Application Study of Microseismic Monitoring Technology in Horizontal Well Fracturing of Complex Structural Reservoir

Abstract

In order to solve the problem of artificial fracture network imaging, especially in complex tectonic area, the fracture attribute is analysed based on attribute characteristics of microseismic events, the impact of faults and natural fracture zones on reservoir reconstruction is monitored in real time. At the same time, the combination of seismic and microseismic interpretation improves the recognition accuracy of complex structural reservoirs, and provides real-time guidance for the optimization and adjustment of fracturing schemes for reservoir reconstruction. Multi wave joint location technology is used to locate the microseismic monitoring events in borehole. The orientation of artificial fracture network is monitored to identify the correlation between the direction of artificial fracture network and the direction of regional stress. Aiming at the complex well area with complex geological conditions, the large-scale reservoir reconstruction is effectively evaluated, and the distribution of fracture network is carefully evaluated, especially the complex reservoirs with natural fracture zone and fault zone, which effectively solves the problem of artificial fracture network imaging and control of tight oil reservoir, and improves the development effect of tight oil. The microseismic monitoring technology in borehole is suitable for large-scale and large-capacity reservoir fracturing reconstruction, and can make fine evaluation of the distribution of fracture network, especially for the complex reservoirs with relatively developed natural fracture zones and fault zones, which can better evaluate the characteristics of complex fracture network. Combining the relationship between seismic attributes and microseismic event attributes, microseismic monitoring technology can guide well location deployment and optimize well pattern. At the same time, it is suggested that the section with the greatest contribution to productivity be analyzed by subsection testing.