On the distributed computing system for computer model operation of oil and gas fields on the basis of iterative conjugation of sector models

Tyumen State University Herald. Physical and Mathematical Modeling. Oil, Gas, Energy


Release:

2015, Vol. 1. №2(2)

Title: 
On the distributed computing system for computer model operation of oil and gas fields on the basis of iterative conjugation of sector models


About the authors:

Stanislav S. Samboretskiy, postgraduate, Tyumen State University
Irina G. Zakharova, Cand. Sci. (Phys.-Math.), Professor, Department of Software, School of Computer Science, University of Tyumen, Tyumen, Russia; i.g.zakharova@utmn.ru, https://orcid.org/0000-0002-4211-7675

Sergey V. Kostuchenko, Dr. Tech. Sci., Professor, chief expert in hydrodinamics modeling "Rosneft"

Abstract:

This article deals with the problem of computer simulation of large oil and gas deposits. The authors consider iterative conjugation of sector models by Schwartz’s method one of the existing methods of solution in domain decomposition. Previously implemented method, focused on multi-core workstation algorithm of conjugation, has been modifi ed because of the need to design and develop a new software system based on the distributed computing. The paradigm of object-oriented programming is taken as a basis for the new software package. Issues of system architecture defi ned structural components containing a basic functionality for the computations according to the algorithm. The authors consider tools for interaction between objects of the system required for distributed computing, the advantages and disadvantages of common approaches. Also, to increase the stability and improve the temporal characteristics of the work, the authors consider ways of solving the problem of fault tolerance in the distributed system and the approach to load balancing.

References:

1. Kudryashov, I. Yu., Maksimov, D. Yu. Modeling of multiphase multicomponent filtration problems on multi-processor computers // Preprints of the Keldysh Institute of Applied Mathematics. 2009. Issue 0. Рp. 68-25.

2. Baryshnikov, A. V. et al. Iterative conjugation as a method of rational approach to modeling the giant reservoir systems // Oil Industry. 2011. I. 20. Рp. 3.

3. Kostyuchenko, S. V., Arzhilovsky, A. V., Bikbulatova, T. G. Simulation technology of large deposits of conjugated systems sector models. Part 1. The analysis of the problem situation // Oil Industry. 2011. № 11. Рp. 52-55.

4. Dzyuba, V. I., Litvinenko, Yu. V., Bogachev, K. Yu., Migrasimov, A. R., Semenko, A. E., Khachaturova, E. A., Eydinov, D. A. Application of Sector Modeling Technology for Giant Reservoir Simulations // SPE 162090-RU. SPE Russian Oil and Gas Exploration and Production Technical Conference and Exhibition, 16-18 October 2012. Moscow, Russia.

5. Kostyuchenko, S. V. Simulation technology of large deposits of conjugated systems sector models. Part 2: Method of iterative conjugation of sector models // Oil Industry. 2012. № 4.

Рp. 96-100.

6. Kostyuchenko, S. V., Tolstolytkin, D. V., Chuprov, A. A., Shinkarev, M. B. Simulation technology of large deposits of the system of conjugate sector models. Part 3: Testing of the technology on the example of reservoir models AV1-5 Samotlor fi eld // Oil Industry. 2013. № 8. Рp. 78-81.

7. Dolean, V., Jolivet, P., Nataf, F. An Introduction to Domain Decomposition Methods: algorithms, theory and parallel implementation. 2015.

8. Kostyuchenko, S. V. et al. Algorithm parallel simulation development of giant oil and gas fi elds with conjugation of sector models // Proceedings of the V scientifi c conference «Supercomputer technologies in the oil and gas industry. Mathematical methods, software and hardware». Moscow, 2015.

9. Kopysov, S. P., Krasnopyorov, I. V., Rychkov, V. N. Object-oriented domain decomposition method // Computational Methods and Programming. 2003 Vol. 4. P. 1.

10. Tanenbaum, E. M. van Steen Distributed Systems. The principles and paradigms. St. Petersburg: Peter, 2003. 877 p.

11. Dagum, L., Menon, R. OpenMP: an industry standard API for shared-memory programming //Computational Science & Engineering, IEEE. 1998. Vol. 5. № 1. Pp. 46-55.

12. Gropp, W. et al. A high-performance, portable implementation of the MPI message passing interface standard //Parallel computing. 1996. Vol. 22. №. 6. Pp. 789-828.

13. Bakken, D. Middleware // Encyclopedia of Distributed Computing. 2001. Vol. 11.

14. Sukhoroslov, O. V. Middleware Ice // Computing problems in a distributed environment / Ed. A. P. Afanasyev. Proceedings of ISA RAS. 2007. Vol. 32. Pp. 33-67.

15. Foster, I. Globus toolkit version 4: Software for service-oriented systems // Network and parallel computing. Springer Berlin Heidelberg, 2005. Pp. 2-13.

16. Fougere, D. et al. NumGrid middleware: MPI support for computational grids // Parallel Computing Technologies. Springer Berlin Heidelberg, 2005. Pp. 313-320.

17. Devine, K. D. et al. New challenges in dynamic load balancing // Applied Numerical Mathematics. 2005. Vol. 52. № 2. Pp. 133-152.

18. Barker K. et al. A load balancing framework for adaptive and asynchronous applications //Parallel and Distributed Systems, IEEE Transactions on. 2004. Vol. 15. № 2. Pp. 183-192.

19. Clarke, D., Lastovetsky, A., Rychkov, V. Dynamic load balancing of parallel computational iterative routines on highly heterogeneous HPC platforms // Parallel Processing Letters. 2011. Vol. 21. № 2. Pp. 195-217.

20. Aluru, S., Sevilgen, F. Parallel domain decomposition and load balancing using spacefi lling curves // High-Performance Computing, 1997. Proceedings. Fourth International Conference on. IEEE, 1997. Pp. 230-235.