Characterizing Subsurface Structures From Hard and Soft Data With Multiple‐Condition Fusion Neural Network

Characterizing Subsurface Structures From Hard and Soft Data With Multiple‐Condition Fusion Neural Network

Abstract Accurately inferring realistic subsurface structures poses a considerable challenge due to the impact of morphology on flow and transport behaviors. Traditional subsurface characterization relies on two primary types of data: hard data, derived from direct subsurface measurements, and soft...

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Bibliographic Details
Main Authors: Zhesi Cui, Qiyu Chen, Jian Luo, Xiaogang Ma, Gang Liu
Format: Article
Language:English
Published: Wiley 2024-11-01
Series:Water Resources Research
Subjects:
hydrogeological modeling
deep learning
multiple data fusion
subsurface characterization
Online Access:https://doi.org/10.1029/2024WR038170
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