找回密碼
 To register

QQ登錄

只需一步,快速開(kāi)始

掃一掃,訪問(wèn)微社區(qū)

打印 上一主題 下一主題

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

[復(fù)制鏈接]
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
 關(guān)于派博傳思  派博傳思旗下網(wǎng)站  友情鏈接
派博傳思介紹 公司地理位置 論文服務(wù)流程 影響因子官網(wǎng) 吾愛(ài)論文網(wǎng) 大講堂 北京大學(xué) Oxford Uni. Harvard Uni.
發(fā)展歷史沿革 期刊點(diǎn)評(píng) 投稿經(jīng)驗(yàn)總結(jié) SCIENCEGARD IMPACTFACTOR 派博系數(shù) 清華大學(xué) Yale Uni. Stanford Uni.
QQ|Archiver|手機(jī)版|小黑屋| 派博傳思國(guó)際 ( 京公網(wǎng)安備110108008328) GMT+8, 2025-10-13 03:54
Copyright © 2001-2015 派博傳思   京公網(wǎng)安備110108008328 版權(quán)所有 All rights reserved
快速回復(fù) 返回頂部 返回列表
海丰县| 东方市| 太原市| 浏阳市| 平度市| 兴海县| 洛南县| 漯河市| 策勒县| 青神县| 淮阳县| 张家川| 攀枝花市| 五河县| 上犹县| 乳源| 佛冈县| 石棉县| 梅河口市| 六盘水市| 霍山县| 思南县| 芒康县| 密云县| 华蓥市| 游戏| 衡水市| 青岛市| 德安县| 临武县| 孟连| 鹿泉市| 乌拉特前旗| 海原县| 西藏| 温宿县| 建水县| 清新县| 肥城市| 阳江市| 七台河市|