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Data-driven selection of the minimum-gradient support parameter in time-lapse focused electrical imaging

(2016) GEOPHYSICS. 81(1). p.A1-A5
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Abstract
We have considered the problem of the choice of the minimum-gradient support (MGS) parameter in focused inversion for time-lapse (TL) electric resistivity tomography. Most existing approaches have relied either on an arbitrary choice of this parameter or one based on the prior information, such as the expected contrast in the TL image. We have decided to select the MGS parameter using a line search based on the value of the TL data root-mean-square misfit at the first iteration of the nonlinear inversion procedure. The latter was based on a Gauss-Newton scheme minimizing a regularized objective function in which the regularization functional was defined by the MGS functional. The regularization parameter was optimized to achieve a certain target level, following the Occam principles. We have validated our approach on a synthetic benchmark using a complex and heterogeneous model and determined its effectiveness on electric tomography TL data collected during a salt tracer experiment in fractured limestone. Our results have determined that the approach was successful in retrieving the focused anomaly and did not rely on prior information.
Keywords
RESISTIVITY TOMOGRAPHY ERT, FRACTURED/KARSTIFIED LIMESTONES, PREFERENTIAL FLOW, INVERSION, TRANSPORT, CONSTRAINT, MODELS, PATHS

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Citation

Please use this url to cite or link to this publication:

MLA
Nguyen, Frédéric et al. “Data-driven Selection of the Minimum-gradient Support Parameter in Time-lapse Focused Electrical Imaging.” GEOPHYSICS 81.1 (2016): A1–A5. Print.
APA
Nguyen, F., Kemna, A., Robert, T., & Hermans, T. (2016). Data-driven selection of the minimum-gradient support parameter in time-lapse focused electrical imaging. GEOPHYSICS, 81(1), A1–A5.
Chicago author-date
Nguyen, Frédéric, Andreas Kemna, Tanguy Robert, and Thomas Hermans. 2016. “Data-driven Selection of the Minimum-gradient Support Parameter in Time-lapse Focused Electrical Imaging.” Geophysics 81 (1): A1–A5.
Chicago author-date (all authors)
Nguyen, Frédéric, Andreas Kemna, Tanguy Robert, and Thomas Hermans. 2016. “Data-driven Selection of the Minimum-gradient Support Parameter in Time-lapse Focused Electrical Imaging.” Geophysics 81 (1): A1–A5.
Vancouver
1.
Nguyen F, Kemna A, Robert T, Hermans T. Data-driven selection of the minimum-gradient support parameter in time-lapse focused electrical imaging. GEOPHYSICS. 2016;81(1):A1–A5.
IEEE
[1]
F. Nguyen, A. Kemna, T. Robert, and T. Hermans, “Data-driven selection of the minimum-gradient support parameter in time-lapse focused electrical imaging,” GEOPHYSICS, vol. 81, no. 1, pp. A1–A5, 2016.
@article{8539841,
  abstract     = {We have considered the problem of the choice of the minimum-gradient support (MGS) parameter in focused inversion for time-lapse (TL) electric resistivity tomography. Most existing approaches have relied either on an arbitrary choice of this parameter or one based on the prior information, such as the expected contrast in the TL image. We have decided to select the MGS parameter using a line search based on the value of the TL data root-mean-square misfit at the first iteration of the nonlinear inversion procedure. The latter was based on a Gauss-Newton scheme minimizing a regularized objective function in which the regularization functional was defined by the MGS functional. The regularization parameter was optimized to achieve a certain target level, following the Occam principles. We have validated our approach on a synthetic benchmark using a complex and heterogeneous model and determined its effectiveness on electric tomography TL data collected during a salt tracer experiment in fractured limestone. Our results have determined that the approach was successful in retrieving the focused anomaly and did not rely on prior information.},
  author       = {Nguyen, Frédéric and Kemna, Andreas and Robert, Tanguy and Hermans, Thomas},
  issn         = {0016-8033},
  journal      = {GEOPHYSICS},
  keywords     = {RESISTIVITY TOMOGRAPHY ERT,FRACTURED/KARSTIFIED LIMESTONES,PREFERENTIAL FLOW,INVERSION,TRANSPORT,CONSTRAINT,MODELS,PATHS},
  language     = {eng},
  number       = {1},
  pages        = {A1--A5},
  title        = {Data-driven selection of the minimum-gradient support parameter in time-lapse focused electrical imaging},
  url          = {http://dx.doi.org/10.1190/GEO2015-0226.1},
  volume       = {81},
  year         = {2016},
}

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