ISSN 0869-6632 (Print)
ISSN 2542-1905 (Online)


For citation:

Sidorenko V. V., Surtaev V. N., Hasanov M. M. New approach to modeling of natural fluvial oil reservoirs. Izvestiya VUZ. Applied Nonlinear Dynamics, 2007, vol. 15, iss. 3, pp. 74-86. DOI: 10.18500/0869-6632-2007-15-3-74-86

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Russian
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51-74+553.982

New approach to modeling of natural fluvial oil reservoirs

Autors: 
Sidorenko Vladislav Viktorovich, Keldysh Institute of Applied Mathematics (Russian Academy of Sciences)
Hasanov Mars Magnavievich, OAO NK "Rosneft"
Abstract: 

We discuss the conception of the adaptive modeling of the natural oil reservoirs. This conception is based on application of simple mathematical algorithms to imitate the physical processes, defining the reservoir structure. As an example the possibility of fluvial reservoir modeling by a cellular automata is considered. 

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Reference: 
  1. Hyne NJ. Nontechnical Guide to Petroleum Geology, Exploration, Drilling and Production. Moscow: Olymp-Business; 2004. 752 p. (in Russian)
  2. Krige DG. A statistical approach to some basic mine valuation problems on the Witwatersrand. Journal of the Chemical, Metallurgical and Mining Society of South Africa. 1951;52:119–139.
  3. Wietzerbin L, Mallet JL. Parametrization of complexe 3D heterogeneities: a new CAD approach. SPE 26423-PA:11–18; 1994. DOI: 10.2118/26423-PA.
  4. Deutsch CV, Wang L. Hierarchical object-based geostatistical modeling of fluvial reservoirs. SPE 36514; 1996.
  5. Shmaryan LE, Deutsch CV. Object-based modeling of fluvial/deepwater reservoirs with fast data conditioning: methodology and case studies. SPE 56821–MS;1999.
  6. Strebelle SB, Journel AG. Reservoir modeling using multiple-point statistics. SPE 71324; 2001.
  7. Strebelle SB, Payrazyan K. Modeling of a deepwater turbidite reservoir conditional to seismic data using multiple-point statistics. SPE 77425; 2002.
  8. Liverpool TB, Edwards SF. The dynamics of a meandering river. Preprint condmat/9608080 (http://arXiv.org).
  9. Meakin P, Sun T, Jossang T, Schwarz K. A simulation model for meandering rivers and their associated sedimentary environments. Physica A. 1996;233:606–618.
  10. Leheny RL, Nagel SR. Model for the evolution of river networks. Phys. Rev. Lett. 1993;71:1470–1473. DOI: 10.1103/PhysRevLett.71.1470.
  11. Loskutov AYu, Mikhailov AS. Introduction to Synergetics. Moscow: Nauka; 1990. 272 p. (in Russian)
  12. Sapozhnikov VB, Nikora VI. Simple computer model of a fractal river network with fractal individual watercourses. J. Phys. A: Math. Gen. 1993;26(15):002. DOI: 10.1088/0305-4470/26/15/002.
  13. Glock WS. The development of drainage system: a synoptic view. Geograph. Rev. 1931;21:475–482.
  14. Hack JT. Studies of longitudinal stream profiles in Virginia and Maryland. US Geol. Surv. Prof. Paper. 1957;294B:45–49.
Received: 
25.09.2006
Accepted: 
26.03.2007
Published: 
29.06.2007
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