Waveform Spectrums and Inversion Algorithms Produce More Accurate Data Compared to Available Methods
This method and device for sinkhole detection uses multiple waveform spectrums to characterize various subterranean properties that contribute to sinkhole formation, without using boring or other intrusive tests. Sinkholes occur worldwide and can cause millions of dollars in property damage as well as endanger human lives. Subsurface conditions such as voids in rock, pockets of air, and running water are all anomalies that cause sinkholes to form. Early detection and repair can take place before dangerous movements of the soil or structure develop. Existing methods of detection, including micro-gravity, electromagnetic resistivity, radar, and seismic refraction all have notable limitations in identifying and quantifying sinkholes. Researchers at the University of Florida have developed a non-destructive, two-stage sinkhole detection method and device that overcomes those limitations. By employing seismic wave fields associated with geometry and material to determine global genetic inversion and deterministic inversion, researchers are able to capture geological or manmade anomalies or the presence of sinkholes within the domain. The genetic algorithm used to evaluate the data, capable of capturing stiff over soft layer, gradation, as well as partial or fully saturated soil and rock conditions, has been tested successfully up to 100 unknowns.
Seismic wave fields and algorithm detect potential sinkhole anomalies and subterranean conditions
- Detects subsurface anomalies in a variety of conditions, increasing the effectiveness in locating and characterizing sinkholes otherwise difficult to identify
- Locates not only geological anomalies but also manmade anomalies, enabling the identification of unknown foundations
- Makes precise measurements right at the surface, eliminating cost of destructive boring or other intrusive methods to identify sinkhole activity
This method and device uses full seismic waves that are much more sensitive to anomalies and produces more accurate data compared to radar and seismic refraction data. The first inversion in the process is a general global genetic algorithm using site data to obtain the general information of soil and rock properties of the domain. The second inversion uses a deterministic algorithm that uses the global inversion results to provide detailed information of anomalies or sinkholes. Current tests have indicated that the two-stage full seismic wave technique is effective at detecting anomalies in Florida soil, comprising medium dense, fine, and silty sand over limestone bedrock, optimal conditions for sinkhole formation. Further testing and investment can develop this technology into a comprehensive commercialized package for sinkhole detection.