Version 1
: Received: 15 July 2024 / Approved: 17 July 2024 / Online: 17 July 2024 (13:34:57 CEST)
How to cite:
Eastwood-Anaba, A.; Ampomah, W.; Ameyaw, A. Production Optimization of an Integrated Asset Model of the Farnsworth Field Unit. Preprints2024, 2024071380. https://doi.org/10.20944/preprints202407.1380.v1
Eastwood-Anaba, A.; Ampomah, W.; Ameyaw, A. Production Optimization of an Integrated Asset Model of the Farnsworth Field Unit. Preprints 2024, 2024071380. https://doi.org/10.20944/preprints202407.1380.v1
Eastwood-Anaba, A.; Ampomah, W.; Ameyaw, A. Production Optimization of an Integrated Asset Model of the Farnsworth Field Unit. Preprints2024, 2024071380. https://doi.org/10.20944/preprints202407.1380.v1
APA Style
Eastwood-Anaba, A., Ampomah, W., & Ameyaw, A. (2024). Production Optimization of an Integrated Asset Model of the Farnsworth Field Unit. Preprints. https://doi.org/10.20944/preprints202407.1380.v1
Chicago/Turabian Style
Eastwood-Anaba, A., William Ampomah and Anthony Ameyaw. 2024 "Production Optimization of an Integrated Asset Model of the Farnsworth Field Unit" Preprints. https://doi.org/10.20944/preprints202407.1380.v1
Abstract
This study provides a methodology for optimizing oil production and CO2 sequestration using an integrated asset model of the Farnsworth Unit field, incorporating extensive geological, geophysical, and engineering data. Sensitivity analysis identified critical parameters impacting oil recovery and CO2 storage, leading to the construction of a proxy model using polynomial regression and radial basis function neural networks, with the latter proving more effective for "What-if" analysis. The sensitivity analysis indicated that the Corey parameters impact cumulative oil produced the most. Comprehensive history matching validated the model against historical production data, ensuring reliability for forecasting and optimization. Two scenarios, "Do-Nothing" and development strategy, were forecasted over 15 years (2020-2035). The "Do-Nothing" scenario resulted in 9.57 MMSTB of oil recovery and 2,822.70 MMlbs of CO2 storage. The development strategy case improved outcomes with 13.95 MMSTB of oil recovery and 5,061.68 MMlbs of CO2 stored, and was selected for optimization using particle swarm optimization. The optimized strategy achieved 14,043,372 STB of cumulative oil and 4,832.18 MMlbs of CO2 stored, and increased the field NPV by 25.84% to $114,871,730. This study underscores the significance of integrated asset modeling in enhancing oil recovery and optimizing CO2-EOR processes, providing valuable insights into operational conditions and constraints.
Keywords
Surface-Coupled Reservoir Modeling and Optimization; Integrated Production System Modeling; Surface Facility Optimization; CO2-EOR Optimization; Optimization of CO2-EOR; Integrated Asset Model
Subject
Engineering, Other
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
