Reframing the magnetotelluric phase tensor for monitoring applications: improved accuracy and precision in strike determinations.
The magnetotelluric method is increasingly being used to monitor electrical resistivity changes in the subsurface. One of the preferred parameters derived from the surface impedance is the strike direction, which is very sensitive to changes in the direction of the subsurface electrical current flow. The preferred method for estimating the strike changes is that provided by the phase tensor because it is immune to galvanic distortions. However, it is also a fact that the associated analytic formula is unstable for noisy data, something that limits its applicability for monitoring purposes, because in general this involves comparison of two or more very similar data sets. One of the issues is that the noise complicates the distribution of estimates between the four quadrants. This can be handled by sending all values to the same quadrant by adding or subtracting the appropriate amount. This is justified by showing that the analytic formula is also a least squares solution. This is equivalent to define penalty functions for the matrix of eigenvalues and then select the minima numerically. Contrary to the analytic formula this numerical approach can be generalized to compute strikes using windows of any number of periods, thus providing tradeoffs between variance and resolution. The performance of the proposed approach is illustrated by its application to synthetic data and to real data from a monitoring array in the Cerro Prieto geothermal field, México.
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Posted 12 Jan, 2021
On 02 Feb, 2021
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Received 12 Dec, 2020
On 12 Dec, 2020
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On 21 Aug, 2020
On 21 Aug, 2020
On 07 Jul, 2020
Received 06 Jul, 2020
Received 15 May, 2020
On 05 May, 2020
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Invitations sent on 23 Apr, 2020
On 23 Apr, 2020
On 22 Apr, 2020
On 18 Apr, 2020
On 17 Apr, 2020
Reframing the magnetotelluric phase tensor for monitoring applications: improved accuracy and precision in strike determinations.
Posted 12 Jan, 2021
On 02 Feb, 2021
On 01 Jan, 2021
On 01 Jan, 2021
On 01 Jan, 2021
On 01 Jan, 2021
Received 12 Dec, 2020
On 12 Dec, 2020
Invitations sent on 11 Nov, 2020
On 11 Nov, 2020
On 10 Nov, 2020
On 10 Nov, 2020
On 10 Nov, 2020
On 26 Sep, 2020
Received 25 Sep, 2020
Received 06 Sep, 2020
On 24 Aug, 2020
On 23 Aug, 2020
On 22 Aug, 2020
Invitations sent on 22 Aug, 2020
On 21 Aug, 2020
On 21 Aug, 2020
On 07 Jul, 2020
Received 06 Jul, 2020
Received 15 May, 2020
On 05 May, 2020
On 23 Apr, 2020
Invitations sent on 23 Apr, 2020
On 23 Apr, 2020
On 22 Apr, 2020
On 18 Apr, 2020
On 17 Apr, 2020
The magnetotelluric method is increasingly being used to monitor electrical resistivity changes in the subsurface. One of the preferred parameters derived from the surface impedance is the strike direction, which is very sensitive to changes in the direction of the subsurface electrical current flow. The preferred method for estimating the strike changes is that provided by the phase tensor because it is immune to galvanic distortions. However, it is also a fact that the associated analytic formula is unstable for noisy data, something that limits its applicability for monitoring purposes, because in general this involves comparison of two or more very similar data sets. One of the issues is that the noise complicates the distribution of estimates between the four quadrants. This can be handled by sending all values to the same quadrant by adding or subtracting the appropriate amount. This is justified by showing that the analytic formula is also a least squares solution. This is equivalent to define penalty functions for the matrix of eigenvalues and then select the minima numerically. Contrary to the analytic formula this numerical approach can be generalized to compute strikes using windows of any number of periods, thus providing tradeoffs between variance and resolution. The performance of the proposed approach is illustrated by its application to synthetic data and to real data from a monitoring array in the Cerro Prieto geothermal field, México.
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7
Figure 8
Figure 9
Figure 10
Figure 11
Figure 12
Figure 13
Figure 14
Figure 15
Due to technical limitations, full-text HTML conversion of this manuscript could not be completed. However, the latest manuscript can be downloaded and accessed as a PDF.