Magnetotelluric(MT)three-dimensional inversion has the advantages of simple data preprocessing, the model is close to actual situation, and the inversion result is more reliable and stable. It is one of the most advanced research topics and would take the place of the dominant two-dimensional inversion definitely. With the improvement of computing capability of computers and the breakthrough in inversion methods, great progress was made in MT three-dimensional inversion in recent years, from the theoretical research and test of this method at the beginning to the current application to practical data interpretation. For the great computation amount of MT three-dimensional inversion, current MT three-dimensional inversion algorithm programs are all implemented in parallel way and it is recommended to do three-dimensional inversion calculations on supercomputing system to make better use of computing resources and improve the inversion efficiency.

Different from the MT three-dimensional inversion algorithm programs which have basically realized the utility function, the practical application of MT three-dimensional inversion is still in an early stage. Users should be familiar with the use of multiple software and fulfill the function manually with the help of the software as follows: generating the files required for the inversion program, connecting to the supercomputer to upload data, inputting the command to perform the inversion, etc. The process of manually connecting and operating calculations is the most primitive cloud computing. All processes need to be done manually, which would cause not only heavy workload and the complicated operation, but also the problems for the long-term effective preservation and management of complex inversion data.

To conquer this, we develop independently a three-dimensional magnetotelluric inversion cloud computing system, toPeak, using Delphi language. This paper introduces some main features of toPeak. To begin with, system design and analysis are carried out in combination with the current situation and system structure and functions are realized. The main idea is to realize a set of cloud computing system platform based on server-client(C/S), on the basis of perfect inversion data management, integrate the most advanced three-dimensional magnetotelluric inversion algorithm program in the cloud, and connect through the Internet to realize all the system functions of three-dimensional magnetotelluric inversion. Then, the different parts of toPeak are introduced separately, including design structures and designs. The server is deployed on the supercomputer system(supercomputing)to receive the data for inversion tasks, configure and manage the storage of the inversion result data. Combined with the Internet connection, the server and the Internet together constitute a computing cloud. The client is deployed on the users’ windows operating system, including Windows visual data integration processing software and Internet operation middleware. The client is designed on the basis of object-oriented programming ideas, with data as the core, using data engineering objects to encapsulate and store all MT data, process and interpret the results, realize data processing inversion and other operations around this data project, and display the process and results of these processing and inversion in graphics using visualization technology. Internet operation middleware connects the client and server based on the SSH protocol to realize data processing and inversion, transmission and command sending and receiving. Furthermore, the whole work flow of inversion using toPeak and parts of procedure of it are shown. At last, some inversion results from toPeak are displayed. toPeak has realized the full functions require for implementing three-dimensional inversion and can grid, process and select, inverse and explain the data. It is a good tool for the practical use of three-dimensional inversion.

On July 12, 2020, an M_S5.1 occurred in Guye, Hebei Province, and as the largest earthquake in the capital circle in recent years, its unique geographical location has attracted more attention. During an earthquake, the electromagnetic properties of underground media will change, so dense electromagnetic observation stations were arranged in the capital circle. In this study, the data of geoelectric resistivity, geoelectric field, and extremely low frequency(ELF)observation within 400km of the Guye earthquake are analyzed using a combination of time-domain waveform analysis, sliding Fourier analysis with annual variation removed, normalized variation rate method(NVRM), and geo-electric azimuthal method. After eliminating the influencing factors such as operation status, observational environment, and the spatial electromagnetic effect, we analyzed the characteristics of electromagnetic phenomena that may be related to the Guye earthquake preliminarily and found that there was a variation process of “trend decrease—accelerated decrease—postseismic recovery” observed in 6 geoelectric resistivity stations and that the normalized variation rate exceeded the threshold value of ±2.4 in 7 stations within one year before the earthquake. In Luanxian station, the intensity of the geoelectric field in the north-south and north-western directions decreased and then rose back before the earthquake. In addition, the azimuth shifted to the direction of the Guye earthquake in the preseismic period, and then returned to the direction of the Luanxian-Laoting Fault. The ELF stations in Wen'an and Fengning precisely recorded the coseismic change of the 16Hz natural magnetic field, in which the variation of the vertical component is twice larger than that of the horizontal component. Under the condition of large subsurface structure difference beneath the stations, the observed electric values from the two stations are distinctively different; moreover, the coseismic disturbance is submerged by the background noise. The subsurface electric structure was obtained by interpolating and inversing the data collected from the ELF stations in the capital area, which indicates that the Guye earthquake occurs near the boundary of the electric property changes. Meanwhile, it shows high electric resistivity in the northern area, low electric resistivity in the southwestern area, and partially low electric resistivity in Baodi and Wen'an, which is consistent with the location of the abnormally stronger ground motion. Regarding the spatial selectivity of the anomalies, we believe it may be related to the direction of the two main conjugated structures in the capital area, which lie in NEE and NW direction, respectively. And the study also enlightens researchers that the investigation of the mechanism of seismic electromagnetic anomaly should start from the coseismic phenomenon, and then focus on the aspects of seismic signal source and propagation path, because the extremely low-frequency observation band is wide and the coseismic electromagnetic signals can be clearly recorded. There are many effective ways to extract electromagnetic signals related to earthquakes from strong interference background, such as making retrospective analysis of moderately strong earthquakes in time, summarizing the electromagnetic anomaly characteristics of different earthquake events, densifying the electromagnetic observation layout appropriately, so that the abnormal information can be mutually corroborated and a variety of means for fusion and comparative analysis can be developed.

