The Three Sisters E-Book

• Herausgeber: John Wiley & Sons
• Kategorie: Wissenschaft und neue Technologien
• Serie: Advances in Natural Gas Engineering
• Sprache: Englisch

Seitenzahl: 430

Veröffentlichungsjahr: 2019

Beschreibung

This is the seventh volume in the series, Advances in Natural Gas Engineering, focusing on carbon dioxide (CO2) capture and sequestration, acid gas injection, and enhanced oil recovery, the "three sisters" of natural gas engineering. This volume includes information for both upstream and downstream operations, including chapters detailing the most cutting-edge techniques in acid gas injection, carbon capture, chemical and thermodynamic models, and much more. Written by some of the most well-known and respected chemical and process engineers working with natural gas today, the chapters in this important volume represent the most state-of-the-art processes and operations being used in the field. Not available anywhere else, this volume is a must-have for any chemical engineer, chemist, or process engineer in the industry. Advances in Natural Gas Engineering is an ongoing series of books meant to form the basis for the working library of any engineer working in natural gas today.

Leseprobe

Contents

Cover

Preface

Chapter 1: Acid Gas Injection: Engineering Steady State in a Dynamic World

1.1 Introduction

1.2 Steady-State Processes

1.3 Basic Process Requirements

1.4 Process Input Variabilities

1.5 Process Output Variables

1.6 AGI Process Associated Variables

1.7 Conclusion

Reference

Chapter 2: A History of AGIS

2.1 Introduction

2.2 Venues

2.3 Keynote Speaker

2.4 Workshops

2.5 Roundtable

2.6 Sponsors

2.7 AGIS Books

2.8 Conclusion

Chapter 3: Acid Gas Injection: Days of Future Passed

3.1 Introduction

3.2 State of the Art

3.3 New Processes

3.4 Modelling

3.5 More Data

3.6 The New Future

References

Chapter 4: Calorimetric and Densimetric Data to Help the Simulation of the Impact of Annex Gases Co-Injected with CO

2

During Its Geological Storage

4.1 Introduction

4.2 Material and Methods

Acknowledgement

References

Chapter 5: Densities and Phase Behavior Involving Dense-Phase Propane Impurities

5.1 Introduction

5.2 Experimental Section

5.3 Results and Discussion

5.4 Conclusion and Future Work

References

Chapter 6: Phase Equilibrium Computation for Acid Gas Mixtures Containing H

2

S Using the CPA Equation of State

6.1 Introduction

6.2 The Cubic-Plus-Association Equation of State

6.3 Association Schemes

6.4 Results and Discussion

6.5 Conclusions

Acknowledgment

References

Chapter 7: High Pressure H

2

S Oxidation in CO

2

7.1 Introduction

References

Chapter 8: Water Content of Carbon Dioxide – A Review

8.1 Introduction

8.2 Literature Review

8.3 Data Analysis

8.4 Experimental Methods

8.5 Conclusions

References

Chapter 9: Molecular Simulation of pK Values and CO

2

Reactive Absorption Prediction

9.1 Introduction

9.2 Thermodynamic Background

9.3 Molecular Simulation Methodology

9.4 Application to the MEA-H

2

O-CO

2

System

References

Chapter 10: A Dynamic Simulation to Aid Design of Shell’s CCS Quest Project’s Multi-Stage Compressor Shutdown System

10.1 Introduction

10.2 Centrifugal Compressor Reversal

10.3 Dynamic Modelling

10.4 Simulation Results

10.5 Modified Blowdown System

10.6 Conclusions

References

Chapter 11: Benefits of Diaphragm Pumps for the Compression of Acid Gas

11.1 Characteristics of Diaphragm Pumps

11.2 Current Projects

11.3 Improving Efficiency of Acid Gas Compression

11.4 Increasing Pressures

11.5 Varying Compositions

11.6 Pressure Pulsation and Synchronization

11.7 Conclusion

References

Chapter 12: Dynamic Solubility of Acid Gases in a Deep Brine Aquifer

12.1 Introduction

12.2 Reservoir Simulation Modeling

12.3 3D Static Model

12.4 History Matching

12.5 Results

12.6 Summary and Conclusions

References

Chapter 13: Tomakomai CCS Demonstration Project of Japan, CO

2

Injection in Progress

13.1 Introduction

13.2 Overview of Tomakomai Project

13.3 Injection Record

13.4 Features of Tomakomai Project

13.5 Conclusion

Acknowledgments

References

Chapter 14: The Development Features and Cost Analysis of CCUS Industry in China

14.1 Introduction

14.2 Characteristics of CCUS Project

14.3 Industry Patterns & Driving Modes

14.4 Composition & Factors of CO

2

Source Cost

14.5 Conclusions

References

Chapter 15: Study on Reasonable Soaking Duration of CO

2

Huff-and-Puff in Tight Oil Reservoirs

15.1 Introduction

15.2 Mechanism of CO

2

Huff-and-Puff in Developing Low Permeability Reservoirs

15.3 CO

2

Diffusion and Mass Transfer in Dense Pores

15.4 Production Simulation of CO

2

Huff-and-Puff

15.5 Conclusion

References

Chapter 16: Potential Evaluation Method of Carbon Dioxide Flooding and Sequestration

16.1 Introduction

16.2 CO

2

Miscible Flooding and Sequestration Potential Evaluation Model and Sequestration Capacity Calculation Method

16.3 Potential Evaluation Model and Calculation Method of CO

2

Sequestration

16.4 An Example of CO

2

Flooding and Sequestration Potential Evaluation

16.5 Conclusions

References

Chapter 17: Emergency Response Planning for Acid Gas Injection Wells

17.1 Introduction

17.2 Hydrocarbon Well Blowout Control Practices

17.3 Acid Gas Blowout Thermodynamics

17.4 Acid Gas Wellbore Dynamics

17.5 Acid Gas Plume Behaviour

17.6 Analogue Performance

17.7 Acid Gas Well Control Procedures

References

Appendix

Index

End User License Agreement

Guide

Cover

Table of Contents

Begin Reading

List of Illustrations

Chapter 1

Figure 1.1

Process Instability - Single Variable.

