Magnetization vector inversion is essential for obtaining magnetization vector information from subsurface rocks. To obtain focused inversion results that better match the true magnetization distributions, sparse constraints are considered to constrain the objective function. A compact magnetization vector inversion method is proposed that can provide accurate inversion results for magnetic data with significant remanent magnetization. Considering the sparse constraint and the correlation between the three magnetization components with different directions, the L1-norm is modified and introduced into the inversion algorithm to obtain compact results. Furthermore, to reduce the computational cost, a randomized singular value decomposition is used to replace the traditional singular value decomposition and iteratively minimize the proposed objective function. Two synthetic models with different magnetization directions are developed to verify the performance of the proposed method. The results of magnetization vectors obtained by the proposed method are focused and accurate. Finally, the proposed method is applied to igneous rocks with strong remanent magnetization in the Haba River area of northwestern China. The distributions, directions of total magnetization and remanent magnetization of the medium-base igneous rocks are revealed by the sparse magnetization vector inversion method, which provides a wealth of information about the concealed deposits in the area.
Natural remanent magnetization diverts the direction of the total magnetization vector from the Earths magnetic field direction. It is important to determine the magnetization direction because the processing and inversion of magnetic data usually need the magnetization direction as a priori information. The conventional strategy for estimating the magnetization direction is to compute the cross-correlation between the reduced-to-the-pole (RTP) field and one magnetic magnitude transform which is insensitive to the magnetization direction. A new theory and method are proposed that the total magnetization direction is determined by computing the multiple correlation coefficients between the RTP field and the multiple direction-insensitive magnitudes transforms, such as the magnetic amplitude and normalized source strength. The linear regression between the RTP field and the direction-insensitive magnitude transforms is established. Then the correlation is computed by the RTP field and the constructed regressor. The proposed method is tested on synthetic data of single and complex models, respectively. Then the method is applied to the field data of the Yeshan region (eastern China) and the Black Hill Norite (southern Australia). The proposed multiple correlation is an extension of conventional cross-correlation method that provides an accurate and robust way to estimate the magnetization direction from a magnetic anomaly.
<p>Natural remanance will distort the direction of the total magnetization of the magnetic source away from the direction of induction magnetization, which brings difficulties in magnetic data processing and susceptibility inversion. To solve the problem affected by remanance, a magnetic data processing and three-dimensional inversion strategy under remanance conditions is proposed: A method of the total magnetization direction estimation based on multiple correlations is proposed and applied to the processing of magnetic data, which can eliminate the influence of remanance and oblique magnetization. Moreover, the influence of remanance can be considered in the subsequent inversion of magnetic data. Adding the information on the direction of total magnetization into the inversion can more accurately depict the location of the underground magnetic source and recover the physical property distribution. This strategy is applied to the ground magnetic survey data of a mining area in Jiangsu, China. The effects of remanance and oblique magnetization on the processing and inversion of magnetic data are eliminated, and the physical properties and spatial distribution of underground magnetic bodies are restored, which provides geophysical evidence for the study of geological interpretation.</p>
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.