Iranian Energy Economics

Estimation of Optimum Crude Oil Production from South Azadegan Oil Field with Emphasizing on Maximum Efficient Rate of Production based on Metaheuristic Algorithm of Particle Swarm Optimization (PSO)

Document Type : Research Paper

Authors

Pouriya Shokri 1
Ali Faridzad 2
Atefeh Taklif 2
Touraj Dehghani 3

1 MA Student of Energy Economics

2 Assistant Professor of Energy Economics, Faculty of Economics, Allameh Tabataba’i University

3 Energy Economics Research Center, Institute for International Energy Studies

https://doi.org/10.22054/jiee.2017.7996
Abstract
The act of planning in order to reach optimum production from crude oil reserves with emphasizing on technical limitations and economic modeling and forecasting, is known as a necessity to earn the maximum profit from oil export incomes and providing national intertemporal interests for oil producing and exporting countries. This study estimates the optimal trend of crude oil production from south Azadegan Iranian oil field by the metaheuristic algorithm of Particle Swarm Optimization (PSO) on a thirty-year period. The concept of maximum efficient rate (MER) is employed to reach the best simulation of technical and physical field properties and moreover, the three price scenarios and two discount rate scenarios are used to apply the economic dynamics of crude oil world market. The results show that applying EOR programs simultaneously during the production by gas injection into the anticline of SARVAK reservoir, proven reserve of the field can be increased up to 6 billion barrels in this period. It also increases the cumulative production up to 3 billion barrels during the simulation period which was about 1.4 billion barrels based on the present RMDP

Keywords

Oil Production
Dynamic Optimization
Enhanced Oil Recovery
Maximum Efficient Rate of Production
Algorithm of Particle Swarm Optimization (PSO)
South Azadegan Oil Fiel

  • Receive Date 18 June 2017
  • Accept Date 24 October 2017
  • First Publish Date 24 October 2017
  • Publish Date 21 March 2017

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