Abstract
In this study, we used the multi-resolution graph-based clustering (MRGC) method for determining the electrofacies (EF) and lithofacies (LF) from well log data obtained from the intraplatform bank gas fields located in the Amu Darya Basin. The MRGC could automatically determine the optimal number of clusters without prior knowledge about the structure or cluster numbers of the analyzed data set and allowed the users to control the level of detail actually needed to define the EF. Based on the LF identification and successful EF calibration using core data, an MRGC EF partition model including five clusters and a quantitative LF interpretation chart were constructed. The EF clusters 1 to 5 were interpreted as lagoon, anhydrite flat, interbank, low-energy bank, and high-energy bank, and the coincidence rate in the cored interval could reach 85%. We concluded that the MRGC could be accurately applied to predict the LF in non-cored but logged wells. Therefore, continuous EF clusters were partitioned and corresponding LF were interpreted, and the distribution and petrophysical characteristics of different LF were analyzed in the framework of sequence stratigraphy.
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Acknowledgments
The authors extend their appreciation to Professors Fan Yiren, Wang Guiwen, Associate Professor Zhang Yuanzhong, and Dr. Wu Hongliang, their critical and constructive comments and suggestions greatly improved the paper.
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This Study is supported by the National Science and Technology Major Project of China (No. 2011ZX05029-003), and CNPC Science Research and Technology Development Project, China (No. 2013D-0904).
Tian Yu received his MS from Yangtze University in 2010. He is currently a Ph. D. student at China University of Mining and Technology, Beijing. His main research interests are sedimentary reservoir and logging geological research.
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Tian, Y., Xu, H., Zhang, XY. et al. Multi-resolution graph-based clustering analysis for lithofacies identification from well log data: Case study of intraplatform bank gas fields, Amu Darya Basin. Appl. Geophys. 13, 598–607 (2016). https://doi.org/10.1007/s11770-016-0588-3
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DOI: https://doi.org/10.1007/s11770-016-0588-3