HR: 11:45h
AN: NS12A-06    [Abstracts]
TI: Improved Inversion of High-Angle Ray Data in Crosshole GPR Tomography
AU: * Irving, J
EM: jdirving@pangea.stanford.edu
AF: Geophysics Department, Stanford University, Room 360, Mitchell Building, Stanford, CA 94305 United States
AU: Knight, R
EM: rknight@pangea.stanford.edu
AF: Geophysics Department, Stanford University, Room 360, Mitchell Building, Stanford, CA 94305 United States
AB: Over the past decade, crosshole ground-penetrating radar (GPR) tomography has become an important tool for the estimation of subsurface moisture content. In order to produce the highest resolution images possible with this technique, raypaths covering a wide range of angles between the boreholes are required. In practice, however, including high-angle ray data in crosshole GPR inversions often results in poor data fitting and tomographic images with obvious artifacts. As a result, high-angle ray data are usually discarded prior to inverting. This produces stable tomographic images, but with limited horizontal resolution that impacts the use of such images for estimating hydrologic properties. We have found that the incompatibility of high-angle ray data in crosshole GPR tomography can be largely explained by the finite length of the borehole radar antennas. Whereas tomographic inversions treat the antennas as point sources and receivers, in reality the antenna length is often a significant fraction of the borehole separation. At high angles, we have found that first arrival energy can often represent coupling between the tips of the antennas, and not between their centers as is presently assumed. This results in significant geometrical errors in the inversion of high-angle data. The effect is most significant for small borehole separations. We present a means of dealing with high-angle rays in crosshole GPR tomography so that all available data can be incorporated into the inversion process. First, we obtain a starting velocity model from an aperture-limited subset of the available travel time picks. Next, we construct nine different tomographic kernel matrices that represent coupling between all primary radiation points along the antennas (i.e., the antenna centers and tips). Using these kernels, we then determine which coupling path arrives first for each transmitter/receiver configuration in the entire data set. From this information, we construct a new tomographic kernel matrix and solve the system for the velocity distribution between the boreholes. Tests on synthetic data show that this procedure allows for the successful incorporation of all recorded data into crosshole GPR tomography, and produces results with noticeably improved horizontal resolution over aperture-limited data subsets.
DE: 0609 Antennas
DE: 0644 Numerical methods
DE: 0689 Wave propagation (4275)
DE: 1866 Soil moisture
SC: Near-Surface Geophysics [NS]
MN: 2005 Joint Assembly