A Surface-Wave Inversion Method Based on FHLV Loss Function in LSTM-Reference-Cited by-同舟云学术

A Surface-Wave Inversion Method Based on FHLV Loss Function in LSTM

Published:2022 Issue: Volume:19 Page:1-5
ISSN:1545-598X
Container-title:IEEE Geoscience and Remote Sensing Letters
language:
Short-container-title:IEEE Geosci. Remote Sensing Lett.

Author:

Wu Yinghe¹^ORCID,Pan Shulin²^ORCID,Chen Jingyi³,Song Guojie⁴,Gou Qiyong⁵

Affiliation:

1. School of Geoscience and Technology, Southwest Petroleum University, Chengdu, China

2. State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation and the School of Geoscience and Technology, Southwest Petroleum University, Chengdu, China

3. Department of Geosciences, Seismic Anisotropy Group, University of Tulsa, Tulsa, OK, USA

4. School of Science, Southwest Petroleum University, Chengdu, China

5. Shale Gas Research Institute, Petro China Southwest Oil and Gasfield Company, Chengdu, China

Funder

Technology Cooperation Project of the CNPC-SWPU Innovation Alliance

Central Government Funds of Guiding Local Scientific and Technological Development

Nanchong Municipal Government-Universities Scientific Cooperation Project

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Geotechnical Engineering and Engineering Geology

Link

http://xplorestaging.ieee.org/ielx7/8859/9651998/09810261.pdf?arnumber=9810261

Reference20 articles.

1. Automatic stacking-velocity estimation using similarity-weighted clustering

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3. Near-surface velocity analysis for single sensor data: An integrated workflow using surface waves;alyousuf;Proc AI Struct -Regularized Inversion 88th Annu Int Meeting SEG Expanded,2018

4. Extracting Dispersion Curves From Ambient Noise Correlations Using Deep Learning

5. Deep Learning for Extracting Dispersion Curves

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