Figure 1.2

Process Instability - Dual Variable – Destructive Offset.

Figure 1.3

Process Instability - Dual Variable - Constructive Offset.

Figure 1.4

Process Instability - 3 Variables.

Figure 1.5

Process Instability - Multi Variable Offset.

Figure 1.6

JT Effect of Varying Composition.

Chapter 2

Figure 2.1

The Three Sisters, near Canmore Alberta.

Figure 2.2

Covers of the First Six AGIS Books Published by Scrivener Publishing.

Chapter 3

Figure 3.1

Simplified Block Diagram for Acid Gas Injection Process.

Chapter 4

Figure 4.1

Schematic View of the Densimetric Device for Measurements on Gas Loaded Solutions.

Figure 4.2

Density (left) and Apparent Molar Volumes (right) of Aqueous Solutions of...

Figure 4.3

Molar Volume at Infinite Dilution of CO

2

in Water. Left: Results at...

Figure 4.4

Schematic Representation of the Calorimetric Measurements.

Figure 4.5

Enthalpy of Mixing of CO

2

in Water, at 323 K and 5.1 MPa.

Figure 4.6

Enthalpy of Solution of CO

2

in Water and Aqueous Solutions of Electrolytes...

Figure 4.7

Enthalpy of Solution of SO

2

in Pure Water and Aqueous Solutions of...

Figure 4.8

Enthalpy of Solution of Gases as Function of the Composition of the Solution;...

Chapter 5

Figure 5.1

The density measurement of CS

2

dissolved in a dense propane phase at...

Figure 5.2

The apparent molar volumes of CO

2

dissolved in a dense propane phase...

Figure 5.3

The

p-x

phase diagram for a system of CO

2

and propane at...

Figure 5.4

The apparent molar volumes of CS

2

dissolved in a dense propane phase...

Chapter 6

Figure 6.1

Comparison of calculation results against experimental data (CPA calculation of...

Figure 6.2

H

2

S-H

2

O Vapour-liquid Equilibria at 377 K (CPA Calculation...

Figure 6.3

H

2

S-H

2

O Vapour-liquid Equilibria at 377 K (CPA Calculation...

Figure 6.4

H

2

S-H

2

O Vapour-liquid Equilibria at 377 K (CPA Calculation...

Figure 6.5

H

2

S-H

2

O Vapour-liquid Equilibria at 410 K (CPA Calculation...

Figure 6.6

H

2

S-H

2

O Vapour-liquid Equilibria at 410 K (CPA Calculation...

Figure 6.7

H

2

S-H

2

O Vapour-liquid Equilibria at 410 K (CPA Calculation...

Figure 6.8

H

2

S-H

2

O Vapour-liquid Equilibria at 444 K (CPA Calculation...

Figure 6.9

H

2

S-H

2

O Vapour-liquid Equilibria at 444 K (CPA Calculation...

Figure 6.10

H

2

S-H

2

O Vapour-liquid Equilibria at 444 K (CPA Calculation...

Figure 6.11

The Absolute Deviation between Simulated Solubility of H

2

S and Experi...

Figure 6.12

The Absolute Deviation between Simulated Solubility of H

2

S and...

Figure 6.13

The Absolute Deviation between Simulation Solubility of H

2

S and...

Figure 6.14

The Absolute Deviation between Simulation Solubility of H

2

S and...

Figure 6.15

The Absolute Deviation between Simulation Solubility of H

2

S and...

Figure 6.16

The Absolute Deviation between Simulation Solubility of H

2

S and...

Chapter 7

Figure 7.1

Schematic of the In-House Built High-Pressure Heterogeneous Catalytic Reactor.

Figure 7.2

H

2

S Oxidation Equilibrium Calculation with...

Chapter 8

Figure 8.1

Water content of carbon dioxide – Wiebe and Gaddy [2].

Figure 8.2

Water Content of Carbon Dioxide – Stone (1943). Pressures 1.52 to 6.08...

Figure 8.3

Water content of carbon dioxide – Malinin (1953).

Figure 8.4

Water content of carbon dioxide – Tödheide and Franck [3].

Figure 8.5

Water Content of Carbon Dioxide – Ohgaki

et al.

[Takenouchi and...

Figure 8.6

Water Content of CO

2

– Coan and King [18].

Figure 8.7

Water Content of Carbon Dioxide – Zawisza and Malesińska [6].

Figure 8.8

Water Content of Carbon Dioxide – Chrastil [19].

Figure 8.9

Water Content of Carbon Dioxide – Gillespie and Wilson [20].

Figure 8.10

Water Content of Carbon Dioxide - Song

et al.,

[37].

Figure 8.11

Water Content of Carbon Dioxide – Song and Kobayashi [21].

Figure 8.12

Water Content of Carbon Dioxide at 8.274 MPa – Song and Kobayashi [21].

Figure 8.13

Water Content of Carbon Dioxide – Briones

et al.,

[42].

Figure 8.14

Water Content of Carbon Dioxide – Nakayama

et al.,

[22].

Figure 8.15

CO

2

-H

2

O Mixture Dew Points – Patel

et al.,

...

Figure 8.16

Water Content of Carbon Dioxide – Müller

et al.,

[44].

Figure 8.17

Water Content of Carbon Dioxide – d’Souza

et al.,

(1988).

