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Flow and Transport for CO2 Storage
Thursday 29th October – Friday 30th October 2015, London
www.ukccsrc.ac.uk
Agenda.................................................................................................................................................................................................... 2Speakers and Chairs.................................................................................................................................................................................................... 3Delegate List.................................................................................................................................................................................................... 6Martin Blunt - Pore-scale processes....................................................................................................................................................................................................... 8Marc Hesse - Long-term safety of geological CO2 storage....................................................................................................................................................................................................... 50Jeroen Snippe - Multiphase flow modelling of calcite dissolution patterns....................................................................................................................................................................................................... 129
AGENDA 29th October 2015 12:00 - 13:00 Arrival & registration 13:00 - 13:15 Introduction to meeting – Catriona Reynolds (Imperial College London) 13:15 - 14:00 Pore-scale dynamics and the interpretation of flow processes - Martin Blunt (Imperial College
London) 14:00 - 14:45 TBC - Tony Espie (BP) 14:45 - 15:30 20 years and 20 million tonnes: Statoil storage experience - Andrew Cavanagh (Statoil) 15:30 - 16:00 Break Poster & Session 16:00 - 16:45 Characterising flow behaviour for gas injection: relative permeability of CO2-brine and N2-
water in heterogeneous rocks - Catriona Reynolds (Imperial College London) 16:45 - 17:30 Long-term safety of geological CO2 storage: Lessons from Bravo Dome Natural CO2 reservoir -
Marc Hesse (University of Texas at Austin) 17:30 - 18:30 Evening reception Poster Session 19:00 onwards Dinner (Med Kitchen, 25–35 Gloucester Road, London SW7 4PL, Tel: 020 7589 1383) 30th October 2015 08:30 - 09:00 Coffee Poster Session 09:00 - 09:45 Monitoring and modelling the flow and dissolution of geologically stored CO2 - Jerome Neufeld
(University of Cambridge) 09:45 - 10:30 Enhanced storage performance through CO2-Enhanced Oil Recovery - Stuart Haszeldine
(University of Edinburgh) 10:30 - 11:15 Migration of CO2 through layered sedimentary sequences - Chris MacMinn (University of
Oxford) 11:15 - 11:45 Break Poster Session 11:45 - 12:30 Multiphase Flow Modelling of Calcite Dissolution Patterns from Core Scale to Reservoir Scale -
Jeroen Snippe (Shell) 12:30 - 13:15 Musings on the properties of a mobile CO2 layer flowing in porous sand: integrating
monitoring and modelling - Andy Chadwick (BGS) 13:15 - 13:30 Meeting Close - Sam Krevor (Imperial College London)
SPEAKERS AND CHAIRS Martin J. Blunt Martin Blunt joined Imperial in June 1999 as a Professor of Petroleum Engineering. He served as Head of the Department of Earth Science and Engineering from 2006-2011. He Previous to this he was Associate Professor of Petroleum Engineering at Stanford University in California. Before joining Stanford in 1992, he was a research reservoir engineer with BP in Sunbury-on-Thames. He holds MA and PhD (1988) degrees in theoretical physics from Cambridge University. Professor Blunt's research interests are in multiphase flow in porous media with applications to oil and gas recovery, contaminant transport and clean-up in polluted aquifers and geological carbon storage. He performs experimental, theoretical and numerical research into many aspects of flow and transport in porous systems, including pore-scale modelling of displacement processes, and large-scale simulation using streamline-based methods. He has written over 200 scientific papers and is Editor of Transport in Porous Media. In 2011 he was awarded the Uren Award from the Society of Petroleum Engineers for outstanding contributions to the technology of petroleum engineering made before the age of 45. Andrew Cavanagh Dr Andrew Cavanagh - I hold a doctorate in petroleum system analysis from the University of Edinburgh (2003). I am a senior research scientist on CO2 Storage for Statoil, based in Trondheim since 2013. My focus is on subsurface flow modeling, CCS and CO2 EOR innovation. Before joining Statoil, I worked for Permedia and Landmark, a small research group in Ottawa, Canada, and a large service company in Denver, Colorado. Back then, I designed simulators for the oil and