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Titlebook: Machine Learning in the Oil and Gas Industry; Including Geoscience Yogendra Narayan Pandey,Ayush Rastogi,Luigi Sapute Book 2020 Yogendra Na

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樓主: crusade
21#
發(fā)表于 2025-3-25 03:54:22 | 只看該作者
Reservoir Engineering,lgorithms have provided the industry with an additional mechanism to solve problems and gain insights. Machine learning applications in the oilfield are observed in drilling engineering for ROP optimization [1], differential pipe sticking [2], identification of sweet spots [3], petrophysical modelin
22#
發(fā)表于 2025-3-25 08:37:25 | 只看該作者
23#
發(fā)表于 2025-3-25 14:11:58 | 只看該作者
Opportunities, Challenges, and Future Trends, of the shifting of many manufacturing sites to Africa, South Asia, and India, non-OECD countries will experience two to four times more growth than OECD countries [1]. The oil and gas industry will continue to exhibit an era of growth. More than half of the global energy demand in 2018 was supplied
24#
發(fā)表于 2025-3-25 17:59:07 | 只看該作者
25#
發(fā)表于 2025-3-25 20:38:21 | 只看該作者
Yogendra Narayan Pandey,Ayush Rastogi,Luigi SaputeContains real-life oil and gas company examples, based on data sets from those industries.Covers supervised and unsupervised learning.Covers diverse industry topics, including geophysics, geological m
26#
發(fā)表于 2025-3-26 02:25:13 | 只看該作者
27#
發(fā)表于 2025-3-26 06:39:46 | 只看該作者
28#
發(fā)表于 2025-3-26 11:49:06 | 只看該作者
Python Programming Primer,s. However, before you can implement those solutions, you need to learn how to code the applicable machine learning algorithms. This makes understanding a computer programming language necessary before diving into machine learning.
29#
發(fā)表于 2025-3-26 15:34:37 | 只看該作者
30#
發(fā)表于 2025-3-26 17:02:23 | 只看該作者
Book 2020as exploration and production life cycle in the context of data flow through the different stages of industry operations. This leads to a survey of some interesting problems, which are good candidates for applying machine and deep learning approaches. The initial chapters provide a primer on the Pyt
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