Figure 8.18

Water Content of Carbon Dioxide – Ohgaki

et al.,

[23]. The Two...

Figure 8.19

Water Content of Carbon Dioxide – Sako

et al.,

[46].

Figure 8.20

CO

2

-H

2

O Mixture Dew Points – Mather and Franck [59]...

Figure 8.21

Water Content of Carbon Dioxide – King

et al.,

[47].

Figure 8.22

Water Content of Carbon Dioxide – Dohrn

et al.,

[48].

Figure 8.23

Water Dew Point Pressures and Temperatures for Known Compositions of...

Figure 8.23a

Water Dew Point Pressures for Known Compositions of...

Figure 8.24

Water Content of Carbon Dioxide – Bamberger

et al.,

[27].

Figure 8.25

Water Content of Carbon Dioxide – Sabirzyanov

et al.,

[28].

Figure 8.26

Water Content of Carbon Dioxide – Valtz

et al.,

[29].

Figure 8.27

Water Dew Point Temperatures – Jarne

et al.,

[30].

Figure 8.28

Vapor Concentration Enhancement Factors

g

w

for Compressed...

Figure 8.29

Water Content of Carbon Dioxide – Chapoy

et al.,

[32].

Figure 8.30

Water Content of Carbon Dioxide – Tabasinejad

et al.,

[33].

Figure 8.31

Water Content of Liquid CO

2

in Equilibrium with Hydrates –...

Figure 8.32

Water Content of Liquid CO

2

in Equilibrium with Hydrates –...

Figure 8.33

Water Content of Carbon Dioxide – Kim

et al.,

[49].

Figure 8.34

Water Content of Carbon Dioxide – Hou

et al.,

[5].

Figure 8.35

Water Content of Carbon Dioxide in Equilibrium with Hydrates – Chapoy...

Figure 8.36

Water Content of Supercritical Carbon Dioxide - Wang

et al.,

(2013).

Figure 8.37

Water Content of CO

2

in Equilibrium with Hydrates – Burgass...

Figure 8.38

Water Content of Carbon Dioxide – Jasperson

et al.,

[66], Wiltec...

Figure 8.39

Water Content of Carbon Dioxide at 40 °C – Foltran

et al.,

...

Figure 8.40

Water Content of Carbon Dioxide - Meyer and Harvey (2015).

Figure 8.41

Water Content of Carbon Dioxide – Caumon

et al.,

[36].

Figure 8.42

Dew Points of Water in Carbon Dioxide – Comak

et al.,

[51].

Chapter 9

Figure 9.1

Composition of Solution Species as a Function of Loading.

Figure 9.2

CO

2

Partial Pressure as a Function of Loading.

Chapter 10

Figure 10.1

Block Flow Diagram for Quest Unit.

Figure 10.2

Shell’s Quest Compressor by MAN Diesel & Turbo.

Figure 10.3

Compressor Coverage Chart [from 13th Edition of the GPSA Engineering Data Book...

Figure 10.4

Generic Centrifugal Compressor Performance Curves, Courtesy of VMGSim.

Figure 10.5

Generic Four-Quadrant Compressor Map [4],...

Figure 10.6

Compressor speed vs. torque input to dynamic model in VMGSim.

Figure 10.7

Compressor Performance Curves in VMGSim.

Figure 10.8

Model building work process [7].

Figure 10.9

Valve Characteristics (Controlling Flow with Ball Valves).

Figure 10.10

Quest compressor original design flow diagram.

Figure 10.11

Compressor Operating vs. Simulated Discharge Pressures per Stage.

Figure 10.12

Quest compressor original design flow diagram.

Figure 10.13

Actual Compressor Speed Profile after Blowdown System modifications.

Chapter 11

Figure 11.1

Diaphragm Pump Head.

Figure 11.2

Diaphragm Condition Monitoring for Liquefied Gases.

Figure 11.3

Diaphragm Condition Monitoring With Solenoid Valve.

Figure 11.4

Triplex Diaphragm Pump G3M for Acid Gas Compression.

Figure 11.5

Triplex Diaphragm Pump G3R for Acid Gas Compression.

Figure 11.6

Different Approaches for the Compression of Acid Gas.

Figure 11.7

Condensation Pressure of Acid Gas at Varying Compositions.

Figure 11.8

Relative Compression of Acid Gas at Varying Compositions and Suction Conditions,...

Figure 11.9

Resulting Discharge Temperature of Acid Gas at Varying Compositions and Suction...

Figure 11.10

Required Stroke Frequency of Selected Pump to Compress Acid Gas at Varying...

Figure 11.11

Model of a Suction Side Pipeline for a Pulsation Study.

Figure 11.12

Comparison of Theoretical Volume Flow Pulsations; Left: Three-Headed Pump;...

Figure 11.13

Maximum Pressure Amplitudes at One Location in a Pipe Network for Two...

Chapter 12

Figure 12.1

The 3D Structure of the Model.

Figure 12.2

The Correlative Intervals Depicted on a Well Log in the Area of Interest.

Figure 12.3

Vertical Porosity Distribution in the Model.

Figure 12.4

History Match of Well Pressures and Injection Rates.

Figure 12.5

Comparison of H

2

S and CO

2

Plumes at the End of 10 Years...

Figure 12.6

Comparison of H

2

S and CO

2

Plumes in Layers 15 and 20 at...

Figure 12.7

Reservoir Pressure Profiles During the Periods of Injection and Injection...

Figure 12.8

An Evolution of the Concentration of H

2

S and CO

2

Away from...

Figure 12.9

Evolution of Mole Fraction of H

2

S and CO

2

Away from the...

Figure 12.10

Comparison of H

2

S and CO

2

Solubility at a Distance Away...

