Imaging the subsurface using induced seismicity and ambient noise: 3-D tomographic Monte Carlo joint inversion of earthquake body wave traveltimes and surface wave dispersion
Imaging the subsurface using induced seismicity and ambient noise: 3-D tomographic Monte Carlo joint inversion of earthquake body wave traveltimes and surface wave dispersion
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DOI：
10.1093/gji/ggaa230
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发表时间：
2020-05
影响因子：
2.8
通讯作者：
Xin Zhang;C. Roy;A. Curtis;A. Nowacki;B. Baptie
中科院分区：
文献类型：
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作者：
Xin Zhang;C. Roy;A. Curtis;A. Nowacki;B. Baptie
地震体波走时层析成像和表面波色散层析成像已广泛用于表征地震和研究地球的地下结构。由于这些类型的问题通常是显着非线性的并且具有非唯一解，因此马尔可夫链蒙特卡罗方法已被用来寻找概率解。体波和表面波数据通常单独反演以产生独立的速度模型。然而，体波层析成像通常对发生地震的子体积周围的结构敏感，并且在较浅的地球中产生有限的分辨率，而表面波层析成像通常对较浅的结构敏感。为了更好地估计地下特性，我们同时使用体波和面波数据联合反演地震速度结构和地震位置。我们将新的联合反演方法应用于英国的一个矿场，该矿场发生了诱发地震，并在小型本地台站网络上进行了记录，并且可以从同一台站获得环境噪声记录。处理环境噪声以获得接收器间表面波色散测量值，该测量值与当地地震的体波到达时间联合反演。结果表明，使用两种类型的数据，可以比独立反演更好地约束震源参数和速度结构。为了进一步理解和解释结果，我们进行综合测试来比较体波反演和联合反演的结果。结果表明，如果仅使用体波数据，源参数和速度之间的权衡似乎会使结果出现偏差，但通过使用联合反演方法可以很大程度上解决这个问题。因此，使用环境地震噪声和我们的完全非线性反演提供了一种有价值的改进方法来对地下速度和地震活动进行成像。
Seismic body wave traveltime tomography and surface wave dispersion tomography have been used widely to characterize earthquakes and to study the subsurface structure of the Earth. Since these types of problem are often significantly non-linear and have non-unique solutions, Markov chain Monte Carlo methods have been used to find probabilistic solutions. Body and surface wave data are usually inverted separately to produce independent velocity models. However, body wave tomography is generally sensitive to structure around the subvolume in which earthquakes occur and produces limited resolution in the shallower Earth, whereas surface wave tomography is often sensitive to shallower structure. To better estimate subsurface properties, we therefore jointly invert for the seismic velocity structure and earthquake locations using body and surface wave data simultaneously. We apply the new joint inversion method to a mining site in the United Kingdom at which induced seismicity occurred and was recorded on a small local network of stations, and where ambient noise recordings are available from the same stations. The ambient noise is processed to obtain inter-receiver surface wave dispersion measurements which are inverted jointly with body wave arrival times from local earthquakes. The results show that by using both types of data, the earthquake source parameters and the velocity structure can be better constrained than in independent inversions. To further understand and interpret the results, we conduct synthetic tests to compare the results from body wave inversion and joint inversion. The results show that trade-offs between source parameters and velocities appear to bias results if only body wave data are used, but this issue is largely resolved by using the joint inversion method. Thus the use of ambient seismic noise and our fully non-linear inversion provides a valuable, improved method to image the subsurface velocity and seismicity.