James C. Cannia

Base of principal aquifer for parts of the North Platte, South Platte, and Twin Platte Natural Resources Districts, western Nebraska

After initial processing by SkyTEM, the data were inverted using the Aarhus Geophysics Aps, (Aarhus, Denmark) program Workbench (Auken and others, 2009). To make the AEM data useful for geologic interpretation, numerical inversion converted measured data into a depth-dependent subsurface resistivity model, which was displayed as a resistivity profile. The inverted resistivity model (referred to hereafter as inverted AEM profiles), along with sensitivity analyses and test-hole information, were used to identify hydrogeologic features such as bedrock highs and paleochannels. A depth of investigation (DOI) calculation using the method given in Christiansen and Auken (2010) for each sounding is included in appendix 2 of U.S. Geological Survey Crustal Geophysics and Geochemistry Science Center (2014). The DOI can be defined as a critical depth below which the resistivity value is no longer constrained and interpretations of layer boundaries applied below DOI should be used with caution. Details on the data processing and inversion modeling can be located in Smith and others (2009, 2010). An interpretation of the location of the BOA was completed using a GIS that output x, y, and z coordinates. Before interpreting the inverted AEM profiles, several complementary datasets were included and graphically displayed in twoand three-dimensional GIS environments. Complementary data included test-hole lithology, test-hole geophysical logs (including natural-gamma and normal resistivity; University of Nebraska-Lincoln, Conservation and Survey Division, 2014; J.C. Cannia, U.S. Geological Survey, written commun., 2012; Hobza and Sibray, 2014; T.A. Kuntz, Adaptive Resources Inc., written commun., 2012), TDEM resistivity models (Abraham and others, 2012; M.A. Kass, U.S. Geological Survey, written commun., 2014), airborne measurements of the intensity of 60-hertz power-line interference, airborne measurements of the magnetic total-field intensity, aerial photographs (Esri, 2014), unpublished bedrock outcrop maps (R.F. Diffendal, Jr., University of Nebraska-Lincoln, Conservation and Survey Division, unpub. data, 2013; J.B. Swinehart, University of Nebraska-Lincoln, Conservation and Survey Division, unpub. data, 2013), and the 10-m digital elevation model (DEM; Nebraska Department of Natural Resources, 1998). The inverted AEM profiles were displayed as colored resistivity profiles within the GIS environment. To assist interpretation, the inverted AEM profiles were plotted using a consistent color scale, and all of the datasets for each NRD were placed in the same projected coordinate system. This allowed the data to be examined at varying spatial scales, and for data to be iteratively displayed or hidden to fully examine how the geophysical data correlated with complementary datasets. The overview of the process of creating BOA maps from inverted AEM profiles is described below with a more detailed discussion included in the subsequent subsections. Geologic interpretation involved manually picking locations (BOA elevations) on the displayed AEM profile by the project geophysicist, hydrologist, and geologist. These locations, or picks, of the BOA (herein referred to as BOA picks; typically the top of the Brule) were then stored in a georeferenced database. The BOA picks were made by comparing the inverted AEM profile along a flight line to the known lithology of the area based on lithologic descriptions and borehole geophysical logs from test holes. Using a GIS to view all available data at one time in a spatially georeferenced manner provides a high degree of confidence in the elevation values for the picks. The point dataset of the BOA picks’ elevation was the input to a surface-interpolation algorithm of the GIS. A contouring algorithm subsequently was used to construct contours of the BOA elevation. The generated contours then were manually adjusted based on the interpreted location of paleovalleys eroded into the BOA surface and associated bedrock highs. The interpreted BOA surface is the result of erosion and subsequent valley-filling fluvial deposition from eastward draining streams (Cannia and others, 2006), and therefore is not expected to contain enclosed depressions. These newly revised contours were compared with land-surface elevation as a consistency check. Where the interpolated BOA intersected land surface, the contours were reshaped manually to follow the 10-m DEM. This was done to correct areas in the final dataset where the BOA elevation exceeded the land surface. As another consistency check, the DOI information (appendix 2, U.S. Geological Survey Crustal Geophysics and Geochemistry Science Center, 2014) was compared to the BOA-pick depth. In nearly every case, the BOA picks were above the DOI depth. In cases where the BOA picks exceeded the DOI, the supported BOA contours are dashed to indicate the contour locations are inferred (fig. 2); however, the inferred BOA contours and BOA picks are included in the final GIS dataset because they are supported by test-hole and other complementary geophysical data.

Fast and Effective Groundwater Mapping from 10 to 300 M Depth with Accurate Processing and Inversion of SkyTEM Data

We present results from an airborne electromagnetic survey for groundwater mapping near Sidney, Nebraska, commissioned by the US Geological Survey in cooperation with the North Platte, South Platte, and Twin Platte Natural Resource Districts to SkyTEM Aps and Aarhus Geophysics who did processing and inversion. An important innovation of this project is near real-time processing and inversion performed daily in the field. A test of the SkyTEM system over a demonstration area, surveyed prior to collecting data in the project area, was used to illustrate the effectiveness of the system in resolving the target containing a series of aquifers of varying thicknesses. Because SkyTEM data require no leveling and complex bias removal procedures, the data can be used immediately after each flight, without need of time consuming bias compensation or leveling procedures. A fast, first-pass processing (decoupling etc) can immediately start and, upon completion, the inversion is carried out. With a quad-core desktop it is possible to process and invert overnight, with full non-linear inversion, an average day’s worth of EM data acquisition. Although the results are not as accurate as obtained from more thorough processing and multiple inversion runs, they are sufficient to evaluate the systems resolution and accuracy, and allow for informed decisions to move forward with production flights in the project areas. The data from these production areas were processed in the office to eliminate large and dense coupling effects due to power lines, pipelines, and irrigation infrastructure, and then inverted with a spatially-constrained inversion, which incorporates prior information to produce more robust results. From a hydrogeological standpoint, the results obtained greatly improved the understanding of the groundwater system, mapping aquifer thickness over ranges of 10 m to 300 meters. The SkyTEM system is unique among other Airborne TEM instruments also for the capacity to resolve shallow layers, that traditinally require HEM systems. We present a comparison with ancillary information, including ground-based electromagnetic measurements, borehole lithologic and geophysical logs. Using selected prior information to constrain spatially the inversion can further improve the resolution of some model parameters.

Airborne electromagnetic surveys: A quantitative tool for groundwater management

GEM Beijing 2011: International Workshop on Gravity, Electrical & Magnetic Methods and Their Applications Beijing, China. October 10-13, 2011. Airborne electromagnetic surveys: A quantitative tool for groundwater management Jared D. Abraham*, U. S. Geological Survey, Denver Colorado; James C. Cannia, U. S. Geological Survey, Mitchell, Nebraska; and Burke J. Minsley, U. S. Geological Survey, Denver, Colorado