gas industry. I have a background in basin-to-reservoir scale fluid flow modeling and an interest in CO2 management, which was sparked by post-doctoral research at GFZ Potsdam on ice sheets and petroleum systems in the Arctic as geological climate change drivers. Andy Chadwick Andy Chadwick has over thirty years’ experience in most aspects of seismic geophysics, structural geology and basin analysis and is currently an Individual Merit Research Scientist at the British Geological Survey. Since 1998 he has become increasingly involved with underground CO2 storage, participating in many European CO2 research projects and a number of others funded by the UK and overseas governments, research councils and industry. Andy’s main interests lie in storage site performance prediction and monitoring. Current research directions include quantitative analysis of time-lapse seismic data to characterise CO2 plumes, and history-matched flow modelling to understand detailed modes of CO2 migration in reservoirs. Andy has advised a number of national and international regulatory bodies and is particularly interested in developing pragmatic integrated monitoring systems and strategies for industrial-scale storage sites that meet anticipated regulatory requirements. He has published over 150 scientific papers and books on a range of topics including more than sixty on CCS. Tony Espie Tony is an Advisor on CO2 Storage within BP Alternative Energy based at Sunbury in the UK where he manages a technology development programme on performance prediction for storage systems. He has been engaged in developing CO2 capture and storage technology since the mid 1990’s. This has included source-sink matching for capture and storage within BP, the evaluation of CO2 EOR options in Alaska, the North Sea, and the Middle
East and assessing saline aquifer options in Australia. He initially trained as a Chemical Engineer at the University of Canterbury in New Zealand where he completed a PhD in the field of liquid-liquid separations technology. His professional career started in the nuclear industry in the United Kingdom modelling coupled heat transfer and flow processes in the UK designed Advanced Gas Cooled Reactors. Tony joined BP as a reservoir engineer in 1985 where his responsibilities focused upon technology development to enhance and optimise oil and gas recovery processes. This included characterising the mechanisms controlling multiphase displacement in porous media and the design and monitoring of gas injection processes for Enhanced Oil recovery. Stuart Haszeldine Stuart has 25 years’ experience working with subsurface information from basin-scale to field-scale in hydrocarbon extraction and in waste disposal. He was awarded the Scottish Science Prize in 1999, and elected Fellow of the Royal Society of Edinburgh in 2003. Since 2005 he has created the UK's largest University group examining CO2 storage geology, with a particular focus on natural analogues and seepage processes through overburden. He is currently co-leader of the Scottish Centre for Carbon Storage, lead scientist on CO2 storage for the UK Energy Research Centre, and co-leader of the academic network UKCCSRC. He served as advisor to the 2005-6 UK Parliament Science and Technology Committee on CO2 capture and storage. Several pieces of evidence have been submitted to UK government consultations on CCS Marc Hesse Marc Hesse is a computational geoscientist interested in the dynamics of porous media in geological and environmental processes. Due to his broad training, his work bridges both the classical solid-earth sciences and the environmental sciences and energy geosciences. Marc believes that porous media provide a unifying theme across the geosciences and he is actively developing and teaching a range of new and innovative courses on porous media from a geoscience perspective. Marc initially studied Geology at the Technical University of Munich and the University of Edinburgh where he has developed an interest in a broad range of geological phenomena. Recognizing the importance of fluid dynamics and mathematical modeling in the study of porous media Marc shifted towards applied mathematics and its applications in the geosciences during his graduate education at the Massachusetts Institute of Technology, the University of Cambridge, and Stanford University and during his postdoc at Brown University. In 2009 Marc joined the Jackson School of Geosciences and the Institute of Computational Engineering and Sciences at the University of Texas. Chris MacMinn Chris earned his PhD from MIT, where he worked with Ruben Juanes on the fluid dynamics of geological CO2 storage. He was then a Postdoctoral Fellow of the Yale Climate & Energy Institute (Yale University) before joining the University of Oxford in October 2013. His research is currently focused on various aspects of the coupling between flow, transport, and deformation in the subsurface.
