Modeling, control, and optimization of natural gas processing plants / William A. Poe, Saeid Mokhatab.

Format:

Book

Author/Creator:

Poe, William A., author.

Language:

English

Subjects (All):

Natural gas.

Gas manufacture and works.

Physical Description:

1 online resource (302 pages) : illustrations

Edition:

1st ed.

Place of Publication:

Amsterdam, [Netherlands] : Gulf Professional Publishing, 2017.

Summary:

Modeling, Control, and Optimization of Natural Gas Processing Plants presents the latest on the evolution of the natural gas industry, shining a light on the unique challenges plant managers and owners face when looking for ways to optimize plant performance and efficiency, including topics such as the various feed gas compositions, temperatures.

Contents:

Front Cover

MODELING, CONTROL, AND OPTIMIZATION OF NATURAL GAS PROCESSING PLANTS

Copyright

CONTENTS

ACKNOWLEDGMENT

1 - Introduction to Natural Gas Processing Plants

1.1 INTRODUCTION

1.2 NATURAL GAS PROCESSING OBJECTIVES

1.3 GAS PROCESSING PLANT CONFIGURATIONS

1.3.1 Gas Plant with Hydrocarbon Dew Pointing

1.3.1.1 Inlet Separation Facility

1.3.1.2 Condensate Stabilization

1.3.1.3 Acid Gas Removal Unit

1.3.1.3.1 Chemical Solvent Processes

1.3.1.3.2 Physical Solvent Processes

1.3.1.3.3 Mixed Solvent Processes

1.3.1.4 Sulfur Recovery and Handling Unit

1.3.1.4.1 Claus Sulfur Recovery Technology

1.3.1.4.2 Sulfur Degassing

1.3.1.4.2.1 Aquisulf Process

1.3.1.4.2.2 D'GAASS Process

1.3.1.4.3 Sulfur Storage and Handling

1.3.1.4.4 Tail Gas Treating Unit

1.3.1.4.5 Acid Gas Enrichment Unit

1.3.1.4.6 Sulfur Scavenger Unit

1.3.1.5 Gas Dehydration Unit

1.3.1.5.1 Conventional TEG Dehydration Process

1.3.1.5.2 Enhanced TEG Dehydration Process

1.3.1.6 Hydrocarbon Dew Pointing

1.3.1.6.1 Hydrocarbon Dew Pointing with Joule-Thomson Cooling

1.3.1.6.2 Hydrocarbon Dew Pointing with Propane Refrigeration

1.3.1.6.3 Deep Hydrocarbon Dew Pointing

1.3.1.7 Nitrogen Rejection

1.3.1.7.1 Single-Column Nitrogen Rejection

1.3.1.7.2 Double-Column Nitrogen Rejection

1.3.1.7.3 Three-Column Nitrogen Rejection

1.3.1.7.4 Two-Column Nitrogen Rejection

1.3.1.8 Gas Compression and Transmission

1.3.2 Gas Plant for NGL Production

1.3.2.1 Carbon Dioxide Removal

1.3.2.2 Dehydration and Mercaptan Removal

1.3.2.3 Mercury Removal

1.3.2.3.1 Nonregenerative Mercury Sorbents

1.3.2.3.2 Regenerative Mercury Adsorbents

1.3.2.3.3 Process Considerations

1.3.2.4 NGL Recovery.

1.3.2.4.1 Lean Oil Absorption

1.3.2.4.2 Turboexpander NGL Recovery Processes

1.3.2.4.3 Modern NGL Recovery Processes

1.3.2.4.3.1 Dual-Column Reflux Process

1.3.2.4.3.2 Gas Subcooled Process

1.3.2.4.3.3 Ortloff SCORE

1.3.2.4.3.4 Residue Gas Recycle

1.3.2.4.3.5 Fluor Twin-Column High Absorption Process

1.3.2.4.3.6 Fluor Twin-Reflux Absorption Process

1.3.2.4.4 Other Hydrocarbons Removal Processes

1.3.2.4.4.1 Solid Bed Adsorption

1.3.2.4.4.2 Membrane Separation

1.3.2.4.4.3 Twister Supersonic Separation

1.3.2.5 NGL Fractionation

1.3.2.5.1 Fractionation Column Design and Operation

1.3.2.5.2 Liquid Products Processing

1.3.2.5.2.1 NGL Contaminants Treating

1.3.2.5.2.1.1 Caustic Processes

1.3.2.5.2.1.2 Molecular Sieve Technology

1.3.2.5.2.1.3 Amine Processes

