The “Nedra” (“Depths”) publishing house is preparing to release the book "Application of Machine Learning Methods for Probabilistic Forecasting of Oil Production", written by Maksim Nazarenko, an employee of Lukoil Mid-East Limited, in collaboration with Doctor of Technical Sciences, member of Russian Academy of Natural Science, Professor of Gubkin Russian State University of Oil and Gas Anatoly Borisovich Zolotukhin.
The book addresses the main issues related to the quantitative assessment of risks and uncertainties in the production forecast and the calculation of estimated ultimate recovery (the quantity of oil and gas that is potentially recoverable) in waterflooded oil fields using machine learning methods and models of displacement curves.
The authors give examples of failure to achieve the planned economic efficiency of oil and gas production projects while ignoring the quantitative assessment of risks and uncertainty. They also describe in details the main field-statistical methods for predicting oil production, such as models of displacement curves and decline curve analysis method. The book covers different methods of machine learning and their practical application in solving the problem of probabilistic forecasting of oil production. According to the authors, utilization of these methods improve the quality of forecasting and decision making, contributing to a significant increase in the efficiency of oil and gas production projects.
The book is intended for engineering, technical and scientific workers employed in the oil and gas industry. Starting from April 2021, it will be available for purchase in the online store of the “Nedra” publishing house: https://shop.nedrainform.ru/
From the very beginning, my professional activity was associated with the LUKOIL oil company. I got interested in the topic of application of production-statistical models back in 2012 while working in the Moscow office of LUKOIL Overseas.
Later, I continued to work on this topic while studying at Texas A&M University (USA) with a Master of Science degree in Petroleum Engineering. There I adopted foreign experience in the implementation of various methods for production forecasting, the practical application of machine learning methods, and also studied the quantitative assessment of risks and uncertainty and its impact on the economic efficiency of oil and gas production projects.
I applied the acquired knowledge first in the Lukoil Overseas office in Dubai, and then on the West Qurna-2 project in Iraq. I collected the material for this book while working in various divisions of LUKOIL, as well as while studying machine learning methods in the University.
I would like to thank all my colleagues and managers for their support and exchange of experience, especially A.P. Ermilov, M.I. Mustafayev, I.S. Nikiforov, L.L. Pozdeev, A.G. Proshchenkov, V.V. Rogachev, A.S. Ushakov, A.V. Shalinov, V.F. Shcherbyak.
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