Figure 12.11

Preferential Solubility of H

2

S in Layer 20 for Case 1.

Figure 12.12

Comparison of H

2

S and CO

2

Plumes for Base Case.

Figure 12.13

Comparison of H

2

S and CO

2

Plumes for Case 1.

Figure 12.14

Comparison of H

2

S and CO

2

Plumes for Case 2.

Chapter 13

Figure 13.1

CO

2

Injection and Site Survey Projects in Japan.

Figure 13.2

Company Profile and Project Framework.

Figure 13.3

Flow Scheme of Tomakomai Project.

Figure 13.4

Aerial Photo of Capture and Injection Facilities.

Figure 13.5

CO

2

Capture Facilities and Compressors.

Figure 13.6

Heads of Injection Wells.

Figure 13.7

Schematic Geological Section.

Figure 13.8

Project Schedule.

Figure 13.9

Injection Record to Moebetsu Formation (Sandstone).

Figure 13.10

Location of Wells and Monitoring Facilities.

Figure 13.11

Schematic Diagram of Monitoring System.

Figure 13.12

Seismic Monitoring Area.

Figure 13.13

Micro-Seismicity Monitoring Results.

Figure 13.14

Natural Earthquakes Monitoring Results.

Figure 13.15

Injection Wells for Tomakomai Project.

Figure 13.16

Monitoring of Marine Environment.

Figure 13.17

CO

2

Capture Process.

Figure 13.18

Location of CCS site and Tomakomai City (Source of photo [3]).

Figure 13.19

Public Outreach Activities.

Figure 13.20

Example of Information Disclosure on Website.

Figure 13.21

Examples of Public Outreach Activities.

Chapter 14

Figure 14.1

Distribution of the world’s large-scale integrated CCUS projects.

Figure 14.2

Pie chart of the carbon capture amount constitution of the world’s...

Figure 14.3

Pie chart of CO

2

emission constitution in China.

Figure 14.4

Distributions of CO

2

Emissions of 8 kinds of enterprises in China.

Figure 14.5

Distributions of carbon sources in China.

Figure 14.6

Relationship between capture cost, compression cost and CO

2

flow.

Figure 14.7

Relationship between transportation cost and distance, CO

2

flow.

Figure 14.8

Estimated costs of different kinds of emission sources.

Chapter 15

Figure 15.1

Flow chart for calculation of diffusion coefficient.

Figure 15.2

Regression curve for diffusion coefficient.

Figure 15.3

Variation curve of diffusion coefficient under different pressures.

Figure 15.4

Chart of diffusion concentration.

Figure 15.5

The single well model of CO

2

huff-and-puff.

Figure 15.6

Comparison of oil recovery for CO

2

huff-and-puff under different...

Figure 15.7

The correlation between oil recovery percent and average oil draining rate as a...

Figure 15.8

The variation of oil displacement rate for all rounds under different soaking...

Chapter 16

Figure 16.1

Component diagram.

Figure 16.2

Map of contact and intrusion in 1/4 area of the five-spot pattern.

Chapter 17

Figure 17.1

Wellbore Gas Temperature vs. Depth.

Figure 17.2

78/20/2% H

2

S/CO

2

/C

1

Phase Envelope with...

Figure 17.3

49/49/2% H

2

S/CO

2

/C

1

Phase Envelope with...

Figure 17.4

20/78/2% H

2

S/CO

2

/C

1

Phase Envelope with...

List of Tables

Chapter 2

Table 2.1

Location and venues for the first seven AGIS.

Table 2.2

AGIS Keynote speakers and their titles.

Table 2.3

AGIS Workshop titles and presenters.

Chapter 3

Table 3.1

Three generations of acid gas injection projects.

Table 3.2

Data from the al hosn (shah sour gas development) as an example of a third...

Chapter 6

Table 6.1

Association energies for the H

2

S-H

2

O complex.

Table 6.2

Association schemes for compounds.

Table 6.3

The summary of best results of H

2

S-H

2

O system.

Table 6.4

CPA parameters for H

2

S and H

2

O involved in this study.

Table 6.5

Example cross association and self-association processes between...

Table 6.6

The coefficients of regression for different association schemes of...

Table 6.7

Simulation results of solubility for different association schemes at 377 K.

Table 6.8

Simulation results of solubility for different association schemes at 410 K.

Table 6.9

Simulation results of solubility for different association schemes at 444 K.

Table 6.10

a Comparison for the solubilities for H

2

O in this work and in literature...

Chapter 8

Table 8.1

Experimental investigations of the water content of carbon dioxide.

Table 8.2

Experimental data for water content in equilibrium with hydrates [12].

Table 8.3

Original experimental water content data in CO

2

-Rich Phase –...

Table 8.4

Recently measured data of water content in CO

2

-Rich Phase –...

Table 8.5

Experimental water content in CO

2

-Rich Phase - From Song and Kobayashi...

Table 8.6

Jackson

et al.,

[25] water solubility data in supercritical CO

2

.

Table 8.7

Expérimental data point for the System CO

2

-H

2

O...

Table 8.8

Hydrate dissociation temperature of CO

2

– Youssef

et al.,

...

Table 8.9

Water content of carbon dioxide – Jasperson

et al.,

[66], Korea...

Table 8.10

Comparison of water content of CO

2

between Comak

et al.,

and...

Table 8.11

Water content of pure CO

2

– Loring

et al.

,...

Table 8.12

Measurement principles of direct methods:.

Table 8.13

Measurement principles of indirect methods.

Table 8.14

Experimental methods used for studying water content of carbon dioxide.

Chapter 10

Table 10.1

Quest compressor stage speeds, MAN diesel & turbo.

Table 10.2

Compressor commissioning bull gear reverse rotation after trips.