The first control source extremely low frequency(CSELF)electromagnetic observation network through the world, consisting of 30 fixed stations located in the Beijing captical circle region(15 staions)and the sourthern secton of the north-south earthquake belt(15 stations), China, has been established under the support of the wireless electromagnetic method(WEM)project, one of the national science and technology infrastructure construction projects during the 11th Five-year Plan period. As a subsystem of the WEM project, the CSELF network is mainly to study the relationship between elctromagnetic anomalies and mechanisms of earthquake, and further improve our ability to monitor and predict earthquakes by monitoring real-time dynamic changes in both electromagnetic fields and subsurface electric structure. Carrying out the detection of the underground background electric structure in the CSELF network area/station is an important part of this project and of great significance to play its role in the study of earthquake prediction and forecast. In this paper, we elaborate how to acquire the subsurface electric structure of the CSELF network in the Beijing captical circle region and make a simple explanation for the structure. Firstly, a short magnetotelluric(MT)profile, almostly perpendicular to the regional geological strike, was deployed at each station of the CSELF network in the capital circle region during the 2016 and a total of 60 broadband MT sites was collected using ADU -07e systems. Then, all the time series data were processed carefully using the robust method with remote reference technique to MT transfer functions. MT data quality was assessed using the D+algorithm. In general, data at most sites are of high quality as shown by the good consistency in the apparent resistivity and phase curves. Different impedance tensor decomposition methods including the phase tensor analysis, Groom and Bailey(GB)tensor decompositon, and statistical image method based on multi-site, multi-frequency tensor decompositon were used to analyze data dimensionality and directionality. For data inversion, on the one hand, one-dimensional(1-D)subsurface electrical resistivity structures at each station and MT site were derived from 1-D adaptive regularized MT inversion algorithm. On the other hand, we also imaged the 2-D electric structures along the short MT profile by the nonlinear conjugate gradients inversion algorithm at each station. Robustness of all 2-D structures along each short profile were verified by sensitivity tests. Although fixed stations and MT sites are limited and distributed unevenly, the 3-D inversion of 15 stations was also performed to produce a 3-D crustal electrical resistivity model for the entire network using the modular system for 3-D MT inverson: ModEM based on the nonlinear conjugate gradients algorithem. Intergrating 1-D, 2-D and 3-D inversion results, the resistivity structure beneath the CSELF network in captical circle region revealed some significant features: The crustal electrical structures are mainly characterized by high resistivity beneath the Yinshan-Yanshan orogenic belt in the northern margin of North China, the Taihangshan area in the middle, the Jiao-Liao block in the east, while the North China Plain and Shanxi depression areas have relatively lower resistivity in the crust; There are obvious electrical resistivity difference on both sides of the gravity gradient of Taihang Mountains and the Tanlu fault zone, which indicates they could be manifested as an electric structure boundary zone, respectively. Overall, the electric structure characteristics of the entire network area shows high correspondence with the regional geological structure and earthquake activity to some extent. In summary, implementing the detection of underground electrical resistivity structure in the CSELF network of the capital circle region will provide important foundations for the researches on the regional seismogenic environment, the generation mechanism of seismic electromagnetic anomaly signals, and earthquake prediction and forecast.

