DEVELOPING AN ENHANCED OIL RECOVERY SOFTWARE BY UTILIZING BIG DATA ANALYTICS TO EVALUATE VARIOUS ENHANCED RECOVERY METHODS

With the current challenges with depleted reservoirs and problems associated with heavy oil production, the implementation of the most cost-effective and feasible enhanced oil recovery method is inevitable. There are a wide range of EOR methods available and developed, which are in most cases expensive and complicated to carry out. Therefore, an extensive preliminary screening procedure is necessary before conducting a field-scale EOR method. However, there is not a comprehensive database or software available to carry out this extensive preliminary study which can be used as a reliable source. The current EOR software in the market do not cover the whole range of EOR methods, or they are just using conventional computation methods which are not robust and can not adopt to newer candidate reservoirs with specific and unique conditions. Furthermore, for the case of sequential oil recovery methods utilization there is not even enough experimental data and information available. It has been found that soft computing and optimization tools can be successfully used in the area of data mining and reservoir management in oil and gas industry. TO BE CONT'D

Intern: 
Medhi Mohammadpoor
Faculty Supervisor: 
Farshid Torabi
Province: 
Saskatchewan
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