Dean. S. Oliver, Albert. C. Reynolds, Ning Liu
Inverse Theory for Petroleum Reservoir Characterization and History Matching
Dean. S. Oliver, Albert. C. Reynolds, Ning Liu
Inverse Theory for Petroleum Reservoir Characterization and History Matching
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A guide to the use of inverse theory for estimation of flow parameters in porous media.
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A guide to the use of inverse theory for estimation of flow parameters in porous media.
Produktdetails
- Produktdetails
- Verlag: Cambridge University Press
- Seitenzahl: 394
- Erscheinungstermin: 2. Februar 2018
- Englisch
- Abmessung: 244mm x 170mm x 21mm
- Gewicht: 678g
- ISBN-13: 9781108462075
- ISBN-10: 1108462073
- Artikelnr.: 51383023
- Verlag: Cambridge University Press
- Seitenzahl: 394
- Erscheinungstermin: 2. Februar 2018
- Englisch
- Abmessung: 244mm x 170mm x 21mm
- Gewicht: 678g
- ISBN-13: 9781108462075
- ISBN-10: 1108462073
- Artikelnr.: 51383023
Dean S. Oliver is the Mewbourne Chair Professor in the Mewbourne School of Petroleum and Geological Engineering at the University of Oklahoma, where he was the Director for four years. Prior to joining the University of Oklahoma, he worked for seventeen years as a research geophysicist, staff reservoir engineer, and research scientist in reservoir characterization for Chevron and for Saudi Aramco. He also spent six years as a professor in the Petroleum Engineering Department at the University of Tulsa. Professor Oliver has been awarded 'best paper of the year' awards from two journals and received the SPE Reservoir Description and Dynamics Award in 2004. He is currently the Executive Editor of the SPE Journal. His research interests are in inverse theory, reservoir characterization, uncertainty quantification, and optimization.
Preface
1. Introduction
2. Examples of inverse problems
3. Estimation for linear inverse problems
4. Probability and estimation
5. Descriptive geostatistics
6. Data
7. The maximum a posteriori estimate
8. Optimization for nonlinear problems using sensitivities
9. Sensitivity coefficients
10. Quantifying uncertainty
11. Recursive methods
Bibliography
Index.
1. Introduction
2. Examples of inverse problems
3. Estimation for linear inverse problems
4. Probability and estimation
5. Descriptive geostatistics
6. Data
7. The maximum a posteriori estimate
8. Optimization for nonlinear problems using sensitivities
9. Sensitivity coefficients
10. Quantifying uncertainty
11. Recursive methods
Bibliography
Index.
Preface
1. Introduction
2. Examples of inverse problems
3. Estimation for linear inverse problems
4. Probability and estimation
5. Descriptive geostatistics
6. Data
7. The maximum a posteriori estimate
8. Optimization for nonlinear problems using sensitivities
9. Sensitivity coefficients
10. Quantifying uncertainty
11. Recursive methods
Bibliography
Index.
1. Introduction
2. Examples of inverse problems
3. Estimation for linear inverse problems
4. Probability and estimation
5. Descriptive geostatistics
6. Data
7. The maximum a posteriori estimate
8. Optimization for nonlinear problems using sensitivities
9. Sensitivity coefficients
10. Quantifying uncertainty
11. Recursive methods
Bibliography
Index.