Journal
JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING
Volume 156, Issue -, Pages 858-867Publisher
ELSEVIER SCIENCE BV
DOI: 10.1016/j.petrol.2017.06.066
Keywords
Reservoir heterogeneity; Analytic Hierarchy Process; Fuzzy Logic; Composite index; Distribution of remaining oil
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Funding
- CNPC [2016ZX05010001]
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There are three substantial challenges in quantitatively characterizing reservoir heterogeneity. The first challenge is that a single parameter is inadequate due to the existence of one-sidedness and blind spots. The second challenge lies in choosing which method to integrate multiple parameters. The third is how to predict the heterogeneity between wells for a complicated lithological reservoir. A new workflow is presented to address these problems. Nine parameters are integrated into one composite index (CI) using the Analytic Hierarchy Process (ARP) and Fuzzy Logic (FL). The CI calculated on wells is taken as hard data, the Lithology Ratio Model (LRM) is taken as constraint condition between wells, and the distribution of the CI is established using Sequential Gauss Simulation (SGS). The results show that the disadvantages of a single parameter are overcome. The CI is more reasonable and comprehensive, and the predicted CI between wells is more in line with geologic law under the constraints of the LRM. Most importantly there is a good correlation between the remaining oil enrichment area and the area CI > 0.5 in the contour map of the composite index (CMCI); therefore, the CMCI can be used to predict the distribution of remaining oil and improve oil recovery.
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