| Inverse Theory for Petroleum Reservoir Characterization and History Matching Contributor(s): Oliver, Dean (Author), Reynolds, Albert (Author), Liu, Ning (Author) |
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ISBN: 052188151X ISBN-13: 9780521881517 Publisher: Cambridge University Press OUR PRICE: $184.30 Product Type: Hardcover - Other Formats Published: June 2008 |
| Additional Information |
| BISAC Categories: - Science | Earth Sciences - Geology - Science | Physics - Geophysics - Nature | Natural Resources |
| Dewey: 553.280 |
| LCCN: 2008298434 |
| Physical Information: 0.9" H x 6.9" W x 9.7" (2 lbs) 394 pages |
| Descriptions, Reviews, Etc. |
| Publisher Description: This book is a guide to the use of inverse theory for estimation and conditional simulation of flow and transport parameters in porous media. It describes the theory and practice of estimating properties of underground petroleum reservoirs from measurements of flow in wells, and it explains how to characterize the uncertainty in such estimates. Early chapters present the reader with the necessary background in inverse theory, probability and spatial statistics. The book demonstrates how to calculate sensitivity coefficients and the linearized relationship between models and production data. It also shows how to develop iterative methods for generating estimates and conditional realizations. The text is written for researchers and graduates in petroleum engineering and groundwater hydrology, and can be used as a textbook for advanced courses on inverse theory in petroleum engineering. It includes many worked examples to demonstrate the methodologies and a selection of exercises. |
Contributor Bio(s): Liu, Ning: - Ning Liu holds a Ph.D. from the University of Oklahoma in petroleum engineering and now works as a Reservoir Simulation Consultant at Chevron Energy Technology Company. Dr Liu is a recipient of the Outstanding Ph.D. Scholarship Award at the University of Oklahoma and the Student Research Award from the International Association for Mathematical Geology (IAMG). Her areas of interest are history matching, uncertainty forecasting, production optimization, and reservoir management. |