Selection of Hydraulic Fracturing Candidates in Iranian Carbonate Oil Fields: A Local Computerized Screening of Zone and Well Data

Hydraulic Fracturing (HF) is a mature technique to rehabilitate the productivity of a hydrocarbon formation, but Iranian oil companies are taking the primary steps to practice it in their oil fields. A couple of operations have been practiced but the unproductive results emphasized on the importance of Candidate Selection method. There is not a standard procedure or computerized tool to select primary candidates from Iranian carbonate oil fields. This paper presents the development of a locally written interface to automatically select specific zones for special operations like HF. The program is written in MATLAB in such a way to anticipate the missing data by Neural Network and Fuzzy Logic technique and then integrate large amount of data from different disciplines. In the end, data are mechanically screened based on the user selected parameters, cut-offs and weight factors. Results of screening within the limitations are prioritized in stacked bars to make decision easier. This tool is applied for a purpose of candidate selection for HF in M oil field located in south of Iran. This field has 585 zones which each zone has more than 30 parameters form different disciplines. The result of this programming is printed schematically and it is easy to see the quality of each criteria. This technique can be applied for unlimited number of zones and wells.