Inverting airborne electromagnetic (AEM) data with Zohdy's method

Sattel, Daniel

doi:10.1190/1.1990217

Cited by 49 publications

(30 citation statements)

References 35 publications

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“…Airborne electromagnetic (AEM) data acquired for exploration or environmental applications are commonly modelled using algorithms such as conductivity depth transforms (CDTs) or layered earth inversions (LEIs) that assume a 1D earth (Wolfgram and Karlik, 1995;Sattel, 2005). To date, full 2.5D or 3D inversion of AEM data remains limited, and in many respects unrealistic and unnecessary particularly for hydrogeological investigations in many Australian basins.…”

Section: Introductionmentioning

confidence: 99%

Spatially constrained inversion for quasi 3D modelling of airborne electromagnetic data – an application for environmental assessment in the Lower Murray Region of South Australia

Viezzoli

Auken

Munday

2009

Exploration Geophysics

109

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We present an application of spatially constrained inversion (SCI) of SkyTEM (airborne electromagnetic) data for defining spatial patterns of salinisation in the Bookpurnong irrigation area located in the lower Murray Basin of South Australia. SCI uses Delaunay triangulation to set 3D constraints between neighbouring soundings, taking advantage of the spatial coherency that may be present in the dataset. Conductivity information for individual soundings is linked through the spatial constraints, from well determined parameters to locally poorly determined parameters. For the survey presented here, SCI generated maps detail the spatial variability of floodplain salinisation, the extent of floodplain sediments influenced by lateral recharge and flushing along stretches of the Murray River, and the variable quality of groundwater in deeper semiconfined aquifers of the Murray Group. Available borehole and other ancillary information, such as vegetation density and health patterns, match the observed conductivity variations seen in the SCI results, even at the very near surface (%2m depth). The SCI provides more accurate and spatially consistent results compared with those from single site inversions. They are also more uniform and detailed than maps obtained with single point Layered Earth Inversions or a laterally constrained inversion. In this example, the SCI provided reliable quasi 3D modelling, that confirmed and improved the hydrogeological knowledge of the area, indicating that the technique would have application with helicopter electromagnetic data in similar settings throughout the lower Murray Basin of Australia.

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Section: Introductionmentioning

confidence: 99%

Spatially constrained inversion for quasi 3D modelling of airborne electromagnetic data – an application for environmental assessment in the Lower Murray Region of South Australia

Viezzoli

Auken

Munday

2009

Exploration Geophysics

109

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“…Constable et al (1987) first apply this method to EM inversion, and Sattel (2005) and Vallée and Smith (2009a) apply it to airborne time-domain EM data inversion. The usual weighted least-squares criterion can be expressed as (Constable et al, 1987) …”

Section: Occam's Inversionmentioning

confidence: 99%

Review on airborne electromagnetic inverse theory and applications

et al. 2015

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Airborne electromagnetic (AEM) data processing and inversion has progressed from the early conductivity-depth imaging, to 1D inversion for a layered earth model, and most recently to 2D/3D inversions. The new processes have used methods for searching for solutions, applying constraints, and focusing images, such as Occam's, laterally constrained, and holistic inversions. For airborne data imaging and 1D inversion, some algorithms are fast, whereas others have control over data misfit and the vertical or lateral smoothness. Beyond 1D algorithms, 2D/3D inversions are based on currently used methods such as isolated conductor models (which are good for highly conductive orebodies in resistive background) and techniques that discretized regions that are used for more complex structures and backgrounds. In the latter case, the computations are slow, so research is focusing on time-efficient computer algorithms for solving the equations such as Gauss-Newton, quasi-Newton, and nonlinear conjugate gradient algorithms. For the electromagnetic (EM) problem, the solution can be obtained in a more practical time frame if material that has minimal impact is ignored. Two approaches can be used to speedup the EM inversion process -the moving footprint and direct solver methods. We hope our work will to some extent help stimulate and focus the research in AEM inversion.

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“…Huang and Fraser, 2002), conductivity depth transforms (e.g. Wolfgram and Karlik, 1995;Macnae et al, 1998;Fullagar and Reid, 2001), S-inversion (Tartaras et al, 2000;Combrinck, 2008), Zohdy's method (Sattel, 2005), layered earth inversions (e.g. Chen and Raiche, 1998;Farquharson et al, 2003;Christensen et al, 2010), laterally constrained layered earth inversions (e.g.…”

Section: Introductionmentioning

confidence: 99%

3D inversion of airborne electromagnetic data using a moving footprint

Cox

Wilson

Zhdanov

2010

Exploration Geophysics

200

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Abstract. It is often argued that 3D inversion of entire airborne electromagnetic (AEM) surveys is impractical, and that 1D methods provide the only viable option for quantitative interpretation. However, real geological formations are 3D by nature and 3D inversion is required to produce accurate images of the subsurface. To that end, we show that it is practical to invert entire AEM surveys to 3D conductivity models with hundreds of thousands if not millions of elements. The key to solving a 3D AEM inversion problem is the application of a moving footprint approach. We have exploited the fact that the area of the footprint of an AEM system is significantly smaller than the area of an AEM survey, and developed a robust 3D inversion method that uses a moving footprint. Our implementation is based on the 3D integral equation method for computing data and sensitivities, and uses the re-weighted regularised conjugate gradient method for minimising the objective functional. We demonstrate our methodology with the 3D inversion of AEM data acquired for salinity mapping over the Bookpurnong Irrigation District in South Australia. We have inverted 146 line km of RESOLVE data for a 3D conductivity model with 310 000 elements in 45 min using just five processors of a multi-processor workstation.

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Inverting airborne electromagnetic (AEM) data with Zohdy's method

Cited by 49 publications

References 35 publications

Spatially constrained inversion for quasi 3D modelling of airborne electromagnetic data – an application for environmental assessment in the Lower Murray Region of South Australia

Spatially constrained inversion for quasi 3D modelling of airborne electromagnetic data – an application for environmental assessment in the Lower Murray Region of South Australia

Review on airborne electromagnetic inverse theory and applications

3D inversion of airborne electromagnetic data using a moving footprint

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