The paper examines modern approaches to the selection and evaluation of the effectiveness of geological and technical measures (GTM) aimed at enhancing oil recovery and deve-loping hard-to-recover reserves. The primary objective is to identify optimal methods that ensure high technical and economic efficiency under complex geological and operational conditions.

The study analyzes traditional and modern methods for assessing GTM effectiveness, including extrapolation of basic production characteristics, analysis of oil production decline curves, and forecasting using probabilistic-statistical models. The paper emphasizes the insufficient reliability of traditional approaches due to data uncertainties, multi-criteria considerations, and the non-linear interaction of factors. A review of literature highlights the potential use of fuzzy logic, "least concessions" methods, cluster analysis, and expert systems, which allow accounting parameter boun-dary uncertainties and making more accurate decisions in the context of incomplete data.

Examples of applying modern methods to various oil fields are provided. The possibility of developing integrated information systems on decision support, incorporating mathematical algorithms, databases, and predictive models, is discussed. Particular attention is given to selection of parameters to evaluate the effectiveness of measures, such as physical and geological characteristics, water cut, oil production rates, and economic indicators.

The paper substantiates the necessity for further improvement of approaches to GTM evaluation and planning. It proposes the integration of modern methods for data analysis, modeling, and forecasting to enhance the reliability and accuracy of decisions, thereby contributing to the successful optimization of oil field development and risk reduction.

Keywords: oil field, geological and technical measures, fuzzy cluster analysis, forecasting, decision-making

REFERENCES

Abasov M.T., Efendiyev G.M., Strekov A.S. et al. Comparative evaluation of GTM effectiveness based on comprehensive information. Oil Industry, No. 10, 2003, pp. 70-73 (in Russian). 

Akhmetov D.A., Efendiyev G.M., Karazhanova M.K., Koylibaev B.N. Classification of hard-to-recover hydrocarbon reserves in Kazakhstan using fuzzy cluster analysis. 13th International Conference on Application of Fuzzy Systems and Soft Computing, ICAFS 2018. Warsaw, Poland, August 27-28, 2018, pp. 865-872. 

Efendiyev G.M., Mammadov P.Z., Piriverdiyev I.A., Mammadov V.N. Clustering of geological objects using the FCM algorithm and evaluation of the rate of lost circulation. Procedia Computer Science, Vol. 102, 2016, pp. 159-162, DOI: 10.1016/S1877-0509(16)32664-3. 

Efendiyev G.M., Mammadov P.Z., Piriverdiyev I.A., Mammadov V.N. Estimation of lost circulation rate using fuzzy clustering of geological objects by petrophysical properties. Visnyk Taras Shevchenko National University of Kyiv, Geology, Vol. 2 (81), 2018, pp. 28-33, DOI: 10.17721/1728-2713.81.04. 

Efendiyev G.M., Moldabayeva G.Z., Abbasova S.V., Tuzelbayeva Sh.R. Models and methods of analysis and decision-making in controlling technological processes of oil and gas production under conditions of uncertainty. SOCAR Proceedings, No. 1, 2025.

Fakhretdinov R.N., Kaledin Yu.A., Zhitkova M.V. The potential of modern information technologies in assessing the effectiveness of enhanced oil recovery methods. Oil Industry, No. 3, 2001, pp. 54-55 (in Russian).

Glukhikh I.N., Pyankov V.N., Zabolotnov A.R. Situational models in corporate knowledge bases for geological and technical measures. Oil Industry, No. 6, 2002, pp. 45-48 (in Russian).

Ilyushin P.Yu., Rakhimzyanov R.M., Solovyev D.Yu., Kolychev I.Yu. Analysis of well intervention aimed at oil production enhancement in the Perm krai's fields. Bulletin of the Perm National Research Polytechnic University. Geology, Oil, Gas and Mining. Perm, No. 15, 2015, pp. 81-89, DOI: 10.15593/2224-9923/2015.15.9 (in Russian).

Kazakov A.A. Methodological support for unified approaches to assessing the effectiveness of EOR methods. Technologies of Fuel and Energy Complex, Supplement to Oil and Capital journal, No. 2, 2003, pp. 47-53 (in Russian). 

Kazakov A.A. Methodology for assessing the effectiveness of GTM based on oil production decline curves. Oil Industry, No. 12, 1999, pp. 31-34 (in Russian). 

