Proceedings of the First Mandalika International Multi-Conference on Science and Engineering 2022, MIMSE 2022 (Mechanical and Electrical) (MIMSE-M-E-I-2022)

<Previous Article In Volume
Next Article In Volume>

Optimization of CO2 Enhanced Oil Recovery Operating Conditions: A Case Study of El Morgan Oil Field Reservoir, Gulf of Suez, Egypt

Authors
Sonny Irawan1, *, Achmad Nadhif Masruri2, Naufal Septio1, Cahaya Sultan Iskandar1, Totok Ruki Biyanto1
1Department of Petroleum Engineering, Nazarbayev University, Astana, Kazakhstan
2Department of Engineering Physics, Sepuluh Nopember Institute of Technology, Surabaya, Indonesia
*Corresponding author. Email: irawan.sonny@nu.edu.kz
Corresponding Author
Sonny Irawan
Available Online 26 December 2022.
DOI
10.2991/978-94-6463-078-7_25How to use a DOI?
Keywords
Optimization; Enhanced Oil Recovery; Genetic Algorithm; Particle Swarm Optimization
Abstract

Oil and gas are energy sources that experience the fastest growth among other energy sources. The oil recovery process can be divided into three recovery stages, namely primary oil recovery, secondary recovery and tertiary recovery or commonly called Enhanced oil recovery (EOR). Enhanced oil recovery (EOR) is an oil recovery used to recover residual oil that cannot be recovered by using waterflooding. According to the US Department of Energy, the tertiary recovery method has a successful recovery factor of up to 75%. EOR also helps reduce CO2 emissions. However, to get optimal results for CO2 EOR, several parameters must be optimized, such as mass flow rate, injection pressure and temperature. To create a pressure drop model for CO2 EOR, several equations are used, including the Begg’s-brill equation for the injection well dan production well model, the Darcy equation for the reservoir model. Based on the optimization results using Genetic algorithm and Particle swarm optimization, it was found that the profit increased by 97.4782% and 97.478%, respectively, with an increase from 994.2268 USD/days to 39425.92 USD/day for Genetic algorithm and 994.2268 USD/days to 39422.95 USD/day for Particle Swarm Optimization (PSO).

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Download article (PDF)

<Previous Article In Volume
Next Article In Volume>
Volume Title
Proceedings of the First Mandalika International Multi-Conference on Science and Engineering 2022, MIMSE 2022 (Mechanical and Electrical) (MIMSE-M-E-I-2022)
Series
Advances in Engineering Research
Publication Date
26 December 2022
ISBN
10.2991/978-94-6463-078-7_25
ISSN
2352-5401
DOI
10.2991/978-94-6463-078-7_25How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Sonny Irawan
AU  - Achmad Nadhif Masruri
AU  - Naufal Septio
AU  - Cahaya Sultan Iskandar
AU  - Totok Ruki Biyanto
PY  - 2022
DA  - 2022/12/26
TI  - Optimization of CO₂ Enhanced Oil Recovery Operating Conditions: A Case Study of El Morgan Oil Field Reservoir, Gulf of Suez, Egypt
BT  - Proceedings of the First Mandalika International Multi-Conference on Science and Engineering 2022, MIMSE 2022 (Mechanical and Electrical) (MIMSE-M-E-I-2022)
PB  - Atlantis Press
SP  - 252
EP  - 268
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6463-078-7_25
DO  - 10.2991/978-94-6463-078-7_25
ID  - Irawan2022
ER  -