1. Quantitative Evaluation of Paleocene Reservoir Diagenetic Facies by Logging in Lishui West Sag, East China Sea Basin
- Author
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Ji Teng, Qiang Fu, Jun Qin, Wenrui Ma, Guanyu Zhang, and Kailong Feng
- Subjects
diagenetic facies ,diagenetic comprehensive coefficient ,logging identification ,East China Sea Basin ,Lishui West Sag ,Mineralogy ,QE351-399.2 - Abstract
Exploration in the Lishui West Sag of the East China Sea Basin is limited by the scarcity of offshore drilling sites, and the prediction of deep, high-quality reservoirs is challenging using only geophysical methods. This study introduces a quantitative approach to diagenetic facies division in individual wells based on logging data, providing a new method and perspective for the prediction of deep, high-quality reservoirs. We employed comprehensive data from core, logging, thin-section casting, cathodoluminescence, scanning electron microscopy, and X-ray diffraction analyses from five wells to study the petrology, physical properties, diagenetic types and strength, and diagenetic minerals of the Paleocene sandstone reservoirs in the Lishui West Sag. Apparent compaction rate, apparent cementation rate, and other quantitative characterization parameters were used to calculate the comprehensive diagenetic coefficient (Cg), and the diagenetic facies were divided into compaction, cementation, and dissolution facies. A logging calculation model for the comprehensive diagenetic coefficient (Cg) and a quantitative identification method for diagenetic facies in individual well reservoirs were established through a fitting analysis between Cg and logging curve parameters. Continuous quantitative identification of vertical diagenetic facies in the five wells in the study area showed that the high-quality reservoirs in wells L1, L2, and L3 within the L1 gas field are characterized by extensive development of dissolution facies, while wells L4 and L5 are dominated by compaction and cementation facies, with poor reservoir properties and no industrial gas flow output. The results demonstrate the reliability of the model method. The establishment of this quantitative characterization method for diagenetic facies using logging data provides guidance for the prediction of favorable reservoirs.
- Published
- 2023
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