Mathematical Theory of Oil and Gas Recovery


Book Description

It is a pleasure to be asked to write the foreword to this interesting new book. When Professor Bedrikovetsky first accepted my invitation to spend an extended sabbatical period in the Department of Mineral Resources Engineering at Imperial College of Science, Technology and Medicine, I hoped it would be a period of fruitful collaboration. This book, a short course and a variety of technical papers are tangible evidence of a successful stay in the UK. I am also pleased that Professor Bedrikovetsky acted on my suggestion to publish this book with Kluwer as part of the petroleum publications for which I am Series Editor. The book derives much of its origin from the unpublished Doctor of Science thesis which Professor Bedrikovetsky prepared in Russian while at the Gubkin Institute. The original DSc contained a number of discrete publications unified by an analytical mathematics approach to fluid flow in petroleum reservoirs. During his sabbatical stay at Imperial College, Professor Bedrikovetsky has refined and extended many of the chapters and has discussed each one with internationally recognised experts in the field. He received great encouragement and editorial advice from Dr Gren Rowan, who pioneered analytical methods in reservoir modelling at BP for many years.




Mathematical Theory of Oil and Gas Recovery


Book Description

It is a pleasure to be asked to write the foreword to this interesting new book. When Professor Bedrikovetsky first accepted my invitation to spend an extended sabbatical period in the Department of Mineral Resources Engineering at Imperial College of Science, Technology and Medicine, I hoped it would be a period of fruitful collaboration. This book, a short course and a variety of technical papers are tangible evidence of a successful stay in the UK. I am also pleased that Professor Bedrikovetsky acted on my suggestion to publish this book with Kluwer as part of the petroleum publications for which I am Series Editor. The book derives much of its origin from the unpublished Doctor of Science thesis which Professor Bedrikovetsky prepared in Russian while at the Gubkin Institute. The original DSc contained a number of discrete publications unified by an analytical mathematics approach to fluid flow in petroleum reservoirs. During his sabbatical stay at Imperial College, Professor Bedrikovetsky has refined and extended many of the chapters and has discussed each one with internationally recognised experts in the field. He received great encouragement and editorial advice from Dr Gren Rowan, who pioneered analytical methods in reservoir modelling at BP for many years.




Technologies and Mathematical Modeling of Fines-assisted Oil and Gas Recovery


Book Description

This is a PhD thesis by publication. It includes seven published/accepted for publication journal papers and two submitted papers in academic peer reviewed journals. The content of the thesis is also published in ten full volume technical papers of Society of Petroleum Engineering (SPE). The thesis develops a theory for single and two-phase flow in porous media accounting for mobilization, migration, and straining of the natural reservoir fines. This phenomenon has been widely reported in laboratory studies and also well history data. The existing mathematical model, widely used in petroleum reservoir simulation, does not agree with laboratory observations. It contains phenomenological empirical constants which cannot be predicted theoretically. The new closed system of governing equations, proposed in the current thesis, is free of the above mentioned shortcomings. The proposed system contains a new theoretical function describing the rock capacity to liberate fines so-called maximum retention function. This function is based on the micro scale conditions of mechanical equilibrium of fine particles in the porous space. The mechanical equilibrium condition is a torque balance of drag, lifting, electrostatic, gravity, and capillary forces. The maximum retention function is derived for both single-phase and two-phase flows in porous media. The comparison between the modified particle detachment model and the maximum retention function and laboratory and well data has shown a good agreement, which validates the model. An exact analytical solution for single-phase flow in porous media with alternating velocity accounting for fines lifting has been derived, allowing for mathematical description of a laboratory test on the suspension injection into reservoir cores with alternating velocities. Good agreement between the laboratory test results and the mathematical modeling predictions validates the theory developed. Both analytical and numerical models for two-phase flow with induced fines migration have been developed. In reservoir scale approximation, the equivalence between the fines assisted water-flood and adsorption-free polymer flood has been investigated. It allows using the existing commercial simulators to model low salinity water-flood. The results of the modeling allow proposing a new technologically effective and economical method for improved sweep efficiency by fines assisted water-flooding. Moreover, modeling of low salinity water injection shows that permeability reduction due to induced fines migration can slow down the encroaching water in oil/gas reservoir under strong water support. It decreases water production during pressure depletion of oil/gas reservoirs and improves the recovery. Also, a small volume injection of low salinity water can be used to reduce the water conning problem in oil/gas wells and prolong the wells production life.




