Probabilistic geological and economic assessment of hard-to-recover reserves in Devonian carbonates

A probabilistic assessment of Upper Devonian carbonate targets is presented, taking into account reservoir heterogeneity, depositional conditions and the preservation of hydrocarbon accumulations. The distinct geological characteristics of the Zavolzhsky, Dankovo-Lebedyansky, Elets and Evlanovo-Liven horizons are retained. Palaeogeographic and predictive maps are linked to resource assessment, a five-factor model of geological chance of success (gCoS) and scenario-based calculation of expected monetary value (EMV). An economic assessment framework is illustrated using a Dankovo-Lebedyansky target as an example. The value of additional information (VOI) is considered as a basis for selecting further studies.

1. Khisamov R.S., Gubaidullin A.A., Bazarevskaya V.G., Yudintsev E.A. (2010). Geology of Complexly Structured Devonian and Carboniferous Carbonate Reservoirs of Tatarstan / ed. by R.S. Khisamov. Kazan: Fen, Academy of Sciences of the Republic of Tatarstan, 283 p. ISBN 978-5-9690-0125-1.

2. Khisamov R.S., Bazarevskaya V.G., Mikhailova O.V., Podavalov V.B. (2016). Domanik Productive Deposits of Tatarstan as an Analogue of U.S. Shale Plays. Subsoil Use XXI Century, 3(60), pp. 82-91. https://nedra21.ru/archive/54/1126/

3. Larochkina I.A. (2013). Concept of Systematic Geological Analysis in Oil Field Prospecting and Exploration in Tatarstan. Kazan: Fen, Academy of Sciences of the Republic of Tatarstan, 232 p.

4. Altunin A.E., Semukhin M.V., Yadryshnikova O.A. (2017). Probabilistic and Fuzzy Models for Assessing Uncertainties and Risks in Hydrocarbon Reserve Estimation. Tyumen State University Herald. Physical and Mathematical Modeling. Oil, Gas, Energy, 3(2), pp. 85-99. https://doi.org/10.21684/2411-7978-2017-3-2-85-99

5. Emelyanova N.M., Poroskun V.I. (2016). Methods of Geological and Economic Evaluation of Oil and Gas Exploration Targets under Uncertainty and Risk. Subsoil Use XXI Century, 5(62), pp. 190- 201. https://nedra21.ru/archive/56/1207/ (accessed: 10.09.2026).

6. Bratvold R.B., Bickel J.E., Lohne H.P. (2009). Value of Information in the Oil and Gas Industry: Past, Present and Future. SPE Reservoir Evaluation & Engineering, 12(4), pp. 630-638. https://doi.org/10.2118/110378-PA

7. Bickel J.E. (2008). The Relationship Between Perfect and Imperfect Information in a Two-Action Risk- Sensitive Problem. Decision Analysis, 5(3), pp. 116-128. https://doi.org/10.1287/deca.1080.0118

8. Belyakov E.O., Lutfullin A.A., Khabipov R.M., Ziyatdinov A.G., Danilov D.S., Tolibova M.F., Lomonosov A.T., Pushin K.A., Khramkova Yu.O. (2024). Specific Features of Selecting Probability Distribution Parameters for Reserve Estimation Variables and Accounting for the Number of Reservoirs within a Horizon in Rapid 1D Probabilistic Assessment of Hydrocarbon Reserves in Carbonate Deposits. Current Problems of Oil and Gas: Proceedings of the VII All- Russian Youth Scientific Conference. Moscow, pp. 117- 120.

9. Nugumanova N.V., Lomonosov A.T., Sudakov V.A., Zatsepina A.V., Belyakov E.O., Lutfullin A.A., Khabipov R.M., Ziyatdinov A.G., Danilov D.S. (2025). Assessment of the Probability of Geological Success in Oil Deposit Exploration. Technological Leadership and Sustainable Development: Innovative Approaches and Solutions for the Future of the Oil and Gas Industry: Proceedings of the International Scientific and Practical Conference Dedicated to the 75th Anniversary of PJSC TATNEFT named after V.D. Shashin. Kazan, pp. 293-299.