No.2(46),2026 PP.188-203

Neftyanaya provintsiya No. 2(46), 2026

A system of features and models for intelligent selection of production enhancement operations

A.D. Papash, A.T. Zaripov, D.M. Papash
DOI: https://doi.org/10.25689/NP.2026.2.188-203

Abstract

The paper discusses intelligent support for selection of production enhancement operations aimed to stimulate production and improve oil recovery. It is shown that selection of production enhancement operations is a multi-criteria task that simultaneously considers natural and geological constraints, current state of development system, design and engineering parameters of well interventions, and economic limitations. A workflow for integration of conventional engineering screening and artificial intelligence methods is proposed, including candidate well classification, prediction of operational benefits, well ranking, and design parameter optimization. Nature-based, conditionally controllable and directly controlled parameters in the design of production enhancement operations are distinguished; it is shown that machine learning and optimization algorithms have the potential to offer the highest practical benefit with the latter two groups of parameters. Based on recent EOR/IOR and reservoir engineering publications, the most common features of selection of formation stimulation methods are summarized and tables appropriate for applied corporate decision support systems are generated. It is concluded that the highest efficiency is provided with hybrid "geology – fluid dynamics - machine learning - optimization - engineering expertise – pilot testing" approach rather than application of AI alone.

Key words:

production enhancement operations, enhanced oil recovery, machine learning, optimization, EOR screening, candidate well selection, digital decision support

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Authors

A.D. Papash, First Category Specialist, Technological Development Center, PJSC «Tatneft»
88 Тельмана St., Almetyevsk, 426462, Russian Federation
E-mail: PapashAD@tatneft.tatar

A.T. Zaripov, DSc (Engineering), First Deputy Director, TatNIPIneft Institute – PJSC Tatneft
186а Sovetskaya St., Almetyevsk, 426462, Russian Federation
E-mail: zat@tatnipi.ru

D.M. Papash, Specialist, Technological Development Center, PJSC «Tatneft»
88 Тельмана St., Almetyevsk, 426462, Russian Federation
E-mail: PapashDM@tatneft.tatar

For citation:

A.D. Papash, A.T. Zaripov, D.M. Papash Sistema priznakov i modeley dlya intellektual'nogo vybora geologo-tekhnicheskikh meropriyatiy [A system of features and models for intelligent selection of production enhancement operations]. Neftyanaya Provintsiya, No. 2(46), 2026. pp. 188-203. DOI https://doi.org/10.25689/NP.2026.2.188-203. EDN MITMRM (in Russian)

© Non-governmental organization Volga-Kama Regional Division of the Russian Academy of Natural Science, 2015-2026 All the materials of the journal are available under the Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/)

A system of features and models for intelligent selection of production enhancement operations A.D. Papash, A.T. Zaripov, D.M. Papash DOI: https://doi.org/10.25689/NP.2026.2.188-203

Key words: production enhancement operations, enhanced oil recovery, machine learning, optimization, EOR screening, candidate well selection, digital decision support

A system of features and models for intelligent selection of production enhancement operations

A.D. Papash, A.T. Zaripov, D.M. Papash
DOI: https://doi.org/10.25689/NP.2026.2.188-203

Key words:

production enhancement operations, enhanced oil recovery, machine learning, optimization, EOR screening, candidate well selection, digital decision support