Ross Brodie

A holistic approach to inversion of frequency-domain airborne EM data

We have developed a holistic method for simultaneously calibrating, processing, and inverting frequency-domain airborne electromagnetic data. A spline-based, 3D, layered conductivity modelcoveringthecompletesurveyareawasrecoveredthrough inversion of the entire raw airborne data set and available independent conductivity and interface-depth data. The holistic inversion formulation includes a mathematical model to account for systematic calibration errors such as incorrect gain and zero

Holistic inversion of frequency-domain airborne electromagnetic data with minimal prior information

The holistic inversion approach for frequency domain airborne electromagnetic data has previously been employed to simultaneously calibrate, process and invert raw frequency-domain data where prior information was available. An alternative formulation has been developed, which is suitable in the case where explicit prior information is not available. It incorporates: a multi-layer vertically-smooth conductivity model; a simplified bias parameterisation; horizontal smoothing with respect to elevation; and cluster computer parallelisation. Without using any prior data, an inversion of 8.0 million data for 3.4 million parameters yields results that are consistent with independently derived calibration parameters, downhole logs and groundwater elevation data. We conclude that the success of the holistic inversion method is not dependent on a sophisticated conceptual model or the direct inclusion of survey-area specific prior information. In addition, acquisition costs could potentially be reduced by employing the holistic approach which largely eliminates the need for high altitude zero-level measurements.

Trans-dimensional Bayesian inversion of airborne electromagnetic data for 2D conductivity profiles

This paper presents the application of a novel trans-dimensional sampling approach to a time domain airborne electromagnetic (AEM) inverse problem to solve for plausible conductivities of the subsurface. Geophysical inverse field problems, such as time domain AEM, are well known to have a large degree of non-uniqueness. Common least-squares optimisation approaches fail to take this into account and provide a single solution with linearised estimates of uncertainty that can result in overly optimistic appraisal of the conductivity of the subsurface. In this new non-linear approach, the spatial complexity of a 2D profile is controlled directly by the data. By examining an ensemble of proposed conductivity profiles it accommodates non-uniqueness and provides more robust estimates of uncertainties. We apply a novel trans-dimensional Bayesian approach using a wavelet parameterisation to airborne electromagnetic (AEM) inversions using data from the Broken Hill region. This approach allows exploration of a range of plausible subsurface conductivity models and provides more robust uncertainty estimates while accounting for potential non-uniqueness.

The 3D inversion of airborne gamma-ray spectrometric data

We present a new method for the inversion of airborne gamma-ray spectrometric line data to a regular grid of radioelement concentration estimates on the ground. The method incorporates the height of the aircraft, the 3D terrain within the field of view of the spectrometer, the directional sensitivity of rectangular detectors, and a source model comprising vertical rectangular prisms with the same horizontal dimensions as the required grid cell size. The top of each prism is a plane surface derived from a best-fit plane to the digital elevation model of the earth’s surface within each grid cell area. The method is a significant improvement on current methods, and gives superior interpolation between flight lines. It also eliminates terrain effects that would normally remain in the data after the conventional processing of these data assuming a flat-earth model. A new method is presented for the inversion of airborne gamma-ray spectrometric line data to a regular grid of radioelement concentration estimates on the ground. The method incorporates the height of the aircraft and the topography. It eliminates terrain effects and improves the interpolation between flight lines.

Optimizing Airborne Electromagnetic (AEM) Inversions for Hydrogeological Investigations using a Transdisciplinary Approach

High-resolution hydrogeophysical data are increasingly acquired as part of investigations to underpin groundwater mapping. However, optimization of AEM data requires careful consideration of AEM system suitability, calibration, validation and inversion methods. In modern laterally-correlated inversions of AEM data, the usefulness of the resulting inversion models depends critically on an optimal choice of the vertical and horizontal regularization of the inversion. Set the constraints too tight, and the resulting models will become overly smooth and potential resolution is lost. Set the constraints too loose, and spurious model details will appear that have no bearing on the hydrogeology. There are several approaches to an automatic choice of the regularization level in AEM inversion based predominantly on obtaining a certain pre-defined data misfit with the smoothest possible model. However, we advocate a pragmatic approach to optimizing the constraints by an iterative procedure involving all available geological, hydrogeological, geochemical, hydraulic and morphological data and understanding. In this approach, in a process of both confirming and negating established interpretations and underlying assumptions, the inversion results are judged by their ability to support a coherent conceptual model based on all available information. This approach has been essential to the identification and assessment of MAR and groundwater extraction options in the Broken Hill Managed Aquifer Recharge project.

Open Source Software for 1D Airborne Electromagnetic Inversion

Geoscience Australia is releasing into the public domain software for the inversion of airborne electromagnetic (AEM) data to a 1D conductivity depth structure. The software includes two different algorithms for 1D inversion of AEM data. The first is a gradient based deterministic inversion code for multi-layer (smooth model) and few-layered (blocky-model) inversions. The second is a reversible-jump Markov chain Monte Carlo stochastic inversion algorithm suitable for assessing model uncertainty. A forward modelling program and some other ancillary programs are also included. The code is capable of inverting data from all of the commercial time-domain systems available in Australia today, including dual moment systems. The software is accessible in three forms. As C++ source code, as binary executables for 64 bit Windows® PCs, and as a service on the Virtual Geophysics Laboratory (VGL). The code is fully parallelized for execution on a high performance cluster computer system via MPI or a multi-core shared memory workstation via OpenMP.

Use of the Resolve Airborne Electromagnetic (AEM) Data in the Assessment of the Salinity Hazard and Risk to Iconic River and Wetland Ecosystems, Murray River, Se Australia

An AEM survey using the RESOLVE frequency domain system has been acquired along a 450 km reach of the Murray River in SE Australia. the AEM data were inverted using the holistic Inversion method, enabling key elements of the hydrogeological system in the shallow sub-surface (top 20-50m) to be mapped with high confidence levels. the AEM data have been used in conjunction with remote sensing, and hydrogeological and hydrogeochemical data obtained from drilling, to determine that healthy vegetation along the Murray River is generally associated with the presence of significant river ‘flush zones’ where fresh groundwater is present at shallow depths, and groundwater salinity is low. the study has also found that the corollary is true: where the river is ‘gaining’, and salt stores are high, vegetation health is generally in decline. Similarly, the AEM data show there is a marked decline in vegetation health towards the western edge of the iconic Gunbower State forest. This appears to be associated with salt being mobilised from irrigation districts on the western margins of the Gunbower forest. In the areas where the river flush zones are discontinuous, and the salt stores and water tables are closer to surface, there is also a risk of salt ingress to the river. in these areas, the data identify areas for targeted salinity management, including sites for potential Salt interception Schemes. This study fills important knowledge gaps particularly the distribution of key elements of the hydrostratigraphy, salinity extent, and the relationships between vegetation health, salinity and groundwater processes. in particular, the project has successfully integrated AEM, remote sensing, and lithological and hydrogeological data from drilling, to identify reaches of the River Murray and areas of iconic wetland ecosystems at risk from groundwater salinisation. these datasets provide geospatial context for targeted salinity and groundwater management actions.