Joining multiple AEM datasets to improve accuracy, cross calibration and derived products: The Spiritwood VTEM and AeroTEM case study

Airborne time-domain electromagnetic methods (AEM) are useful for hydrogeological mapping due to their rapid and extensive spatial coverage and high correlation between measured magnetic fields, electrical conductivity, and relevant hydrogeological parameters. However, AEM data, preprocessing and modelling procedures can suffer from inaccuracies that may dramatically affect the final interpretation. We demonstrate the importance and the benefits of advanced data processing for two AEM datasets (AeroTEM III and VTEM) collected over the Spiritwood buried valley aquifer in southern Manitoba, Canada. Early-time data gates are identified as having significant flightdependent signal bias that reflects survey flights and flight lines. These data are removed from inversions along with late time data gates contaminated by apparently random noise. In conjunction with supporting information, the less-extensive, but broader-band VTEM data are used to construct an electrical reference model. The reference model is subsequently used to calibrate the AeroTEM dataset via forward modelling for coincident soundings. The procedure produces calibration factors that we apply to AeroTEM data over the entire survey domain. Inversion of the calibrated data results in improved data fits, particularly at early times, but some flight-line artefacts remain. Residual striping between adjacent flights is corrected by including a mean empirical amplitude correction factor within the spatially constrained inversion scheme. Finally, the AeroTEM and VTEM data are combined in a joint inversion. Results confirm consistency between the two different AEM datasets and the recovered models. On the contrary, joint inversion of unprocessed or uncalibrated AEM datasets results in erroneous resistivity models which, in turn, can result in an inappropriate hydrogeological interpretation of the study area

Effects of Signal Processing and Antenna Frequency on the Geostatistical Structure of Ground-Penetrating Radar Data

Recent research has suggested that the geostatistical structure of ground-penetrating radar data may be representative of the spatial structure of hydraulic properties. However, radar images of the subsurface can change drastically with application of signal processing or by changing the signal frequency. We perform geostatistical analyses of surface radar reflection profiles in order to investigate the effects of data processing and antenna frequency on the semivariogram structure of radar reflection amplitudes. Surface radar reflection data collected at the Boise Hydrogeophysical Research Site illustrate the processing- and antenna-dependence of radar semivariograms for a fluvial, cobble-and-sand aquifer. Compensating for signal attenuation and spreading using a gain function removes a nonstationary trend from the data and a trace-specific gain function reduces fluctuation of semivariogram values at large lags. Otherwise, geostatistical structures of surface reflection data are quite robust to the effects of data gains. Migration is observed to reduce the strength of diffraction features in the semivariogram fields and to increase the principal exponential range. Principal exponential range increases only slightly after application of migration with a realistic velocity but over-migration results in a significant artificial increase of exponential range. The geostatistical structures of radar reflection data exhibit marked dependence on antenna frequency, thus highlighting the critical importance of the scale of measurement. Specifically, the exponential ranges of radar reflection amplitudes decrease in proportion to the increased signal frequency for the 50 MHz, 100 MHz and 200 MHz range of antennas. Results demonstrate that processing and antenna frequency must be considered before the application of radar reflection data in a geostatistical context

Incorporating a-priori information into AEM inversion for geological and hydrogeological mapping of the Spiritwood Valley Aquifer, Manitoba, Canada

