4.2. MVISEN

This program performs the sensitivity calculation for magnetic vector inversion. Command line syntax is:

mvisen mvisen.inp [nThreads]

For a sample input file type:

mvisen -inp

The argument specifying the number of CPU threads used in the OpenMP format is optional. If this argument is not given to the program, the program will choose to use all of the CPU threads on the machine. This argument allows the user to specify half, for example, of the threads so that the program does not take all available RAM. Note that this option is not available in the MPI-based code used for clusters.

4.2.1. Input files

The table below describes each rows. An example file can be copied from here.

Line

Input

Description

1

mesh

3D Mesh file.

4

obs

Observations file

5

topography

Topography file

6

wvltx

Wavelet type : daubx | symmx | NONE | null (daub2)

7

itol, eps

Wavelet parameters | null (search)
../../_images/mvisen.png

The input parameters for the control file are:

  • obs.mag: The data file that contains the observation locations. Note for sensitivity calculations, standard deviations are not required, but this file may be the observations that will be used in the inversion (with uncertainties).

  • topo.dat: Surface topography. If null is entered, the surface will be treated as being flat on top of the mesh.

  • wvltx: A five-character string identifying the type of wavelet used to compress the sensitivity matrix. The types of wavelets available are Daubechies wavelet with 1 to 6 vanishing moments (daub1, daub2 and so on) and Symmlets with 4 to 6 vanishing moments (symm4, symm5, symm6). Note that daub1 is the Haar wavelet and daub2 is the Daubechies-4 wavelet. The Daubechies-4 wavelet is suitable for most inversions, while the others are provided for user experimentation. If NONE is entered, the program does not use wavelet compression.

  • itol, eps: A positive integer value that specifies how the wavelet threshold level is determined. This line is ignored if no wavelet compression is being used, however a placeholder value must still be used in the input file.

    itol=1: program calculates the relative threshold and eps is the relative reconstruction error of the sensitivity. A reconstruction error of 0.05 (95%) is usually adequate.

    itol=2: the user defines the threshold level and eps is the threshold to be used. If null is entered on this line, a default relative reconstruction error of 0.05 (e.g. 5%) is used and the relative threshold level is calculated (i.e., itol=1 , eps=0.05).

    NOTE The detailed explanation of threshold level and reconstruction error can be found in the wavelet section of this manual.

Note

An example can be found here

4.2.2. Output files

The program mvisen outputs five files. They are:

  1. mviinv.mtx: The sensitivity matrix file to be used in the inversion. This file contains the sensitivity matrix, generalized depth weighting function, mesh, and discretized surface topography. It is produced by the program and its name is not adjustable. It is very large and may be deleted once the work is completed.

  2. mvisen.log: The log file produced by the program for the user’s records on how the sensitivity matrix was formed including the full control file used.

  3. sensitivity_x.txt: This file is a model file that contains the average sensitivity for the Easting component of the magnetization vector for each cell. This file can be used for depth of investigation analysis or for use in designing special model objective function weighting.

  4. sensitivity_y.txt: This file is a model file that contains the average sensitivity for the Northing component of the magnetization vector for each cell. This file can be used for depth of investigation analysis or for use in designing special model objective function weighting.

  5. sensitivity_z.txt: This file is a model file that contains the average sensitivity for the vertical component of the magnetization vector for each cell. This file can be used for depth of investigation analysis or for use in designing special model objective function weighting.