Artificial Intelligence: Excellent Key for Developing E&P Oil Industry in Iraq

Authors

  • Wathiq Almudhafer Iraqi south Oil company
  • Maitham Shaheed Ph.D. .Student, school of Computer Science, Manchester University

DOI:

https://doi.org/10.52716/jprs.v2i1.29

Abstract

A Multidisciplinary study for increasing oil recovery has been made in the present paper. This work has been adopted in the Upper Sandstone member/Zubair formation in South Rumaila Oil Field. The work was achieved by using optimization techniques for determining the optimal future reservoir performance regarding to infill drilling. Two different methods of Genetic Algorithm used to optimize the number and locations of infill wells. The first method is simple adaptive genetic algorithm and the second one is the breeder adaptive. The main parameters depended in this study is the cumulative oil production obtained from the output of reservoir simulation software. These two methods of GA depend on using Net Present Value (NPV) as economic analysis as objective function. The optimal number of infill wells is three wells which have maximum cumulative oil production and maximum value of NPV. The same results from two GA methods have been obtained. The locations of these optimal infill wells located in the crest of the oil field.  

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Published

2011-02-01

How to Cite

(1)
Almudhafer, W. .; Shaheed, M. . Artificial Intelligence: Excellent Key for Developing E&P Oil Industry in Iraq. Journal of Petroleum Research and Studies 2011, 2, 1-25.