Joint inversion of two-dimensional magnetotelluric and surface wave dispersion data with cross-gradient constraints

2020 ◽  
Vol 221 (2) ◽  
pp. 938-950
Author(s):  
Pingping Wu ◽  
Handong Tan ◽  
Changhong Lin ◽  
Miao Peng ◽  
Huan Ma ◽  
...  
Keyword(s):  
Surface Wave ◽  
Velocity Structure ◽  
Joint Inversion ◽  
Wave Dispersion ◽  
Uniqueness Problem ◽  
Inversion Method ◽  
Inversion Algorithm ◽  
Surface Wave Dispersion ◽  
Gradient Constraints ◽  
Dispersion Data

SUMMARY Multiphysics imaging for data inversion is of growing importance in many branches of science and engineering. Cross-gradient constraint has been considered as a feasible way to reduce the non-uniqueness problem inherent in inversion process by finding geometrically consistent images from multigeophysical data. Based on OCCAM inversion algorithm, a direct inversion method of 2-D profile velocity structure with surface wave dispersion data is proposed. Then we jointly invert the profiles of magnetotelluric and surface wave dispersion data with cross-gradient constraints. Three synthetic models, including block homogeneous or heterogeneous models with consistent or inconsistent discontinuities in velocity and resistivity, are presented to gauge the performance of the joint inversion scheme. We find that owning to the complementary advantages of the two geophysical data sets, the models recovered with structure coupling constraints exhibit higher resolution in the classification of complex geologic units and settle some imaging problems caused by the separate inversion methods. Finally, a realistic velocity model from the NE Tibetan Plateau and its corresponding resistivity model calculated by empirical law are used to test the effectiveness of the joint inversion scheme in the real geological environment.

scholarly journals 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

2020 ◽  
Vol 222 (3) ◽  
pp. 1639-1655
Author(s):  
Xin Zhang ◽  
Corinna Roy ◽  
Andrew Curtis ◽  
Andy Nowacki ◽  
Brian Baptie
Keyword(s):  
Surface Wave ◽  
Ambient Noise ◽  
Velocity Structure ◽  
Joint Inversion ◽  
Body Wave ◽  
Source Parameters ◽  
Wave Dispersion ◽  
Inversion Method ◽  
Surface Wave Dispersion ◽  
Wave Data

SUMMARY 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.

scholarly journals A proper methodology aimed at surface wave tomography

1997 ◽  
Vol 40 (1) ◽  
Author(s):  
F. J. Sabadell ◽  
F. J. Serón ◽  
J. Badal
Keyword(s):  
Surface Wave ◽  
Convex Sets ◽  
Velocity Structure ◽  
Imaging Techniques ◽  
Spatial Prediction ◽  
Wave Dispersion ◽  
Inversion Method ◽  
Surface Wave Dispersion ◽  
Wave Tomography ◽  
Ray Path

When applying a methodology for obtaining the 3D shear-wave velocity structure of a medium from surface wave dispersion data, the problem must be considered with caution since one inverts path-averaged velocities and the use of any inversion method entails some drawbacks such as lack of uniqueness, unwarranted stability and constraints affecting the data. In order to avoid the application of consecutive inversions and to overcome these drawbacks, we propose alternative mapping methods, for example spatial prediction methods, or else the use of an algorithm that, from a mathematical viewpoint, can be understood through the application of the orthogonal projection theorem onto convex sets (POCS). Among the first ones, we try inverse weighted distance interpolation. The POCS algorithm we have used discretises a second order differential equation for the velocity field with boundary conditions. All these imaging techniques aimed at volumetric modelling and the visualisation of data are discussed, and finally we show some results based on ray path velocities obtained previously by inversion of phase and group velocities of Rayleigh waves propagating across the Iberian peninsula.

USTClitho2.0: Updated Unified Seismic Tomography Models for Continental China Lithosphere from Joint Inversion of Body-Wave Arrival Times and Surface-Wave Dispersion Data

2021 ◽  
Author(s):  
Shoucheng Han ◽  
Haijiang Zhang ◽  
Hailiang Xin ◽  
Weisen Shen ◽  
Huajian Yao
Keyword(s):  
Surface Wave ◽  
Joint Inversion ◽  
Body Wave ◽  
Wave Dispersion ◽  
Surface Wave Dispersion ◽  
Arrival Times ◽  
Velocity Models ◽  
Dispersion Data ◽  
Wave Travel ◽  
Wave Arrival

Abstract Xin et al. (2019) presented 3D seismic velocity models (VP and VS) of crust and uppermost mantle of continental China using seismic body-wave travel-time tomography, which are referred to as Unified Seismic Tomography Models for Continental China Lithosphere 1.0 (USTClitho1.0). Compared with previous models of continental China, the VP and VS models of USTClitho1.0 have the highest spatial resolution of 0.5°–1.0° in the horizontal direction and are useful for better understanding the complex tectonics of continental China. Although USTClitho1.0 is implicitly constrained by surface-wave data by using the VS model from surface-wave tomography and the converted VP model as initial models for body-wave travel-time tomography, the predicted surface-wave dispersion curves from USTClitho1.0 do not fit the observed data well. Here, we present updated 3D VP and VS models of the continental China lithosphere (USTClitho2.0) by joint inversion of body-wave arrival times and surface-wave dispersion data. Compared with the previous joint inversion scheme of Zhang et al. (2014), similar to Fang et al. (2016), it is further improved by including the sensitivity of surface-wave dispersion data to VP in the new joint inversion system. As a result, the shallow VP structure is also better imaged. In addition, the new joint inversion scheme considers the large topography variations between the eastern and western parts of China. Thus, USTClitho2.0 better resolves the upper-crustal structure of the Tibetan plateau. Compared with USTClitho1.0, USTClitho2.0 fits both body-wave arrival times and surface-wave dispersion data. Thus, the new velocity models are more accurate and can serve as a better reference model for regional-scale tomography and geodynamic studies in continental China.

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