Applied Optimization in the Petroleum Industry

Preface
Intended Audience
The Book’s Contents
Chapter 1: Introduction to Petroleum and Petrochemical Industries
Chapter 2: Introduction to Optimization Models and Techniques
Chapter 3: Optimum Locations of Multiple Drilling Platforms
Chapter 4: Simulation-Based Optimization of Refinery Valve Inspection Frequency
Chapter 5: Operations and Workforce Scheduling for Refinery Turnaround Maintenance
Chapter 6: Simulation-Based Scheduling of Pipeline Maintenance Crews
Chapter 7: Optimum Gasoline Blending in Petroleum Refining
Chapter 8: Employee Scheduling in Remote Oil Industry Work Sites
Chapter 9: Optimum Planning of a Distribution Supply Chain for Refined Oil Products
Chapter 10: Berth Allocation for Loading Tankers at an Oil Export Terminal
Acknowledgments
Contents
About the Author
1 Introduction to Petroleum and Petrochemical Industries
1.1 Historical Background
1.1.1 History of the Petroleum Industry
1.1.2 History of the Petrochemical Industry
1.2 Main Processes of the Petroleum Industry
1.2.1 Exploration
1.2.2 Production
1.2.3 Upstream
1.2.4 Midstream
1.2.5 Refining (Downstream)
1.3 Main Processes of the Petrochemical Industry
1.3.1 Feedstock Preparation
1.3.2 Upstream Petrochemical Industry
1.3.3 Intermediate Petrochemical Industry
1.3.4 Downstream Petrochemical Industry
1.4 Main Oil Products and Their Uses
1.4.1 Crude Oil Types
1.4.2 Types of Natural Gas
1.4.3 Types of Refined Oil Products
1.5 Types of Petrochemical Products
1.5.1 Olefin Products
1.5.2 Aromatics Products
1.5.3 SynGas Products
1.6 Integrated Petroleum and Petrochemical Industrial System
1.7 Literature on Optimization in the Petroleum Industry
1.7.1 Optimization in the Petroleum Industry at Large
1.7.2 Optimization in the Exploration and Production Stage
1.7.3 Optimization in the Refining Stage
1.7.4 Optimization in the Transportation Stage
1.7.5 Future Trends in the Petroleum Industry
1.8 Summary and Conclusions
References
2 Introduction to Optimization Models and Techniques
2.1 Introduction to Optimization
2.2 Unconstrained Optimization
2.3 Linear Programming
2.3.1 LP Graphical Solution
2.3.2 The Simplex Method
2.4 Other Mathematical Programming Techniques
2.4.1 Integer Programming
2.4.2 Goal Programming
2.4.3 Network Models
2.4.4 Dynamic Programming (DP)
2.4.5 Stochastic Programming
2.4.6 Nonlinear Programming
2.5 Meta-heuristic Algorithms
2.5.1 Genetic Algorithms (GA)
2.5.2 Simulated Annealing (SA)
2.5.3 Tabu Search (TS)
2.5.4 Particle Swarm Optimization (PSO)
2.6 Simulation-Based Optimization
2.7 Summary and Conclusions
References
3 Optimum Locations of Multiple Drilling Platforms
3.1 Introduction
3.2 Relevant Literature
3.3 The Offshore Drilling Problem
3.3.1 Problem Description
3.3.2 Model Costs and Parameters
3.4 Case 1: Fixed Rig Locations
3.4.1 Case 1a. Equal Number of Wells Per Platform
3.4.2 Case 1b. Unrestricted Number of Wells Per Platform
3.5 Case 2: Optimum Platform Locations
3.5.1 Case 2 Optimum Solution Model
3.5.2 Case 2a. Solution with Equal Number of Wells Per Rig
3.5.3 Case 2b. Solution with Unrestricted Number of Wells Per Rig
3.6 Case 2 Heuristic Solution
3.6.1 Case 2 Heuristic Solution: Stage 1
3.6.2 Case 2 Heuristic Solution: Stage 2
3.6.3 Case 2a. Heuristic Solution with Equal Number of Wells Per Rig
3.6.4 Case 2b. Heuristic Solution with Unrestricted Number of Wells Per Rig
3.6.5 Evaluation of the Heuristic Solution
3.7 Summary and Conclusions
References
4 Simulation-Based Optimization of Refinery Valve Inspection Frequency
4.1 Introduction
4.2 Review of Related Work
4.2.1 Analytical Inspection Interval Models
4.2.2 Simulation Inspection Interval Models
4.2.3 Reasons for Using a Simulation Approach
4.3 Data Collection and Analysis
4.3.1 Data Collection
4.3.2 Factors Affecting Valve Failure Rates
4.3.3 Determining Probability Distributions
4.4 Modeling and Simulation