Table 10.3

Steady-state vs. Dynamic modelling comparison.

Table 10.4

Compressor dynamic simulation data requirements [5].

Table 10.5

Equivalent length of valves and fittings in feet (FIG. 17.4) [6].

Table 10.6

Bull gear r.p.m. with different blowdown valve combinations.

Chapter 12

Table 12.1

Initial conditions of the acid gas injection at the well.

Table 12.2

Acid gas composition and pressure at end of 10 years of injection for layer 15.

Table 12.3

Acid gas composition and pressure at the end of 10 years of injection for layer...

Chapter 13

Table 13.1

CO

2

Capture energy.

Chapter 14

Table 14.1

Characteristic comparison between foreign and chinese projects.

Table 14.2

Capture costs in each stage of development ($/tCO

2

).

Chapter 15

Table 15.1

Physical parameter sheet of reservoirs and fluids.

Chapter 16

Table 16.1

Parameter data table.

Table 16.2

Reservoir screening criteria for CO

2

flooding and sequestration.

Chapter 17

Table 17.1

Acid gas escape temperature at surface.

Table 17.2

Cases selected for wellbore modelling.

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Scrivener Publishing100 Cummings Center, Suite 541JBeverly, MA 01915-6106

Publishers at ScrivenerMartin Scrivener ([email protected])Phillip Carmical ([email protected])

The Three Sisters

Acid Gas Injection, Carbon Capture and Sequestration, and Enhanced Oil Recovery

Edited by

Ying Wu

John J. Carroll

Yongle Hu

This edition first published 2019 by John Wiley &; Sons, Inc., 111 River Street, Hoboken, NJ 07030, USA and Scrivener Publishing LLC, 100 Cummings Center, Suite 541J, Beverly, MA 01915, USA © 2019 Scrivener Publishing LLC For more information about Scrivener publications please visit www.scrivenerpublishing.com.

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Library of Congress Cataloging-in-Publication Data

ISBN 978-1-119-51006-2

Preface

The seventh edition of the International Acid Gas Injection Symposium (AGIS VII) was held in Calgary, Canada in May 2018. The Symposium covers topics related to acid gas injection (AGI), carbon capture and sequestration (CCS), and the use of CO2 for enhanced oil recovery (EOR). This volume is a collection of select works presented at the Symposium.

The Keynote address was presented by Jim Maddocks, the CEO of Gas Liquids Engineering in Calgary, Canada and this is the first chapter of the book.

For the first time there was an award for the Best Student Paper, which was presented to Hanmin Tu. Miss Tu is doing a joint PhD at Southwest Petroleum University in Chengdu, China and the University of Regina in Regina Saskatchewan. Her paper is Chapter 6.

Another paper worth noting was our first contribution from Japan. Yoshihiro Sawada presented a review of the Tomakomai CCS Demonstration Project in the Hokkaido Prefecture in northern Japan. This is Chapter 12 in this volume.

Alice Wu wrote a history of AGIS up to and including this book. In her paper, Chapter 2, you will discover why we chose the title for this volume.

YW, JJC, & YH

June 2018

Chapter 1Acid Gas Injection: Engineering Steady State in a Dynamic World

Jim Maddocks

Gas Liquids Engineering Ltd. Calgary, Alberta, Canada

Corresponding author:[email protected]

Abstract

Acid gas injection (AGI), while widely used throughout the energy industry, still has significant learning and development opportunities, particularly as flows and pressures increase, and design engineers begin to stretch the limits of conventional AGI design thinking.

This paper and presentation is intended to provide some background and thoughts on the nature of acid gas injection, the uncertainties, the possibilities, and the myriad of issues that can be present during a typical design cycle. With a significant number of rapidly changing inter-related process variables, the engineering/design team needs to consider acid gas injection as a very transient and dynamic process. Adapting the design process and altering the way we think about, approach, design, fabricate and finally operate acid gas injection systems requires some innovative critical thinking skills, some learning on the custom nature of the systems involved, and finally the realization that the AGI system will ultimately have to adapt to the environment.

Keywords: Acid gas injection, compression, water content

1.1 Introduction

Acid gas is composed of a mixture of H2S and/or CO2 and usually water vapour. Acid gas, a byproduct of gas treating systems, is often considered to be a simplistic binary mixture of H2S and CO2. There are frequently other contaminants including methane, BTEXs, amine, and other hydrocarbon components. Carbon capture streams are typically pure CO2 although there are other contaminants co-captured with the carbon dioxide.

The very nature of acid gas compression and injection means that these AGI “systems” are nothing more than the glorified “garbage trucks” of gas processing. The design team has a very limited ability to manage the inputs to the process, a very limited ability to control the outputs, and the system barely even gets to talk to the upstream “garbage generator”. Basically, it’s desirable that this “garbage truck” simply do its job, quietly, efficiently, and as cheaply/painlessly as possible with minimal operator intervention and low maintenance.

1.2 Steady-State Processes

As engineers, we’re trained to understand, develop, and then control steady-state processes. We do this hundreds of thousands of times with pumps, compressors, turbines, heaters, coolers, and a multitude of other processes. This is one way of simplifying a design problem. In many cases, we don’t know anything other than steady-state and we proceed blindly assuming that the process will operate in “steady-state”. Nothing could be further from the truth.

Every process, every moment, and every single second of our day is filled with processes in constant transition. Everything from our furnace, to our cars, to the internet, is filled with constant change. Nothing is steady-state. The temperature of your house is constantly changing even with the best “smart” thermostat. The speed of your car is always changing. Your heart rate goes up and down according to external and internal stimuli, energy and forces. Even a simple system like cruise control on your vehicle is constantly experiencing micro-changes in inputs (like hills, curves, vehicle mass, and wind) and the system control output is expected to compensate for all these changes. It does this (usually seamlessly) and the user seldom notices the minor variations in speed.