Buried valleys are important hydrogeological structures in Canada and other glaciated terrains, providing sources of groundwater for drinking, agriculture and industrial applications. Hydrgeological exploration methods such as pumping tests, boreholes coring or ground-based geophysical methods (seismic and electrical resistivity tomography) provide limited spatial information and are inadequate to efficiently predict the sustainability of these aquifers at the regional scale. Airborne geophysics can be used to significantly improve geological and hydrogeological knowledge on a regional scale. There has been demonstrated success at using airborne electromagnetics for mapping and characterization of buried valleys in different geological contexts (Auken et al., 2008; Jørgensen et al., 2003; Jørgensen et al., 2009; Steuer et al., 2009). Despite the fact that both electromagnetic surveys and reflection seismic profiling are used extensively in hydrogeological mapping, integration of the methods is a relatively unexplored discipline (Høyer et al., 2011). The Spiritwood Valley is a Canada-USA trans-border buried valley aquifer that runs approximately NW – SE and extends 500 km from Manitoba, across North Dakota and into South Dakota (Winter et al., 1984). The Spiritwood aquifer system consists of glacially deposited silt and clay with sand and gravel bodies, infilling a broad north-south trending valley that has been identified primarily based on water wells information (Wiecek, 2009). The valley is incised into bedrock consisting of fractured siliceous shale. As part of its Groundwater Geoscience Program, the Geological Survey of Canada (GSC) has been investigating buried valley aquifers in Canada using airborne and ground-based geophysical techniques. To obtain a regional three-dimensional assessment of complex aquifer geometries for the Spiritwood, both geophysical and geological investigations were performed with the aim to develop an integrated conceptual model for a quantitative description of the aquifer system. In 2010, the Geological Survey of Canada conducted an airborne electromagnetic (AeroTEM III) survey over a 1062 km2 area along the Spiritwood Valley, north of the US border (Oldenborger 2010a, 2010b). AEM inversion results show multiple resistive valley features inside a wider, more conductive valley structure within the conductive bedrock (Fig. 1). Furthermore, the complexity of the geometries, spatial distribution and size of the channels is evident. Other ground based data collected in the survey area make it possible to provide some constraints on the AEM resistivity model. Downhole resistivity logs were collected that provide information on the electrical model relative to the geological layers (Crow et al., 2012). In addition, over 10 line-km of electrical resistivity data and 42 km of high resolution landstreamer seismic reflection data (Figs. 2a, 2b) were collected at selected sites (Oldenborger et al., 2012). In this short paper we present results obtained from the data inversion and an example of integration of ancillary seismic data into the AEM inversion. In particular, the elevation to a layer (shale bedrock elevation) as interpreted from seismic is added to the inversion to constrain the resistivity model

Recent AEM Case Study Examples of a Full Waveform Time-Domain System for Near-Surface and Groundwater Applications

Early time or high frequency airborne electromagnetic data (AEM) are desirable for shallow sounding or mapping of resistive areas but this poses difficulties due to a variety of issues, such as system bandwidth, system calibration and parasitic loop capacitance. In an effort to address this issue, a continued system design strategy, aimed at improving its early-channel VTEM data, has achieved fully calibrated, quantitative measurements closer to the transmitter current turn-off, while maintaining reasonably optimal deep penetration characteristics. The new design implementation, known as “Full Waveform” VTEM was previously described by Legault et al. (2012). This paper presents some case-study examples of a Full Waveform helicopter time-domain EM system for near-surface application

3D Hydrogeological Model Building Using Airborne Electromagnetic Data

We develop a 3D geological modelling procedure supported by the combination of helicopter time-domain electromagnetic data, seismic reflection data, and water well records for the Spiritwood buried valley aquifer system in Manitoba, Canada. Our procedure is an innovative hybrid of knowledge-driven and data-driven schemes that provides a clear protocol for incorporating different types of geophysical data into a 3D stratigraphic model framework. The limited spatial density of water well bedrock observations precludes detection of the buried valley bedrock topography and renders the water well records alone inadequate for accurate hydrogeological model building. The expert interpretation of the geophysical data allows for leveraging of a spatially extensive dataset with rich information content that would be otherwise difficult to utilize for lithostratigraphic classification

Optimized arrays for 2D cross-borehole electrical tomography surveys

The use of optimized arrays generated using the ‘Compare R’ method for cross-borehole resistivity measurements is examined in this paper. We compare the performances of two array optimization algorithms, one that maximizes the model resolution and another that minimizes the point spread value. Although both algorithms give similar results, the model resolution maximization algorithm is several times faster. A study of the point spread function plots for a cross-borehole survey shows that the model resolution within the central zone surrounded by the borehole electrodes is much higher than near the bottom end of the boreholes. Tests with synthetic and experimental data show that the optimized arrays generated by the ‘Compare R’ method have significantly better resolution than a ‘standard’ measurement sequence used in previous surveys. The resolution of the optimized arrays is less if arrays with both current (or both potential) electrodes in the same borehole are excluded. However, they are still better than the ‘standard’ arrays

