56 citations · 244 across the 13 of their papers we have counts for
5 papers · 1 filter
Using explainability to design physics-aware CNNs for solving subsurface inverse problems
Jodie Crocker, Krishna Kumar, Brady R. Cox
We present a novel method of using explainability techniques to design physics-aware neural networks. We demonstrate our approach by developing a convolutional neural network (CNN)…
DAS for 2D MASW Imaging: A Case Study on the Benefits of Flexible Sub-Array Processing
Michael B. S. Yust, Brady R. Cox, Joseph P. Vantassel +1
Distributed acoustic sensing (DAS) is a relatively new technology for recording stress wave propagation, with promising applications in both engineering and geophysics. DAS's abili…
Mapping Depth to Bedrock, Shear Stiffness, and Fundamental Site Period at CentrePort, Wellington using Surface Wave Methods: Implications for Local Seismic Site Amplification
Joseph P. Vantassel, Brady R. Cox, Liam Wotherspoon +1
Wellington's port (CentrePort) experienced significant damage from the 7.8 Kaikōura earthquake as a result of soil liquefaction, lateral spreading, and shaking-induced damage…
A Frequency-Velocity CNN for Developing Near-Surface 2D Vs Images from Linear-Array, Active-Source Wavefield Measurements
Aser Abbas, Joseph P. Vantassel, Brady R. Cox +2
This paper presents a frequency-velocity convolutional neural network (CNN) for rapid, non-invasive 2D shear wave velocity (Vs) imaging of near-surface geo-materials. Operating in…
Extracting High-Resolution, Multi-Mode Surface Wave Dispersion Data from Distributed Acoustic Sensing Measurements using the Multichannel Analysis of Surface Waves
Joseph P. Vantassel, Brady R. Cox, Peter G. Hubbard +1
We rigorously assess the potential for extracting high-resolution, multi-mode surface wave dispersion data from distributed acoustic sensing (DAS) measurements using active-source…