Every part of our world is constantly in a state of dynamic transition. The weather is never constant; our ambient is always warming or cooling slightly, moisture content is changing, and the system is adapting. The belief in steady-state performance is a misnomer.

In order to understand and evaluate the dynamic nature of this process, it’s important to establish a different way of understanding this process.

Part of this learning process involves the use of “critical thinking skills”. These skills are defined as:

Critical thinking is that mode of thinking — about any subject, content, or problem — in which the thinker improves the quality of his or her thinking by skillfully analyzing, assessing, and reconstructing it. Critical thinking is self-directed, self-disciplined, self-monitored, and self-corrective thinking. It presupposes assent to rigorous standards of excellence and mindful command of their use. It entails effective communication and problem-solving abilities, as well as a commitment to overcome our native egocentrism and sociocentrism [1].

This style of thinking forces us to reconsider our basic assumptions in a design process – it’s an essential tool in the design of an acid gas system.

As engineers and designers, we’re expected to make steady-state approximations because they allow us to essentially draw a design line in the sand. Obviously, if a client stated that the compressor would see a flow varying from 30 to 60 e3m3/day of acid gas, we’d likely establish a “steady-state” design flow condition of 60 e3m3/day and then find a way to adapt to the low flow case. However, even recognizing that this high flow case is unsteady and dynamic, there are dozens of other non-steady-state variables in the system. Many are unnoticeable, some actually cancel each other out, and finally, some compound themselves into potentially serious process issues. Many of these changes take place over seconds, hours, days, or even months as the machines and processes begin to experience wear. Even the frequency of the change itself is changing. In order to fully understand, design, and control a process, we have to know that our understanding of steady-state is at best, a semi-educated guess.

1.3 Basic Process Requirements

1.3.1 Process Needs

The acid gas streams are often captured at low pressure (40–80 kPa[g]) from either a gas treating facility or a carbon capture system. Carbon dioxide (or CO2) gathered from EOR systems may be captured at moderately higher pressures (170 kPa[g]) and pure makeup CO2 supply pressures are often higher. As the AGI equipment and injection process is often downstream of many other larger process units, the acid gas system is expected to handle everything extracted in the amine unit or recovered from the reservoir. This means that flows, composition, temperature, and often pressures are highly variable and can change quickly without notice (and often without apparent reason). In order to prevent process upsets, shutdowns, and potentially regulatory non-compliance, it’s important that the acid gas injection system be able to adapt quickly (and with stability) to the changes.

1.4 Process Input Variabilities

1.4.1 Compositional Variances

While an acid gas injection system is usually designed as a steady-state process, it is far from a steady-state operation. Typically, the EPC engineering team requests a primary plant feedstock analysis from a different business unit within the owner’s company. In many cases, this feedstock is a known parameter and the owner company has a high degree of confidence in the analysis. However, in many newer developments, particularly in shale gas and tight gas developments, the field or reservoir has insufficient flowing history. In some cases, the Owner development engineering teams “take their best shot” at the anticipated composition. In order to provide for maximum regulatory and design flexibility, these teams often inflate or exaggerate the H2S fraction in the feed gas to reduce the capital risk of under-design. In many cases, they aren’t aware of the risk of having a large design allowance. The end result is that the composition of feed gas to the facility is often dramatically different than anticipated. As the field development matures, the composition can also evolve – in some cases, this may mean:

A changing hydrocarbon content with altered gas dew points and heavy components like C

5

+;

H

2

S and CO

2

can vary in either direction – sometimes rapidly;

New and unexpected components may appear including oxygen, elemental sulphur, mercaptans, toluene, benzenes, and COS.

In some cases, the feedstock may contain other unexpected contaminants. Various wellhead treating chemicals and production chemicals like wax dispersants, sulphur solvents, triazine, hydrate inhibitors including methanol, and asphaltenes solvents can be troublesome for amine plants and can trigger operational upsets and foaming events. These foaming events are often random and unpredictable and can:

Alter the pickup of H

2

S and CO

2

by shifting system kinetics and mass transfer

Potentially alter the co-adsorption of hydrocarbons

Result in significant (and rapid) flow variances as the foam breaks and re-forms

Often, these changes are simultaneous and rapid, making the prediction of acid gas compressor steady-state feedstock a challenging issue.

Redeployment of facilities often means that the industry is installing equipment in a service that may not be an ideal fit for the system. In other cases, the owner companies may need to significantly customize or even swap the solvent in the process. These seemingly minor process changes can have a dramatic effect on how the system performs.

In the natural gas midstreaming industry, it’s common for the midstream clients to vary (intentionally or otherwise) their production rates, compositions, water content, and even contaminants. While midstream operators usually specify maximum contaminant levels (wax/asphaltenes/solids), it’s difficult to manage or control to the degree required and some producers use the midstreamer as a receiver of all things. Producers can (and often do) inject unusual chemicals and experimental well treating technologies that can cause havoc inside an operating amine plant.