4.5 Output Analysis
4.6 Summary and Conclusions
References
5 Operations and Workforce Scheduling for Refinery Turnaround Maintenance
5.1 Introduction
5.2 Relevant Literature
5.3 Model Formulation
5.3.1 Assumptions
5.3.2 Input Values
5.3.3 Decision Variables
5.3.4 The Integer Linear Programming Model
5.3.5 Values of G and T and Bounds on N and Z
5.3.6 Size of the Optimum ILP Model
5.4 Heuristic Solution Method
5.4.1 Heuristic Stage 1
5.4.2 Heuristic Stage 2
5.4.3 Size of the Heuristic ILP Model
5.5 Case Study
5.5.1 Optimum Solution of the Case Study
5.5.2 Heuristic Solution of the Case Study
5.6 Evaluation of the Heuristic Method
5.7 Summary and Conclusions
References
6 Simulation-Based Scheduling of Pipeline Maintenance Crews
6.1 Introduction
6.2 Literature Review
6.3 Problem Description
6.4 Data Collection and Analysis
6.5 The Simulation Model
6.5.1 Model Assumptions
6.5.2 Model Definitions
6.5.3 Model Design
6.5.4 Duration of the Simulation Runs
6.5.5 Model Verification
6.5.6 Model Validation
6.5.7 Number of Replications
6.6 Optimizing Days-Off Schedules
6.6.1 Performance of Current Schedules
6.6.2 Optimum Machinist Schedules
6.6.3 Optimum Schedules of the Other Specializations
6.7 Summary and Conclusions
References
7 Optimum Gasoline Blending in Petroleum Refining
7.1 Introduction
7.2 Literature Review
7.3 The Gasoline Blending Problem
7.3.1 Refining and Blending Processes
7.3.2 Blending Process Inputs and Outputs
7.3.3 Gasoline Specifications
7.4 Calculating Blend Properties from Component Properties
7.4.1 Calculating the E70 of the Blend
7.4.2 Calculating the RVP of the Blend
7.4.3 Calculating the VLI of the Blend
7.4.4 Calculating the RON of the Blend
7.5 Gasoline Blending Case Study
7.6 Nonlinear Programming Optimization Model
7.6.1 Notation
7.6.2 Objective Function
7.6.3 Production Constraints
7.6.4 Specification Constraints
7.7 Solution Process and Results
7.7.1 Stage 1: LP Solution of Linearized Approximation
7.7.2 Stage 2: NLP Solution Using LP Solution as the Initial Point
7.7.3 Case Study Solution Results
7.8 Summary and Conclusions
References
8 Employee Scheduling in Remote Oil Industry Work Sites
8.1 Introduction
8.2 Literature Review
8.3 Problem Definition and Formulation
8.3.1 Problem Description
8.3.2 Model Assumptions
8.3.3 Model Notation
8.3.4 Model Formulation
8.4 Determining the Workforce Size
8.4.1 Minimum W for the Simplified Model
8.4.2 Minimum W for the Full Model
8.5 Determining the Days-Off Assignments
8.5.1 Four Active Days-Off Patterns
8.5.2 Seven Active Days-Off Patterns
8.5.3 Eight Active Days-Off Patterns
8.5.4 Ten Active Days-Off Patterns
8.5.5 Eleven Active Days-Off Patterns
8.5.6 The Days-Off Scheduling Procedure
8.6 Summary and Conclusions
References
9 Optimum Planning of a Distribution Supply Chain for Refined Oil Products
9.1 Introduction
9.2 Literature Review
9.3 Problem Description
9.4 Model Formulation
9.4.1 Model Assumptions
9.4.2 Model Indices
9.4.3 Given Parameters
9.4.4 Decision Variables
9.4.5 Objective Function
9.4.6 Supply, Demand, and Material Balance Constraints
9.4.7 DC Capacity Constraints
9.4.8 SC to DC Transportation Link Constraints
9.4.9 DC to DM Transportation Link Constraints
9.4.10 DC to DC Transportation Link Constraints
9.5 Given Data
9.6 Model Solution
9.7 Summary and Conclusions
References
10 Berth Allocation for Loading Tankers at an Oil Export Terminal
10.1 Introduction
10.2 Review of Relevant Literature
10.3 Problem Description
10.4 Berth Allocation Optimization Model
10.4.1 Model Assumptions
10.4.2 Model Indices
10.4.3 Given Parameters
10.4.4 Decision Variables
10.4.5 Objective Function
10.4.6 Constraints
10.4.7 Calculating the Value of S
10.5 Berth Allocation Case Study
10.6 Summary and Conclusions
References
Appendix A Bibliography: Optimization in the Petroleum Industry
A.1 Exploration
A.2 Production
A.3 Refining
A.4 Transportation
Index