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Partners in Environmental Technology Technical Symposium & Workshop, Washington, D.C., December 2-4, 2008 SERDP MM1573: Simultaneous Inversion of UXO Parameters and Background Response Kevin A. Kingdon, Nicolas Lhomme and Stephen D. Billings Sky Research, Inc Ashland, Oregon Leonard R. Pasion (P.I.) and Douglas W. Oldenburg Univ. of British Columbia Vancouver, B.C., Canada Inverting TEM data for Dipole Parameters assuming an Additive Background MM1573 PROJECT OVERVIEW: Background: Identifying unexploded ordnance (UXO) reliably and efficiently without excavating large numbers of non-UXO is one of the Department of Defense’s most pressing environmental problems. The task of discriminating UXO from non-UXO items is more difficult when sensor data are collected at sites where an electromagnetically active host contributes a large background signal that masks the response of UXO. These include sites contaminated with geological noise originating from magnetic soil and sites requiring UXO detection in conductive sea water. In regions of highly magnetic soil, magnetic and electromagnetic sensors often detect large anomalies that are of geologic rather than metallic origin. Objective: This project focuses on the accurate recovery of target parameters from geophysical sensor data, even in cases when targets of interest sit in a magnetic or conductive host. Technical objectives include: 1. Determining the extent to which a highly conductive or magnetic host interacts with a buried metallic target and 2. Developing improved recovery of target parameters by simultaneously inverting target parameters and the properties of the host material. Acknowledgements We would like to thank Ben Barrowes for collecting MPV data with us in Ashland, Oregon. We would also like to thank Tom Bell and Jim Kingdon for providing us with the Camp Sibert scrap polarizations derived from TEMTADS in-air measurements. tilt Investigating the Effect of Magnetic Geology on EMI Data through Numerical Modeling of Maxwell’s Equations EH3D is a flexible forward modelling program developed at UBC-GIF for calculating the EM fields resulting from a wide range of time domain electromagnetic sources and source waveforms, over a 3D earth that is discretized using a mesh of rectangular cells. These codes were used to model the response of a compact metallic target and a host that has both viscous remnant magnetic as well as conductive properties. Simple geological scenarios were also modelled and compared with multi component data collected over the same geological features. χ(ω) Frequency (Hz) Real Imag Real Imag Frequency (Hz) Example: Modelling the VRM Response EH3D correctly models the viscous remnant magnetization (VRM) response Target in Halfspace Target in Freespace Halfspace Only σ = 0.1 S/m σ = 0.1 S/m σ =1e4 S/m σ =1e4 S/m χ(ω) χ(ω) Target in Halfspace Target in Freespace Real Real Imag Imag Halfspace Only σ = 0.1 S/m σ = 0.1 S/m σ =1e4 S/m σ =1e4 S/m Target in a Conductive Host Target in a Conductive and VRM Host EH3D Modelling of a Bump 2. Investigating the effect of terrain on Data • EMI responses generated from irregularities in the topography while surveying. • EH3D was used to model the response for a bump and a trench . • Excellent agreement was observed when comparing the modelling results with data collected using the MPV sensor. EH3D Modelling of a Trench Real and imaginary values of the H field for all frequencies modeled in EH3D for a target in a half-space (top 2 panels) and a half-space (middle 2 panels). The bottom 2 panels plot the derived target in free-space solution obtained by differencing the soundings at the center of the loop between the top row of panels and the middle row of panels. The EH3D computed solution for a target in free-space is also plotted in the bottom row panels. Example 1: Modelling multi-component, multi- static sensor data • Man Portable Vector (MPV) TEM Sensor Data collected at Sky Research UXO test plot in Ashland, OR • Soil soundings exhibits the characteristic VRM decay R2 R3 R4 Modelling TEM data collected at sites with magnetic geology Example 2: Modelling EMI Array Data 1. Investigating the Additivity of the Soil and Target responses • The highest conductivity (s=10 -1 S/m) half-space was chosen as that is the scenario most likely to produce current channeling which would pose the most difficulties in the assumption that a target and host soil response can be treated as separate, additive responses. • Soundings are compared for the free-space computed directly from EH3D with a derived half-space achieved by differencing the soundings extracted at the center of the loop for the EH3D solutions obtained for the target in a half-space and the half-space only models. • The agreement is excellent at all frequencies and additivity is valid for the model considered. Thus a processing procedure that involves