Frequency and/or Time Domain HEM Systems for Defining Floodplain Processes Linked to the Salinisation along the Murray River?

Munday, Tim; Fitzpatrick, Andrew; Reid, James; Berens, Volmer; Sattel, Daniel

doi:10.1071/aseg2007ab095

Cited by 9 publications

(12 citation statements)

References 5 publications

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“…In 2008, the frequency‐domain HEM data were acquired using the RESOLVE system. The repeat survey of time‐ and frequency‐domain EM data can provide an opportunity to investigate the relative merits of these methods (Munday et al, ). The RESOLVE system acquires horizontal coplanar in‐phase and quadrature responses at five frequencies.…”

Section: Joint Inversion Of Field Datamentioning

confidence: 99%

Mono‐Model Parameter Joint Inversion by Gramian Constraints: EM Methods Examples

Ogunbo

2019

Earth and Space Science

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Joint inversions of coincident geophysical data are usually constrained to produce more reliable subsurface models. Structural, petrophysical, model parameter correlation, empirical, and transforms are some of the published constraints. The Gramian constraint provides a broad mathematical framework for implementing the aforementioned constraints. The Gramian constraint is formed from the determinant of the inner products of the model parameters involved. Previous works have used the Gramian constraint to invert multimodal parameters of different geophysical methods. But there has not been any extension of Gramian‐constrained joint inversion to mono‐model parameter from similar geophysical methods, for example, a similar conductivity or resistivity model from time‐ and frequency‐domain airborne electromagnetic methods. I implement the Gramian‐constrained joint inversion of time‐ and frequency‐domain airborne EM (AEM) data. This implementation allows the Gramian constraint to enhance the linear correlation of the model parameter between the two methods as the number of iterations increases. Improvement of the final joint inversion results over the standalone models is noticeable for both 3% noise‐contaminated synthetic and field data experiments. The field data jointly inverted are the high moment time‐domain SkyTEM data and frequency‐domain RESOLVE helicopter EM data acquired over the salinized Bookpurnong Irrigation District in South Australia in 2006 and 2008, respectively.

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Section: Joint Inversion Of Field Datamentioning

confidence: 99%

Mono‐Model Parameter Joint Inversion by Gramian Constraints: EM Methods Examples

Ogunbo

2019

Earth and Space Science

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“…Ground-based, riverborne and AEM methods have been deployed with the intent of mapping the distribution of salinity in the floodplain soils and groundwater. We refer the readers to Munday et al (2007) for a more detailed description of the geology, hydrology, and various river, borehole, ground and airborne electromagnetic surveys.…”

Section: Case Study -Bookpurnongmentioning

confidence: 99%

Preview Number 146

2010

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“…It was originally developed for highresolution surveys targeting freshwater hydrological problems, but over the past few years it has been utilised in a wider range of applications including mapping buried iron ore palaeochannels (Reid and Viezzoli, 2007) and salinity Munday et al, 2007). On the Galapagos Islands the system gave high-resolution data forming the basis of a very comprehensive hydrological and geomorphological understanding of the Santa Cruz Island (d' Ozouville et al, 2008).…”

Section: Introductionmentioning

confidence: 98%

An integrated processing scheme for high-resolution airborne electromagnetic surveys, the SkyTEM system

Auken

Christiansen

Westergaard³

et al. 2009

Exploration Geophysics

181

107

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TheSkyTEMhelicopter-bornetransientelectromagneticsystemwas developedin2004.Thesystemyieldsunbiased data from10to12 ms aftertransmitter currentturn-off.The systemis equipped with several devices enablinga complete modelling of the movement of the system in the air, facilitating excellent high-resolution images of the subsurface.An integrated processing and inversion system for SkyTEM data is discussed. While the authors apply this system with SkyTEM data, most of the techniques are applicable for airborne electromagnetic data in general. Altitude data are processed using a simple recursive filtering technique that efficiently removes reflections from trees. The technique is completely general and can be used to filter altitude data from any airborne system. Raw voltage data that are influenced by electromagnetic coupling to man-made structures are culled from the dataset to avoid uncoupled data being distorted by coupled data, and geometrical corrections are applied to correct for pitch and roll of the transmitter frame. Data are de-spiked and averaged using trapezoid-shaped filter kernels. A Laterally Constrained Inversion using smooth models is actively used to evaluate the processing, and the final inversion is tightly connected to the processing procedures.

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Frequency and/or Time Domain HEM Systems for Defining Floodplain Processes Linked to the Salinisation along the Murray River?

Cited by 9 publications

References 5 publications

Mono‐Model Parameter Joint Inversion by Gramian Constraints: EM Methods Examples

Mono‐Model Parameter Joint Inversion by Gramian Constraints: EM Methods Examples

Preview Number 146

An integrated processing scheme for high-resolution airborne electromagnetic surveys, the SkyTEM system

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