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Feasibility and Limitations of Void Detection Using Gravity Gradiometry
Detecting and characterizing near-surface voids is a long-standing problem in near-surface geophysics primarily because of the low signal-to-noise ratio due to the typically small sizes of these targets. Anticipated advances in gravity gradiometry instrumentation and data acquisition may provide the improved resolution required to address these targets. In this paper, we investigate void detection using simulated full tensor gravity gradiometry data. We show through numerical simulations that low-altitude gravity gradiometry can observe signals from voids well above the modern instrument noise level. We develop a practical detection algorithm to determine the tunnel orientation and its location in the subsurface. The algorithm first finds the tunnel orientation through a tensor rotation and then solves for the tunnel location in the subsurface based on the directional vectors obtained from the rotated tensor data. We use this algorithm to study the feasibility and limitations of the gravity gradiometry technique in void detection. We conclude that the method can be effective in many practical scenarios.
Feasibility and Limitations of Void Detection Using Gravity Gradiometry
Detecting and characterizing near-surface voids is a long-standing problem in near-surface geophysics primarily because of the low signal-to-noise ratio due to the typically small sizes of these targets. Anticipated advances in gravity gradiometry instrumentation and data acquisition may provide the improved resolution required to address these targets. In this paper, we investigate void detection using simulated full tensor gravity gradiometry data. We show through numerical simulations that low-altitude gravity gradiometry can observe signals from voids well above the modern instrument noise level. We develop a practical detection algorithm to determine the tunnel orientation and its location in the subsurface. The algorithm first finds the tunnel orientation through a tensor rotation and then solves for the tunnel location in the subsurface based on the directional vectors obtained from the rotated tensor data. We use this algorithm to study the feasibility and limitations of the gravity gradiometry technique in void detection. We conclude that the method can be effective in many practical scenarios.
Feasibility and Limitations of Void Detection Using Gravity Gradiometry
Li, Yaoguo (author) / Rim, Hyoungrea / McKenna, Jason R
2016
Article (Journal)
English
Local classification TIB:
770/3710/5670
BKL:
38.03
Methoden und Techniken der Geowissenschaften
/
74.41
Luftaufnahmen, Photogrammetrie
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