Seismic Foundation Model (SFM): a next generation deep learning model in geophysics

H Sheng, X Wu, X Si, J Li, S Zhang, X Duan - Geophysics, 2024 - library.seg.org
While computer science has seen remarkable advancements in foundation models, they
remain underexplored in geoscience. Addressing this gap, we introduce a workflow to …

Machine Learning Developments and Applications in Solid‐Earth Geosciences: Fad or Future?

YE Li, D O'malley, G Beroza, A Curtis… - … Research: Solid Earth, 2023 - Wiley Online Library
After decades of low but continuing activity, applications of machine learning (ML) in solid
Earth geoscience have exploded in popularity. This special collection provides a snapshot …

Joint inversion of geophysical data for geologic carbon sequestration monitoring: A differentiable physics‐informed neural network model

M Liu, D Vashisth, D Grana… - Journal of Geophysical …, 2023 - Wiley Online Library
Geophysical monitoring of geologic carbon sequestration is critical for risk assessment
during and after carbon dioxide (CO2) injection. Integration of multiple geophysical …

[HTML][HTML] Evaluating geophysical monitoring strategies for a CO2 storage project

S Anyosa, J Eidsvik, D Grana - Computers & Geosciences, 2024 - Elsevier
Geophysical monitoring of CO 2 storage projects enables informed decision making of
injection strategies. When monitoring projects are designed, decisions should be made …

Time-lapse seismic inversion for CO2 saturation with SeisCO2Net: An application to Frio-II site

ZX Leong, T Zhu, AY Sun - International Journal of Greenhouse Gas …, 2024 - Elsevier
Seismic monitoring of geological CO 2 storage (GCS) involves highly nonlinear seismic
inversion and petrophysical inversion, making it challenging to estimate CO 2 volume …

Deep learning for characterizing CO2 migration in time-lapse seismic images

H Sheng, X Wu, X Sun, L Wu - Fuel, 2023 - Elsevier
Abstract Time-lapse (or 4-D) seismic data play an important role in monitoring the spatial CO
2 distribution during and after the injection period. However, traditional interpretation or …

[HTML][HTML] Characterization of petrophysical and seismic properties for CO2 storage with sensitivity analysis

YJ Dong, Y Shen, K Guo, XQ Wu, Q Mao, WY Sun… - Petroleum Science, 2024 - Elsevier
Saline aquifers are considered as highly favored reservoirs for CO 2 sequestration due to
their favorable properties. Understanding the impact of saline aquifer properties on the …

Geological reservoir characterization tasks based on computer vision techniques

L da Silva Bomfim, MVT Soares, AC Vidal… - Marine and Petroleum …, 2024 - Elsevier
Reservoir characterization is of great importance in oil and gas exploration and production.
To automate and improve the procedures involved in this task, several approaches in the …

Assimilation of geophysics-derived spatial data for model calibration in geologic co2 sequestration

B Chen, MM Morales, Z Ma, Q Kang, RJ Pawar - SPE Journal, 2024 - onepetro.org
Uncertainty in geological models usually leads to large uncertainty in the predictions of risk-
related system properties and/or risk metrics (eg, CO 2 plumes and CO 2/brine leakage …

Reservoir multiparameter prediction method based on deep learning for CO2 geologic storage

D Li, S Peng, Y Guo, Y Lu, X Cui, W Du - Geophysics, 2023 - library.seg.org
Time-lapse seismic difference refers to the comprehensive response of fluid saturation, pore
pressure, and porosity. However, the contribution of different parameters to the seismic …