›› 2017, Vol. 38 ›› Issue (4): 1-1.doi: 10.7657/XJPG20170418

   

Sweet Spot Identification with Well-Logging Data and Production Prediction for Coalbed Methane: A Case Study from Southern Shizhuang Block in Qinshui Basin

YU Jie1, QIN Ruibao1, LIANG Jianshe1, SUN Jianmeng2, WEI Xiaohan2, HUANG Tao1   

  1. (1.Research Institute, CNOOC, Beijing 100028, China; 2.School of Geosciences, China University of Petroleum, Qindao, Shandong 266580, China)
  • Online:2019-01-01 Published:1905-07-16

Abstract: The paper introduces a method to solve the problems in sweet spot identification and production prediction in coalbed methane wells by using conventional well logging data. Taking No.3 coal seam in southern Shizhuang block of Qinshui basin as an example and starting from the average daily gas production in individual CBM wells, the paper discusses the logging response characteristics of the coal seam and calculates the key parameters of the coal seam such as coal texture index, productivity index, gas content, gas saturation, critical desorption pressure and coal roof & floor features by using caliper, natural potential, gamma-ray, deep lateral resistivity and density logging curves. The paper establishes a composite coal-seam quality parameter by using coal texture index and productivity index, builds up criteria to identify CBM sweet spot with logging data by integrating the composite quality parameter, gas content, critical desorption pressure and coal roof & floor features, and predicts CBM production by using gas content and gas saturation in coal seams, and production scale coefficient. The application results from 97 CBM wells in the study area show that the accuracy rate of the prediction method can reach 84%.

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