Evaluation of Geology and Reservoir Characteristic of Sarvak Formation Using Adaptive Neuro-Fuzzy Method in One of the Hydrocarbon Fields of Southwest Iran

Authors

1 Ph. D. student, of Mining Engineering, Urmia University, Urmia, Iran

2 Assoc. Prof., Dept., of Mining Engineering, Urmia University, Urmia, Iran

Abstract

Azadegan field is one of Iran's oil fields, which is located in an area of 1500 km2 in the southwest of Iran in the northern Dezful region. According to the geological survey of the region, in the anticlines excavated in Azadegan field after the Aghajari formation, the Gachsaran, Asmari, Pabdeh, Jahrom, Gurpi, Tabor, Sarvak and Fahlian formations, are placed in the usual geological sequence. At present, in the Azadegan oil field, production is carried out from four oil formations, including Kazhdami, Gadvan, Fahlian andSarvak, although the main reservoir of this field is the Sarvak formation and it is composed of carbonate rocks. On the other hand, permeability is the most important factor for accurate description and modeling of hydrocarbon reservoir rocks. Usually, the standard methods for determining permeability are core analysis and well testing. These methods are very expensive, also the wells of a field do not have a core. As a result, because well logs are usually available in all the wells of a field, it will be very important to provide a method or methods that can provide the petrophysical properties of the reservoir, including permeability, using well logs. Smart methods are new, low-cost and accurate methods that can indirectly estimate reservoir permeability in the shortest possible time using well drilling data. Therefore, by using different well logs and the method of adaptive neural-fuzzy inference system (ANFIS), the permeability in Sarvak Formation, one of the hydrocarbon reservoirs in southwestern Iran, has been indirectly estimated. In order to use this intelligent method, the database was divided into two parts: training data (1754 data) and test data for evaluating the models (752 data). The results show the very appropriate performance of the intelligent method in permeability estimation. Therefore, the smart model can be used as a powerful, fast and accurate method for indirect estimation of permeability in reservoirs where permeability has not been measured through core.

Keywords

References

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New Findings in Applied Geology
Volume 17, Issue 34 - Serial Number 34
December 2023
Pages 127-141

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History

  • Receive Date: 26 June 2022
  • Revise Date: 22 October 2022
  • Accept Date: 27 November 2022

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