國立高雄大學圖資館 |

語系: 繁體中文

說明(常見問題)

圖資館首頁

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Quantitative geosciencesdata analyti...

Ma, Y. Z.

Quantitative geosciencesdata analytics, geostatistics, reservoir characterization and modeling /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Quantitative geosciencesby Y. Z. Ma.
其他題名:	data analytics, geostatistics, reservoir characterization and modeling /
作者:	Ma, Y. Z.
出版者:	Cham :Springer International Publishing :2019.
面頁冊數:	xxv, 640 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
標題:	Earth sciences.
電子資源:	https://doi.org/10.1007/978-3-030-17860-4
ISBN:	9783030178604$q(electronic bk.)

Quantitative geosciencesdata analytics, geostatistics, reservoir characterization and modeling /
Ma, Y. Z.

Quantitative geosciencesdata analytics, geostatistics, reservoir characterization and modeling /[electronic resource] :by Y. Z. Ma. - Cham :Springer International Publishing :2019. - xxv, 640 p. :ill., digital ;24 cm.

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$q(electronic bk.)

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

196069
Earth sciences.

LC Class. No.: QE26.3 / .M399 2019

Dewey Class. No.: 550

Quantitative geosciencesdata analytics, geostatistics, reservoir characterization and modeling /
LDR:03758nmm a2200325 a 4500 001 563837
003 DE-He213
005 20191203155659.0
006 m d
007 cr nn 008maaau
008 200311s2019 gw s 0 eng d
020 $a 9783030178604$q(electronic bk.)
020 $a 9783030178598$q(paper)
024 7 $a 10.1007/978-3-030-17860-4 $2 doi
035 $a 978-3-030-17860-4
040 $a GP $c GP
041 0 $a eng
050 4 $a QE26.3 $b .M399 2019
072 7 $a THF $2 bicssc
072 7 $a SCI024000 $2 bisacsh
072 7 $a THF $2 thema
082 0 4 $a 550 $2 23
090 $a QE26.3 $b .M111 2019
100 1 $a Ma, Y. Z. $3 849544
245 1 0 $a Quantitative geosciences $h [electronic resource] : $b data analytics, geostatistics, reservoir characterization and modeling / $c by Y. Z. Ma.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2019.
300 $a xxv, 640 p. : $b ill., digital ; $c 24 cm.
505 0 $a 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.
520 $a 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.
650 0 $a Earth sciences. $3 196069
650 0 $a Quantitative research. $3 367894
650 1 4 $a Fossil Fuels (incl. Carbon Capture) $3 515750
650 2 4 $a Quantitative Geology. $3 286724
650 2 4 $a Geotechnical Engineering & Applied Earth Sciences. $3 542182
650 2 4 $a Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences. $3 348605
650 2 4 $a Operations Research/Decision Theory. $3 273963
650 2 4 $a Geophysics/Geodesy. $3 274000
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer eBooks
856 4 0 $u https://doi.org/10.1007/978-3-030-17860-4
950 $a Energy (Springer-40367)