PVT properties are necessary for reservoir/well performance forecast and optimization. In absence of PVT laboratory measurements, finding the right correlation to estimate accurate PVT properties could be challenging. PVT Property Correlations: Selection and Estimation discusses techniques to properly calculate PVT properties from limited information. This book covers how to prepare PVT properties for dry gases, wet gases, gas condensates, volatile oils, black oils, and low gas-oil ration oils. It also explains the use of artificial neural network models in generating PVT properties. It presents numerous examples to explain step-by-step procedures in using techniques designed to deliver the most accurate PVT properties from correlations. Complimentary to this book is PVT correlation calculator software. Many of the techniques discussed in this book are available with the software. This book shows the importance of PVT data, provides practical tools to calculate PVT properties, and helps engineers select PVT correlations so they can model, optimize, and forecast their assets.

Autorentext
Dr. Ahmed El-Banbi is currently a professor of Petroleum Engineering and chair of the department at the American University in Cairo (AUC). He has 25 years of diversified international experience in reservoir and petroleum engineering. He worked as an engineer, trainer, and a technology developer. Ahmed spent 12 years with Schlumberger where he held a variety of technical and managerial positions in 5 countries. He has considerable experience in managing multi-disciplinary teams and performing integrated reservoir studies. Previously, he had shorter assignments with a major oil company and a consulting company in addition to academic research and teaching experience. He authored and co-authored more than eighty technical papers, two book chapters, and holds one US patent. He has been on numerous SPE committees, program chair for the North Africa Technical Conference and Exhibition, and technical reviewer for the SPE Reservoir Engineering and Evaluation Journal and other journals. Ahmed holds BS and MS degrees from Cairo University, and an MS and PhD degrees from Texas A&M University; all in petroleum engineering. Dr. Ahmed Alzahabi is currently an Assistant Professor at the University of Texas of the Permian Basin. He earned a PhD and a MS, both in petroleum engineering from Texas Tech University and an MS from Cairo University. He previously served as a researcher at the Energy Industry Partnerships, working in the field of energy to solve complex problems for the industry. He is experienced in introducing new technologies in well-placement and fracturing in conventional and unconventional oil and gas reservoirs. His research involves developing techniques for Permian Wolfcamp exploitation. He has participated in six US patent applications, edited and reviewed for multiple journals, and is active in SPWLA, SPE, NAGPS, SEG, and AAPG. He has contributed a book chapter and is writing a book on Fracturing Horizontal wells. Mr. Ahmed El-Maraghi is a senior petroleum engineer with Qarun Petroleum Company. He has ten years experience in reservoir and production engineering. He has extensive experience in well test analysis and has performed several reservoir studies. Ahmed also worked as a trainer and software developer. He is an avid user and developer of artificial intelligence tools in petroleum engineering. Ahmed holds a BS from Suez Canal University, MS from Cairo University and he is currently a PhD candidate in Cairo University researching in neural networks applications in log interpretation. Ahmed authored and coauthored six papers.

Inhalt

Introduction2. Reservoir-Fluid Classification3. Dry Gases4. Wet Gases5. Gas Condensates6. Volatile Oil7. Black Oils8. Low Gas-Oil Ratio Oils9. Selection of PVT Correlations10. Artificial Neural Network Models for PVT Properties

AppendixA: Oil Correlations FormulaB: Gas Correlations FormulaC: Oil Correlations Range of ApplicabilityD: Gas Correlations Range of ApplicabilityE: Artificial Neural Network (ANN) Models Rnage of ApplicabilityF: Worksheets for Oil PVT Correlations Selection