Zobrazeno 1 - 3
of 3
pro vyhledávání: '"Mads Christian Lund Lorentzen"'
Publikováno v:
Lorentzen, M, Bredesen, K, Mosegaard, K & Nielsen, L 2022, ' Estimation of shear sonic logs in the heterogeneous and fractured Lower Cretaceous of the Danish North Sea using supervised learning ', Geophysical Prospecting, vol. 70, no. 8, pp. 1410-1431 . https://doi.org/10.1111/1365-2478.13252
Shear wave velocity information is valuable in many aspects of seismic exploration and characterization of reservoirs. However, shear wave logs are not always available in the interval of interest due to cost and time-saving purposes. In this study,
Autor:
Lars Hjelm, Henrik Vosgerau, Florian Walther Harald Smit, Carsten Møller Nielsen, Ulrik Gregersen, Rasmus Rasmussen, Kenneth Bredesen, Mads Christian Lund Lorentzen, Finn Mortanson Mørk, Bodil Wesenberg Lauridsen, Gunver Krarup Pedersen, Lars Henrik Nielsen, Anders Mathiesen, Shahjahan Laghari, Lars Elmer Kristensen, Emma Sheldon, Trine Dahl-Jensen, Karen Dybkjær, Christian Alonzo Hidalgo, Lasse Martin Rasmussen
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ef31a9fdf3ced301a302f817150b849b
Autor:
Klaus Mosegaard, Mads Christian Lund Lorentzen, Kenneth Bredesen, Lars Nielsen, Florian Walther Harald Smit, Torsten Hundebøl Hansen
Publikováno v:
Lorentzen, M C L, Bredesen, K, Smit, F W H, Hansen, T H, Nielsen, L & Mosegaard, K 2022, ' Mapping Cretaceous faults using a convolutional neural network-A field example from the Danish North Sea ', Bulletin of the Geological Society of Denmark, vol. 71, pp. 31-50 . https://doi.org/10.37570/bgsd-2022-71-03
Lorentzen, M C L, Bredesen, K, Smit, F W H, Hansen, T H, Nielsen, L & Mosegaard, K 2022, ' Mapping Cretaceous faults using a convolutional neural network – A field example from the Danish North Sea ', Bulletin of the Geological Society of Denmark, vol. 71, pp. 31-50 . https://doi.org/10.37570/bgsd-2022-71-03
Lorentzen, M C L, Bredesen, K, Smit, F W H, Hansen, T H, Nielsen, L & Mosegaard, K 2022, ' Mapping Cretaceous faults using a convolutional neural network – A field example from the Danish North Sea ', Bulletin of the Geological Society of Denmark, vol. 71, pp. 31-50 . https://doi.org/10.37570/bgsd-2022-71-03
The mapping of faults provides essential information on many aspects of seismic exploration, characterisation of reservoirs for compartmentalisation and cap-rock integrity. However, manual interpretation of faults from seismic data is time-consuming
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8d6aea73a0110343c88d944683dc5629
https://curis.ku.dk/portal/da/publications/mapping-cretaceous-faults-using-a-convolutional-neural-network--a-field-example-from-the-danish-north-sea(11d43fae-7c63-4e56-a428-09a5d79f886f).html
https://curis.ku.dk/portal/da/publications/mapping-cretaceous-faults-using-a-convolutional-neural-network--a-field-example-from-the-danish-north-sea(11d43fae-7c63-4e56-a428-09a5d79f886f).html