MT2DInvMatlab—A program in MATLAB and FORTRAN for two-dimensional magnetotelluric inversion

Lee, Seong Kon; Kim, Hee Joon; Song, Yoonho; Lee, Choon-Ki

doi:10.1016/j.cageo.2008.10.010

Cited by 52 publications

(27 citation statements)

References 27 publications

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“…Consequently, the preliminary analysis of this dataset (as presented in the Gold Undercover Reports) was conducted using two independent algorithms in order to provide two comparative models and increase confidence in the interpretation of the section. Based on a linearised leastsquares fit with smoothness regularisation for 2-D inversions, both algorithms incorporate the finite-element method for forward modelling in the inversion stage, but adopt two different schemes to determine the regularisation parameters, these are: Akaike Basian Information Criteria (Uchida 1993) and Active Constraint balancing (Yi et al 2003;Lee et al 2009). Following the completion of the TEM transect (Dennis et al 2010) and applying statics corrections to the dataset, the original 2-D sections were used as an a priori guide for generating new models.…”

Section: Inversion Routinesmentioning

confidence: 99%

Magnetotelluric survey for undercover structural mapping, Central Victoria

Dennis

Moore

Cull

2011

Australian Journal of Earth Sciences

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Section: Inversion Routinesmentioning

confidence: 99%

Magnetotelluric survey for undercover structural mapping, Central Victoria

Dennis

Moore

Cull

2011

Australian Journal of Earth Sciences

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“…Usually, the topography simulation in EM induction is implemented using the finite-element method because triangular elements could allow to precisely model the arbitrary surface. By moving the nodes of triangular or rectangular elements in the vertical direction according to the elevation of the air-earth interface, we can obtain the topographic response of EM induction (Holcombe and Jiracek, 1984;Wannamaker et al, 1986;Lee et al, 2009). In this study, the topography had been integrated into the inversion program OCCAM2DMT to model the terrain effect.…”

Section: Data Processingmentioning

confidence: 99%

Mineral Exploration using CSAMT data: Application to Longmen region metallogenic belt, Guangdong Province, China

Peng

Guiju

et al. 2013

GEOPHYSICS

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A controlled-source audio-frequency magnetotelluric (CSAMT) survey has been carried out to investigate potential iron (Fe) and polymetallic (Pb-Zn-Cu) deposits in Longmen region, which is one of the main metallogenic belts in southern China. Conducting geophysical surveys in this area is quite difficult due to mountainous terrain, dense forest, and thick vegetation cover. A total of 560 CSAMT soundings were recorded along twelve surveying lines. Two-dimensional Occam's inversion scheme was used to interpret these CSAMT data. The resulting electric resistivity models showed that three large-scale highly conductive bodies exist within the surveying area. By integrated interpretation combined with available geologic, geophysical, and geochemical data in this area, three prospective mineral deposits were demarcated. Based on the CSAMT results, a borehole penetrating approximately 250-m depth was drilled at the location of 470 m to the northwest end of line 06, defined with a massive pyrite from the depth of 52-235 m with 7%-16% Fe content, as well as locally highgrade Pb-Zn-and Ag-Ti-bearing ores.

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“…If the constraint matrix, C is assumed as the zeroth order, i.e., the identity matrix equation (9) corresponds to the Marquardt-Levenberg damping method; on the other hand, it is the smoothness-constrained least-squares inversion when C is assumed as second order. In the present work, the smoothness-constrained non-linear (non-linearity occurs due to regularization parameter and matrix C, which is used to constrain the model) least-squares inversion is implemented for solving the regularized inverse problems (Monteiro Santos et al 2006;Lee et al 2009) as In the present work, the smoothness-constrained non-linear (non-linearity occurs due to regularization parameter and matrix C, which is used to constrain the model) least-squares inversion is implemented for solving the regularized inverse problems (Monteiro Santos et al 2006;Lee et al 2009) as…”

Section: N V E R S I O N a P P R O A C Hmentioning

confidence: 99%

Fast imaging of subsurface conductors using very low‐frequency electromagnetic data

Singh

Sharma

2015

Geophysical Prospecting

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The study presents a fast imaging technique for the very low‐frequency data interpretation. First, an analytical expression was derived to compute the vertical component of the magnetic field at any point on the Earth's surface for a given current density distribution in a rectangular block on the subsurface. Current density is considered as exponentially decreasing with depth, according to the skin depth rule in a particular block. Subsequently, the vertical component of the magnetic field due to the entire subsurface was computed as the sum of the vertical component of the magnetic field due to an individual block. Since the vertical component of the magnetic field is proportional to the real part of very low‐frequency anomaly, an inversion program was developed for imaging of the subsurface conductors using the real very low‐frequency anomaly in terms of apparent current density distribution in the subsurface. Imaging results from the presented formulation were compared with other imaging techniques in terms of apparent current density and resistivity distribution using a standard numerical forward modelling and inversion technique. Efficacy of the developed approach was demonstrated for the interpretation of synthetic and field very low‐frequency data. The presented imaging technique shows improvement with respect to the filtering approaches in depicting subsurface conductors. Further, results obtained using the presented approach are closer to the results of rigorous resistivity inversion. Since the presented approach uses only the real anomaly, which is not sensitive to very small isolated near‐surface conducting features, it depicts prominent conducting features in the subsurface.

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MT2DInvMatlab—A program in MATLAB and FORTRAN for two-dimensional magnetotelluric inversion

Cited by 52 publications

References 27 publications

Magnetotelluric survey for undercover structural mapping, Central Victoria

Magnetotelluric survey for undercover structural mapping, Central Victoria

Mineral Exploration using CSAMT data: Application to Longmen region metallogenic belt, Guangdong Province, China

Fast imaging of subsurface conductors using very low‐frequency electromagnetic data

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