961 to 970 of 1,312 Results
Plain Text - 3.5 MB -
MD5: bf15082a4f8b254c3ecc7a82c2f51025
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MS Excel Spreadsheet - 1.0 MB -
MD5: d9ba00472acffe52fb7fa8e82e458486
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Adobe PDF - 171.9 KB -
MD5: 2df1ddd0781a2abb2d76938c8735e7e3
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May 20, 2022 -
Supporting Data for: Direct multi-modal inversion of geophysical logs using deep learning
Markdown Text - 4.7 KB -
MD5: 44eb6bf27b67c4aab0e24989a3231e50
Readme file |
May 20, 2022 -
Supporting Data for: Direct multi-modal inversion of geophysical logs using deep learning
Plain Text - 4.7 KB -
MD5: 44eb6bf27b67c4aab0e24989a3231e50
readme file |
May 20, 2022 -
Supporting Data for: Direct multi-modal inversion of geophysical logs using deep learning
Python Source Code - 5.1 KB -
MD5: 8f59527c03a6460aae2a377812b9ca64
Python code that can be used for generation of realizations |
May 20, 2022 -
Supporting Data for: Direct multi-modal inversion of geophysical logs using deep learning
Plain Text - 19.7 KB -
MD5: bb082061306cc1dc0afcd128f972d344
CC-BY-SA-4.0 license |
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 |