Scientific and technical journal

«Environmental protection in oil and gas complex»

ISSN 2411-7013

Environmental protection in oil and gas complex
Development and justification of approaches to forecasting greenhouse gas emissions indicators as a part of an oil and gas company strategic planning

UDC: 620.9
DOI: 10.33285/2411-7013-2023-5(314)-49-58

Authors:

SHEVELEVA NADEZHDA A.1,
RESHETNIKOVA ELENA B.2,
SLAMIKHINA NINA V.2,
GALIMOVA SVETLANA SH.2

1 Luzin Institute of Economic Problems - Subdivision of the Federal Research Centre "Kola Science Centre of the Russian Academy of Sciences", Apatity, Russiа
2 Union of Health Safety and Environment Professionals, Moscow, Russia

Keywords: greenhouse gases, greenhouse gas emissions forecast, emission reduction strategy, emission reduction calculation approach, net zero emissions, oil and gas industry, strategic planning in oil and gas industry, key performance indicators, climate change management

Annotation:

The article presents the results of development and approbation of approaches of various levels of accuracy to forecasting greenhouse gas emissions from various segments of oil and gas complex using absolute (operational and technological) primary data and specific indexes of emissions as well as their combinations. The proposed approaches to forecasting greenhouse gas emissions are applicable for calculating emissions in the context of various segments of oil and gas production and take into account the industry specifics of segments of the oil and gas complex: geological prospecting, production, processing, marketing, service, etc. The developed approaches could be used by oil and gas companies, trying to achieve the goal of greenhouse gas emissions reduction by establishing intermediate and target performance indicators for greenhouse gas emissions reduction. The article also presents options of implementing the results of emissions forecasting, depending on the company's goals: the approaches to the strategic management of greenhouse gases emissions reduction are compared on the basis of static and dynamic approaches to forecasting, their key features are revealed.

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