1.4.2 Flow Variances

Flow variances are often the most frequent, and most obvious (and thought to be the most challenging) to respond to in the design and operation of an acid gas injection system. As noted above, it is not uncommon for amine plant regeneration systems to swing and allow for a significant (and rapid) variation in the flow of Stage 1 acid gas. Designers expect a very flexible control system as the requirements can go from design flow to less than 25% (4:1 turndown) in a matter of seconds if the amine system and/or control system is unstable. Since the majority of acid gas compression systems are reciprocating positive displacement compressors, this significant decrease in flow is a dramatic change in 1st stage suction volumetric flow. Even minor changes in volumetric capacity must be managed quickly otherwise suction pressure will rise and fall rapidly. While the compressor is designed often to a single design point, the amine regeneration system will deliver the acid gas depending on the regen system performance. This amine regeneration performance is dependent on a number of system variables:

System cleanliness and “normal” contaminants

Ability of the system to generate stripping steam

Control system performance, valve performance, and system dynamics

Size of the system

Amine Regeneration Condenser performance

Time and thermal lags

Amine reboiler thermal momentum, driving force and performance

Most design teams are able to manage the flow changes with process control, typically a combination of speed and auto-bypassing; however, these systems need to have a rapid response without generating their own inherent process instability. Previous papers have examined the need for acid gas compressor capacity management, but it should be noted that the bypassing arrangements may not be identical as the composition shifts. Depending on the shifting composition, pressures, and phase behaviour, the bypass valves may not perform as required and the system will fail. Engineering the bypass assembly is a critically important step in acid gas system design.

1.4.3 Initial Suction Temperature Variances

Temperature variances are somewhat less disruptive as long as the system has the mechanical limits to manage the temperature swings. The primary issue with feed acid gas temperature is the changing water content. Clearly, lower inlet gas temperatures will suppress water content and will lower the amount of water rejected by the AGI compressor. It should be noted that, while this does lower overall water recovery rates, lower initial suction does not alter the final hydrate in the injection fluid.

As well, lower temperatures will lower the 1st stage discharge temperature and will also lower the volumetric requirement. For example, decreasing suction temperature from 30 to 10 °C will increase available compressor capacity by just over 4% with only a 2% increase in required power. Water content will decrease considerably but this usually has very little impact if the remaining stages operate as before. In addition to the water content, rapidly swinging inlet temperatures will trigger intercooler instability. If the system is operating well, the 1st stage after cooler will manage this bouncing temperature and will dampen out the variances. However, in some cases, oscillating cooler inlet temperatures can put the process cooling system into a poor response resulting in even bigger cooler outlet temperature swings leading to an eventual shutdown.

Even moderate ambient temperature swings can have a significant effect on cooling performance (both in discharge cooling as well as piping systems) and corresponding compression system consistent performance. This means that part of the success of any capacity management system is predictable temperature stability. This is even more important in an acid gas compressor where temperature, composition, and water content are closely connected. As well, long suction headers can introduce a time lag or system delay into the response of the compressors; long piping runs can also provide for condensation, fluid buildup, slugging, and carryover.

Poor or incorrect designed recycle systems within the compressor can have an effect on system Stage 1 suction temperatures. Excessive use of the cold recycle arrangement can begin to swing the suction temperature. It is exceedingly difficult for a compressor aftercooler to manage this as the temperature instability will be pushed through the machine. This, in turn, will likely generate more system instability.

1.4.4 Initial Suction Pressure Variances

First-stage suction pressure has the most direct impact on system capacity. At the lower suction pressures common in most AGI systems, even a 10 kPa decrease in suction pressure will have a major effect on available system capacity. Available compressor capacity drops by almost 8% with a similar power drop with only a 10 kPa drop – this reinforces the need for good suction pressure control as well as consistent system performance. Given the low system pressures, the system must control to a very precise pressure. While 50–100 kPa[g] swings in a normal natural gas compressor application suction pressure are not uncommon (and are not usually considered a problem), this system is expected to control AGI compressor suction pressure within a 3–7 kPa range or tighter. Large swings in control will cause feedback to the amine unit and cause process instability resulting in sour amine, acid gas and main gas flaring, off-spec products, and increased operating costs. In some facilities, the acid gas compressor is used to directly manage the pressure in the regeneration system. This can be quite successful and avoids any additional pressure drops on the suction of the acid gas compressor system or pressure increases in the amine regeneration system; however, it takes careful tuning of the compressor control loops. Suction pressure loop stability is one of the most important criteria in compressor design planning. Equally important is the need to perform a full range of system sensitivity runs to establish capacity vs. suction pressures.

1.4.5 Amine Plant Generated Instability

Amine processing systems can display a high degree of inherent instability. This is generated by a number of factors including poor designs, insufficient residence time, foaming, control instability, off-design operation, ambient sensitivity, amine chemistry issues, and many others. As such, it’s not uncommon for an amine process package to experience some process swings. Some of these are due to control system bounces, while others are due to ambient temperature variations, thermal momentum, and system dynamics. In many cases, this instability generates rapid changes in acid gas flows and compositions. The acid gas compression system is expected to manage this seamlessly.

Many amine plant designs utilize an MDEA-based solvent (either generic or proprietary) to manage the H2S pickup and CO2 slip. While the H2S reaction is typically an instantaneous one (as long as the amine is relatively lean), the degree of CO2 pickup is based on system kinetics and fluid chemistry. These kinetic factors are triggered by mass transfer, thermodynamics; factors which are influenced by system physical parameters like residence times, weir heights, tray counts, level control response, and of course, temperature. While reboiler temperature will be relatively stable, many of the other system temperatures including lean amine cooling and reflux condensing are variable. Thus, many of the factors that affect CO2 slip are also driven by system factors that are also changing. In many cases, the temperature, pressure, flow and composition are changing simultaneously. It will be almost impossible to have a steady or near-steady-state operation with multiple integrated changes happening simultaneously.

Amine plant regeneration systems often have a considerable thermal time lag. This is due to reboiler kinetics and response to increased heat requirements, large thermal mass of process fluid and steel, and delays in temperature response to changes in inputs. In some cases, this thermal time lag results in system instability and temperature swings. It should be noted that increased heat input will not change the reboiler temperature but will drive increasing amounts of steam into the system until the overhead temperature begins to register the increase. In some cases, the control system will overheat the system until a series of thermal swings becomes evident and the system stability is impaired. These thermal lags usually result in system swings in acid gas rate, composition and conditions.