The Mathematics of Oil Recovery


Book Description

Based on a conference on mathematical aspects of oil recovery problems, this work reports recent research on fluid flow in oil reservoirs. Particular emphasis is placed on the mathematical and numerical methods used.




Reservoir Simulation


Book Description

This book covers and expands upon material presented by the author at a CBMS-NSF Regional Conference during a ten-lecture series on multiphase flows in porous media and their simulation. It begins with an overview of classical reservoir engineering and basic reservoir simulation methods and then progresses through a discussion of types of flows—single-phase, two-phase, black oil (three-phase), single phase with multicomponents, compositional, and thermal. The author provides a thorough glossary of petroleum engineering terms and their units, along with basic flow and transport equations and their unusual features, and corresponding rock and fluid properties. The practical aspects of reservoir simulation, such as data gathering and analysis, selection of a simulation model, history matching, and reservoir performance prediction, are summarized. Audience This book can be used as a text for advanced undergraduate and first-year graduate students in geology, petroleum engineering, and applied mathematics; as a reference book for geologists, petroleum engineers, and applied mathematicians; or as a handbook for practitioners in the oil industry. Prerequisites are calculus, basic physics, and some knowledge of partial differential equations and matrix algebra.Contents List of Figures; List of Tables; List of Notation; Preface; Introduction; Chapter 1: A Glossary of Petroleum Terms; Chapter 2: Single-Phase Flow and Numerical Solution; Chapter 3: Well Modeling; Chapter 4: Two-Phase Flow and Numerical Solution; Chapter 5: The Black Oil Model and Numerical Solution; Chapter 6: Transport of Multicomponents in a Fluid and Numerical Solution; Chapter 7: Compositional Flow and Numerical Solution; Chapter 8: Nonisothermal Flow and Numerical Solution; Chapter 9: Practical Topics in Reservoir Simulation; Bibliography; Index.




Mathematics in Oil Production


Book Description

This collection of papers, presented at the last IMA conference in Cambridge, covers recent developments in non-linear mathematics and electronic computers which have led to substantial advances in the field of fluid mechanics and related transport phenomena.




The Mathematics of Reservoir Simulation


Book Description

This book describes the state of the art of the mathematical theory and numerical analysis of imaging. Some of the applications covered in the book include computerized tomography, magnetic resonance imaging, emission tomography, electron microscopy, ultrasound transmission tomography, industrial tomography, seismic tomography, impedance tomography, and NIR imaging.




Mathematics of Oil Recovery


Book Description




Machine Learning Guide for Oil and Gas Using Python


Book Description

Machine Learning Guide for Oil and Gas Using Python: A Step-by-Step Breakdown with Data, Algorithms, Codes, and Applications delivers a critical training and resource tool to help engineers understand machine learning theory and practice, specifically referencing use cases in oil and gas. The reference moves from explaining how Python works to step-by-step examples of utilization in various oil and gas scenarios, such as well testing, shale reservoirs and production optimization. Petroleum engineers are quickly applying machine learning techniques to their data challenges, but there is a lack of references beyond the math or heavy theory of machine learning. Machine Learning Guide for Oil and Gas Using Python details the open-source tool Python by explaining how it works at an introductory level then bridging into how to apply the algorithms into different oil and gas scenarios. While similar resources are often too mathematical, this book balances theory with applications, including use cases that help solve different oil and gas data challenges. - Helps readers understand how open-source Python can be utilized in practical oil and gas challenges - Covers the most commonly used algorithms for both supervised and unsupervised learning - Presents a balanced approach of both theory and practicality while progressing from introductory to advanced analytical techniques