Abstract

Lacustrine carbonate reservoirs, extensively distributed in China, have extensive oil and gas exploration potential. However, such reservoirs are characterized by high content of terrigenous debris and complex lithofacies, and the resultant high difficulty in lithofacies identification severely restrains exploration expansion and efficient development, especially for the Upper Member of the Paleogene Lower Ganchaigou Formation (E32) of the Yingxi area in the Qaidam Basin, with burial depths generally greater than 4000 m. This research targets this area and develops a methodology for detailed lithofacies identification, after systematically investigating the characteristics of lithofacies and well log responses of lacustrine carbonate rocks, on the basis of a massive volume of data of cores, thin sections, and experiments of the study area. The analysis identified lithofacies in the Upper Member of the Paleogene Lower Ganchaigou Formation of the Yingxi area, namely, pack-wackestone, mudstone, laminated carbonate, muddy gypsum, and limy claystone. The analysis of well log response characteristics suggested that natural gamma ray, matrix density, and bulk density were sensitive to lithofacies. Then, for the first time, the rock fabric factor (RFF) method was proposed, and the lithofacies identification plot was based on the calculated RFF and high-definition spectroscopy log. The presented methodology was applied to 55 wells in the study area. The average accuracy of lithofacies interpretation in 14 cored wells reached 82.4%, indicating good application performance. This method improves the lithofacies identification accuracy of lacustrine carbonate rocks, which is of great significance for investigating the reservoir distribution law and guiding exploration and development.

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