1.3.2.5.2.2 Dehydration

1.3.3 Integrating NGL Recovery and LNG Production Plants

1.4 GAS PLANT SUPPORT SYSTEMS

1.4.1 Utility and Off-site

1.4.2 Process Control Systems

1.4.3 Safety Systems

1.5 OPTIMAL DESIGN AND OPERATIONS OF NATURAL GAS PROCESSING PLANTS

1.5.1 Process Modeling and Simulation

1.5.2 Process Control

1.5.3 Process Optimization

REFERENCES

2 - Process Modeling and Simulation

2.1 INTRODUCTION

2.1.1 Definition of Process Simulation

2.1.2 Benefits of Simulation in Gas Processing Plants

2.1.3 Chapter Objectives

2.2 THERMODYNAMICS

2.3 STEADY-STATE VERSUS DYNAMIC MODELS

2.4 SIMULATION OBJECTIVES VERSUS MODELING EFFORT

2.4.1 Shortcut Versus Rigorous Models

2.4.2 Lumped Parameter Versus Distributed Models

2.4.3 Commercial Models Versus Bespoke Models

2.5 PROCESS SIMULATION APPROACHES

2.5.1 Modular Approach for Steady-State Models

2.5.2 Equation Solver Approach for Steady-State Models

2.5.3 Combined Approach in Steady-State Models.

2.5.4 Modular Approach for Dynamic Models

2.5.5 Equation Solver Approach for Dynamic Models

2.5.6 Hybrid Approach for Dynamic Models

2.6 PROCESS SIMULATION BEST PRACTICES

2.6.1 Chemical Components and Thermodynamic Models

2.6.1.1 Component Lists

2.6.1.2 Thermodynamic Model Selection

2.6.2 The Simulation Model

2.6.2.1 Model Speed and Iterations

2.6.2.2 Solution Order

2.6.2.3 Model Robustness

2.7 CASE STUDIES

2.7.1 Gas Dehydration with TEG

2.7.1.1 Thermodynamic Model Selection

2.7.1.2 Modeling the TEG Dehydration System

2.7.2 Sour Gas Sweetening with Amines

2.7.2.1 Thermodynamic Model Selection

2.7.2.2 Modeling the Absorption and Regeneration

2.7.3 Turboexpander NGL Recovery

2.7.3.1 Thermodynamic Model Selection

2.7.3.2 Modeling the Multistream Exchanger

2.7.3.3 Modeling the Turboexpander

2.7.4 MEG Regeneration

2.7.4.1 Thermodynamic Model Selection

2.7.4.2 Modeling the Process

3 - Process Control

3.1 DYNAMIC PROCESS CHARACTERISTICS

3.1.1 Resistance-Type Processes

3.1.2 Capacitance-Type Processes

3.1.3 Process Dead Time

3.1.4 Inertia-Type Processes

3.1.5 Combinations of Dynamic Characteristics

3.1.6 Examples: Simple Systems

3.1.6.1 Vessels and Piping

3.1.6.2 Heat Exchangers

3.1.6.3 Pipelines

3.1.6.4 Effects of Variable Conditions

3.2 CONTROL SYSTEM COMPONENTS

3.3 CLOSED-LOOP CONTROL

3.3.1 On-Off Control

3.3.2 Proportional Control

3.3.3 Integral Control

3.3.4 Derivative Control

3.3.5 Proportional-Integral-Derivative Control

3.3.6 Advanced Control

3.3.6.1 Feedforward Control

3.3.6.2 Cascade Control

3.3.6.3 Override and Selectors

3.3.6.4 Interaction and Decoupling

3.3.6.5 Nonlinear Control

3.3.6.6 Adaptive Control

3.3.6.7 Internal Model Control

3.3.6.8 Model Predictive Control

3.4 DEGREES OF FREEDOM.

3.5 CONTROL LOOP TUNING

3.5.1 Quality of Control

3.5.2 Controller Response

3.5.2.1 Peak-Related Criteria

3.5.2.2 Time-Related Criteria

3.5.2.3 When There Is No Overshoot

3.5.3 Error Performance Criteria

3.5.4 Tuning Methods

3.5.4.1 Process Reaction Curve Methods

3.5.4.1.1 Ziegler-Nichols Open-Loop Procedure

3.5.4.1.2 Cohen-Coon Tuning Method

3.5.4.1.3 Internal Model Control Tuning Rules

3.5.4.2 Constant Cycling Methods

3.5.4.2.1 Ziegler-Nichols Closed-Loop Method

3.5.4.3 Autotune Variation Technique

