Microearthquake Detection and Its Tectonic Implications in the Eastern Segment of the East Kunlun Fault Zone
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摘要: 本文整理了一套包括微震检测、地震去噪、震相拾取和地震定位的构建高精度地震目录数据的处理流程。收集了青海省内东昆仑断裂带东段20个数字地震台站记录的2009—2018年的连续地震数据，并应用该流程进行微震检测、去噪和定位。首先，从台网中心提供的
3198 个地震事件目录中筛选出1200 个信噪比高且震相较为明显的地震事件作为模板事件，利用基于图像处理器加速的模板匹配定位方法（GPU-M&L）进行遗漏地震的检测与识别，然后利用基于神经网络的地震波形去噪方法进行去噪处理，再结合基于深度学习的震相拾取技术和双差定位方法对去噪后的地震事件进行震相拾取和定位。使用GPU-M&L共检测出13318 个地震事件，约为台网地震目录事件数量的4.2倍；去噪后得到7514 个地震事件，约为台网地震目录事件数量的2.3倍，完备震级从台网目录的ML 1.5降低至ML 0.9。定位后共获得7247 个地震事件，精定位结果显示，东昆仑断裂带东段的地震以中小震为主，在空间上呈窄条带状或簇状分布，震源深度的优势分布深度为0～15 km；在101°E附近地震的空间展布发生变化，主要沿阿万仓断裂带向东南展布；在玛沁-玛曲段可能存在地震空区。本研究的微震结果为研究东昆仑断裂带东段地震活动性、发震断层的深部构造等提供了重要的数据基础。Abstract: To comprehensively analyze the seismic activity of the East Kunlun Fault Zone from 2009 to 2018, we developed a procedure encompassing microearthquake detection, seismic denoising, seismic phase picking, and seismic location to construct a seismic catalog. We collected continuous waveforms recorded by 20 stations in the eastern segment of the East Kunlun Fault Zone from January 2009 to December 2018. From the3198 seismic events listed in the China Earthquake Networks Center (CENC) catalog, we selected1200 events with clear seismic phases and high signal-to-noise ratios as template events. Using the Graphics Processing Unit-based Match and Locate (GPU-M&L) method, we detected a total of 13,318 earthquake events, including the template events, which is roughly 4.2 times the number of events in the CENC catalog. Next, we employed the neural network-based seismic waveform denoising technique (DeepDenoiser) to extract seismic signals from the noise. By examining the time-domain and frequency-domain characteristics of noise and seismic signals, we further identified and confirmed 7514 seismic events, approximately 2.3 times the number reported by the CENC. The complete magnitude of the detected catalog decreased from ML 1.5, as given by the CENC, to ML 0.9 in this study. Subsequently, we applied the deep neural network-based seismic arrival-time picking algorithm (PhaseNet) to pick the seismic phases. Finally, using the double-difference localization method (hypoDD), we finely located 7247 events. The results show that earthquakes in the eastern segment of the East Kunlun Fault Zone are linearly distributed or clustered, with focal depths predominantly ranging from 0 to 15 km. East of 101°E, the spatial distribution of earthquakes mainly spreads southeastward along the Awancang Fault Zone. Additionally, our results indicate a possible seismic gap in the Maqin-Maqu segment. This study provides an important database for further research on seismic activity and deep seismogenic faults in the eastern segment of the East Kunlun Fault Zone. -
图 1 研究区域地震事件和台站分布图
Figure 1. The distribution of earthquake events and stations in the study area
图 2 利用GPU-M&L方法检测到的地震事件
Figure 2. An example of earthquake event detection by using GPU-ML
图 3 台网目录事件（黑色圆点）与GPU-M&L检测地震事件（红色圆点）震中分布图
Figure 3. Distributions of events （the black dots）from the catalog and the events （the red dots） detected by GPU-M&L
图 4 台网中心地震目录与GPU-M&L检测结果的地震事件对比
Figure 4. The comparison of magnitude–frequency between the catalogue events and the detected events
图 5 1.58级地震事件波形去噪前后对比
Figure 5. The waveform comparison of a ML 1.58 event before and after denoising
图 6 利用DeepDenoiser对不同台站记录到的同一个地震事件Z分量去噪前后波形对比
Figure 6. The waveform comparison of Z components before and after denoising
图 7 台网中心地震目录与去噪后地震事件震级-数量对比
Figure 7. The magnitude–frequency comparison between the catalogue events and the denoised events
图 8 去噪后目录与原始目录最小完备震级对比
Figure 8. The MC comparison between the original and denoised catalogues
图 10 去噪后的地震事件P波和S波走时曲线
Figure 10. The time-distance curves for P and S waves, as illustrated in the left and right panels respectively
图 11 台网目录事件（灰色圆点）与新目录地震事件（红色圆点）重定位后分布对比
Figure 11. The event distribution given by the CENC catalogue （gray dots） and the relocated catalogue （red dots）
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