Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Ruoshui Zhou"'
Publikováno v:
Artificial Intelligence in Geosciences, Vol 1, Iss , Pp 31-35 (2020)
Fault interpretation plays a critical role in understanding the crustal development and exploring the subsurface reservoirs such as gas and oil. Recently, significant advances have been made towards fault semantic segmentation using deep learning. Ho
Externí odkaz:
https://doaj.org/article/8e865be363ed446caaaad57573e59060
Publikováno v:
IEEE Transactions on Geoscience and Remote Sensing. 61:1-16
Publikováno v:
GEOPHYSICS. 87:IM189-IM206
Fault surface extraction plays a vital role in structural interpretation and structural modeling, which can enhance our understanding of geologic structures. Significant effort has been invested in fault surface extraction in the past few years. Thes
Publikováno v:
Acta Geophysica. 69:2187-2203
Fault detection of seismic data is a key step in seismic data interpretation. Many techniques have got good seismic fault detection results by supervised deep learning, which assumes that the training data and the prediction data have a similar data
Publikováno v:
Geophysical Prospecting. 69:1218-1234
Significant advances have been made towards fault detection using deep learning. However, the fault labelling of seismic data requires great human effort. The resulting small sample problem makes traditional deep learning methods difficult to achieve
Publikováno v:
Artificial Intelligence in Geosciences. 1:31-35
Fault interpretation plays a critical role in understanding the crustal development and exploring the subsurface reservoirs such as gas and oil. Recently, significant advances have been made towards fault semantic segmentation using deep learning. Ho
Publikováno v:
Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering ISBN: 9783030980047
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::984bb1e5182b2b13e52d40c931d10c7f
https://doi.org/10.1007/978-3-030-98005-4_23
https://doi.org/10.1007/978-3-030-98005-4_23
Publikováno v:
SEG Technical Program Expanded Abstracts 2019.