Application of Artificial Intelligence to Evaluate CO2 Flooding Profits for an Iranian Oil Field
Publish place: 06th International Congress on Chemical Engineering
Publish Year: 1388
نوع سند: مقاله کنفرانسی
زبان: English
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ICHEC06_538
تاریخ نمایه سازی: 1 مهر 1388
Abstract:
CO2 flooding as one of the Enhanced Oil Recovery (EOR) methods enormously developed during recent years. In this job, physical properties of CO2 widely studied, then reactions between this gas and reservoir fluid considered and based on that most important effective parameters for application of this method evaluated. It has been tried via Adaptive Network-based Fuzzy Interface System (ANFIS) along with more than 200 field data from all around the world to design a model proficient to foresight the best EOR method for a particular oil reservoir. Inputs for this model would be seven number of the most important reservoir representative parameters and as a result quantity of extra recovered oil is obtained. Based on the amount of oil recovery in different EOR methods it would be possible to choose the best method. Finally, based on designed model, Cumulative oil production in case of CO2 injection forecasted for an Iranian Oil Field. Based on the results for 15 years cumulative production, CO2 injection established as the best candidate for field application.
Authors
Ehsan Esmaeil Nezhad
Department of Petroleum Engineering, Shahid Bahonar University of Kerman, Iran
Mohammad Ranjbar
Energy and Environmental Engineering Research Centre (EERC), Shahid Bahonar University of Kerman, Iran
Hossein Nezam Abadi
Department of Electrical Engineering, Shahid Bahonar University of Kerman, Iran
Farokh Shoaei Fard Khamseh
Senior Reservoir Engineer, Iranian Offshore Oil Company, Tehran, Iran
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