subtracting a background EM response from the data to produce a response that can be modeled as a UXO in free-space is a reasonable procedure. Magnetic susceptibility model based on lab measurements of Kaho’olawe soil (MM1414) Orientation Test • Multi-Sensor Towed Array Detection System (MTADS) EMI data were collected at Camp Sibert, Alabama. • Of the anomalies identified from the MTADS EM61 data, several produced empty holes when excavated. • Due to the presence of magnetic soils we expect that changes in ground clearance (due to wheels moving over small scale topography) might explain some of the anomalies. • The MTADS sensor does not have an altimeter. Detrended elevation data is used to estimate a ground clearance Cell 644 • An approximately 40 mV anomaly was detected in the NS lines • The detrended elevation suggests that there is a variation of approximately 13 cm in the ground clearance Line 76 Cell 809 Ground Clearance Estimated from Elevation Data Predicted Geologic Response MTADS first time channel - Detrended -600 -400 -200 0 200 Original Data Frequency (Hz) Signal (ppm) Tg: Real Tg: Imag Soil: Real Soil: Imag -300 -200 -100 0 100 200 300 Frequency (Hz) Signal (ppm) Corrected Data Easting (m) Northing (m) In Phase, 30 Hz -1 0 1 -1 -0.5 0 0.5 1 -700 -600 -500 -400 -300 -200 -100 0 Easting (m) Northing (m) In Phase, 30 Hz, corrected -1 0 1 -1 -0.5 0 0.5 1 -350 -300 -250 -200 -150 -100 -50 0 Front Right Left Center - coaxial Sensor Tilt (degrees) Examples of anomalies with soil signals Example 2. Inversion of Geonics EM63 TEM data at Camp Sibert Example1. Inversion of Geophex GEM3 FEM data at Camp Sibert Vertical Components Radial Components Azimuthal Components Rx2,Rx3,Rx4 Observed data Predicted data Residual Observed data Predicted data Residual Channel 1 Channel 20 Left: Data fit for a pair of soundings. S1 is located away from the target. S2 is located at the anomaly peak. At late times the S2 sounding is dominated by the soil response. Right: Small scale variations in the data due to geology are modelled. Height Test Front Right Left Center - coaxial Height Above Ground (m) We use a Viscous Remanent Magnetization (VRM) model to identify soundings that correspond to soil, and then estimate a spatially smooth background magnetic susceptibility. The magnetically susceptible background is then subtracted from the sensor data, which are then inverted to obtain estimates of the dipole polarization tensor. Time (ms) EM63 Response (mV) S1 S2 L1 S2 S1 L1 meters EM61 mV Channel 1 Line 15 Line 518 In this example, the detrending processing does not accurately estimate ground clearance. As a result, our estimated ground response appears shifted by 30 mV, but still matches the shape of the measured response. In this example, we simultaneously estimate the background signal and the target dipole polarizations. The background susceptibility is assumed to spatially vary as a plane (3 parameters). Polarizations obtained from TEMTADS in-air measurements Estimated polarizations when inverting data for 3 unique polarizations Estimated polarizations when inverting data for 2 unique polarizations Inversions are carried out in two steps. First the dipole model is used to recover the position, orientation and components of the polarization tensor at all frequencies. Then, the instantaneous amplitudes L(w) at frequency w for the 3-dipole polarizations are fit to the four-parameter model of Miller et al. (2001): where k is the object amplitude, t is a response time- constant, s is a factor that controls the magnitude of asymptotes at high and low-frequency, and c is a parameter that controls the width of the in-phase peak response. -346.22 -343.88 -1539.32 -647.12 89.98 436.03 -427.48 -127.14 Depth = 0.47 m Depth = 0.4 m Depth = 0.72 m Depth = 1.06 m Example of soil correction. Soundings that classified as being as soil, are used to form a soil model. A thin plate spline is used to interpolate the soil model to all soundings Recovered polarization parameters. The time constant parameter separates the 4.2 inch and partial mortars. Above: The recovered polarizations match the polarizations determined from TEMTADS in-air measurements. The data SNR is not quite large enough for an accurate recovery of the secondary polarizations. To simplify the calculations we make a number of assumptions: 1. The geologic response will primarily be due to viscous remnant magnetization (VRM), and not conductivity. 2. The response for a loop with an arbitrary orientation can be approximated to have the form This assumption greatly simplifies our calculations, as the functions A and f(t) are function of survey and sensor parameters, and not the geologic properties of the subsurface. 3. Topography does not need to be modeled. 4. The transmitter loop can be approximated as multiple dipole moments. Imag Imag Real Real Real Imag Imag Imag Real Real Raw Elevation Detrended Elevation Observed vs. Predicted
