页岩气产能预测方法的优选与评价

Optimization and evaluation of prediction methods for shale gas productivity

王乾宇 吴飞鹏 孙秋分 戴传瑞 刘静

中国石油大学（华东）石油工程学院，山东 青岛 266580 中国石油杭州地质研究院，浙江 杭州 310023

School of Petroleum Engineering, China University of Petroleum, Qingdao 266580, China Hangzhou Institute of Geology, Petrochina, Hangzhou 310023, China

合理的页岩气产能预测方法是动态储量评估和提高开发效益的关键。基于常用的6种产量递减方法，结合页岩气流动状态划分和某区块页岩气井实际生产数据，建立了页岩气井后期生产数据获取方法及产能预测方法优选规律。研究结果表明：对进入拟稳态阶段的生产井，前期流动状态参数对后期产能预测影响较大；前期流动状态参数在-0.40~-0.04时，产能预测选用改进延伸指数递减法或改进Duong递减法；前期流动状态参数在-0.50~-0.40时，产能预测选用双曲递减法或改进延伸指数递减法。对未进入拟稳态阶段的生产井，前期流动状态参数在-0.40~-0.04时，选用0.5×改进Duong递减法+0.5×改进延伸指数递减法获取后期生产数据；前期流动状态参数在-0.50~-0.40时，选用0.5×改进延伸指数递减法+0.5×双曲递减法获取后期生产数据；基于获取的后期生产数据，利用优选方法进行产能预测。选取实际生产数据，对进入拟稳态阶段的生产井进行分析，预测产量的误差平均为4.51%，证明了产能预测方法优选规律的可靠性。

Reasonable prediction methods for shale gas productivity is the key to evaluate dynamic reserve and enhance development benefit. Based on six common production decline methods, the method of late shale gas data acquisition and optimization rule of productivity prediction method are established in combination with flow state division of shale gas and actual production data from shale gas wells in a block. The results show that: for the production wells entering the quasi-steady state stage, the early flow state has great influence on the late productivity prediction. When the early flow state parameters range from -0.40 to -0.04, the modified SEPD (YM-SEPD) method or improved Duong declining method is chosen to predict productivity; when the early flow state parameters range from -0.50 to -0.40, hyperbolic decline method or YM-SEPD method are chosen to predict productivity. For the production wells not entering the quasi-steady state stage, when the early flow state parameters range from -0.40 to -0.04, 0.5 × improved Duong declining method+0.5 × YM-SEPD method are chosen to get the late production data; when the early flow state parameters range from -0.50 to -0.40, 0.5 × hyperbolic decline method +0.5 × YM-SEPD method are chosen to get the late production data. Based on the acquired late data, the productivity prediction is carried out through the optimization methods. The actual production data was selected to analysize evaluation case of well entering the pseudo-steady state stage, with an average error of 4.51% in productivity prediction, which proves the reliability of optimization rule of productivity prediction method.

10.6056/dkyqt202304005