Scientific and technical journal

«Automation and Informatization of the fuel and energy complex»

ISSN 0132-2222

In this issue
Automation and Informatization of the fuel and energy complex
In this issue
№7 (576), July 2021
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RISK ANALYSIS WHEN APPLYING ARTIFICIAL INTELLIGENCE TECHNOLOGIES IN OIL AND GAS PRODUCING INDUSTRY

UDC: 004.85+89:681.518:658.5.012.7:622.06
DOI: 10.33285/0132-2222-2021-7(576)-17-27

Authors:

DMITRIEVSKY ANATOLY NIKOLAEVICH 1,2,
EREMIN NIKOLAY ALEXANDROVICH 1,2,
LOZHNIKOV PAVEL SERGEEVICH 3,4,
KLINOVENKO SERGEY ALEXANDROVICH4,
STOLYAROV VLADIMIR EVGENIEVICH1,
INIVATOV DANIIL PAVLOVICH3

1 Oil and Gas Research Institute RAS, 3, Gubkin Street, Moscow, 119333
2 Gubkin Russian State University of Oil and Gas (National Research University), 65, Leninsky prospect, Moscow, 119991
3 Omsk State Technical University, 11, Mira Prospekt, Omsk, 644050
4 Scientific-Research Institute of Natural Gases and Gas Technologies - GAZPROM VNIIGAZ, 142717, Moscow region, g. Leninsky, p. Razvilka, pr-d Projected number 5537, bld. 15, bldg. 1

Keywords: artificial intelligence, system, risk, damage, intelligent technologies, big Data, drilling, oil and gas production

Annotation:

The paper describes possible risks in the oil and gas industry when using artificial intelligence technologies. The digital economy is becoming a key element of the competitiveness of the Russian fuel and energy complex. The transition from export-raw materials to resource-innovative development is the first stage of the implementation of the digital modernization strategy. The oil and gas complex currently has the world's largest mineral resource base, developed infrastructure, qualified personnel and significant innovation potential, including the ability to implement digital technologies and high-conversion industries, which implies a large-scale, fast and efficient return on invested financial resources, new business models to maintain the leading positions of hydrocarbons production in the long term. These capabilities can only be achieved through the introduction of technologies based on the acquisition and processing of large amounts of data, machine learning and digital twins in order to minimize uncertainty factors and risk assessment, as well as to prevent possible abnormal situations and minimize damage caused by technological regimes violation. Uncertainty factors can make it difficult to predict the financial, social, logistical and other business conditions, therefore, long-term major projects may not be implemented. The paper also considers the reasons for the current conservative policy on the innovative products promotion in the oil and gas industry as well as the integration of digital and technological decision-makings that improve the efficiency of management of production facilities of the production infrastructure. The main possible risks and the degree of their risk impact on the project are presented. Possible measures to reduce risks and their consequences are presented on the example of creating a high-performance intelligent system for preventing drilling of oil and gas wells, which allows creating a basis for the transition to unpopulated technologies for preventing accidents and remote work in oil and gas fields.

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