Fast 3D time-domain airborne EM forward modeling using random under-sampling

2021 ◽  
pp. 104357
Author(s):  
Wang Haoman ◽  
Liu Yunhe ◽  
Yin Changchun ◽  
Ren Xiuyan ◽  
Cao Jin ◽  
...  
2016 ◽  
Vol 134 ◽  
pp. 11-22 ◽  
Author(s):  
Changchun Yin ◽  
Yanfu Qi ◽  
Yunhe Liu ◽  
Jing Cai

2017 ◽  
Vol 70 (0) ◽  
pp. 69-79
Author(s):  
Hideki Mizunaga ◽  
Kiyotaka Ishinaga

Author(s):  
Yanfu Qi ◽  
Xiu Li ◽  
Changchun Yin ◽  
Huaiyuan Li ◽  
Zhipeng Qi ◽  
...  
Keyword(s):  

2016 ◽  
Vol 13 (4) ◽  
pp. 701-711 ◽  
Author(s):  
Yun-He Liu ◽  
Chang-Chun Yin ◽  
Xiu-Yan Ren ◽  
Chang-Kai Qiu
Keyword(s):  

2019 ◽  
Author(s):  
Yanfu Qi* ◽  
Xiu Li ◽  
Changchun Yin ◽  
Zhipeng Qi ◽  
Naiquan Sun ◽  
...  

Author(s):  
Xin Huang ◽  
Colin G. Farquharson ◽  
Changchun Yin ◽  
Xiaoyue Cao ◽  
Bo Zhang ◽  
...  

2017 ◽  
Vol 36 (12) ◽  
pp. 1033-1036 ◽  
Author(s):  
Mathias Louboutin ◽  
Philipp Witte ◽  
Michael Lange ◽  
Navjot Kukreja ◽  
Fabio Luporini ◽  
...  

Since its reintroduction by Pratt (1999) , full-waveform inversion (FWI) has gained a lot of attention in geophysical exploration because of its ability to build high-resolution velocity models more or less automatically in areas of complex geology. While there is an extensive and growing literature on the topic, publications focus mostly on technical aspects, making this topic inaccessible for a broader audience due to the lack of simple introductory resources for newcomers to computational geophysics. We will accomplish this by providing a hands-on walkthrough of FWI using Devito ( Lange et al., 2016 ), a system based on domain-specific languages that automatically generates code for time-domain finite differences.


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