Seismic multi-attribute approach using visual saliency for subtle fault visualization-Reference-Cited by-同舟云学术

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Seismic multi-attribute approach using visual saliency for subtle fault visualization

Published:2022-11-23 Issue: Volume: Page:1-8
ISSN:0812-3985
Container-title:Exploration Geophysics
language:en
Short-container-title:Exploration Geophysics

Author:

Singh Gagandeep¹,Mahadik Rahul²,Mohanty William K.¹,Routray Aurobinda²,Datta Deepan³,Panda Sanket Smarak²

Affiliation:

1. Department of Geology & Geophysics, Indian Institute of Technology, Kharagpur, West Bengal, India

2. Department of Electrical Engineering, Indian Institute of Technology, Kharagpur, West Bengal, India

3. Department of Advanced Technology Development Centre, Indian Institute of Technology, Kharagpur, West Bengal, India

Publisher

Informa UK Limited

Subject

Geology,Geophysics

Link

https://www.tandfonline.com/doi/pdf/10.1080/08123985.2022.2144722

Reference25 articles.

1. Multi-attribute ant-tracking and neural network for fault detection: a case study of an Iranian oilfield

2. State-of-the-Art in Visual Attention Modeling

3. Brouwer, F., and A. Huck. 2011. An integrated workflow to optimize discontinuity attributes for the imaging of faults. Attributes: New views on seismic imaging – Their use in exploration and production. GCSSEPM, 31st Annual Conference Publication, 533.

4. Chopra, S., and K.J. Marfurt. 2007. Seismic attributes for prospect identification and reservoir characterization. Society of Exploration Geophysicists and European Association of Geo-Scientists and Engineers.

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