7 citations · 26 across the 15 of their papers we have counts for
10 papers · 1 filter
: Multi-parameter Benchmark Datasets for Elastic Full Waveform Inversion of Geophysical Properties
Shihang Feng, Hanchen Wang, Chengyuan Deng +6
Elastic geophysical properties (such as P- and S-wave velocities) are of great importance to various subsurface applications like CO sequestration and energy exploration (e.g.,…
Auto-Linear Phenomenon in Subsurface Imaging
Yinan Feng, Yinpeng Chen, Peng Jin +3
Subsurface imaging involves solving full waveform inversion (FWI) to predict geophysical properties from measurements. This problem can be reframed as an image-to-image translation…
Enhanced prediction accuracy with uncertainty quantification in monitoring CO2 sequestration using convolutional neural networks
Yanhua Liu, Xitong Zhang, Ilya Tsvankin +1
Monitoring changes inside a reservoir in real time is crucial for the success of CO2 injection and long-term storage. Machine learning (ML) is well-suited for real-time CO2 monitor…
Extremely Weak Supervision Inversion of Multi-physical Properties
Shihang Feng, Peng Jin, Xitong Zhang +4
Multi-physical inversion plays a critical role in geophysics. It has been widely used to infer various physical properties~(such as velocity and conductivity). Among those inversio…
Connect the Dots: In Situ 4D Seismic Monitoring of CO2 Storage with Spatio-temporal CNNs
Shihang Feng, Xitong Zhang, Brendt Wohlberg +2
4D seismic imaging has been widely used in CO sequestration projects to monitor the fluid flow in the volumetric subsurface region that is not sampled by wells. Ideally, real-t…
Multiscale Data-driven Seismic Full-waveform Inversion with Field Data Study
Shihang Feng, Youzuo Lin, Brendt Wohlberg
Seismic full-waveform inversion (FWI), which uses iterative methods to estimate high-resolution subsurface models from seismograms, is a powerful imaging technique in exploration g…