Seafloor massive sulphide exploration using deep-towed controlled source electromagnetics: Navigational uncertainties
Seafloor massive sulphide exploration using deep-towed controlled source electromagnetics: Navigational uncertainties
Deep-towed geophysical surveys require precise knowledge of navigational parameters such as instrument position and orientation because navigational uncertainties reflect in the data and therefore in the inferred geophysical properties of the sub-seafloor. We address this issue for the case of electrical conductivity inferred from controlled source electromagnetic data. We show that the data error is laterally variable due to irregular motion during deep towing, but also due to lateral variations in conductivity, including those resulting from topography. To address this variability and quantify the data error prior to inversion, we propose a two-dimensional perturbation study. Our workflow enables stable and geologically reliable results for multi-component and multi-frequency inversions. An error estimation workflow is presented, which comprises the assessment of navigational uncertainties, perturbation of navigational parameters, and forward modelling of electric field amplitudes for a homogeneous and then a heterogeneous sub-seafloor conductivity model. Some navigational uncertainties are estimated from variations of direct measurements. Other navigational parameters required for inversion are derived from the measured quantities and their error is calculated by means of error propagation. Some navigational parameters show direct correlation with the measured electric fields. For example, the antenna dip correlates with the vertical electric field and the depth correlates with the horizontal electric field. For the perturbation study each standard deviation is added to the navigational parameters. Forward models are run for each perturbation. Amplitude deviations are summed in quadrature with the stacking error for a total, laterally varying, data error. The error estimation is repeated for a heterogeneous sub-seafloor model due to the large conductivity range (several orders of magnitude), which affects the forward model. The approach enables us to utilize data from several components (multiple electric fields, frequencies and receivers) in the inversion to constrain the final model and reduce ambiguity. The final model is geologically reasonable, in this case enabling the identification of conductive metal sulphide deposits on the seafloor.
1215-1227
Gehrmann, Romina A.S.
1ee547b2-aa53-4d38-9d36-a2ccc3aa52e2
Haroon, Amir
05a1f75d-ff5a-40cf-a6cf-c2c437e0058a
Morton, McKinley
7b76d25d-9813-4671-a2cd-0bb4648b780f
Djanni, Axel T.
af73a5c3-9429-4a95-8988-fdb9740ad5e9
Minshull, Timothy A.
bf413fb5-849e-4389-acd7-0cb0d644e6b8
February 2020
Gehrmann, Romina A.S.
1ee547b2-aa53-4d38-9d36-a2ccc3aa52e2
Haroon, Amir
05a1f75d-ff5a-40cf-a6cf-c2c437e0058a
Morton, McKinley
7b76d25d-9813-4671-a2cd-0bb4648b780f
Djanni, Axel T.
af73a5c3-9429-4a95-8988-fdb9740ad5e9
Minshull, Timothy A.
bf413fb5-849e-4389-acd7-0cb0d644e6b8
Gehrmann, Romina A.S., Haroon, Amir, Morton, McKinley, Djanni, Axel T. and Minshull, Timothy A.
(2020)
Seafloor massive sulphide exploration using deep-towed controlled source electromagnetics: Navigational uncertainties.
Geophysical Journal International, 220 (2), .
(doi:10.1093/gji/ggz513).
Abstract
Deep-towed geophysical surveys require precise knowledge of navigational parameters such as instrument position and orientation because navigational uncertainties reflect in the data and therefore in the inferred geophysical properties of the sub-seafloor. We address this issue for the case of electrical conductivity inferred from controlled source electromagnetic data. We show that the data error is laterally variable due to irregular motion during deep towing, but also due to lateral variations in conductivity, including those resulting from topography. To address this variability and quantify the data error prior to inversion, we propose a two-dimensional perturbation study. Our workflow enables stable and geologically reliable results for multi-component and multi-frequency inversions. An error estimation workflow is presented, which comprises the assessment of navigational uncertainties, perturbation of navigational parameters, and forward modelling of electric field amplitudes for a homogeneous and then a heterogeneous sub-seafloor conductivity model. Some navigational uncertainties are estimated from variations of direct measurements. Other navigational parameters required for inversion are derived from the measured quantities and their error is calculated by means of error propagation. Some navigational parameters show direct correlation with the measured electric fields. For example, the antenna dip correlates with the vertical electric field and the depth correlates with the horizontal electric field. For the perturbation study each standard deviation is added to the navigational parameters. Forward models are run for each perturbation. Amplitude deviations are summed in quadrature with the stacking error for a total, laterally varying, data error. The error estimation is repeated for a heterogeneous sub-seafloor model due to the large conductivity range (several orders of magnitude), which affects the forward model. The approach enables us to utilize data from several components (multiple electric fields, frequencies and receivers) in the inversion to constrain the final model and reduce ambiguity. The final model is geologically reasonable, in this case enabling the identification of conductive metal sulphide deposits on the seafloor.
Text
ggz513
- Accepted Manuscript
More information
Accepted/In Press date: 13 November 2019
e-pub ahead of print date: 14 November 2019
Published date: February 2020
Identifiers
Local EPrints ID: 436120
URI: http://eprints.soton.ac.uk/id/eprint/436120
ISSN: 0956-540X
PURE UUID: 054b6218-9dfe-4e52-9db8-fd7cf5e73aa4
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Date deposited: 29 Nov 2019 17:30
Last modified: 07 Oct 2020 02:09
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Contributors
Author:
Romina A.S. Gehrmann
Author:
Amir Haroon
Author:
McKinley Morton
Author:
Axel T. Djanni
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