Abstract
The adequate location of wells in oil and environmental applications has a significant economical impact on reservoir management. However, the determination of optimal well locations is both challenging and computationally expensive. The overall goal of this research is to use the emerging Grid infrastructure to realize an autonomic dynamic data-driven self-optimizing reservoir framework. In this paper, we present the use of distributed data to dynamically drive the optimization of well placement in an oil reservoir.
The research presented in this paper is supported in part by the National Science Foundation Grants ACI 9984357, EIA 0103674, EIA 0120934, ANI 0335244, CNS 0305495, CNS 0426354, IIS 0430826, ACI-9619020 (UC Subcontract 10152408), ANI-0330612, EIA-0121177, SBR-9873326, EIA-0121523, ACI-0203846, ACI-0130437, CCF-0342615, CNS-0406386, CNS-0426241, ACI-9982087, CNS-0305495, NPACI 10181410, DOE ASCI/ASAP via grant numbers PC295251 and 82-1052856, Lawrence Livermore National Laboratory under Grant B517095 (UC Subcontract 10184497), Ohio Board of Regents BRTTC BRTT02-0003, and DOE DE-FG03-99ER2537.
Chapter PDF
Similar content being viewed by others
Keywords
- Reservoir Simulator
- Grid Service
- Reservoir Management
- Significant Economical Impact
- Open Grid Service Architecture
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
References
Bittencourt, A.C., Horne, R.N.: Reservoir development and design optimization. In: SPE Annual Technical Conference and Exhibition, San Antonio, Texas (1997) SPE 38895
Guyaguler, B., Horne, R.N.: Uncertainty assessment of well placement optimization. In: SPE Annual Technical Conference and Exhibition, New Orleans, Louisiana (2001) SPE 71625
Pan, Y., Horne, R.: Improved methods for multivariate optimization of field development scheduling and well placement design. In: SPE Annual Technical Conference and Exhibition, New Orleans, Louisiana (1998) SPE 49055
Yeten, B., Durlofsky, L.J., Aziz, K.: Optimization of nonconventional well type, location, and trajectory. SPE Journal 8, 200–210 (2003) SPE 86880
Foster, I., Kesselman, C.: The Grid 2: Blueprint for a New Computing Infrastructure. Morgan Kaufmann, San Francisco (2004)
Parashar, M., Klie, H., Catalyurek, U., Kurc, T., Matossian, V., Saltz, J., Wheeler, M.: Application of grid-enabled technologies for solving optimization problems in data-driven reservoir studies. The International Journal of Grid Computing: Theory, Methods and Applications (FGCS) 21, 19–26 (2005)
Matossian, V., Bhat, V., Parashar, M., Peszynska, M., Sen, M., Stoffa, P., Wheeler, M.F.: Autonomic oil reservoir optimization on the grid. Concurrency and Computation: Practice and Experience 17, 1–26 (2005)
Bangerth, W., Klie, H., Matossian, V., Parashar, M., Wheeler, M.F.: An autonomic reservoir framework for the stochastic optimization of well placement. Cluster Computing: The Journal of Networks, Software Tools, and Applications (2004) (to appear)
IPARS: Integrated Parallel Reservoir Simulator, The University of Texas at Austin, http://www.ices.utexas.edu/CSM
Sen, M., Stoffa, P.: Global Optimization Methods in Geophysical Inversion. In: Berkhout, A.J. (ed.) Advances in Exploration Geophysics 4. Elsevier, Amsterdam (1995)
Spall, J.C.: Introduction to stochastic search and optimization, estimation, simulation and control. John Wiley & Sons, Inc., Publication, New Jersey (2003)
Bangerth, W., Klie, H., Wheeler, M.F., Stoffa, P.L., Sen, M.K.: On optimization algorithms for the reservoir oil well placement problem. Comp. Geosc. (2004) (submitted)
Open Grid Services Architecture Data Access and Integration, http://www.ogsadai.org.uk
Hastings, S., Langella, S., Oster, S., Saltz, J.: Distributed data management and integration: The mobius project. In: GGF Semantic Grid Workshop 2004, pp. 20–38 (2004)
Li, X., Agrawal, G.: Using xquery for flat-file based scientific datasets. In: The 9th International Workshop on Data Base Programming Languages, DBPL (2003)
Narayanan, S., Kurc, T., Catalyurek, U., Zhang, X., Saltz, J.: Applying database support for large scale data driven science in distributed environments. In: Proceedings of the Fourth International Workshop on Grid Computing (Grid 2003), Phoenix, Arizona, pp. 141–148 (2003)
Weng, L., Agrawal, G., Catalyurek, U., Kurc, T., Narayanan, S., Saltz, J.: An approach for automatic data virtualization. In: The Thirteenth IEEE International Symposium on High-Performance Distributed Computing, HPDC-13 (2004)
Agarwal, M., Bhat, V., Li, Z., Liu, H., Matossian, V., Putty, V., Schmidt, C., Zhang, G., Parashar, M., Khargharia, B., Hariri, S.: Automate: Enabling autonomic applications on the grid. In: Autonomic Computing Workshop, The Fifth Annual International Workshop on Active Middleware Services (AMS 2003), Seattle, WA USA, pp. 365–375 (2003)
Mann, V., Parashar, M.: Discover: A computational collaboratory for interactive grid applications. In: Berman, F., Fox, G., Hey, T. (eds.) Grid Computing: Making the Global Infrastructure a Reality, pp. 727–744. John Wiley & Sons, Chichester (2003)
Parashar, M., von Laszewski, G., Verma, S., Gawor, J., Keahey, K., Rehn, N.: A CORBA Commodity Grid Kit. Concurrency and Computations: Practice and Experience 14, 1057–1074 (2002)
Matossian, V., Parashar, M.: Enabling peer-to-peer interactions for scientific applications on the grid. In: Kosch, H., Böszörményi, L., Hellwagner, H. (eds.) Euro-Par 2003. LNCS, vol. 2790, pp. 1240–1247. Springer, Heidelberg (2003)
Muralidhar, R., Parashar, M.: A Distributed Object Infrastructure for Interaction and Steering. Special Issue - Euro-Par 2001, Concurrency and Computation: Practice and Experience 15, 957–977 (2003)
Liu, H., Parashar, M.: Dios++: A framework for rule-based autonomic management of distributed scientific applications. In: Kosch, H., Böszörményi, L., Hellwagner, H. (eds.) Euro-Par 2003. LNCS, vol. 2790, pp. 66–73. Springer, Heidelberg (2003)
Matossian, V., Parashar, M.: Autonomic optimization of an oil reservoir using decentralized services. In: Proceedings of the 1st International Workshop on The Challenges for Large Applications in Distributed Environments (CLADE 2003), pp. 2–9. Computer Society Press (2003)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Parashar, M. et al. (2005). Towards Dynamic Data-Driven Optimization of Oil Well Placement. In: Sunderam, V.S., van Albada, G.D., Sloot, P.M.A., Dongarra, J.J. (eds) Computational Science – ICCS 2005. ICCS 2005. Lecture Notes in Computer Science, vol 3515. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11428848_85
Download citation
DOI: https://doi.org/10.1007/11428848_85
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-26043-1
Online ISBN: 978-3-540-32114-9
eBook Packages: Computer ScienceComputer Science (R0)