| 书目名称 | Quantitative Geosciences: Data Analytics, Geostatistics, Reservoir Characterization and Modeling | | 编辑 | Y. Z. Ma | | 视频video | | | 概述 | Presents a unique fusion of multidisciplinary geosciences: geology, petrophysics, geophysics, geostatistics and integrated data analytics.Emphasizes the integration of descriptive geology and quantita | | 图书封面 |  | | 描述 | Earth science is becoming increasingly quantitative in the digital age. Quantification of geoscience and engineering problems underpins many of the applications of big data and artificial intelligence. This book presents quantitative geosciences in three parts. Part 1 presents data analytics using probability, statistical and machine-learning methods. Part 2 covers reservoir characterization using several geoscience disciplines: including geology, geophysics, petrophysics and geostatistics. Part 3 treats reservoir modeling, resource evaluation and uncertainty analysis using integrated geoscience, engineering and geostatistical methods. As the petroleum industry is heading towards operating oil fields digitally, a multidisciplinary skillset is a must for geoscientists who need to use data analytics to resolve inconsistencies in various sources of data, model reservoir properties, evaluate uncertainties, and quantify risk for decision making. This book intends to serve as a bridge for advancing the multidisciplinary integration for digital fields. The goal is to move beyond using quantitative methods individually to an integrated descriptive-quantitative analysis. In big data, everyt | | 出版日期 | Book 2019 | | 关键词 | Reservoir Modeling; Data Analytics for E&P; Reservoir Uncertainty Analysis; Petroleum Geostatistics; Res | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-030-17860-4 | | isbn_softcover | 978-3-030-17862-8 | | isbn_ebook | 978-3-030-17860-4 | | copyright | Springer Nature Switzerland AG 2019 |
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发表于 2025-3-21 17:15:32
