We present a new methodology, spatially constrained inversion (SCI), that produces quasi-3D conductivity modeling of electromagnetic (EM) data using a 1D forward solution. Spatial constraints are set between the model parameters of nearest neighboring soundings. Data sets, models, and spatial constraints are inverted as one system. The constraints are built using Delaunay triangulation, which ensures automatic adaptation to data density variations. Model parameter information migrates horizontally through spatial constraints, increasing the resolution of layers that would be poorly resolved locally. SCI produces laterally smooth results with sharp layer boundaries that respect the 3D geological variations of sedimentary settings. SCI also suppresses the elongated artifacts commonly seen in interpretation results of profile-oriented data sets. In this study, SCI is applied to airborne time-domain EM data, but it can also be implemented with other ground-based or airborne data types.
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.
The passage of the Sustainable Groundwater Management Act in California has highlighted a need for cost-effective ways to acquire the data used in building conceptual models of the aquifer systems in the Central Valley of California. One approach would be the regional implementation of the airborne electromagnetic (AEM) method. We acquired 104 line-kilometers of data in the Tulare Irrigation District, in the Central Valley, to determine the depth of investigation (DOI) of the AEM method, given the abundance of electrically conductive clays, and to assess the usefulness of the method for mapping the hydrostratigraphy. The data were high quality providing, through inversion of the data, models displaying the variation in electrical resistivity to a depth of approximately 500 m. In order to transform the resistivity models to interpreted sections displaying lithology, we established the relationship between resistivity and lithology using collocated lithology logs (from drillers' logs) and AEM data. We modeled the AEM response and employed a bootstrapping approach to solve for the range of values in the resistivity model corresponding to sand and gravel, mixed coarse and fine, and clay in the unsaturated and saturated regions. The comparison between the resulting interpretation and an existing cross section demonstrates that AEM can be an effective method for mapping the large-scale hydrostratigraphy of aquifer systems in the Central Valley. The methods employed and developed in this study have widespread application in the use of the AEM method for groundwater management in similar geologic settings.
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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