APPLICATION OF OPTIMIZATION AND NEURAL NETWORK ALGORITHMS FOR EFFECTIVE PORTFOLIO OF GEOLOGICAL AND TECHNOLOGICAL ACTIVITIES FORMATION OF AN OIL COMPANY
Denisov O.V
DOI https://doi.org/10.25689/NP.2019.1.90-101
Abstract
The article presents the result of the research of reasonable selection of geological and technological activities for an activities portfolio formation of an oil company in the context of restrictions on production volume and investment area. The number of statistical, neural network, optimization algorithms has been applied while solving this issue. The possibility of using Kohonen self-organizing maps for clustering activities under the terms of use and technologies is considered. It was proposed to build a probabilistic model for evaluating the effectiveness of the planned activities based on Bayesian networks, which can be visualized as an acyclic directed graph reflecting the consistent interrelation of the parameters included in the model. This model is based on the accumulated statistics of the activities effectiveness and other characteristics. The constructed model allows us to obtain a nomogram of the probability distribution of a given activity for any combination of parameters, for example, the probability of achieving exact or approximate value of the activity effectiveness specific measure. After evaluating the effectiveness of the planned activity, the task of forming an optimal portfolio of geological and technological activities under the restrictions on the production volume and capital expenditures can be set. The issue of forming a portfolio of geological and technological activities for a large oil company has been studied and solved using the implemented package of optimization algorithms (branch and bound method, genetic algorithms, cross-entropy method). The software tool for the effective investment portfolio formation in the "Development and production of oil" block of PJSC TATNEFT has been implemented. The tool has significantly increased the planned net present value and the number of activities taken in the portfolio under restrictions on production volume and capital expenditures.
References
1. Nasybullin A.V. Sozdanie i promyshlennoe vnedrenie metodov upravleniya razrabotkoĭ mestorozhdeniĭ na osnove metodov avtomatizirovannogo proektirovaniya [Development and commercialization of CAD-based reservoir management methods]. A.V. Nasybullin, F.M. Latifullin, D.A. Razzhivin, R.Z. Sattarov, R.R. Ahmetzyanov, A.S. Sultanov. Neftyanoye Khozyaistvo, No. 7, 2007.pp. 88-91. (in Russian)
2. Kohonen, Т. Self-Organizing Maps (Third Extended Edition), New York, 2001, 501 pages.
3. Lazareva R.G. Primenenie nejrosetevyh podhodov v zadache planirovaniya metodov uvelicheniya nefteotdachi plastov [Application of neural network approaches to solve the task of planning of enhanced oil recovery methods]. Lazareva R.G., Denisov O.V. Proc.of ХХ Anniversary International Conference on computational mechanics and modern application systems. Moscow: Moscow Aviation Inst. Publ., 2017. pp. 151-153. (in Russian)
4. Tulupyev A.L. Bajesovskie seti: logiko-veroyatnostnyj podhod [Bayesian network: probabilistic logic approach]. Tulupyev A.L. Nikolenko S.I., Sirotkin A.V. St-Petersburg: Nauka Publ., 2006. 607 p. (in Russian)
5. Struchenkov V.I. Dinamicheskoe programmirovanie v primerah i zadachah [Dynamic programming in examples and problems] Moscow-Berlin: Direct-Media Publ., 2015. 275 p. (in Russian) 6. Benham T., Duan Q., Kroese D.P., Liquet B. (2017) CEoptim: Cross-Entropy R package for optimization. Journal of Statistical Software, 76(8), 1-29.
7. Artemkina L.R. Problemy investicionnogo planirovaniya v neftegazodobyvayushchih kompaniyah [Problems of investment planning in oil and gas companies] Upravlencheskie Nauki, Vol. 7, No. 4, 2017. pp. 64-71. (in Russian)
8. Denisov O.V. Razrabotka metodologii resheniya zadachi i realizaciya informacionnogo instrumenta formirovaniya effektivnogo investicionnogo portfelya PAO «Tatneft» [Working out of a methodology for solving a problem and realization of information tool for forming of efficient PJSC TATNEFT investment portfolio]. Denisov O.V., Chirikin A.V. Abstracts of papers for VIII International Research-to-Practice Conference Prakticheskie aspekty neftepromyslovoj himii [Practical aspects of oil-field chemistry]. Ufa: BashNIPIneft Publ., 2018. pp. 176-178. (in Russian)
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