Jared D. Abraham

Field experiment provides ground truth for surface nuclear magnetic resonance measurement

A field experiment was conducted in the High Plains Aquifer, central United States, to explore the mechanisms governing the non-invasive Surface NMR (SNMR) technology. We acquired both SNMR data and logging NMR data at a field site, along with lithology information from drill cuttings. This allowed us to directly compare the NMR relaxation parameter measured during logging, T2, to the relaxation parameter T2 * measured using the SNMR method. The latter can be affected by inhomogeneity in the magnetic field, thus obscuring the link between the NMR relaxation parameter and the hydraulic conductivity of the geologic material. When the logging T 2 data were transformed to pseudo- T2 * data, by accounting for inhomogeneity in the magnetic field and instrument dead time, we found good agreement with T 2 * obtained from the SNMR measurement. These results, combined with the additional information about lithology at the site, allowed us to delineate the physical mechanisms governing the SNMR measurement. Such understanding is a critical step in developing SNMR as a reliable geophysical method for the assessment of groundwater resources. Citation: Knight, R., E. Grunewald, T. Irons, K. Dlubac, Y. Song, H. N. Bachman, B. Grau, D. Walsh, J. D. Abraham, and J. Cannia (2012), Field experiment provides ground truth for surface nuclear magnetic resonance measurement, Geophys. Res. Lett., 39, L03304,

Numerical modeling of an enhanced very early time electromagnetic (VETEM) prototype system

In this paper, two numerical models are presented to simulate an enhanced very early time electromagnetic (VETEM) prototype system, which is used for buried-object detection and environmental problems. Usually, the VETEM system contains a transmitting loop antenna and a receiving loop antenna, which run on lossy ground to detect buried objects. In the first numerical model, the loop antennas are accurately analyzed using the method of moments (MoM) for wire antennas above or buried in lossy ground. Then, the conjugate gradient (CG) methods, with the use of the fast Fourier transform (FFT) or MoM, are applied to investigate the scattering from buried objects. Reflected and scattered magnetic fields are evaluated at the receiving loop to calculate the output electric current. However, the working frequency for the VETEM system is usually low and, hence, two magnetic dipoles are used to replace the transmitter and receiver in the second numerical model. Comparing these two models, the second one is simple, but only valid for low frequency or small loops, while the first modeling is more general. In this paper, all computations are performed in the frequency domain, and the FFT is used to obtain the time-domain responses. Numerical examples show that simulation results from these two models fit very well when the frequency ranges from 10 kHz to 10 MHz, and both results are close to the measured data.

3-D imaging of large scale buried structure by 1-D inversion of very early time electromagnetic (VETEM) data

A simple and efficient method for large scale three-dimensional (3D) subsurface imaging of inhomogeneous background is presented. One-dimensional (1D) multifrequency distorted Born iterative method (DBIM) is employed in the inversion. Simulation results utilizing synthetic scattering data are given. Calibration of the very early time electromagnetic (VETEM) experimental waveforms is detailed along with major problems encountered in practice and their solutions. This discussion is followed by the results of a large scale application of the method to the experimental data provided by the VETEM system of the U.S. Geological Survey. The method is shown to have a computational complexity that is promising for on-site inversion.

Basalt-flow imaging using a high-resolution directional borehole radar

A new high-resolution directional borehole radar-logging tool (DBOR tool) was used to log three wells at the Idaho National Engineering and Environmental Laboratory (INEEL). The radar system uses identical directional cavity-backed monopole transmitting and receiving antennas that can be mechanically rotated while the tool is stationary or moving slowly in a borehole. Faster reconnaissance logging with no antenna rotation was also done to find zones of interest. The microprocessor-controlled motor/encoder in the tool can rotate the antennas azimuthally, to a commanded angle, accurate to a within few degrees. The three logged wells in the unsaturated zone at the INEEL had been cored with good core recovery through most zones. After coring, PVC casing was installed in the wells. The unsaturated zone consists of layered basalt flows that are interbedded with thin layers of coarse-to-fine grained sediments. Several zones were found that show distinctive signatures consistent with fractures in the basalt. These zones may correspond to suspected preferential flow paths. The DBOR data were compared to core, and other borehole log information to help provide better understanding of hydraulic flow and transport in preferential flow paths in the unsaturated zone basalts at the INEEL.

