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Quantitative Geosciences: Data Analytics, Geostatistics, Reservoir Characterization and Modeling

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Quantitative Geosciences: Data Analytics, Geostatistics, Reservoir Characterization and Modeling/ by Y. Z. Ma.
作者:	Ma, Y. Z.
面頁冊數:	XXV, 640 p. 294 illus., 167 illus. in color.online resource. :
Contained By:	Springer Nature eBook
標題:	Fossil fuels. -
電子資源:	https://doi.org/10.1007/978-3-030-17860-4
ISBN:	9783030178604

Quantitative Geosciences: Data Analytics, Geostatistics, Reservoir Characterization and Modeling
Ma, Y. Z.

Quantitative Geosciences: Data Analytics, Geostatistics, Reservoir Characterization and Modeling[electronic resource] /by Y. Z. Ma. - 1st ed. 2019. - XXV, 640 p. 294 illus., 167 illus. in color.online resource.

Preface -- 1. Introduction and Overview -- Part 1: Reservoir Characterization -- 2. Essential Reservoir Geology and Multi-Scales of Petroleum Reservoir Heterogeneities -- 3. Introduction to Petrophysical Reservoir Characterization -- 4. Practical Seismic Reservoir Characterization -- 5. Statistical and Data Analytical Reservoir Characterization -- 6. Geostatistical Reservoir Characterization -- 7. Integrated Facies and Lithofacies Analysis, Identification and Classification -- Part 2: Geological and Reservoir Modeling -- 8. Constructing a Reservoir-Model Framework -- 9. Geostatistical Modeling Methods -- 10. Facies and Lithofacies Modeling -- 11. Porosity Modeling -- 12. Permeability Modeling -- 13. Fluid-Saturation Modeling -- 14. Uncertainty Analysis and Volumetrics Evaluation -- Part 3: Special and Advanced Topics -- 15. Naturally Fractured Reservoir Characterization and Modeling -- 16. Updating a Reservoir Model and Feedback Loop in Reservoir Modeling -- 17. Ranking Reservoir Models -- 18. Reservoir Model Upscaling, Simulation and Validation -- 19. Common and Uncommon Pitfalls in Integrated Reservoir Characterization and Modeling -- 20. Planning an Integrated Reservoir Characterization and Modeling Project -- 21. Towards a Fully Integrated Reservoir Characterization, Modeling and Uncertainty Analysis for Petroleum Resource Management and Field Development. .

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, everything tells us something, but nothing tells us everything. This book emphasizes the integrated, multidisciplinary solutions for practical problems in resource evaluation and field development.

ISBN: 9783030178604

Standard No.: 10.1007/978-3-030-17860-4doiSubjects--Topical Terms:

654433
Fossil fuels.

LC Class. No.: TJ163.13-163.25

Dewey Class. No.: 662.6

Quantitative Geosciences: Data Analytics, Geostatistics, Reservoir Characterization and Modeling
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