Complex of Programs for Assessing the Reserves of Hydrocarbons and Subcalculating Parameters in the Conditions of Uncertainty

About the authors:

Olga A. Yadryshnikova, Cand. Sci. (Tech.), Chief Manager, Algorithmization Department, Tyumen Petroleum Research Center; oayadrishnikova@tnnc.rosneft.ru

Alexander Ye. Altunin, Cand. Sci. (Tech.), Senior Expert, Tyumen Petroleum Research Center; aealtunin@rosneft.ru

Abstract:

In the oil and gas industry, a large amount of heterogeneous geological and geophysical information is necessary to assess hydrocarbon reserves. There are high risks of incorrect assessment of hydrocarbon reserves in the absence or inaccurate information.

In this article, the authors estimate oil and gas reserves in the cases, when there is insufficient data, especially at the stage of exploration of deposits. Therefore, the methods of probabilistic and fuzzy implementations are of particular interest since deterministic estimation does not provide knowledge about the calculation error. An adequate assessment of the estimated parameters in difficult conditions, unconventional, and complex built-up promising hydrocarbon reserves is required. The modern technology “Digital Kern” is considered promising. A comprehensive approach to solving problems using all kinds of data on complex oil and gas facilities is required.

The authors have used probabilistic methods, methods of the theory of fuzzy sets and fuzzy logic, as well as methods of pattern recognition. This article presents a set of programs that uses an integrated approach and implements both a model for calculating reserves and determining the estimated parameters using new modern intelligent computing technologies for processing information in assessing hydrocarbon reserves under uncertainty. They include:

• probabilistic and fuzzy methods for estimating reserves and determining estimated parameters under conditions of various types of uncertainty and risk for gas, gas condensate and oil fields;
• comprehensive assessment of sandiness and oil-saturated areas from core photographs in daylight ultraviolet light;
• recognition of cracks, determination of geometrical characteristics, fractured porosity and permeability from micrographs of petrographic thin sections and core tomograms.

This software complex is intended to improve the quality in the assessment of hydrocarbon reserves, improve the reliability of determining the estimated petrophysical parameters in the absence or absence of data.

References:

1. Altunin A. E., Semukhin M. V., Yadryshnikova O. A. 2017. “Probabilistic and Fuzzy Models to Evaluate Uncertainties and Risks Related to HC Reserves Estimation”. Tyumen State University Herald. Physical and Mathematical Modeling. Oil, Gas, Energy, vol. 3, no 2, pp. 85-99. DOI: 10.21684/2411-7978-2017-3-2-85-99
2. Altunin A. E., Semukhin M. V., Yadryshnikova O. A. 2013. “Ispol’zovaniye al’ternativnykh i modifitsirovannykh veroyatnostnykh metodov dlya otsenki neopredelennostey i riskov pri podschete zapasov uglevodorodov” [The Use of Alternative and Modified Probabilistic Methods to Evaluate Uncertainties and Risks When Estimating Hydrocarbon Reserves]. Rosneft Research and Technology Bulletin, no 3, pp. 42-47.
3. Altunin A. E., Semukhin M. V., Yadryshnikova O. A. 2015. “Metody analiza razlichnykh vidov neopredelennosti pri modelirovanii neftegazovykh ob”yektov” [Analysis Methods of Various Uncertainty Types for Modeling Oil and Gas Targets]. Rosneft Research and Technology Bulletin, no 38, pp. 66-72.
4. Petersilye V. I., Poroskun V. I., Yatsenko G. G. (eds.). 2003. Metodicheskiye rekomendatsii po podschetu geologicheskikh zapasov nefti i gaza ob”yemnym metodom [Methodical Recommendations about Calculation of Geological Oil and Gas Reserves by a Volume Method]. Moscow-Tver: All-Russian Research Geological Oil Institute, Tvergeofizika.
5. Yadryshnikova O. A., Altunin A. E., Semukhin M. V. 2017. Software state registration certificate No 2017662359 “Programmnyy kompleks dlya otsenki zapasov uglevodorodov i podschetnykh parametrov v usloviyakh neopredelennosti” [Program Complex for Reserves Assessment Hydrocarbons and Subcalculating Parameters in the Uncertainty Conditions]. Applied 6 September. Published 3 November.
6. Semukhin M. V., Yadryshnikova O. A., Serkin M. F. et al. 2017. “Razrabotka sistemy raspoznavaniya treshchin dlya polucheniya eksperimental’nykh dannykh po snimkam petrograficheskikh shlifov kerna” [Development of the System Cracks Recognition for Receiving Experimental Data According to Pictures of Petrographic Core Shlif]. Oil Industry, no 5, pp. 27-31.
7. Altunin A. E., Semukhin M. V., Yadryshnikova O. A. et al. 2018. Patent No 2654372 “Sposob otsenki neftenasyshchennosti kerna gornykh porod po fotografiyam obraztsov v dnevnom svete” [Assessment Way of Oil Saturation Rocks Core according To Samples Photos in a Daylight].
8. Uzhga-Rebrov O. I. 2004. Upravleniye neopredelennostyami [Uncertainty Management]. Vol. 1. Sovremennyye kontseptsii i prilozheniya teorii veroyatnostey [Modern Concepts and Applications of Probability Theory]. Rezekne: RA Izdevniecība.
9. Yadryshnikova O. A. 2015. “Kompleksnyye kriterii dlya polucheniya psevdo-karotazhnoy krivoy otsenki peschanistosti (NTG) po fotografiyam kerna v dnevnom svete i ul’trafioletovom izluchenii” [Complex Criteria for Receiving Pseudo-Logging Curve Assessment of Sandiness (NTG) according to Core Photos in a Daylight and Ultra-Violet Radiation]. Proceedings of the 6th Russian Research Conference “Novyye informatsionnyye tekhnologii v neftegazovoy otrasli i obrazovanii”, pp. 110-114. Tyumen: Industial university of Tyumen.
10. Bellman R. Е., Zadeh L. A. 1970. “Decision-Making in Fuzzy Environment”. Management Science, vol. 17, no 4, pp. B-141-B-164.
11. Mohaghegh S. D. 2017. Shale Analytics: Data-Driven Analytics in Unconventional Resources. USA: Springer. DOI: 10.1007/978-3-319-48753-3