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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.

Ambient seismic noise tomography is a novel, low-impact method to investigate the Earth's structure. While most passive seismic studies focus on structures at crustal scales, there are only few examples of this technique being applied in a mineral exploration context. In this study, we performed an ambient seismic experiment to ascertain the relationship between the shallow shear wave velocity and mineralized zones in the Erzgebirge in Germany, one of the most important metal provinces in Europe. Late Variscan mineralized greisen and veins occurring in the Geyer-Ehrenfriedersdorf mining district of the Central Erzgebirge were mined from medieval times until the end of the 19th century. These occurrences represent a significant resource for commodities of high economic importance, such as tin, tungsten, zinc, indium, bismuth and lithium. Based on ambient noise data from a dense "LARGE-N" network comprising 400 low-power, short-period seismic stations, we applied an innovative tomographic inversion technique based on Bayesian statistics (transdimensional, hierarchical Monte Carlo search with Markov Chains using a Metropolis/Hastings sampler) to derive a three-dimensional shear wave velocity model. An auxiliary 3D airborne time-domain electromagnetic dataset is used to provide additional insight into the subsurface architecture of the area. The velocity model shows distinct anomalies down to approximately 500 m depth that correspond to known geological features of the study area, such as (a) gneiss intercalations in the mica schist-dominated host rock, imaged by a SW-NE striking low velocity zone with a moderately steep northerly dip, and (b) a NW-trending strike-slip fault, imaged as a subvertical linear zone cross-cutting and offsetting this low velocity domain. Similar to the velocity data, the electromagnetic data exhibit north-dipping (high-conductivity) structures in the mica schists, corresponding to the strike and dip of the predominant metamorphic fabric. An unsupervised classification performed on the bivariate 3D dataset yielded nine spatially coherent classes, one of which shows a high correspondence to drilled greisen occurrences in the roof zone of a granite pluton. The relatively high mean shear velocity and resistivity values of this class could be explained by changes in density and composition during greisen formation as observed in other areas of the Erzgebirge. Our study demonstrates the great potential of the cost-efficient and low-impact ambient noise technology for mineral exploration, especially when combined with other independent geophysical datasets. [ABSTRACT FROM AUTHOR]

IP effects in AEM data are subject of current research around the world. There have been success stories and it is now practical to model AIP. It is widely accepted that failure to account for IP effects, when present, will produce artefacts in the resistivity model. However there still is a need to study more accurately the boundaries of the effect on AEM data and of its relevance, beyond common past acceptance. This paper provides a clear and extensive overview of detectable AIP effects in the data space, without imposing simplistic assumptions (e.g. fixing some parameters to arbitrary values or limited boundaries), beside using a 1D approach. We produce forward responses with dispersive resistivity for hundreds of thousands of combinations of Cole–Cole model parameters (different rock types) and AEM system transfer functions. The results are analysed using various metrics (e.g. sum of negative voltages, exponential fitting), presented with a series of 3D plots that capture different AIP signatures in the transients. Experiments include half spaces, 2 and 3 layer models, combined with different waveforms, Rx types (dB/dt and B), Tx-Rx geometries, flying heights, base frequencies. The results allow a clear assessment of the different aspects of AIP effects over a wide range of geological and geophysical situations. Measured AIP effects are mostly focused in the range of τ from 10−2 s to 10−4 s. Measurable AIP effects depend on AEM system's specs, are often unpredictable, can originate from chargeable layers at considerable depth, are heavily affected by layering and can occur over a wide range of situations. Deeper chargeable layers do not necessarily produce fainter AIP anomalies. What can be generalised is that AIP effects are increased most often by the presence of a resistive bedrock, often using slow turn-off of the waveform, are generally better observed with B field instead of dB/dt and lowering base frequencies. They can vary abruptly, due to the rapidly changing relative contribution of pure EM and pure IP responses. AIP effects can occur more often than previously thought and should not be discarded a-priori from any AEM survey. [ABSTRACT FROM AUTHOR]

Electromagnetics (EM) has been used extensively for Volcanic Hosted Massive Sulphide (VHMS) exploration in Australia. Exploring under conductive cover introduces significant limitations when using EM to identify bedrock conductivity anomalies that may be associated with VHMS deposits. We present an alternative approach, whereby robust geological modelling of the Airborne Electromagnetic (AEM) data plays a major role in the exploration strategy in the Bryah and Yerrida Basins of central Western Australia. The AEM is not only used for the identification of bedrock conductors but also forms a critical dataset constraining a robust basin-wide geological model. This model is used to identify priority areas for follow up surface geophysics and geochemistry. A patchwork of AEM surveys, covering portions of the Bryah and Yerrida basins, has been acquired by various explorers and contractors during the last decade. Systems and system specifications vary greatly. Accordingly, accurate geological interpretation of a basin-scale area, flown using various systems, cannot be derived from either raw data or fast/approximate conductivity products provided by contractors. All datasets require reconciliation with a common workflow and robust modelling strategy. Historic AEM data acquired with different systems along the edges of the tenure have been reprocessed and inverted. The remaining central block awaits the contractor's arrival before the data is subject to the same workflow. The end result will be a seamless basin-wide 3D conductivity model (extending over 6500 km2), which will inform the geological interpretation and subsequent follow-up exploration efforts. The preliminary 3D models already allow clear identification and modelling of the pyritic shale horizons, enabling the anomalous geochemistry and strongly conductive nature of these units to be discounted in the targeting process [ABSTRACT FROM AUTHOR]