Research identifies potential for converting oil wells to geothermal energy in North Caucasus, indicating significant investment needs.
Purpose: to develop a methodology for the comprehensive assessment of the Russian oil well stock to identify promising areas for their conversion to geothermal energy sources. Methods: the study employed methods of normalization and aggregation of indicators, the index method, the ranking method (within the framework of the integral dynamic indicator), Spearman’s rank correlation method, as well as rating construction and grouping techniques. This comprehensive approach ensures the objectivity of the obtained results. Results: based on the analysis of oil well reserves condition in Russian regions, territories with the highest potential for converting oil wells into geothermal energy sources were identified. A comprehensive evaluation methodology was developed, incorporating integral indicators of well conditions and oil production dynamics. Priority regions were identified, characterized by a high proportion of wells under conservation, high reservoir water saturation, and declining productivity. These priority areas include the regions of the North Caucasus Federal District. The study determined the factors most significantly influencing the implementation of projects aimed at converting oil wells into geothermal sources such as technical characteristics of wells and availability of investment resources. Conclusions and Relevance: according to the analysis conducted using the developed methodology, the North Caucasus Federal District was identified as a priority territory for pilot projects aimed at converting oil wells into geothermal energy sources. Its high degree of oil resource depletion and the abundance of mothballed wells create optimal conditions for technology testing. The implementation of such projects will reduce decommissioning costs, generate additional revenue from green energy, and contribute to carbon footprint reduction. Key barriers remain: limited access to technical and economic data (due to commercial confidentiality) and the need for significant investment.
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Kuznetsov et al. (2025) studied this question.
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