The East Kunlun Fault is a giant fault in northern Tibetan, extending eastward and a boundary between the Songpan-Ganzi block and the West Qinling orogenic zone. The East Kunlun Fault branches out into a horsetail structure which is formed by several branch faults. The 2017 Jiuzhaigou M_S7.0 earthquake occurred in the horsetail structure of the East Kunlun Fault and caused huge casualties. As one of several major faults that regulate the expansion of the Tibetan plateau, the complexity of the deep extension geometry of the East Kunlun Fault has also attracted a large number of geophysical exploration studies in this area, but only a few are across the Jiuzhaigou earthquake region. Changes in pressure or slip caused by the fluid can cause changes in fault activity. The presence of fluid can cause the conductivity of the rock mass inside the fault zone to increase significantly. MT method is the most sensitive geophysical method to reflect the conductivity of the rock mass. Thus MT is often used to study the segmented structure of active fault zones. In recent years MT exploration has been carried out in several earthquake regions and the results suggest that the location of main shock and aftershocks are controlled by the resistivity structure. In order to study the deep extension characteristics of the East Kunlun Fault and the distribution of the medium properties within the fault zone, we carried out a MT exploration study across the Tazang section of the East Kunlun Fault in 2016. The profile in this study crosses the Jiuzhaigou earthquake region. Other two MT profiles that cross the Maqu section of East Kunlun Fault performed by previous researches are also collected. Phase tensor decomposition is used in this paper to analyze the dimensionality and the change in resistivity with depth. The structure of Songpan-Ganzi block is simple from deep to shallow. The structure of West Qinlin orogenic zone is complex in the east and simple in the west. The structure near the East Kunlun Fault is complex. We use 3D inversion to image the three MT profiles and obtained 3D electrical structure along three profiles. The root-mean-square misfit of inversions is 2.60 and 2.70. Our results reveal that in the tightened northwest part of the horsetail structure, the East Kunlun Fault, the Bailongjiang Fault, and the Guanggaishan-Dieshan Fault are electrical boundaries that dip to the southwest. The three faults combine in the mid-lower crust to form a “flower structure”that expands from south to north. In the southeastward spreading part of the horsetail structure, the north section of the Huya Fault is an electrical boundary that extends deep. The Tazang Fault has obvious smaller scale than the Huya Fault. The Minjiang Fault is an electrical boundary in the upper crust. The Huya Fault and the Tazang Fault form a one-side flower structure. The Bailongjiang and the Guanggaishan-Dieshan Fault form a “flower structure”that expands from south to north too. The two “flower structures”combine in the high conductivity layer of mid-lower crust. In Songpan-Ganzi block, there is a three-layer structure where the second layer is a high conductivity layer. In the West Qinling orogenic zone, there is a similar structure with the Songpan-Ganzi block, but the high conductivity layer in the West Qinling orogenic zone is shallower than the high conductivity layer in the Songpan-Ganzi block. The hypocenter of 2017 M_S7.0 Jiuzhaigou earthquake is between the high and low resistivity bodies at the shallow northeastern boundary of the high conductivity layer. The low resistivity body is prone to move and deform. The high resistivity body blocked the movement of low resistivity body. Such a structure and the movement mode cause the uplift near the East Kunlun Fault. The electrical structure and rheological structure of Jiuzhaigou earthquake region suggest that the focal depth of the earthquake is less than 11km. The Huya Fault extends deeper than the Tazang Fault. The seismogenic fault of the 2017 Jiuzhaigou earthquake is the Huya Fault. The high conductivity layer is deep in the southwest and shallow in the northeast, which indicates that the northeast movement of Tibetan plateau is the cause of the 2017 Jiuzhaigou earthquake.

Many synthetic model studies suggested that the best way to obtain good 3D interpretation results is to distribute the MT sites at a 2D grid array with regular site spacing over the target area. However, MT 3D inversion was very difficult about 10 years ago. A lot of MT data were collected along one profile and then interpreted with 2D inversion. How to apply the state-of-the-art 3D inversion technique to interpret the accumulated mass MT profiles data is an important topic. Some studies on 3D inversion of measured MT profile data suggested that 2D inversions usually had higher resolution for the subsurface than 3D inversions. Meanwhile, they often made their interpretation based on 2D inversion results, and 3D inversion results were only used to evaluate whether the overall resistivity structures were correct. Some researchers thought that 3D inversions could not resolute the local structure well, while 2D inversion results could agree with the surface geologic features much well and interpret the geologic structures easily. But in the present paper, we find that the result of 3D inversion is better than that of 2D inversion in identifying the location of the two local faults, the Shade Fault(SDF)and the Yunongxi Fault(YNXF), and the deep structures.
In this paper, we first studied the electrical structure of SDF and YNXF based on a measured magnetotelluric(MT) profile data. Besides, from the point of identifying active faults, we compared the capacity of identifying deep existing faults between 2D inversion models and 3D models with different inversion parameters. The results show that both 2D and 3D inversion of the single-profile data could obtain reasonable and reliable electrical structures on a regional scale. Combining 2D and 3D models, and according to our present data, we find that both SDF and YNXF probably have cut completely the high resistivity layer in the upper crust and extended to the high conductivity layer in the middle crust. In terms of the deep geometry of the faults, at the profile's location, the SDF dips nearly vertically or dips southeast with high dip angle, and the YNXF dips southeast at depth. In addition, according to the results from our measured MT profile, we find that the 3D inversion of single-profile MT data has the capacity of identifying the location and deep geometry of local faults under present computing ability. Finally, this research suggests that appropriate cell size and reasonable smoothing parameters are important factors for the 3D inversion of single-profile MT data, more specifically, too coarse meshes or too large smoothing parameters on horizontal direction of 3D inversion may result in low resolution of 3D inversions that cannot identify the structure of faults. While, for vertical mesh size and data error thresholds, they have limited effect on identifying shallow tectonics as long as their changes are within a reasonable range. 3D inversion results also indicate that, to some extent, adding tippers to the 3D inversion of a MT profile can improve the model's constraint on the deep geometry of the outcropped faults.