Author
Listed:
- Toufighi, Seyed Pendar
- Sahebi, Iman Ghasemian
- Soltani, Zahra
Abstract
This study explores the application of evolutionary game theory to optimize long-term extraction strategies for common oil fields, focusing on the North Pars field shared by Iran and Qatar. The research aims to identify optimal management policies for shared resources by modeling the strategic interactions between these countries. The analysis incorporates key factors such as recovery rates, and information asymmetry, providing a realistic framework for decision-making. The study reveals that full cooperation between Iran and Qatar yields the highest long-term payoffs, emphasizing the benefits of strategic alignment. However, the game-theoretic model also indicates an equilibrium where Iran cooperates, and Qatar does not, resulting in higher payoffs for Qatar. This highlights the challenges in achieving mutual cooperation and underscores the need for robust legal frameworks and negotiation strategies. Using real data from the North Pars field, the mathematical model optimizes extraction values and payoffs, demonstrating the potential of technological advancements and strategic planning. The optimized extraction rates are 147,865 barrels per day for Iran and 265,748 barrels per day for Qatar. The study shows that increasing a country's potential payoff accelerates the convergence towards a stable, cooperative strategy. The findings suggest that evolutionary strategies, informed by dynamic geopolitical and economic conditions, enhance the management of shared oil resources.
Suggested Citation
Toufighi, Seyed Pendar & Sahebi, Iman Ghasemian & Soltani, Zahra, 2025.
"Evolutionary dynamics in common oil resource management for enhancing long-term strategic interactions,"
Resources Policy, Elsevier, vol. 105(C).
Handle:
RePEc:eee:jrpoli:v:105:y:2025:i:c:s0301420725001394
DOI: 10.1016/j.resourpol.2025.105597
Download full text from publisher
As the access to this document is restricted, you may want to
for a different version of it.
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:jrpoli:v:105:y:2025:i:c:s0301420725001394. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
We have no bibliographic references for this item. You can help adding them by using this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/30467 .
Please note that corrections may take a couple of weeks to filter through
the various RePEc services.