Mathematical geoenergy : discovery, depletion, and renewal
Language: English Series: Geophysical monograph series; no. 241Publication details: Wiley New Jersey 2019; American Geophysical Union 2019 WashingtonDescription: viii, 365pISBN:- 9781119434290
- 333.79 P965m
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PK Kelkar Library, IIT Kanpur | General Stacks | 333.79 P965m (Browse shelf(Opens below)) | Available | A185563 |
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| 333.79 N42 New energy economy | 333.79 Op2c Operations research and environmental management | 333.79 P277 Patterns of energy use in developing countries | 333.79 P965m Mathematical geoenergy | 333.79 R279 Reliance review of energy markets | 333.79 R293 Renewable energy | 333.79 R498e4 Energy and the environment [4th ed.] |
AGU 100 Advancing earth and space science
GeoEnergy encompasses the range of energy technologies and sources that interact with the geological subsurface. Fossil fuel availability studies have historically lacked concise modeling, tending instead toward heuristics and overly-complex processes. Mathematical GeoEnergy: Oil Discovery, Depletion and Renewal details leading-edge research based on a mathematically-oriented approach to geoenergy analysis.
Volume highlights include:
Applies a formal mathematical framework to oil discovery, depletion, and analysis
Employs first-order applied physics modeling, decreasing computational resource requirements
Illustrates model interpolation and extrapolation to fill out missing or indeterminate data
Covers both stochastic and deterministic mathematical processes for historical analysis and prediction
Emphasizes the importance of up-to-date data, accessed through the companion website
Demonstrates the advantages of mathematical modeling over conventional heuristic and empirical approaches
Accurately analyzes the past and predicts the future of geoenergy depletion and renewal using models derived from observed production data
Intuitive mathematical models and readily available algorithms make Mathematical GeoEnergy: Oil Discovery, Depletion, and Renewal an insightful and invaluable resource for scientists and engineers using robust statistical and analytical tools applicable to oil discovery, reservoir sizing, dispersion, production models, reserve growth, and more.
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