水力压裂微地震事件分布趋势分析——以MY1井微地震监测为例

Distribution trend analysis of hydraulic fracturing events: taking MY1 Well microseismic monitoring as an example

李德伟 杨瑞召 张都 郭嘉梁 王博爱

中国矿业大学（北京），北京 100083

China University of Mining & Technology, Beijing 100083, China

水力压裂是非常规油气储层开发中极为重要的增产手段，微地震监测可以获得水力压裂储层改造的多种重要信息，然而，目前水力压裂诱发的微地震事件还不能被准确地预测。文中以MY1井微地震监测为例，应用三维地震获取的波阻抗和自动断层提取属性（AFE）分析微地震事件分布与地层岩性及天然裂缝之间的关系。首先，通过计算波阻抗与岩石弹性模量、泊松比之间的关系，确定储层高脆性岩石区域；其次，利用AFE识别储层天然裂缝的闭合状态和最大主应力方向；最后，通过储层脆性区域和应力状态共同分析微地震事件分布规律。波阻抗、AFE分析结果与微地震定位结果对比表明，在高波阻抗区域易发生裂缝，裂缝的发育趋势与该区域的最大主应力方向基本一致。微地震事件分布趋势分析有助于进一步了解压裂裂缝的控制因素，以及如何精确预测水力压裂的范围。

Hydraulic fracturing is an extremely important means of increasing production for unconventional oil and gas reservoir. Microseismic monitoring can obtain a variety of important information from hydraulic fracturing. However, current hydraulic fracturing cannot accurately predict the distribution of microseismic events. In this article, taking MY1 Well microseismic monitoring as an example, the wave impedance and automatic fault extraction attribute(AFE) acquired by 3D seismic are used to analyze the relationship between the distribution trend of microseismic events and stratum lithology and faults. First of all, the reservoir high-brittle rock region is determined by calculating the relationship between wave impedance and rock elastic modulus and Poisson′s ratio. Secondly, the 3D seismic automatic fault extraction attribute is used to identify the closed state and the maximum principal stress direction of the natural fracture of the reservoir. Finally, the fracture zone is analyzed by the reservoir fragile zone and the stress state. The comparison of wave impedance and AFE results with microseismic positioning results indicates that cracks are prone to occur in the high impedance region, and the development trend of the crack is approximately the same as the maximum principal stress direction of the region. Distribution trend analysis of microseismic events is useful for further understanding the control factors on fractures and accurate predicting the extent of hydraulic fracturing.

10.6056/dkyqt201903016