Physics-driven deep-learning inversion with application to transient electromagnetics
Machine learning, and specifically deep-learning (DL) techniques applied to geophysical
inverse problems, is an attractive subject, which has promising potential and, at the same …
inverse problems, is an attractive subject, which has promising potential and, at the same …
Deep learning for 3-D magnetic inversion
The difficulty of 3-D magnetic inversion is to use 2-D magnetic anomaly data to obtain 3-D
magnetic susceptibility structure. The contribution of the underground medium to the …
magnetic susceptibility structure. The contribution of the underground medium to the …
Real‐time deep‐learning inversion of seismic full waveform data for CO2 saturation and uncertainty in geological carbon storage monitoring
Deep‐learning inversion has recently drawn attention in geological carbon storage research
due to its potential of imaging and monitoring carbon storage in real time, significantly …
due to its potential of imaging and monitoring carbon storage in real time, significantly …
Coupled physics-deep learning inversion
Application of machine learning (ML) or deep learning (DL) to geophysical data inversion is
a growing topic of interest. Opportunities are in the areas of enhanced efficiency, resolution …
a growing topic of interest. Opportunities are in the areas of enhanced efficiency, resolution …
Deep learning joint inversion of seismic and electromagnetic data for salt reconstruction
Y Sun, B Denel, N Daril, L Evano… - SEG Technical …, 2020 - library.seg.org
Depth imaging projects dedicated to hydrocarbon exploration or field development rely
heavily on velocity model building. When salt bodies are present, their accurate delineation …
heavily on velocity model building. When salt bodies are present, their accurate delineation …
Self-supervised, active learning seismic full-waveform inversion
ABSTRACT A novel recursive, self-supervised machine-learning (ML) inversion scheme is
developed. It is applied for fast and accurate full-waveform inversion of land seismic data …
developed. It is applied for fast and accurate full-waveform inversion of land seismic data …
Electrical imaging of hydraulic fracturing fluid using steel-cased wells and a deep-learning method
Steel-cased wells used as long electrodes (LEs) in a surface-electric or electromagnetic
survey can enhance anomalous signals from deep hydraulic fracturing zones filled by …
survey can enhance anomalous signals from deep hydraulic fracturing zones filled by …
Deep learning inversion of gravity data for detection of CO2 plumes in overlying aquifers
We developed an effective U-Net based deep learning (DL) model for inversion of surface
gravity data on a rectangular grid to predict 2-D high-resolution subsurface CO 2 distribution …
gravity data on a rectangular grid to predict 2-D high-resolution subsurface CO 2 distribution …
Modeling extra-deep electromagnetic logs using a deep neural network
Modern geosteering is heavily dependent on real-time interpretation of deep
electromagnetic (EM) measurements. We have developed a methodology to construct a …
electromagnetic (EM) measurements. We have developed a methodology to construct a …
Deep learning multiphysics network for imaging CO2 saturation and estimating uncertainty in geological carbon storage
Multiphysics inversion exploits different types of geophysical data that often complement
each other and aims to improve overall imaging resolution and reduce uncertainties in …
each other and aims to improve overall imaging resolution and reduce uncertainties in …