Research Catalog

Title

Inverse theory for petroleum reservoir characterization and history matching / Dean S. Oliver, Albert C. Reynolds, Ning Liu.

Author

Oliver, Dean Stuart.

Publication

Cambridge : Cambridge University Press, 2008.

Items in the Library & Off-site

Details

Additional Authors

• Reynolds, Albert C.
• Liu, Ning.

Description

xii, 380 pages : illustrations; 26 cm

Summary

"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." "This volume is aimed at graduate students and resarchers 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, an extensive bibliography, and a selection of student exercises."--Jacket.

Subject

• Petroleum reserves > Mathematical models
• Inversion (Geophysics)
• Petroleum reserves > Mathematical models
• Erdgasgeologie
• Erdgaslagerstätte
• Erdölgeologie
• Erdöllagerstätte
• Fluid-Fels-System
• Hydraulik
• Inversion Mathematik
• Permeabilität
• Porosität
• Speichergestein
• Strömungsmechanik
• Olja (petroleum)
• Oljeprospektering

Bibliography (note)

• Includes bibliographical references (p. 367-377) and index.

Contents

• EXAMPLES OF INVERSE PROBLEMS: Density of the Earth -- Acoustic tomography -- Steady-state 1D flow in porous media -- History matching in reservoir simulation -- ESTIMATION FOR LINEAR INVERSE PROBLEMS: Characterization of discrete linear inverse problems -- Solutions of discrete linear inverse problems -- Singular value decomposition -- Backus and Gilbert method -- PROBABILITY AND ESTIMATION: Random variables -- Expected values -- Bayes' rule -- DESCRIPTIVE GEOSTATISTICS: Geologic constraints -- Univariate distribution -- Multi-variate distribution -- Gaussian random variables -- Random processes in function spaces -- DATA: Production data -- Logs and core data -- Seismic data -- THE MAXIMUM A POSTERIORI ESTIMATE: Conditional probability for linear problems -- Model resolution -- Doubly stochastic Gaussian random field -- Matrix inversion identities -- OPTIMIZATION FOR NONLINEAR PROBLEMS USING SENSITIVITIES: Shape of the objective function -- Minimization problems -- Newton-like methods -- Levenberg-Marquardt algorithm -- Convergence criteria -- Scaling -- Line search methods -- BFGS and LBFGS -- Computational examples --
• SENSITIVITY COEFFICIENTS: The Frechet derivative -- Discrete parameters -- One-dimensional steady-state flow -- Adjoint methods applied to transient single-phase flow -- Adjoint equations -- Sensitivity calculation example -- Adjoint method for multi-phase flow -- Reparameterization -- Examples -- Evaluation of uncertainty with a posteriori covariance matrix -- QUANTIFYING UNCERTAINTY: Introduction to Monte Carlo methods -- Sampling based on experimental design -- Gaussian simulation -- General sampling algorithms -- Simulation methods based on minimization -- Conceptual model uncertainty -- Other approximate methods -- Comparison of uncertainty quantification methods -- RECURSIVE METHODS: Basic concepts of data assimilation -- Theoretical framework -- Kalman filter and extended Kalman filter -- The ensemble Kalman filter -- Application of EnKF to strongly nonlinear problems -- 1D example with nonlinear dynamics and observation operator -- Example-geologic facies.

ISBN

• 9780521881517
• 052188151X

LCCN

2008298434

OCLC

• ocn181141231
• 181141231
• SCSB-9332466

Owning Institutions

Princeton University Library