1. A multi-mineral model for predicting petrophysical properties of complex metamorphic reservoirs: Case study of the Bozhong Depression, Bohai Sea.
- Author
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Guoqiang Zhang, Zhongjian Tan, Guibin Zhang, Dong Li, Chenchen Liu, Zhang Zhang, Jun Cao, and Xin Lei
- Subjects
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PETROPHYSICS , *METAMORPHIC rocks , *HYDROCARBON reservoirs , *PLAGIOCLASE , *X-ray diffraction - Abstract
Interpreting reservoir properties through log data and logging responses in complex strata is critical for efficient petroleum exploitation, particularly for metamorphic rocks. However, the unsatisfactory accuracy of such interpretations in complex reservoirs has hindered their widespread application, resulting in severe inconvenience. In this study, we proposed a multi-mineral model based on the least-square method and an optimal principle to interpret the logging responses and petrophysical properties of complex hydrocarbon reservoirs. We began by selecting the main minerals based on a comprehensive analysis of log data, X-ray diffraction, petrographic thin sections and scanning electron microscopy (SEM) for three wells in the Bozhong 19-6 structural zone. In combination of the physical properties of these minerals with logging responses, we constructed the multi-mineral model, which can predict the log curves, petrophysical properties and mineral profile. The predicted and measured log data are evaluated using a weighted average error, which shows that the multi-mineral model has satisfactory prediction performance with errors below 11% in most intervals. Finally, we apply the model to a new well "x" in the Bozhong 19-6 structural zone, and the predicted logging responses match well with measured data with the weighted average error below 11.8% for most intervals. Moreover, the lithology is dominated by plagioclase, K-feldspar, and quartz as shown by the mineral profile, which correlates with the lithology of the Archean metamorphic rocks in this region. It is concluded that the multi-mineral model presented in this study provides reasonable methods for interpreting log data in complex metamorphic hydrocarbon reservoirs and could assist in efficient development in the future. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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