Frequency Domain Electromagnetic Data - Inverted Data
Dates
Publication Date
2019-03-12
Citation
Miller, B.V., Payne, J.D., Killion III, W.F., and Adams, R.F., 2019, Geophysical surveys and geospatial data for Bob Kidd Lake, Washington County, Arkansas: U.S. Geological Survey data release, https://doi.org/10.5066/P9I4W2P0.
Summary
FDEM Processing The frequency domain electromagnetic (FDEM) data were downloaded from the GEM-2 instrument and aggregated into a single data file. The data were manually despiked and smoothed to remove negative values and the effects of metallic objects. A drift correction was applied by finding the average in-phase and average quadrature values for each frequency transmitted each time the base station was occupied. This average value was then used to calculate a linear trend of the data in time and the linear trend was subtracted from the data set. After the data were drift corrected, the data was leveled by calculating the arithmetic mean of the survey data subtracting that value from the dataset to level all the data around [...]
Summary
FDEM Processing
The frequency domain electromagnetic (FDEM) data were downloaded from the GEM-2 instrument and aggregated into a single data file. The data were manually despiked and smoothed to remove negative values and the effects of metallic objects. A drift correction was applied by finding the average in-phase and average quadrature values for each frequency transmitted each time the base station was occupied. This average value was then used to calculate a linear trend of the data in time and the linear trend was subtracted from the data set. After the data were drift corrected, the data was leveled by calculating the arithmetic mean of the survey data subtracting that value from the dataset to level all the data around zero. Each frequency was then converted to pseudodepth using IX1D (Interprex, Inc.; version 3.0). Then, using a 1-D electrical model derived from an electrical resistivity sounding collected over the base station, a forward model calculation was performed to determine the parts-per-million (ppm) shift necessary for each frequency to match the electrical resistivity sounding. The calculated ppm value for each frequency was then added back into the FDEM dataset that had been leveled around zero to produce the processed data set.
Before importing the processed data into the inversion software, the corresponding topography data was added to each data point by sampling a grid of the GPS point cloud collected over the dam.
Processed data were read into the Workbench Ground Conductivity Module (Aarhus Geophysical, Inc.; version 5.5.0.0) at a sounding distance of 1 m and were smoothed using a moving average filter with 5 m width for all filtered frequencies. The quadrature component of the data were then inverted using the 1D laterally constrained inversion. The “Smooth” Inversion setting was chosen with model converging to the L2 norm and the model was discretized into 12 layers beginning at a depth of 0.2 m and ending at 10 m. The starting resistivity value was set to “Auto”. The lateral and vertical constraints were set to the “Loose” settings. The Prior Constraint was set to “Unconstrained”. The inversion was set to stop at 10 iterations or when the convergence condition was satisfied.