Reliability of resistivity quantification for shallow subsurface water processes

The reliability of surface-based electrical resistivity tomography (ERT) for quantifying resistivities for shallow subsurface water processes is analysed. A method comprising numerical simulations of water movement in soil and forward-inverse modeling of ERT surveys for two synthetic data sets is presented. Resistivity contrast, e.g. by changing water content, is shown to have large influence on the resistivity quantification. An ensemble and clustering approach is introduced in which ensembles of 50 different inversion models for one data set are created by randomly varying the parameters for a regularisation based inversion routine. The ensemble members are sorted into five clusters of similar models and the mean model for each cluster is computed. Distinguishing persisting features in the mean models from singular artifacts in individual tomograms can improve the interpretation of inversion results. Especially in the presence of large resistivity contrasts in high sensitivity areas, the quantification of resistivities can be unreliable. The ensemble approach shows that this is an inherent problem present for all models inverted with the regularisation based routine. The results also suggest that the combination of hydrological and electrical modeling might lead to better results.Comment: 12 figure

Electrical-hydraulic relationships observed for unconsolidated sediments in the presence of a cobble framework

Mechanistic models now exist to predict hydraulic conductivity (K) from the spectral induced polarization (SIP) response of granular media. We examined the predictions of such a model on unconsolidated coarse fluvial sediments and compared them to those obtained with a modified Kozeny Carman (KC) model. Samples were retrieved from the Boise Hydrogeophysical Research Site (BHRS), located on a gravel bar adjacent to the Boise River, Idaho. A sample holder (0.102 m diameter and 0.12 m in length) was designed to include the cobble framework in reconstituted samples representing the primary stratigraphic units defined based on porosity variation at this site. SIP (0.001-1000 Hz) and K (from Darcy tests) measurements were recorded for twelve samples, with SIP measurements made as a function of pore fluid conductivity (3-300 mS/m); grain, grain size distribution (GSD) and total porosity. K prediction with the KC model was improved after discounting of the cobble framework and multiplying by the tortuosity resulting from matrix “capillaries” around the cobbles, resulting in estimates within 0.5 orders of magnitude of the measurements. K prediction with a mechanistic SIP model based on Stern layer polarization (SLP model) that requires an estimate of the GSD alsoalso required discounting for the cobble framework to obtain estimates within 0.5 orders of magnitude of the measurements. Similarly, the SLP model over predicts the measured imaginary conductivity (σ") unless the cobble framework is discounted, which then results in estimates of σ” within 0.1 orders of magnitude of the measurements. This can be explained by the fact that the cobbles polarize at frequencies well below the minimum measurement frequency (0.001 Hz). The SLP model for K prediction parameterized in terms of the formation factor and imaginary conductivity performed well for the ten samples with a cobble framework without modification as the imaginary conductivity directly senses the matrix grain size characteristics, whereas the formation factor captures the porosity reduction and tortuosity resulting from the presence of the cobble framework (capillary tortuosity). Our findings suggest that the estimation of contrasts in hydraulic conductivityK in coarse sediments may be achievable through measurements of electrical properties after appropriate consideration of the cobble fractio

Image Texture Characterization Using the Discrete Orthonormal S-Transform

We present a new efficient approach for characterizing image texture based on a recently published discrete, orthonormal space-frequency transform known as the DOST. We develop a frequency-domain implementation of the DOST in two dimensions for the case of dyadic frequency sampling. Then, we describe a rapid and efficient approach to obtain local spatial frequency information for an image and show that this information can be used to characterize the horizontal and vertical frequency patterns in synthetic images. Finally, we demonstrate that DOST components can be combined to obtain a rotationally invariant set of texture features that can accurately classify a series of texture patterns. The DOST provides the computational efficiency and multi-scale information of wavelet transforms, while providing texture features in terms of Fourier frequencies. It outperforms leading wavelet-based texture analysis methods