1,621 to 1,630 of 12,879 Results
May 20, 2022 -
Supporting Data for: Direct multi-modal inversion of geophysical logs using deep learning
Python Source Code - 1.2 KB -
MD5: a8803f4a86664b8a22151a0d28926188
Python script for conversion from numpy to nc files, which are used for deposition |
May 20, 2022 -
Supporting Data for: Direct multi-modal inversion of geophysical logs using deep learning
Network Common Data Form - 9.2 MB -
MD5: ceb18211f836ff0eb87db0f7d449a04e
The testing dataset containing the realizations each consisting of series of angles, the stratigraphic vertical depths (SVD), and the vertical section (VS) coordinates of stratigraphic curves |
May 20, 2022 -
Supporting Data for: Direct multi-modal inversion of geophysical logs using deep learning
Network Common Data Form - 457.8 MB -
MD5: 4c1896f602b3feca1810047309d41c52
The training dataset containing the realizations each consisting of a series of angles, the stratigraphic vertical depths (SVD), and the vertical section (VS) coordinates of stratigraphic curves |
May 20, 2022 -
Supporting Data for: Direct multi-modal inversion of geophysical logs using deep learning
Python Source Code - 5.4 KB -
MD5: 8820b78733145a9149eb87620aee4d77
Python script to generate the dataset |
May 20, 2022 -
Supporting Data for: Direct multi-modal inversion of geophysical logs using deep learning
PNG Image - 158.3 KB -
MD5: 18ad687e904961ad85b2d1206d4e0319
Example of generated stratigraphic curves |
May 18, 2022 - University of Bergen
Saether, Mathias M., 2022, "Replication data for: Compressional wave phase velocity measurements during hydrate growth in partially and fully water saturated sandstone", https://doi.org/10.18710/GDT85X, DataverseNO, V1
This data set contains the raw data from experiments where the compressional wave velocity has been measured in eight methane hydrate bearing Bentheim sandstones. One experiment is conducted for each sandstone. In this document, data for 8 experiments are given. The hydrate satur... |
Plain Text - 6.6 KB -
MD5: c38eb51d654b31bbd519d44b0dbeaf5f
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Network Common Data Form - 13.6 KB -
MD5: 83b0789ffa752f0c369754e894a4eeb1
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Network Common Data Form - 291.4 MB -
MD5: c2edb32769cb54b101f2156a43046045
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Network Common Data Form - 291.4 MB -
MD5: a773f82b8c1da74bc50884e1dc2a8c7d
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