A simple but efficient non-linear method for 2D inversion of magnetic field data based on Ridge-Regression algorithm

Document Type : Research Paper


1 School of Mining, College of Engineering, University of Tehran, Tehran, Iran

2 Faculty of Mining, Petroleum and Geophysics, Shahrood University of Technology, Shahrood, Iran


In geophysical exploration, inversion is carried out on the observed data to generate a geophysical model, approximating the subsurface geological struc­ture. In the interpretation of magnetic data, the subsurface model parameters are found by a proper inversion scheme. Hence, it will be possible to obtain the entire parameters of any features (e.g. Dike) including depth, width, and location. In this paper, theoretical and field studies were carried out to interpret the total components of magnetic anomalies of dikes at the finite depth. Moreover, a least-squares approach was used for depth determination using anomalous magnetic data. Potential field data inversion can be achieved through many optimization techniques. This study, however, it is attempted to develop an efficient two-dimensional (2D) inversion algorithm based on the Ridge Regression routine. The developed method was programmed using Matlab software and applied to three sets of synthetic magnetic data containing different percent of random noise to find out how good the results are. It was found that the proposed 2D inversion method can produce an accurate subsurface model that precisely explains the synthetic data in each case of data inversion. Finally, the method was applied to the real total magnetic field (TMF) data of Moghan Sedimentary basin. In that case, the estimated sedimentary basement depths were found to be in good agreement with that of the seismic data acquired before.


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