In addition to this, amine system contaminants, like heat stable salts, can alter amine solution chemistry resulting in erratic performance, poor absorption, off-spec products, increased corrosion, and operating upsets. The use of anti-foams (silicone or otherwise), corrosion inhibitors, physical solvent enhancers, and other “process chemicals can also alter the amine plant’s performance. Many facilities use variants of MDEA which uses a mass transfer based kinetic based CO2 pickup rather than a conventional primary or secondary amine. This means that system turndown can potentially affect the pickup of CO2 and consequently the composition and phase behaviour of the acid gas.

Certain amine plant designs utilize amine solution chemistry that allows for the pickup of mercaptans like Shell Sulfinol™ or Huntsman DGA™. In many cases, these physical solvent additives or hybrid solutions allow for the increased pickup of heavy hydrocarbons as a co-adsorbent. While these hydrocarbons do not typically make up a significant % of the acid gas flow, they can have other deleterious impacts including:

Altered phase envelopes with shifting hydrocarbon dew points.

Altered water equilibrium data

Poor wellbore density

Finally, the discovery of new reserves can force the amine unit into an operational regime that was not conceived during the initial design. The redeployment of used equipment has a similar challenge in that seldom is this equipment a perfect fit for the process.

Depending on the level and type of contamination, the acid gas system has considerable potential for instability simply generated from the upstream amine system.

1.5 Process Output Variables

1.5.1 Discharge Pressure Variances

In most cases, compressor discharge is held steady either by a compressor discharge block valve or a wellhead PCV. In reality, this PCV really just sets a minimum discharge pressure that will keep the compressor in some sort of steady-state condition. The actual discharge pressure can and will vary depending on the injectability of the fluid into the formation. The operator, for the most part, has very little control over this pressure. Should the formation experience damage, become plugged with debris or contaminants, or become inoperable in some way, then this compressor discharge pressure will rise to try and push the acid gas into the formation. The nature of the injection process is that the wellbore fluid head +the discharge pressure, must overcome the friction losses, and the reservoir pressure. Thus, the success of the injections scheme is directly related to the density of the wellbore fluid, which in turn, is directly related to temperature, pressure, and composition.

The introduction of non-condensable gas into the wellbore will drive down the fluid level as the gas breakout sits in the top of the fluid level. The resulting loss of fluid head will require a corresponding increase in compressor discharge pressure. Similar to this issue, the density of the fluid in the wellbore is a function of fluid temperature – acid gas arriving hotter or colder than anticipated will alter the fluid density. Luckily in most AGI applications, the fluid pipeline velocity is so slow that the acid gas often shows up at the wellsite at ground temperature regardless of the temperature entering the pipeline. However, in shorter injection schemes, the varying temperature of the fluid can have dramatic effects on both the fluid density as well as the injection pressure.

Varying discharge pressure will certainly make itself known through interstage pressure variances. This, in turn, will alter the phase equilibrium of the acid gas, will alter the water capacity of the fluid, and will alter the cooling and water extraction needs of the system. Varying discharge pressure may move the system into a different part of the phase envelope and may impair system performance – for example, on an interstage dehydration system that needs to operate at a certain point in the phase envelope for optimal water removal. In an acid gas pumping application, a pressure move that results in fluid at pump suction at the critical point, will almost certainly result in unpredictable pump performance. As well, varying discharge pressure can have an effect on recycle valve performance.

Depending on the type of acid gas injection scheme, reservoir life and capacity can also have an effect on system performance. As the reservoir begins to fill and achieves ultimate capacity, we can expect bottom hole pressure to rise. This is seldom a rapid change but it is not controllable and will obviously result in an increase in tubing head injection pressure and ultimately a loss of injectability.

An additional variable, not often considered, is the effect of pushing acid gas into the formation. Depending on the permeability, the fluid, and the flow, it may take significant pressure to overcome the sandface differential. Varying flows and to a lesser degree, composition, can make wellhead pressure variable. The presence of wellbore issues, while seldom predictable, can also result in flow based pressure issues. Downhole check valves, improperly performing tubular equipment, undersized tubing and contaminants like solid sulphur can make the system very dynamic, and very unpredictable.

1.6 AGI Process Associated Variables

1.6.1 Variable Response Mechanisms

In many process systems, process response to a single input can be approximated by a sinusoidal wave. While process tuning attempts to reduce this offset, it is not uncommon to see this type of response in a cooler. In many cases, this sinusoidal response is small enough to be insignificant (see Figure 1.1).

Figure 1.1 Process Instability - Single Variable.

In some cases, the instability of the multiple loops can actually cancel each other out resulting in a system that “appears” to have a steady-state response. As an example, this could represent an increase in suction gas flow combined with a decrease in suction temperature thus negating the swings in volumetric flow. See Figure 1.2 for a dual variable system.

Figure 1.2 Process Instability - Dual Variable – Destructive Offset.

Alternately, in some cases, the variable frequency is identical and in a similar fashion and the resulting overall system response can be additive. This can be represented by the response to a cooler control issue combined with a capacity control issue. The overall response is dramatically worse as can be seen in Figure 1.3 (light grey line):

Figure 1.3 Process Instability - Dual Variable - Constructive Offset.

However, in other cases, depending on a number of factors and process variables, the instability is propagated through the system until the final process has departed dramatically from its original setpoint (light grey line), see Figure 1.4. This is a combination of multiple variables like compressor capacity control (speed plus recycle), scrubber level control, and cooler control.

Figure 1.4 Process Instability - 3 Variables.

Finally, Figure 1.5 shows a series of multiple variables showing the potential overall system response on the light grey line. This is the combined