter and discrete cosine parameterization, SPE 108761, Proc of the Annual Technical Conf and Exhibition, Nov 11--14, Anaheim, CA
• 20: Li, G. and Reynolds, A. C. 2007. An iterative ensemble Kalman filter for data assimilation, SPE 109808, Proc of the SPE Annual Technical Conf and Exhibition, Nov 11--14, Anaheim, CA
• 21: Arroyo-Negrete, E. Devagowda, D. Datta-Gupta, A. 2006. Streamline assisted ensemble Kalman filter for rapid and continuous reservoir model updating. Proc of the Int. Oil & Gas Conf and Exhibition, SPE 104255, Dec 5--7, China
• 22: ECLIPSE Reservoir Engineering Software http://www.slb.com/content/services/software/reseng/index.a sp

INDEX TERMS

Primary Classification:
  C. Computer Systems Organization
  C.2 COMPUTER-COMMUNICATION NETWORKS
      C.2.4 Distributed Systems

General Terms:
Algorithms, Design, Performance

Keywords:
EnKF, GridWay, TIGRE, energy exploration, reservoir modeling