Co-operative inversion of electrical resistivity tomography and seismic reflection data: An example with landslides data
|dc.identifier.citation||Kieu, D. and Kepic, A. 2019. Co-operative inversion of electrical resistivity tomography and seismic reflection data: An example with landslides data.|
© 2019 24th European Meeting of Environmental and Engineering Geophysics. All rights reserved. Seismic and electrical resistivity tomography methods are recognized as powerful tools to investigate landslides. The effectiveness of an investigation significantly increases if we can exploit the strengths of the each method and complement this information in a combinative model. In this study, we perform co-operative inversion of the two datasets, seismic reflection and geo-electrical, through a fuzzy clustering technique. In inverting any one dataset alone this method constructs models that include regions relating similar parameters. Most conventional inversion processes tend to use a smoothing criteria to choose to obtain a final solution, but the highly variable physical properties due to the faults and groundwater seeps in our dataset preclude this approach. The co-operative inversion of seismic and geo-electrical data can exploit advantages of the both methods, to build a better model than models inverted from a single dataset alone. Finally, our process can provides the cluster image, namely pseudo-lithology, from the co-operative inversion models of the two methods. This can make interpretation much easier for geologists rather than using the inverted models of petrophysical parameters.
|dc.title||Co-operative inversion of electrical resistivity tomography and seismic reflection data: An example with landslides data|
|dcterms.source.title||24th European Meeting of Environmental and Engineering Geophysics|
|dcterms.source.series||24th European Meeting of Environmental and Engineering Geophysics|
|curtin.department||WASM: Minerals, Energy and Chemical Engineering (WASM-MECE)|
|curtin.accessStatus||Fulltext not available|
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