The paper presents a technique to invert two-dimensional (2D) full wavefields using simulated annealing and a finite-difference solution of the 2D elastic wave equation in the time-distance domain. The algorithm generates all possible wave types (body waves, surface waves, etc.) to simulate complex seismic wavefields and for comparison with observed data. Model runs with both synthetic and actual experimental data sets illustrate the capability of the inversion technique. The results from synthetic data demonstrate the potential of characterizing both low- and high-velocity layers in laterally inhomogeneous profiles, and the inversion results from actual data are consistent with the crosshole, standard penetration test N-value, and material log results. Based on the cases presented, the coupling of global optimization with full waveforms is computationally practical; the results presented herein required less than 1 day of computer time on a standard laptop computer.

We have developed a 3D elastic full-waveform inversion (FWI) method for geotechnical site characterization. The method is based on a solution of 3D elastic-wave equations for forward modeling to simulate wave propagation and a local optimization approach based on the adjoint-state method to update the model parameters. The staggered-grid finite-difference technique is used to solve the wave equations together with implementation of the perfectly matched layer condition for boundary truncation. Seismic wavefields are acquired from geophysical testing using sensors and sources located in uniform 2D grids on the ground surface, and they are then inverted for the extraction of 3D subsurface wave velocity structures. The capability of the presented FWI method is tested on synthetic and field data sets. The inversion results from synthetic data indicate the ability of characterizing laterally variable low- and high-velocity layers. Field experimental data were collected using 96 receivers and a propelled energy generator to induce seismic wave energy. The field data result indicates that the waveform analysis was able to delineate variable subsurface soil layers. The seismic inversion results are generally consistent with invasive standard penetration test N-values, including identification of a low-velocity zone.

Roadways are key components of the modern transportation system. Therefore, assessment of roadway subsidence is critical to the health and safety of the traveling public. Existing seismic refraction and waveform tomography methods can be used for subsidence evaluation; however, the data acquisition time is significant because they require multiple source impacts (shots) along a test line. To mitigate the negative impact caused by closing the traffic flow under seismic testing, a land-streamer seismic testing system and waveform analysis are developed. An existing 2D Gauss-Newton full-waveform inversion (FWI) method is extended for analysis of the land-streamer waveform data. The main advantage of using land-streamer waveform data is that geophones are not coupled to test materials and source-receiver offsets are fixed; thus, the whole test system can be moved along the roadway quickly for data acquisition. To demonstrate the effectiveness of land-streamer waveform data, the FWI method was tested on synthetic and field data sets. The synthetic result reveals that buried voids can be well-characterized by the land-streamer waveform analysis. Field data were collected on asphalt pavement using a 24 channel land streamer and a propelled energy generator to induce seismic wave energy. The test system was towed by a pickup truck along a roadway with an on-going subsidence (repaired sinkhole). The data were collected over 277.5 m distance at a 3 m interval, and the total data acquisition time was approximately 1 h. The field data result indicates that the waveform analysis was able to delineate low-velocity soil zones and laterally variable bedrock. The FWI results are also compared with multichannel analysis of surface wave (MASW) results. The 2D [ ] profiles from the FWI and MASW methods are consistent; however, the FWI method provides more detailed information ([ ] of [ ] cells) of low-velocity anomalies for assessment of roadway subsidence.

An application of two-dimensional (2D) time-domain full waveform tomography is presented to evaluate existing foundations using surface-based seismic wave fields. The full waveform inversion (FWI) technique is based on a finite-difference solution of 2D elastic wave equations and the Gauss–Newton inversion method. Both compression-wave (P-wave) and shear-wave (S-wave) velocities are inverted independently and simultaneously to increase the credibility of characterized profiles. The FWI technique was applied on both synthetic and real experimental data sets. Inverted results of synthetic data revealed that individual embedded foundation elements (piles) and soil between piles were distinguished. For real experimental data, seismic surface wave fields were measured next to two drilled shafts with a 1.2-m diameter and a 15-m length and then inverted by the FWI technique. The waveform analysis successfully profiled embedded shaft elements and subsurface soil stratigraphy, and shaft lengths of 15 m we...

A technique is presented to invert full waveforms using a genetic algorithm. The inversion scheme is based on a finite-difference solution of the 2-D elastic wave equation in the time-distance domain. The strength of this approach is the ability to generate all possible wave types (body waves and surface waves, etc.) and thus to simulate complex seismic wavefields that are then compared with observed data to infer subsurface properties. The capability of this inversion technique is tested with both synthetic and real experimental data sets. The inversion results from synthetic data show the ability of characterizing both low- and high-velocity layers, and the inversion results from real data are generally consistent with crosshole, SPT N-value, and material log results, including the identification of a buried low-velocity layer. Based upon the cases presented, coupling of global optimization with full waveforms is computationally practical, as the results presented herein were all achieved in about two hours of computer time on a standard laptop computer.