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Bridges & Structures


Interstate Technical Group on Abandoned Underground Mines
An Interactive Forum

Subsurface Void Detection using Seismic Tomographic Imaging

Presenter: Roland Gritto, Earth Science Division
University/Organization: Lawrence Berkeley National Laboratory
Phone: 510-486-7118
Fax: 510-486-5686
Email: rgritto@lbl.gov
Mailing Address: One Cyclotron Road
MS 90-1116
Berkeley, California 94720


Tomographic imaging has been widely used in scientific and medical fields to remotely image media in a nondestructive way. This paper introduces a spectrum of seismic imaging applications to detect and characterize voids in coal mines. The application of seismic waves to detect changes in coal relies on two types of waves: body waves refracted along the interface between coal and bedrock (i.e., refracted P-waves) and channel waves that propagate directly through the coal (dispersive wave trains of the Rayleigh or Love type). For example, a P-wave tomography study to find underlying old mine workings in a coal mine in England, produced velocity patterns that revealed increases in velocity where high stress concentrations occur in the rock, which are most likely connected to old pillars left in support of the old working areas. At the same time, low velocities were found in areas of low stress concentrations, which are related to roof collapses indicating the locations of mined areas below. The application of channel wave tomography to directly image the presence of gaseous CO2 in a low velocity oil reservoir showed that the injected CO2 followed an ancient flow channel in the reservoir migrating from the injector to the producer well. The study showed how channel waves are preferable over refracted P-waves, as the latter were only marginally affected by the presence of the gas in the low-velocity channel. Similar approaches show great promise for the detection of voids in coal mines. Finally, a newly developed technique, based on scattering theory, revealed that the location and the size of a subsurface cavity could be accurately determined even in the presence of strong correlated and uncorrelated noise.

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Updated: 06/27/2017
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