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Clearly divided into three main sections, this practical book familiarizes readers with the area of planning in petroleum refining and petrochemical industry, while introducing several planning and modeling strategies encompassing single site refinery plants, multiple refinery networks, petrochemical networks, and refinery and petrochemical planning systems. It equally provides an insight into possible research directions and recommendations for the area of refinery and petrochemical planning.Furthermore, several appendices are included to explain the general background necessary, including stochastic programming, chance constraint programming, and robust optimization.For engineers and managers working in the petroleum industry as well as academic researchers in production, logistics, and supply chain management.
List of contents
PART I: BackgroundPETROLEUM REFINING AND PETROCHEMICAL INDUSTRY OVERVIEWRefinery OverviewMathematical Programming in RefiningRefinery ConfigurationPetrochemical Industry OverviewPetrochemical FeedstockRefinery and Petrochemical Synergy BenefitsPART II: Deterministic Planning ModelsPETROLEUM REFINERY PLANNINGProduction Planning and SchedulingOperations Practices in the PastTypes of Planning ModelsRegression-Based Planning: Example of the Fluid Catalytic CrackerArtificial-Neural-Network-Based Modeling: Example of Fluid Catalytic CrackerYield Based Planning: Example of a Single RefineryGeneral RemarksMULTISITE REFINERY NETWORK INTEGRATION AND COORDINATIONIntroductionLiterature ReviewProblem StatementModel FormulationIllustrative Case StudyConclusionPETROCHEMICAL NETWORK PLANNINGIntroductionLiterature ReviewModel FormulationIllustrative Case StudyConclusionMULTISITE REFINERY AND PETROCHEMICAL NETWORK INTEGRATIONIntroductionProblem StatementModel FormulationIllustrative Case StudiesConclusionPART III: Planning Under UncertaintyPLANNING UNDER UNCERTAINTY FOR A SINGLE REFINERY PLANTIntroductionProblem DefinitionDeterministic Model FormulationStochastic Model FormulationAnalysis MethodologyIllustrative Case StudyGeneral RemarksROBUST PLANNING OF MULTISITE REFINERY NETWORKSIntroductionLiterature ReviewModel FormulationSample Average Approximation (SAA)Illustrative Case StudyConclusionROBUST PLANNING FOR PETROCHEMICAL NETWORKSIntroductionModel FormulationValue to Information and Stochastic SolutionIllustrative Case StudyConclusionSTOCHASTIC MULTISITE REFINERY AND PETROCHEMICAL NETWORK INTEGRATIONIntroductionModel FormulationScenario GenerationIllustrative Case StudyConclusionAPPENDIX A: Two-Stage Stochastic ProgrammingAPPENDIX B: Chance Constrained ProgrammingAPPENDIX C: SAA Optimal Solution Bounding
About the author
Dr. Khalid Al-Qahtani is a senior process engineer at Saudi Aramco, Saudi Arabia. He holds a B.S. in Chemical Engineering from the King Fahd University of Petroleum & Minerals and a Ph.D. in Chemical Engineering from the University of Waterloo, Canada. He has worked in the petroleum industry for more than 10 years. Dr. Al-Qahtani is a process and project engineer specializing in the fields of oil treatment, gas processing and refining operations. Dr. Al-Qahtani is a member of different scientific societies and published his work in several refereed journals and international conferences.
Ali Elkamel is a professor of Chemical Engineering at the University of Waterloo, Canada. He holds a B.S. in Chemical and Petroleum Refining Engineering and a B.S. in Mathematics from Colorado School of Mines, an M.S. in Chemical Engineering from the University of Colorado-Boulder, and a PhD in Chemical Engineering from Purdue University. Prof. Elkamel's specific research interests are in computer-aided modeling, optimization, and simulation with applications to the petroleum and petrochemical industry. Prior to joining the University of Waterloo, he was at Purdue University, P&G, Italy, Kuwait University, and the University of Wisconsin, Madison. He has also taught a number of short courses to industry, including optimization and cost awareness, quantitative decision making, computer-aided problem solving, refinery economics and planning, and practical process engineering. He has contributed more than 200 publications in refereed journals and international conference proceedings and serves on the editorial board of several journals.
Summary
Clearly divided into three main sections, this practical book familiarizes readers with the area of planning in petroleum refining and petrochemical industry, while introducing several planning and modeling strategies encompassing single site refinery plants, multiple refinery networks, petrochemical networks, and refinery and petrochemical planning systems. It equally provides an insight into possible research directions and recommendations for the area of refinery and petrochemical planning.
Furthermore, several appendices are included to explain the general background necessary, including stochastic programming, chance constraint programming, and robust optimization.
For engineers and managers working in the petroleum industry as well as academic researchers in production, logistics, and supply chain management.
