Methods for Petroleum Well Optimization

Automation and Data Solutions

Rasool Khosravanian, Bernt S. Aadnoy

• Publisher: Gulf Professional Publishing
• Year: 2021
• Print ISBN: 9780323902311
• eBook ISBN: 9780323902328
• Topic: Physical Sciences
• Subtopic: Energy

Drilling and production wells are becoming more digitalized as oil and gas companies continue to implement machine learning andbig data solutions to save money on projects while reducing energy and emissions. Up to now there has not been one cohesiveresource that bridges the gap between theory and application, showing how to go from computer modeling to practical use. Methodsfor Petroleum Well Optimization: Automation and Data Solutions gives today's engineers and researchers real-time data solutionsspecific to drilling and production assets. Structured for training, this reference covers key concepts and detailed approaches frommathematical to real-time data solutions through technological advances. Topics include digital well planning and construction,moving teams into Onshore Collaboration Centers, operations with the best machine learning (ML) and metaheuristic algorithms,complex trajectories for wellbore stability, real-time predictive analytics by data mining, optimum decision-making, and case-basedreasoning. Supported by practical case studies, and with references including links to open-source code and fit-for-use MATLAB, R,Julia, Python and other standard programming languages, Methods for Petroleum Well Optimization delivers a critical training guidefor researchers and oil and gas engineers to take scientifically based approaches to solving real field problems. - Bridges the gap between theory and practice (from models to code) with content from the latest research developments supported by practical case study examples and questions at the end of each chapter - Enables understanding of real-time data solutions and automation methods available specific to drilling and production wells, suchas digital well planning and construction through to automatic systems - Promotes the use of open-source code which will help companies, engineers, and researchers develop their prediction and analysissoftware more quickly; this is especially appropriate in the application of multivariate techniques to the real-world problems of petroleum well optimization

Table of contents

• Cover
• Front Matter
• Table of Contents
• Copyright
• Preface
• Acknowledgment I
• Acknowledgment II
• List of Illustrations
• List of Tables
• Chapter One : Introduction to digital twin, automation and real-time centers
• Chapter Two : Petroleum well optimization
• Chapter Three : Wellbore friction optimization
• Chapter Four : Wellbore trajectory optimization
• Chapter Five : Wellbore hydraulics and hole cleaning: optimization and digitalization
• Chapter Six : Mechanical specific energy and drilling efficiency
• Chapter Seven : Data-driven machine learning solutions to real-time ROP prediction
• Chapter Eight : Advanced approaches and technology for casing setting depth optimization
• Chapter Nine : Data mining in digital well planning and well construction
• Chapter Ten : Well completion optimization by decision-making
• Chapter Eleven : Monte Carlo simulation in wellbore stability optimization
• Chapter Twelve : Case-based reasoning (CBR) in digital well planning and construction
• Index
• A