Characterization of Horizontal Fractures in Shale Gas Reservoirs Using a Rock-Physics-Based Method Integrated With SA-PSO Algorithm and CNN

Zhang, Xiaodong; Guo, Zhiqi; Liu, Cai

doi:10.1109/tgrs.2024.3472057

IEEE Trans. Geosci. Remote Sensing

2024

DOI: 10.1109/tgrs.2024.3472057

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Characterization of Horizontal Fractures in Shale Gas Reservoirs Using a Rock-Physics-Based Method Integrated With SA-PSO Algorithm and CNN

Xiaodong Zhang,

Zhiqi Guo,

Cai Liu

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Cited by 2 publications

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Deep-Learning for Change Detection Using Multi-Modal Fusion of Remote Sensing Images: A Review

Saidi,

Idbraim,

Karmoude

et al. 2024

Remote Sensing

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Remote sensing images provide a valuable way to observe the Earth’s surface and identify objects from a satellite or airborne perspective. Researchers can gain a more comprehensive understanding of the Earth’s surface by using a variety of heterogeneous data sources, including multispectral, hyperspectral, radar, and multitemporal imagery. This abundance of different information over a specified area offers an opportunity to significantly improve change detection tasks by merging or fusing these sources. This review explores the application of deep learning for change detection in remote sensing imagery, encompassing both homogeneous and heterogeneous scenes. It delves into publicly available datasets specifically designed for this task, analyzes selected deep learning models employed for change detection, and explores current challenges and trends in the field, concluding with a look towards potential future developments.

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Characterization of Horizontal Fractures in Shale Gas Reservoirs Using a Rock-Physics-Based Method Integrated With SA-PSO Algorithm and CNN

Cited by 2 publications

References 54 publications

Satellite retrieval of oceanic particulate organic carbon: Towards an accurate and seamless dataset for the global ocean

Satellite retrieval of oceanic particulate organic carbon: Towards an accurate and seamless dataset for the global ocean

Deep-Learning for Change Detection Using Multi-Modal Fusion of Remote Sensing Images: A Review

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