# Teleseismic Tomography for Imaging the Upper Mantle Beneth Northeast China
## 1 Introduction  
Tomographic imaging technology is a geophysical inversion interpretation method, which uses medical Computed Tomography (CT) for reference. Tomographic technology is to use slice images to describe the specific shape of objects. This technology was first used in medical X-ray imaging of human organs, named CT imaging. In addition to medical CT imaging, tomographic technology has been widely used in many disciplines, such as atmospheric science, marine science, biology, and geophysics [1]. Among them, using seismic data to image the earth's interior is one of the core research contents of geophysics and even geoscience [2]. Computer science developed very fast in the 1970s, and many computing devices have been used in earth science. Seismologists first introduced tomographic technology into seismology in 1974, and published the first work related to seismic tomographic imaging from 1976 to 1977 [3, 4]. Seismic tomography is similar to medical CT, which is also based on a large number of cross-path constraints [5]. In the process of seismic tomography, the stations receiving seismic wave rays cannot be moved [6]. Theunderground rays received by seismic tomography come from all directions, therefore, the arrangement of seismic receivers can consider dense lines or scattered grids [7]. The seismic tomographic source can be a source of artificial explosion or a passive source similar to the source of natural earthquakes. The scope of the study extends from a small local area to a global area [8]. Generally speaking, the study of the local area is often related to engineering problems, such as refraction tomography [9]. However, in the large-scale tomographic study, more attention has been paid to the study of flame mechanism, geodynamics related to mantle plume and plate subduction [10; 11; 12]. The main difference between local and teleseismic tomography lies in the location of the earthquake. In the study of teleseismic tomography, the seismic source is usually thousands of kilometers away from the receiver array [13]. The crust and upper mantle are the target areas, which are located under the receiving array [14]. The study of teleseismic tomography needs an important premise that the velocity inhomogeneity of the lower mantle is that the seismic wave has enough small amplitude and long wavelength. When the condition is satisfied, the wave front of the seismic wave incident in the study area has a small curvature [15]. In Local Earthquake Tomography (LET), teleseismic tomography is usually performed in 3-D [16]. In general, the basis of teleseismic tomography requires the relative travel time residual of the first arrival P-wave, and the parameterization of the model is quite similar to that used in LET, which both have continuous velocity block and node information [17]. In the initial seismic tomographic study, some scholars established a travel time tomographic method based on the relative delay of local seismic events under the stations in the study area, and obtained the crustal P-wave velocity structure near the San Andreas fault in Bear Valley, California, USA in 1974 [18]. In 1977, these scholars completed a further study, using the teleseismic data recorded on the norsar array to retrieve the velocity structure at a depth of 126 km [19]. In 1982, [PERSON] and gibbons improved the method considering the amplitude of the seismic wave, and constrained the upper mantle velocity model within 150-200 km underground of the norsar area [20]. With the continuous progress of numerical methods in solving linear equations, the improvement of computing power, and the emergence of a large number of seismic stations during the cold war, the available seismic data are increasing. In 1984, the results of global lower mantle tomography were obtained for the first time [21]. Their model takes a constant velocity block as a parameter, and the initial model is composed of a structure with constant lateral velocity, the obtained results come from linear inversion.