Reservoir Quality Evaluation of the Asmari Formation by Integrating Diagenesis and Different Rock Typing Methods in Mansurabad Oilfield
Author(s):
Article Type:
Research/Original Article (دارای رتبه معتبر)
Abstract:
In this research, by studying 752 thin sections prepared from core and cuttings samples of two wells from the Mansourabad oilfield, nine microfacies were identified in a carbonate ramp type platform environment. Based on the description of the studied sections and petrography analysis, the most important diagenesis processes affecting the Asmari Formation were identified. According to the patterns of the facies change and well logs, five third-order depositional sequences (A to E) with the age of the Rupelian/Chattian to the Burdigalian were identified. Using the clustering method, five electrical facies were identified for both wells. One of the common methods to determine the flow units in the reservoir is the use of important and practical methods of indicating the flow unit zone using the modified Lorenz diagram methods. Using the FZI method on the estimated porosity-permeability data led to the identification of five hydraulic flow units in the well#8 and 6 flow units in the well#14. Moreover, by using the Lorenz method, six flow units for well#8 and three flow units for well#14 were identified using the porosity and permeability data estimated from the well log; which include speed, reservoir and baffle flow units. Based on the results of SMLP and the FZI methods of the estimated porosity and permeability, they provided the best and most complete separation method in this reservoir and are considered the most suitable method for determining rock types. By combining different methods in determining flow units, six and three flow units can be finally introduced for the Asmari Formation in the studied wells. The results of this study can be used in the development and better understanding of the Asmari Reservoir in the Mansourabad Oilfield.
Keywords:
Language:
Persian
Published:
Petroleum Research, Volume:33 Issue: 132, 2024
Pages:
63 to 80
https://magiran.com/p2683743
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