Loclization Method Research Of The Weak Microseismic Signal

Hydraulic fracturing is an important technology in the development of unconventional oil and gas reservoirs such as shale and tight sandstone,and microseismic monitoring is currently the main method to evaluate and adjust hydraulic fracturing.In recent years,with the development of unconventional oil and gas,the research and application of microseismic monitoring technology at home and abroad has developed rapidly,but there are still some key technologies that need further research.This paper focuses on the characteristics of weak microseismic signals,and studies a series of targeted methods such as denoising,signal recognition,velocity modeling and localization.Those targeted methods are great significance for enhancing the ability of microseismic monitoring technology to serve unconventional oil and gas development.The main procedures of microseismic localization include denoising of microseismic data,automatic identification of effective signals and velocity modeling.The most obvious characteristic of microseismic signals is that the signal-to-noise ratio is very low.Especially the surface microseismic signals are basically submerged in strong background noise.The denoising of microseismic signals is the basic work of microseismic positioning.In this paper,the microseismic denoising method is studied firstly,and the denoising method based on matching pursuit is proposed to improve the signal-to-noise ratio of the original data.The identification of effective microseismic signals in microseismic monitoring is a key step.Conventional single-channel microseismic effective signal identification methods are greatly affected by noise.The signal correlation between multi-channel recorded data is good and the correlation between signal and noise is poor.The total energy and the adjacent record cross-correlation are obtained by the track autocorrelation to obtain the signal energy,which is the ratio of effective signal energy.The signal-to-energy ratio is used as the threshold value for effective signal recognition.In the signal recognition process,the multi-channel cross-correlation is used to effectively suppress the noise,which improves the low-signal-to-noise ratio microseismic signal recognition capability.The establishment of the velocity model is another key technology in microseismic positioning,which directly affects the accuracy of the localization results.In the borehole microseismic monitoring,the layered velocity model is generally applied.Firstly,the PSO algorithm is applied to the optimization of the layered velocity model.Then,based on the problem of velocity modeling in surface microseismic monitoring,equivalent velocity model is proposed based on the uniform velocity model.The velocity model concept and the PSO algorithm is used to establish the model.This model ignores the geological meaning of the conventional velocity model and preserves the geophysical meaning of the velocity model,which reduces the difficulty of velocity modeling while ensuring the localization accuracy.The establishment of velocity model is another key technology in microseismic positioning,which directly affects the accuracy of the localization results.In the borehole microseismic monitoring,the layered velocity model is generally applied.Firstly,the PSO algorithm is applied to the optimization of the layered velocity model.Then,based on the velocity modeling problem in surface microseismic monitoring,a changing equivalent velocity model is proposed based on the uniform velocity model,and the PSO algorithm is used to establish the model.The model ignores the geological meaning of the conventional velocity model and preserves the geophysical meaning of the velocity model,which reduces the difficulty of velocity modeling while ensuring the localization accuracy.The localization of microseismic events is the core problem of microseismic monitoring.The conventional borehole microseismic localization method mainly uses the first arrival time and polarization information,and is not suitable for microseismic events with low signal to noise ratio.In this paper,we utilized the tracking component properties of microseismic events and the stack energy scanning localization method commonly used in surface microseismic monitoring to localize borehole microseismic events.The source localization is obtained by the grid search method.The biggest advantage of this method is that it does not need to pick up the first arrival information,so it is suitable for localization of borehole microseismic events with low signal-to-noise ratio.Aiming at the problem that the velocity model is difficult to establish for surface microseismic localization,this paper proposes a ray-free tracking localization method based on the space-variable equivalent velocity model,which improves the computational efficiency through the equivalent velocity model,multi-level grid search and OpenMP parallel strategy.This method also has better adaptability to complex structures,and the modeling process does not require well information,and the localization process avoids ray tracing and improves computational efficiency.Finally,a typical example of microseismic monitoring and surface microseismic monitoring in a Shengli Oilfield is selected to verify the effectiveness and applicability of the proposed method.It also provides a new idea for the research and application of microseismic monitoring in other oilfields.