Proceedings of International Conference on Applied Innovation in IT
2019/03/06, Volume 7, Issue 1, pp.6571
Uncertainty Analysis of Oil Well Flow Rate on the Basis of Differential Entropy
Ivan Luzyanin, Anton Petrochenkov, Sergey Bochkarev Abstract: Oil well production efficiency depends on the accuracy of the flow rate prediction. The electrical submersible pumps are selecting and the well production control is carrying out based on the predicted values of flow rate. Inaccurate prediction may cause limitations of well deliverability or inefficient pumping. The prediction accuracy of flow rate changes in time related to initial data uncertainty that causes deviations between calculated flow rate values and measured ones. To minimize operating costs the same pump selection and control methods are used for groups of wells operating under the same conditions. However, sometimes wells demonstrate very different behavior even under the same conditions. In these wells flow rate changes becomes unpredictable by the common methods and additional studies required for correct prediction. The problem of finding wells with unpredictable flow rates at the early operation stages is very important because their inefficiency can significantly increase in time without special operation methods. The article considers the method of finding wells with potentially unpredictable flow rate changes with use of the entropy concept. The main feature of this method is that it is appropriate for data of any distribution types with given probability density function. The article discusses the relation between the value of joint reduction in uncertainty obtained from entropies of calculated flow rates and measured ones for a single well and the deviations between these flow rates. The novelty of the article is that the joint reduction in uncertainty in calculated value of well rate when knowing measured well rate is proposed as the measure of the well flow rate predictability.
Keywords: Uncertainty, Differential Entropy, Exponential Distribution Probability Density Function, Well Flow Rate, Oil Field, Oil Production
DOI: 10.25673/13484
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References:
 K. Bjørlykke, Petroleum geoscience: from sedimentary environments to rock physics, SpringerVerlag Berlin Heidelberg, 2010, 508 p.
 G. Takacs, Electrical submersible pump manual: design, operations, and maintenance, Gulf Professional Publishing, 2009, 420 p.
 T. M. Cover, J. A. Thomas, Elements of information theory, 2nd edition, Wiley, 2006, 748 p.
 V. N. Fashchilenko, , S. N. Reshetnyak, Resonant behavior of electric drives of mining machines, Gornyi Zhurnal, vol. 7, 2017, pp. 8083, doi: 10.17580/gzh.2017.07.15.
 N. J. Hyne, Nontechnical guide to petroleum geology, exploration, drilling and production, 2nd edition, Pennwell Books, 2001, 575 p.
 N. L. Johnson S. Kotz, N. Balakrishnan, Continuous univariate distributions, 2nd edition, vol. 1, Wiley, 1994, 761 p.
 J. V. Mihalowicz et. al., handbook of differential entropy, CRC Press, 2014, 220 p.
 I. Ghosh, A. Alzaatreh, A new class of bivariate and multivariate exponential distributions, Far east journal of theoretical statistics, vol. 50, issue 2, 2015, pp. 7798, doi: 10.17654/FJTSMar2015_ 077_098.
 S. Nadarajah, D. Choi, Arnold and Strauss’s bivariate exponential distribution – products and ratios, New Zealand journal of mathematics, vol. 35, 2006, pp. 189199.
 S. K. Iyer, D. Manjunath, R. Manivasakan, Bivariate exponential distributions using linear structures, The Indian journal of statistics, vol. 64, series A, pt. 1, 2002, pp. 156166
 D. Kundu, R. D. Gupta, Bivariate generalized exponential distribution, Journal of multivariate analysis, vol. 100, issue 4, 2009, pp. 581593, DOI: 10.1016/j.jmva.2008.06.012
 B. M. Bemis, Some statistical inferences for the bivariate exponential distribution, dissertation, 1971, 116 p.
 A. Seijas–Macías, A. Oliveira, An approach to distribution of the product of two normal variables, Discussions mathematicae probability and statistics, vol. 32, 2012, pp. 8799, DOI: 10.7151/dmps.1146
 Y. A. Tashkandy, M. A. Omair, A. Alzaid, Bivariate and bilateral gamma distributions, International journal of statistics and probability, vol. 7, no. 2,
 2018, pp. 6679.
 E. Furman, On a multivariate gamma distribution, Statistics and probability letters, vol. 78, 2008, pp. 23532360.
 S. Nadarajah, A. K. Gupta, Some bivariate gamma distributions, Applied mathematics letters, vol. 19, 2006, pp. 767774
 I. Luzyanin , A. Petrochenkov, Practical Aspects of Software Developing for the System of Structural and Functional Analysis of Power Supply Systems in Oil
 Companies, Proceedings Of The 5th International Conference On Applied Innovations In IT, vol. 5, 2017, pp. 6569, doi: 10.13142/KT10005.31, WOS: 000402660300 009
 A. Lyakhomskii et. al., Conceptual design and engineering strategies to increase energy efficiency at enterprises: Research, technologies and personnel, Proceedings of 2015 IV Forum Strategic Partnership of Universities and Enterprises of HiTech Branches (Science. Education. Innovations), 2015, pp. 44–47, doi: 10.1109/IVForum.2015.7388249, wos: 000380529800015.

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