Numerical study of electromagnetic waves generated by a prototype dielectric logging tool

To understand the electromagnetic waves generated by a prototype dielectric logging tool, a numerical study was conducted using both the finite-difference, time-domain method and a frequency-wavenumber method. When the propagation velocity in the borehole was greater than that in the formation (e.g., an air-filled borehole in the unsaturated zone), only a guided wave propagated along the borehole. As the frequency decreased, both the phase and the group velocities of the guided wave asymptotically approached the phase velocity of a plane wave in the formation. The guided wave radiated electromagnetic energy into the formation, causing its amplitude to decrease. When the propagation velocity in the borehole was less than that in the formation (e.g., a water-filled borehole in the saturated zone), both a refracted wave and a guided wave propagated along the borehole. The velocity of the refracted wave equaled the phase velocity of a plane wave in the formation, and the refracted wave preceded the guided wave. As the frequency decreased, both the phase and the group velocities of the guided wave asymptotically approached the phase velocity of a plane wave in the formation. The guided wave did not radiate electromagnetic energy into the formation. To analyze traces recorded by the prototype tool during laboratory tests, they were compared to traces calculated with the finite-difference method. The first parts of both the recorded and the calculated traces were similar, indicating that guided and refracted waves indeed propagated along the prototype tool.

A 1D inversion scheme for large-scale, 3D subsurface imaging of real data

A simple and efficient method for large scale three-dimensional (3D) subsurface imaging of an inhomogeneous background is presented along with an improved background estimation, which is crucial to the reconstruction. A one-dimensional (1D) multifrequency distorted Born iterative method (DBIM) is employed in the inversion of real data provided by the US Geological Survey. Calibration and practical problems are also discussed. A new 3D verification of the method is also provided.

An addendum to "Numerical modeling of an enhanced very early time electromagnetic (VETEM) prototype system"

For original paper see Cui et al. (IEEE Antennas and Propagation Magazine, vol.42, no.2, p.17-27, 2000 April). Cui et al. proposed two numerical models to simulate an enhanced very early time electromagnetic (VETEM) prototype system, used for buried-object detection and environmental problems. In the first model, the transmitting and receiving loop antennas were accurately analyzed using the method of moments (MoM), and then conjugate gradient (CG) methods with the fast Fourier transform (FFT) were utilized to investigate the scattering from buried conducting plates. In the second model, two magnetic dipoles were used to replace the transmitter and receiver, because the working frequency for the VETEM system is usually low. Both the theory and formulation were correct, and the simulation results for the primary magnetic field and the reflected magnetic field were accurate. We have compared the simulation results for the magnetic field reflected by a wire-conductor mesh on the ground with measured data. They fit very well. However, the scattered magnetic fields in the simulation results were inaccurate, because we did not use a sufficient number of iterations in the CG-FFT algorithm when the frequency was very low.

Curie depth and inversion of aero-magnetic data with implications for Hazards on Pagan Island, Commonwealth of the Northern Mariana Islands

Airborne magnetic data have been used to aid in the hazard assessment on Pagan Island. Pagan Island is small active stratovolcano in the Commonwealth of Northern Mariana Islands approximately 320 km north of Saipan. The magnetic survey was part of a geophysical study that was carried out to evaluate the hazards of the Island in 2013. Pagan Island was evacuated during a major eruption in 1981. Recently the island has been assessed for a military training base, an area for mining pozzolan, and for rehabitation from the displaced population resulting from the 1981 eruption. With the remote location and rugged inaccessible nature of Pagan Island the airborne approach was the only logistically feasible way to provide a comprehensive assessment of the location of the heat sources within the volcano. Both spectral analysis and 3D inversion were used in order to provide two alternative means to determine depth to bottom of magnetic source. Locations of the heat sources within the volcano is one of critical pieces of information required for the government of the Commonwealth of the NorthernMariana Island to asses the safety an ultimately the use of the Pagan Island. Results were consistent between the two approaches and zones of shallow and deep Curie point isotherm were independently identified. The government has utilized these data after comparing with other passive seismic data to assist in the hazard assessment of Pagan Island.

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.

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.