3.5.5 PID Tuning Software

3.5.6 Choosing a Tuning Method

3.5.6.1 Flow Loops

3.5.7 Lambda Tuning

3.5.8 First Principles Process Relationships

3.6 INDIVIDUAL UNIT OPERATION CONTROL AND OPTIMIZATION STRATEGIES

3.6.1 Blending

3.6.2 Boilers

3.6.3 Utility Steam Systems

3.6.4 Steam Turbines

3.6.5 Heat Exchangers

3.6.6 Chillers

3.6.7 Compressors

3.6.7.1 Reciprocating Compressors

3.6.7.2 Centrifugal Compressors

3.6.7.2.1 Capacity Control Options

3.6.7.2.2 Surge

3.6.7.2.2.1 Compressor Unit Safeties

3.6.8 Turboexpanders

3.6.9 Distillation

3.6.9.1 Steady State Modeling-Material Balance, Energy Balance

3.6.9.2 Dynamic Model

3.6.9.3 Control Loop Interaction

3.6.9.4 Composition Control

3.6.9.4.1 Composition Control Using Analyzers

3.6.9.4.2 Composition Inferentials-Pressure-Compensated Temperature

3.6.9.5 Pressure Control

3.6.9.6 Liquid Distillate and Inerts

3.6.9.7 Vapor Distillate and Inerts

3.6.9.8 Vapor Recompression

3.6.9.8.1 Feed Control

3.6.9.9 Advanced Controls

3.6.9.9.1 Feedforward Systems

3.6.9.9.2 Dual Composition Control

3.6.9.9.3 Feed Composition Compensation

3.6.9.9.4 Internal Reflux

3.6.9.9.5 Supervisory Control

3.6.9.9.6 Suboptimization

3.6.9.9.7 Feed Maximization

3.6.9.9.8 Feed Enthalpy Control.

3.6.10 Fans

3.6.11 Furnaces

4 - Process Optimization

4.1 INTRODUCTION

4.2 TYPES OF OPTIMIZATION

4.3 CONVENTIONAL OPTIMIZATION TECHNIQUES

4.4 LIMITATIONS OF OPTIMIZATION

4.5 METHODS OF OPTIMIZATION

4.5.1 Continuous Optimization

4.5.2 Linear

4.5.2.1 Linear Programming

4.5.3 Lagrange Multipliers

4.5.4 Nonlinear

4.5.4.1 Hessian Methods

4.5.4.2 Gradient Methods

4.5.4.3 Evaluation of Function Values

4.5.4.4 Quadratic Programming

4.5.5 Discrete

4.5.5.1 Mixed Integer Linear Programming

4.5.5.2 Mixed Integer Nonlinear Programming

4.6 ADVANCED OPTIMIZATION TECHNIQUES

4.6.1 Simulated Annealing

4.6.2 Genetic Algorithms

4.7 DYNAMIC OPTIMIZATION

4.7.1 Linear Quadratic Control

4.7.2 Numerical Methods for Optimal Control

4.8 REAL-TIME OPTIMIZATION

4.8.1 Physical Properties

4.8.2 Optimization Models

4.8.3 Optimization Objective Function

4.8.4 Custom Models

4.8.5 Fractionators

4.8.6 Absorbers and Strippers

4.8.7 Compression Model

4.8.8 Distillation Calculations

4.8.8.1 Tray-to-Tray Distillation Method

4.8.8.2 Demethanizer

4.8.8.3 Deethanizer

4.8.8.4 Depropanizer

4.8.8.5 Debutanizer

4.8.8.6 Butanes Splitter

4.8.9 Refrigeration Models

4.8.10 Demethanizer Feed Chilling Models

4.8.11 Steam and Cooling Water System Models

4.8.12 Turbines

4.8.13 Plant Model Integration

4.8.14 Model Fidelity and Measurement Errors

4.9 PROCESS OPTIMIZATION CASE STUDY

A - Basic Principles of Control Valves

A.1 TYPES OF CONTROL VALVES

A.1.1 Globe Valves

A.1.1.1 Single Port

A.1.1.2 Double Ported

A.1.1.3 Angle Style

A.1.1.4 Three Way

A.1.1.5 Balanced Cage Guided

A.1.1.6 High-Capacity Cage Guided

A.1.2 Rotary Valves

A.1.2.1 Butterfly Valves

A.1.2.2 V-Notch Ball Valves.

A.1.2.3 Eccentric Disk Valves.

Notes:

Includes bibliographical references at the end of each chapters and index.

Description based on print version record.

Description based on publisher supplied metadata and other sources.

ISBN:

9780128029619

0128029617

9780128029817

0128029811

OCLC:

958516689