Development of a tool for the selection of options to optimize the operation of an oil and gas condensate field on the basis of the integrated asset model

Background. To date, integrated modeling (IM) tools of various configurations are used on most of the Company's Assets. With the help of IM, it seems possible to solve specific production tasks of various kinds, the prevailing list of tasks at the project implementation stage concerns identifying bottlenecks, optimizing technological regimes to maximize production, calculating the system for collecting and transporting well products, as well as determining the optimal strategy of the Asset. The implementation, development and use of IM tools in oil and gas companies can largely improve the quality and value of engineering calculations.

All integrated models used have many variables, which in practice makes it much more difficult to find the optimal objective functions, therefore, as a rule, optimizers built into the IM tool package or separately developed external add-ons are used to solve the tasks. With the advent of new equipment and optimization options, it is necessary to expand the functionality of both the IM tools themselves and various types of optimizers. This work is devoted to the development of an optimizer based on IM using primary automation tools (scripts), which contributes to solving the complex problem of debottlenecking in the well production collection system by using small-sized block separation-pumping units (SBSPU) and gas discharge, including into the gas-lift system or pipelines of high pressure. The solution of this problem involves obtaining a synergistic effect on additional production from reducing the pressure in the system to SBSPU and reducing the share of the gas component in the pipeline network for collecting well products.

Aim. Development of a tool based on an IT product, which is an add-on to the main model of the GAP (Petroleum Experts) collection and transport system, this tool is aimed at solving production problems of optimizing the development and operation of oil and gas fields.

Materials and methods. This article describes the calculation steps and mathematical algorithms of the MetActive IT product for determining and selecting the optimal options for optimization with the calculation of hydraulic processes occurring in the network for collecting and transporting well products based on an integrated field model built using the Petroleum Experts product package. To automate the work, the Python programming language with a library of built-in optimization algorithms and the functionality of the Open Server module in PetEx products were used.

Results. As a result of the work:

• an optimization module was developed based on the MetActive IT product, which allows searching for the most efficient sites for the installation of SBSPU and integration with the economic model;
• using the developed tool, a series of test calculations were carried out to select sites for the placement of SBSPU;
• investigated the possibility of exploitation SBSPU in combination with a mobile compressor unit (MCU) in order to compress associated petroleum gas (APG) into a gas-lift (active) gas line or monetize it with digitization of the economic effect;
• the implementation of the instrument in the structural subdivisions of the Company's subsidiary has begun with the prospect of its further development within the framework of the Asset of the Future.

1. Gazizov T.T. Methods of global optimization: tutorial. — Tomsk: V-Spectrum, 2017, 24 p.

2. The Tax Code of the Russian Federation (part two) [Electronic resource]: dated 05.08.2000 N 117-FZ (as amended on 06/28/2022) (as amended and supplemented, effective from 07/01/2022) // Consultant Plus. Access mode: http://www.consultant.ru/document/cons_doc_LAW_28165/d6bd6dac85569ecf4e95caf1807c8c7584ce82ac/

3. Application of integrated modeling in the oil and gas industry / E.V. Filippov, G.N. Chumakov, I.N. Ponomareva, D.A. Martyushev // Subsoil use, 2020, v. 20, no. 4, pp. 386-400. https://doi.org/10.15593/2712-8008/2020.4.7

4. Timonov A.V., Shabonas A.R., Shmidt S.A. Improving the efficiency of field development through the use of machine learning methods to determine the optimal operating modes of injection wells // SPE-206533-RU, 2021, 13 p.