Log-based in situ stress prediction of deep coalbed methane reservoirs in the Daji block
XIE Zheng-Long1(), LIU Zhi-Di1,2(), HAN Hong-Lai1, WANG Duo1, WANG Cheng-Wang3, WANG Wei4, JI Liang4
1. School of Earth Sciences and Engineering, Xi 'an Shiyou University, Xi 'an 710065, China 2. Shaanxi Key Laboratory of Petroleum Accumulation Geology, Xi 'an Shiyou University, Xi 'an 710065, China 3. Engineering Technology Research Institute of PetroChina Coalbed Methane Co., Ltd., Xi 'an 710082, China 4. Hancheng Gas Production Management Area, PetroChina Coalbed Methane Co., Ltd., Hancheng 715400, China
For deep coalbed methane (CBM) exploration and production, accurate in situ stress prediction holds critical significance for safe and efficient drilling and completion of wells. Deep CBM reservoirs, once considered restricted areas for exploration and exploitation, have been highly anticipated owing to their high yields in recent years. However, their in situ stress prediction model has not been investigated effectively. Hence, this study systematically analyzed six in situ stress prediction models commonly used for conventional oil and gas reservoirs and unconventional gas (like CBM) reservoirs. Based on these prediction models, this study calculated the in situ stress, and found that the combined spring model and the Newberry model yielded relatively high accuracy through comparative analysis of closure pressures. To improve the accuracy of in-situ stress prediction models, the effective stress coefficient of coal rocks was employed to optimize the two models. The optimized in-situ stress models yielded prediction accuracy errors reduced by 4%, roughly meeting the requirements of in-situ stress prediction accuracy for deep CBM exploration and production in the Daji block.
谢正龙, 刘之的, 韩鸿来, 王舵, 王成旺, 王伟, 季亮. 大吉区块深部(层)煤层气储层地应力测井预测研究[J]. 物探与化探, 2024, 48(2): 356-365.
XIE Zheng-Long, LIU Zhi-Di, HAN Hong-Lai, WANG Duo, WANG Cheng-Wang, WANG Wei, JI Liang. Log-based in situ stress prediction of deep coalbed methane reservoirs in the Daji block. Geophysical and Geochemical Exploration, 2024, 48(2): 356-365.
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