شماره ركورد كنفرانس :
5048
عنوان مقاله :
Application of Artificial Intelligence to Evaluate CO2 Flooding Profits for an Iranian Oil Field
Author/Authors :
Ehsan ،Esmaeil Nezhad Department of Petroleum Engineering - Shahid Bahonar University of Kerman, Iran , Mohammad ،Ranjbar Shahid Bahonar University of Kerman, Iran , Hossein ،Nezam Abadi Department of Electrical Engineering - Shahid Bahonar University of Kerman, Iran , Farokh ،Shoaei Fard Khamseh Iranian Offshore Oil Company, Tehran, Iran
كليدواژه :
Artificial Intelligence , Fuzzy Interface System , CO2 Flooding , Enhanced Oil Recovery
عنوان كنفرانس :
ششمين كنگره بين المللي مهندسي شيمي
چكيده لاتين :
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.