Khasanov M.M., Mukhamedshin R.K., Khatmullin I.F.  Computer technologies for solving multi-criteria tasks of oil field development monitoring. Vestnik inzhiniringovogo tsentra YUKOS (Bulletin of the YUKOS Engineering Center), No. 2, 2001, pp. 26-29 (in Russian).

Kravchenko Yu.A., Makhno D.A. Principles for building decision-support systems to assess the functional state of decision-makers. 2009. (Electronic resource). http://www.cawater-info.net/pdf/kravchenko-mahno.pdf (in Russian).

Moldabayeva G.Z., Efendiyev G.M., Kozlovskiy A.L., Buktukov N.S., Abbasova S.V. Modeling and adoption of technological solutions to enhance the effectiveness of measures to limit water inflows into oil wells under conditions of uncertainty. ChemEngineering, Vol. 7 (5), No. 89, 2023, https://doi.org/ 10.3390/chemengineering7050089. 

Pyankov V.N., Filev A.I. Integral software complex "Baspro-Analyst". Oil Industry, No. 9, 2000, pp. 109-114 (in Russian). 

Sarvaretdinov R.G., Gilmanova R.Kh., Khisamov R.S. et al. Formation of a database for GTM optimization in oil production. Oil Industry, No. 8, 2001, pp. 32-35 (in Russian). 

Savchenko T.N. Application of cluster analysis methods for processing psychological research data. Experimental Psychology, Vol. 3, No. 2, 2010, pp. 67-86 (in Russian).

Selection of geological and technical measures for influencing the well's near-wellbore zone. 2004. (Electronic resource). https://www.oil-info.ru/content/view/31/51/ (in Russian).

Shakhverdiev A.Kh., Panakhov G.M., Abbasov E.M., Rasulova S.R. On the possibility of regulating viscosity anomalies in heterogeneous mixtures. Bulletin of the Russian Academy of Natural Sciences, No. 1, 2014, pp. 28-33 (in Russian).

Shpurov A.V., Pyankov V.N., Klochkov A.A., Brilliant L.S. Planning GTM effectiveness when forecasting oil production. Oil Industry, 2000, No. 9, pp. 105-108 (in Russian). 

Strekov A.S., Mamedov P.Z., Koyshina A.I. Decision-making on the choice of geological and technical measures under uncertainty. The Seventh international conference on soft computing, computing with words and perceptions in system analysis, decision and control. Turkey, Izmir, September 2-3, 2013, pp. 381-384. 

Syrtlanov V.R., Kadochnikova L.M., Trushnikova O.M. Methods for evaluating the effectiveness of GTM based on three-dimensional hydrodynamic modeling. Oil Industry, No. 6, 2002, pp. 38-40 (in Russian). 

Well Flo – Well modeling and design. (Electronic resource), http://www.weatherford.com/Products/Production/ProductionOptimization/Software/WellFloSoftware/index.htm. 

Wiseman H., Gradijan F. Regulation of shale gas development, including hydraulic fracturing. Energy Institute, University of Texas at Austin; University of Tulsa Legal Studies, Research Paper No. 2011-11, October 31, 2011, 130 p.

Zadeh L.A. Fuzzy sets as a basis for a theory of possibility. Fuzzy Sets and Systems, 1978, No. 1, pp. 3-28, https://doi.org/10.1016/S0165-0114(99)80004-9. 

Zhanturin Zh.K. Approximate assessment of GTM effectiveness indicators with limited information. Bulletin of the Atyrau İnstitute of oil and gas, No. 12, 2007, pp. 63-65 (in Russian).

Zhanturin Zh.K. Development of oil production intensification measures for implementation under various geological and physical conditions in Kazakhstan. PhD dissertation in technical sciences. Atyrau, 2009, 115 pp.  (in Russian).

Zhanturin Zh.K. On forecasting GTM effectiveness based on comprehensive information. Oil and Gas, No. 4, 2008, pp. 45-49 (in Russian).

Zolotukhin A.B., Eremin N.A., Nazarova L.N., Ponomarenko E.M. Fuzzy set theory in the selection of methods for influencing oil reservoirs. Oil Industry, 1991, No. 3, pp. 21-23 (in Russian).