Investigating 2-D MT inversion codes using real field data
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ORIGINAL PAPER
Investigating 2-D MT inversion codes using real field data Reza Ghaedrahmati & Ali Moradzadeh & Nader Fathianpour & Seong Kon Lee
Received: 28 July 2012 / Accepted: 25 January 2013 # Saudi Society for Geosciences 2013
Abstract There are currently a significant number of twodimensional (2-D) and three-dimensional (3-D) inversion codes available for magnetotelluric (MT) data. Through various 2-D inversion algorithms suggested so far, the classical Occam's inversion, the data space Occam's inversion, the nonlinear conjugate gradient (NLCG) method, and the Gauss–Newton (GN) method are fundamental driving methods to find optimum earth models, and OCCAM, DASOCC, NLCG, and MT2DInvMatlab are possible candidates one can find in the public domain that implement these algorithms for 2-D MT inversions, respectively. In this study, we investigate the pros and cons (strength and weakness) of these codes to help one use them efficiently in practical works and, as an introductory guide, further develop (sophisticate or extend) them, especially for the 3-D case. To achieve this goal, we applied each one of the four aforementioned codes on a profile of real MT field dataset. Then, further investigations have been done by performing several inversion tests to see how each code can find the appropriate model to reconstruct the subsurface resistivity structure. Numerical experiments show that the two parameters, regularization and target misfit, in addition to the main criteria of inversion (such as the forward and the sensitivities
R. Ghaedrahmati (*) Shahrood University of Technology, Shahrood, Iran e-mail: [email protected] A. Moradzadeh Faculty of Mining, Petroleum and Geophysics, Shahrood University of Technology, Shahrood, Iran N. Fathianpour Mining Engineering Department, Isfahan University of Technology, Isfahan, Iran S. K. Lee Korea Institute of Geoscience and Mineral Resources (KIGAM), Daejeon, Republic of Korea
calculation method, and the type of inversion algorithm), are very important to produce the expected model in inversion. The regularization parameter that acts to trade off between model norm and data misfit can affect the inversion process in terms of both the computational efficiency and the accuracy of the obtained model. Also, lack of insufficient precision to choose the target misfit can lead the inversion to produce and reach an incorrect model. Keywords 2-D inversion code . Magnetotelluric . Resistivity
Introduction The magnetotelluric (MT) technique is a natural source electromagnetic method by measuring time-varying surface magnetic and electric fields that contain information about vertical and lateral variations of electrical resistivity structure of the Earth (Cagniard 1953; Vozoff 1991). For both qualitative and quantitative interpretations, the significance of inversion analysis of MT data has been increased in the past few decades, and thus, many two-dimensional (2-D) and three-dimensional (3-D) MT inversion algorithms have been published (for 2-D case: deGroot-Hedlin and Con
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