<p>Seismic velocity modeling is being frequently applied for void detection within the first few meters from the surface. Velocity of the medium would likely to be affected at the transition due to construction artifacts, which results in velocity contrast at the boundary between two mediums. These variations indicate a deviation of the medium from natural conditions and provide information on the state of the material or the nature of compaction associated with void. We have demonstrated a combination of surface wave inversion to generate shear velocity models (V<sub>S</sub>) using two Rayleigh wave and Love wave datasets each, to model two well documented pipes and a poorly documented backfill. Data was acquired using two different sources, which are—Source (1) betsy seisgun, and Source (2) thumper (weight drop). Overall, all the V<sub>S</sub> models show anomalous structure in the location of the backfill with velocity increase of ~ 400&#xa0;m/s except the V<sub>S</sub> from source 2 Love wave (~ 300&#xa0;m/s). On the other hand, the western pipe also presents a common anomalous zone with elevated velocity within a background velocity of 200&#xa0;m/s. Although the eastern pipe did not show any detectable anomalous characteristics, still the combination of all the V<sub>S</sub> models resolved the backfilled area and the western pipe indicating that comparable V<sub>S</sub> models derived from various data can be effectively applied for void detection.</p>

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Applications of surface wave modeling for void detection while comparing the data acquired using two sources

  • Md. Iftekhar Alam,
  • M. Salman Abbasi,
  • Lindsey Riikola

摘要

Seismic velocity modeling is being frequently applied for void detection within the first few meters from the surface. Velocity of the medium would likely to be affected at the transition due to construction artifacts, which results in velocity contrast at the boundary between two mediums. These variations indicate a deviation of the medium from natural conditions and provide information on the state of the material or the nature of compaction associated with void. We have demonstrated a combination of surface wave inversion to generate shear velocity models (VS) using two Rayleigh wave and Love wave datasets each, to model two well documented pipes and a poorly documented backfill. Data was acquired using two different sources, which are—Source (1) betsy seisgun, and Source (2) thumper (weight drop). Overall, all the VS models show anomalous structure in the location of the backfill with velocity increase of ~ 400 m/s except the VS from source 2 Love wave (~ 300 m/s). On the other hand, the western pipe also presents a common anomalous zone with elevated velocity within a background velocity of 200 m/s. Although the eastern pipe did not show any detectable anomalous characteristics, still the combination of all the VS models resolved the backfilled area and the western pipe indicating that comparable VS models derived from various data can be effectively applied for void detection.