PVT Property Correlation: Selection and Estimation helps engineers target their correlations based on an expert system. This reference presents several techniques that will allow engineers to select the best PVT correlation, especially when encountering limited reservoir fluid data and conditions. Tested against a large database, these techniques cover different types of fluids, including recent techniques using neural networks. Complimentary software that checks the input reservoir parameters for selecting the most appropriate correlation and a PVT calculator to predict oil properties over a wide range of input data is included.
In reservoir engineering, accurate determination of PVT properties is one of the most critical decisions in reservoir performance and forecasting. However, finding the right correlation is very time consuming and expensive, and today's engineers lack the proper tools for correlation assessment.
This book demonstrates the importance of PVT data and correlations so that today’s reservoir engineers can produce and model stronger and more reliant assets.
- Covers the importance of selecting the most appropriate values for PVT data and correlations without PVT experimental results
- Provides a a comprehensive list of all applicable ranges of PVT correlations, including gas condensate and volatile oil
- Teaches users how to apply practicality with an entire chapter devoted to a variety of reservoir problems and calculation examples
Reservoir Engineers, Well Designers, Production Engineers, Petrophysicists, Petrologists, Petroleum Engineers, Graduates in Petroleum Engineering
1. Introduction to PVT Correlations and their Applications
2. The PVT Properties review of black-oil, volatile oils, wet gasses, dry gases, gas condensate and formation water correlations
3. PVT Models: black-oil, modified black oil (MBO), and compositional
4. PVT Properties correlations for black oils, volatile oils, gas condensates, wet gases, dry gases, and formation water
5. Neural Network Approaches for deriving PVT Properties
6. Expert System Approaches to derive PVT Properties
7. Applications of the Expert System from Petroleum Engineering Examples and Calculations
- No. of pages:
- © Gulf Professional Publishing 2018
- 1st March 2018
- Gulf Professional Publishing
- Paperback ISBN:
Ahmed El-Bandi is currently Professor in petroleum engineering at Cairo University, teaching in reservior engineering and reservoir simulation. He is also Managing Director and Principal Consultant for Impact Energy Solutions, a consulting firm focused on field development projects and integrated reservoir studies. He has twenty-three years' experience in reservoir management and simulation, previously working for Schlumberger in various positions, managing technical staff in UAE, Angola, Oman, and Egypt. He is an active member of SPE, Arab Society for Mining and Petroleum, and Pi Epsilon Tau Society. He developed one patent, and Ahmed earned a PhD and MS degree in petroleum engineering from Texas A&M University and a MS and BS in petroleum engineering from Cairo University.
Professor, Petroleum Engineering, Cairo University, Egypt and Managing Director and Principal Consultant, Impact Energy Solutions, Egypt
Ahmed Alzahabi is currently a Professor at University of Texas (PB). He teaches reservoir engineering, shale reservoirs, multi-stage hydraulic fracturing modeling, and optimum horizontal well placement in unconventional reservoirs. He is one of a group of top-class scientists and engineers (Energy Industry Partnerships) working in the field of energy to solve complex problems for the industry. He is experienced in introducing new technologies in placing wells and fracture stages in conventional and unconventional oil and gas reservoirs and is currently working on international projects in North America and Asia. Previously, he was a Research Fellow/ Post-Doc/Instructor/Project Manager with the Petroleum Engineering Department at Texas Tech University and has taught multiple short courses for Eni Egypt, Kuwait Oil Company, Aramco, and Apache. He interned at Schlumberger, Suez Oil Company, and Oasis Petroleum Company. He developed five patents, edits and reviews multiple journals, and is active in SPWLA, SPE, NAGPS, SEG, and AAPG. Ahmed earned a PhD and a MS, both in petroleum engineering from Texas Tech University under Dr Mohamed Soliman, a MS in petroleum engineering from Cairo University, and a BS in petroleum engineering from Al Azhar University in Egypt.
Professor at University of Texas (PB), USA
Ahmad Al-Maraghi has nine years of total experience as a reservoir engineer, reservoir-engineering instructor and production technologist. He worked with QPC for nine years as a reservoir engineer and production technologist and with OGS for five years as a sub-surface technical advisor and instructor. In addition, he was working with IPR group of companies for seven years as a reservoir engineer consultant. Ahmad also worked as a programmer developing commerical software programs for four years with BAIT computer company, developing an automatic model identification methodology for well test analysis using artificial neural networks. He is currently studying for his PhD in petroleum engineering at Cairo University. He has earned a MSc in petroleum engineering from Cairo University and a BSc in petroleum engineering with honors degree from Suez Canal University.
Senior Reservoir and Petroleum Engineer, Qarun Petroleum Company, Egypt