«Automation and Informatization of the fuel and energy complex»

Analysis of models and methods for optimal wells placement in oil and gas deposits

UDC: 622.32:519.85
DOI: -

Authors:

¹ V.A. Trapeznikov Institute of Control Sciences, Russian Academy of Sciences, Moscow, Russia

Keywords: gas, genetic algorithm, deposit, neural network, oil, optimization, design, well placement

Annotation:

The author of the article analyzes in detail the research results of developing models and algorithms for the optimal placement of wells in oil and gas deposits during 1973–2024. The key stages of the development approaches aimed at improving hydrocarbons development efficiency and reducing costs are discussed. The use of mathematical programming methods (linear, nonlinear, mixed-integer), stochastic algorithms (genetic algorithms, particle swarm optimization), machine learning methods (neural networks, physics-informed neural networks) and their integration with hydrodynamic reservoir modeling to account for complex geological conditions and filtration processes is considered. The advantages of these approaches, such as possibilities of accounting for uncertainty and the search automation are analyzed in detail, alongside with their disadvantages, in particular high computational complexity and multiple addressing hydrodynamic simulators. Special attention is paid to an alternative approach to wells placement optimiziation based on heuristic rules of rational development, which allows circumventing the computational challenges associated with traditional methods. The analysis results can be applicable when designing and implementing automated systems for fields’ development.

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