Inversion of controlled‐source audio‐frequency magnetotelluric data for a horizontally‐layered Earth

1996 ◽  
Author(s):  
Partha S. Routh ◽  
Douglas W. Oldenburg
Keyword(s):  
Audio Frequency ◽  
Magnetotelluric Data ◽  
Controlled Source ◽  
Layered Earth

Three-dimensional inversion of controlled-source audio-frequency magnetotelluric data based on unstructured finite-element method

2020 ◽  
Vol 17 (3) ◽  
pp. 349-360
Author(s):  
Xiang-Zhong Chen ◽  
Yun-He Liu ◽  
Chang-Chun Yin ◽  
Chang-Kai Qiu ◽  
Jie Zhang ◽  
...  
Keyword(s):  
Finite Element Method ◽  
Finite Element ◽  
Three Dimensional ◽  
Audio Frequency ◽  
Magnetotelluric Data ◽  
Controlled Source ◽  
Element Method

Simulated annealing for controlled-source audio-frequency magnetotelluric data inversion

Geophysics ◽  
2012 ◽  
Vol 77 (2) ◽  
pp. E127-E133 ◽  
Author(s):  
Ruo Wang ◽  
Changchun Yin ◽  
Miaoyue Wang ◽  
Guangjie Wang
Keyword(s):  
Simulated Annealing ◽  
Model Updating ◽  
Real Data ◽  
Middle Layer ◽  
Model Parameters ◽  
Audio Frequency ◽  
Magnetotelluric Data ◽  
Controlled Source ◽  
Data Inversion ◽  
Cooling Schedule

Simulated annealing (SA) is used to invert 1D controlled source audio-frequency magnetotelluric (CSAMT) data. In the annealing process, the system energy is taken as the root-mean-square fitting error between model responses and real data. The model parameters are the natural logarithms of the resistivity and the thickness in each layer of the earth. The annealing temperature decreases exponentially, while the model is refreshed randomly according to the temperature and is accepted according to a Boltzmann probability. We first tested the SA on synthetic data and developed a cooling schedule of model updates specifically for CSAMT data inversion. The redesigned cooling schedule reduces the magnitude of the model updating, and makes the solution converge rapidly and stably. For a three-layer model whose resistivity increases with depth, SA has difficulty in obtaining the global solution for the middle layer. However, the solution for such a layer can be significantly improved by using the mean value of the estimates. The inversion of field data from a northern suburb of Beijing, China, demonstrates that starting from a 1D smooth inversion to determine the range of SA parameters permits the SA to obtain very good results from the CSAMT survey data.

scholarly journals Parallel Simulation of Audio- and Radio-Magnetotelluric Data

Minerals ◽  
2019 ◽  
Vol 10 (1) ◽  
pp. 42 ◽  
Author(s):  
Nikolay Yavich ◽  
Mikhail Malovichko ◽  
Arseny Shlykov
Keyword(s):  
Numerical Modeling ◽  
Green’S Function ◽  
Green's Function ◽  
Mineral Exploration ◽  
Iterative Solvers ◽  
Contraction Operator ◽  
Magnetotelluric Data ◽  
Controlled Source ◽  
Em Simulation ◽  
Preconditioned Iterative

This paper presents a novel numerical method for simulation controlled-source audio-magnetotellurics (CSAMT) and radio-magnetotellurics (CSRMT) data. These methods are widely used in mineral exploration. Interpretation of the CSAMT and CSRMT data collected over an area with the complex geology requires application of effective methods of numerical modeling capable to represent the geoelectrical model of a deposit well. In this paper, we considered an approach to 3D electromagnetic (EM) modeling based on new types of preconditioned iterative solvers for finite-difference (FD) EM simulation. The first preconditioner used fast direct inversion of the layered Earth FD matrix (Green’s function preconditioner). The other combined the first with a contraction operator transformation. To illustrate the effectiveness of the developed numerical modeling methods, a 3D resistivity model of Aleksandrovka study area in Kaluga Region, Russia, was prepared based on drilling data, AMT, and a detailed CSRMT survey. We conducted parallel EM simulation of the full CSRMT survey. Our results indicated that the developed methods can be effectively used for modeling EM responses over a realistic complex geoelectrical model for a controlled source EM survey with hundreds of receiver stations. The contraction-operator preconditioner outperformed the Green’s function preconditioner by factor of 7–10, both with respect to run-time and iteration count, and even more at higher frequencies.

Sign in / Sign up

Export Citation Format

Share Document