Research On Micro-seismic Location Method Based On Multi-wave Amplitude And Waveform Semblance

Hydraulic fracturing is an important technology for unconventional petroleum development and oil field stimulation,and micro-seismic monitoring is currently the major way to evaluate hydraulic fracturing effects while the source location is the core task.The forward modeling technique and source location inversion algorithm have been studied in this paper,and the inversion algorithm has been tested and analyzed based on several forward examples.In the forward modeling part,the standard staggered-grid finite difference technique,the PML absorption boundary and the loading method of seismic source have been studied in detail above all.Then considering that received waveform is the interaction result of the incident wave and the reflected wave in ground monitoring because the surface of the earth approximates the free-interface,while micro-seismic only needs the incident wave signal,therefore the influence of the free-interface on the amplitude and the polarization property of the received waveform has been referred in this paper,and the separation of the incident and reflected waves has been achieved successfully based on forward data.In the inversion part,the micro-seismic signal processing scheme has been introduced first in this paper,then the principal of establishing a velocity model based on acoustic logging data and the ray tracing technique in the layer model have been derived in detail.Next the PC-STA/LTA algorithm has been proposed based on polarization analysis technique and the STA/LTA algorithm,which responses better to weak signal than classic STA/LTA algorithm and can realize the detection of the P-and S-wave respectively.Finally,the principle and method of the weighted semblance location algorithm has been proposed by combining the comprehensive semblance location algorithm and the comprehensive amplitude location algorithm.Through the tests and analysis based on different kinds of forward model examples,it has been proved that the weighted semblance algorithm has a lower location error and stronger stability than the other two location algorithms.