TY - GEN
T1 - Automatic salt detection with machine learning
AU - Ma, J.
AU - Yang, F.
AU - Wang, W.
N1 - Publisher Copyright:
© 2018 Society of Petroleum Engineers. All rights reserved.
PY - 2018
Y1 - 2018
N2 - We introduce a novel method to estimate the shapes and positions of salt bodies directly from pre-stack seismic data using a modified fully convolutional network, which we use to perform both data transformation and semantic segmentation. Multiple shots are fed into the network as different channels to increase data redundancy. We generate synthetic data to train the network, and tests show satisfactory results.
AB - We introduce a novel method to estimate the shapes and positions of salt bodies directly from pre-stack seismic data using a modified fully convolutional network, which we use to perform both data transformation and semantic segmentation. Multiple shots are fed into the network as different channels to increase data redundancy. We generate synthetic data to train the network, and tests show satisfactory results.
UR - https://www.scopus.com/pages/publications/85083936568
M3 - 会议稿件
AN - SCOPUS:85083936568
T3 - 80th EAGE Conference and Exhibition 2018: Opportunities Presented by the Energy Transition
BT - 80th EAGE Conference and Exhibition 2018
PB - European Association of Geoscientists and Engineers, EAGE
T2 - 80th EAGE Conference and Exhibition 2018: Opportunities Presented by the Energy Transition
Y2 - 11 June 2018 through 14 June 2018
ER -