Due to the increasing importance of well-logging methods in oil and gas exploration and the high costs of exploratory drilling and core extraction from wells, extraction of petrophysical parameters of reservoir rocks from well logging data has become particularly important. In this way, the in situ data from the reservoir conditions can be used to predict the reservoir behavior for later stages such as reservoir exploitation and engineering. In the present study, using electrofacies clustering of one of the wells in Nowruz oil field, both the lithology zones of the reservoir and changes in reservoir quality at different depths are investigated using well-logging data. Initially, using electrofacies from some well-logging data such as acoustic, density, corrected gamma diagrams, etc., the reservoir electrofacies classifications were performed based on MRGC and SOM methods. It was determined that the selection MRGC clustering methods with 7 classes on the mentioned diagrams showed the best compliance with the predicted lithology in the reservoir and the relevant geological report. It should be noted that the proposed clusters are sensitive to minor changes in lithology. Also, by examining the porosity and permeability data measured from the sample of drilling cores taken in a part of the reservoir, it was found that FZI clustering is able to separate the main lithology zones in the reservoir and is in good agreement with them. According to this result and to eva‎luate the degree of reservoir clustering compliance in terms of reservoir quality index and lithology, the normalized cumulative reservoir quality index (ncRQI) was calculated. The general slope changes in the ncRQI diagram showed a good agreement with the main changes in lithology and changes in the formations in the reservoir. Then, by calculating the slope changes of the ncRQI diagram at each depth of the reservoir and clustering the values of the mentioned slopes by fuzzy logic method, there is an acceptable agreement between the cluster boundaries of the slopes obtained from ncRQI and the MRGC clustering. The results of both clustering showed significant compliance with the reservoir quality index zone presented in the relevant geological report.

حمزه صادقي سرخني، محمد ابطحي فروشاني

نادر فتحيان پور، علي رضا خزعلي