The range of coal-mine underground goaf has continuously expanded over time.Caving,fracture,and deformation zones have also changed,thereby inducing coal-mine water inrush and other environmental disasters.In this stu...The range of coal-mine underground goaf has continuously expanded over time.Caving,fracture,and deformation zones have also changed,thereby inducing coal-mine water inrush and other environmental disasters.In this study,4 D seismic monitoring technology that is effective in reservoir development was used to monitor abnormal changes in coal-mine underground goaf to explore the feasibility of the method.Taking a coal mine in Hancheng,Shaanxi as an example,we used the aforementioned technology to dynamically monitor the abnormal changes in the goaf.Based on the 4 D seismic data obtained in the experiment and the abnormal change characteristics of the coal-mine goaf,the method of 4 D seismic data processing in reservoir was improved.A set of 4 D data processing flow for the goaf was established,and the anomalies in the surface elevation and overlying strata velocity caused by collapse were corrected.We have made the following improvements to the method of 4 D seismic data processing in the reservoir:(1)the static correction problem caused by the changes of surface elevation and destruction of the low-velocity layer has been solved through fusion static correction to comb the low-frequency components of elevation statics with the high-frequency components of refraction statics;(2)the problem of overlying strata velocity changes in the goaf caused by collapse has been solved through the velocity consistency method;(3)the problem of reflection event pull-down in the disturbance area has been solved through space-varying moveout correction based on cross-correlation;and(4)amplitude anomalies in the coal seam caused by the goaf have been addressed using the correction method of space-varying amplitude.Results show that the 4 D seismic data processing and interpretation method established in this study is reasonable and effective.展开更多
Accurately detecting the arrival time of a channel wave in a coal seam is very important for in-seam seismic data processing. The arrival time greatly affects the accuracy of the channel wave inversion and the compute...Accurately detecting the arrival time of a channel wave in a coal seam is very important for in-seam seismic data processing. The arrival time greatly affects the accuracy of the channel wave inversion and the computed tomography （CT） result. However, because the signal-to-noise ratio of in-seam seismic data is reduced by the long wavelength and strong frequency dispersion, accurately timing the arrival of channel waves is extremely difficult. For this purpose, we propose a method that automatically picks up the arrival time of channel waves based on multi-channel constraints. We first estimate the Jaccard similarity coefficient of two ray paths, then apply it as a weight coefficient for stacking the multi- channel dispersion spectra. The reasonableness and effectiveness of the proposed method is verified in an actual data application. Most importantly, the method increases the degree of automation and the pickup precision of the channel-wave arrival time.展开更多
基金funded by the National Key Research and Development Program Subject(No.2018YFC0807804)。
文摘The range of coal-mine underground goaf has continuously expanded over time.Caving,fracture,and deformation zones have also changed,thereby inducing coal-mine water inrush and other environmental disasters.In this study,4 D seismic monitoring technology that is effective in reservoir development was used to monitor abnormal changes in coal-mine underground goaf to explore the feasibility of the method.Taking a coal mine in Hancheng,Shaanxi as an example,we used the aforementioned technology to dynamically monitor the abnormal changes in the goaf.Based on the 4 D seismic data obtained in the experiment and the abnormal change characteristics of the coal-mine goaf,the method of 4 D seismic data processing in reservoir was improved.A set of 4 D data processing flow for the goaf was established,and the anomalies in the surface elevation and overlying strata velocity caused by collapse were corrected.We have made the following improvements to the method of 4 D seismic data processing in the reservoir:(1)the static correction problem caused by the changes of surface elevation and destruction of the low-velocity layer has been solved through fusion static correction to comb the low-frequency components of elevation statics with the high-frequency components of refraction statics;(2)the problem of overlying strata velocity changes in the goaf caused by collapse has been solved through the velocity consistency method;(3)the problem of reflection event pull-down in the disturbance area has been solved through space-varying moveout correction based on cross-correlation;and(4)amplitude anomalies in the coal seam caused by the goaf have been addressed using the correction method of space-varying amplitude.Results show that the 4 D seismic data processing and interpretation method established in this study is reasonable and effective.
基金supported by the National Major Scientific and Technological Special Project during the 13th Five-year Plan Period(No.2016ZX05045003-005)
文摘Accurately detecting the arrival time of a channel wave in a coal seam is very important for in-seam seismic data processing. The arrival time greatly affects the accuracy of the channel wave inversion and the computed tomography （CT） result. However, because the signal-to-noise ratio of in-seam seismic data is reduced by the long wavelength and strong frequency dispersion, accurately timing the arrival of channel waves is extremely difficult. For this purpose, we propose a method that automatically picks up the arrival time of channel waves based on multi-channel constraints. We first estimate the Jaccard similarity coefficient of two ray paths, then apply it as a weight coefficient for stacking the multi- channel dispersion spectra. The reasonableness and effectiveness of the proposed method is verified in an actual data application. Most importantly, the method increases the degree of automation and the pickup precision of the channel-wave arrival time.