Jerome Neufeld Dr Jerome Neufeld is a University Lecturer and Royal Society University Research Fellow at the BP Institute, the Department of Earth Sciences, and the Department of Applied Mathematics and Theoretical Physics at the University of Cambridge. His research focuses on the coupling of thermodynamics and fluid dynamics in multiphase systems found within and on the Earth using theoretical and experimental techniques closely linked with field observations. His research focuses on the flow of multiphase fluids with particular attention on the geological storage of carbon dioxide, and the solidification of multicomponent fluids such as the solidification of sea ice in the polar oceans, the solidification and texturing of crystals in magma chambers, the growth of the Earth’s inner core and the solidification of iron asteroids. More recently he has modelled the viscous deformation of continental collisions and the propagation of magma in the near subsurface. Dr Neufeld has a PhD in geophysics from Yale University and a B.A.Sc. in engineering science from the University of Toronto, and currently is an Official Fellow in Physics at St. Catharine's College, Cambridge. Cat Reynolds Cat is a final year PhD candidate at Imperial College London working in the Department of Earth Science and Engineering and the Qatar Carbonates and Carbon Storage Research Centre. Her research focuses on the multiphase flow behaviour and relative permeability characteristics of CO2 and brine at the core and pore scales, with particular application to geologic CO2 storage in sandstones. Cat holds an MSci in Natural Sciences from the University of Cambridge (2011), and an MSc in Petroleum Geoscience from Imperial College London (2012). Jeroen Snippe Jeroen Snippe is a senior Reservoir Engineer in Shell Global Solutions International B.V. (Rijswijk, Netherlands) and Shell Subject Matter Expert in Integrated Reservoir Modelling. He holds a PhD in theoretical physics (1997) from Leiden University (Netherlands). After his PhD he joined the Shell simulator development team, focusing on static-dynamic model integration, upscaling and gridding. From 2003 to 2009 he worked in Aberdeen on several North Sea oil and gas reservoirs (well & reservoir management and field redevelopment). In 2009 he moved into his current role - research and deployment of Reactive Transport Modelling technologies - and leads a small team on this topic. The team collaborates with several universities, defines and executes complementary internal research, and supports Shell projects on CCS and acid gas injection as well as water injection projects.
DELEGATE LIST
First Name Organisation Pedro Abrantes CO2track Simeon Agada Imperial College London Ali Al-Menhali Imperial College London Mohammed Dahiru Aminu Cranfield University Mike Bickle Cambridge Martin Blunt Imperial College London Maartje Boon Imperial College London Emilie Brady UKCCSRC Andrew Cavanagh Statoil Jiajun Cen Imperial College London Andy Chadwick British Geological Survey Florence Chow Imperial College London Laurence Cowton University of Cambridge John Crawshaw Imperial College London Diganta Das Loughborough University Yacine Debbabi Imperial College London Emmanuel Efika Imperial College London Tony Espie BP Group Technology Simon Franchini Imperial College London Davide Gamboa British Geological Survey Mojgan Hadi Mosleh Imperial College London Stuart Haszeldine SCCS/University of Edinburgh Marc Hesse University of Texas at Austin Vivek Jaiswal LR-Senergy Luke Jenkins University of Oxford Gareth Johnson University of Edinburgh/SCCS Mark Kelman Sam Kevor Imperial College London Rachel Kilgallon University of Edinburgh Peter Lai Imperial College London Qingyang Lin Imperial College London Fiona Llewellyn-Beard University of Cambridge Iain Macdonald QCCSRC, Imperial College London Chris MacMinn University of Oxford Geoff Maitland QCCSRC Hannah Menke Imperial College London Jerome Neufeld University of Cambridge Anh Thy Nguyen Ngo Petro-vision Vahid Niasar University of Manchester JP Nijjer University of Cambridge Ben Niu Imperial College London Thomas Oliveira Imperial College London Kumar Patchigolla Cranfield University Bhavna Patel Imperial College London Joao Paulo Pereira Nunes Imperial College London Ronny Pini Imperial College London
Kazeem Rabiu Loughborough University Cat Reynolds Imperial College London Tarik Saif Imperial College London Saeed Salimzadeh Imperial College London Yolanda Sanchez-Vicente Imperial College of London Seyed Shariatipour Coventry University Olivia Sloan Imperial College London Jeroen Snippe Shell Weparn Julian Tay Imperial College London Konstantina Vogiatzaki City University Hayley Vosper British Geological Survey
UK Carbon Capture and Storage Research Centre (UKCCSRC) The UKCCSRC brings together over 1000 members including over 200 of the UK’s world-class CCS academics to provide a national focal point for CCS research and development. The Centre is a virtual network where academics, industry, regulators and others in the sector collaborate to analyse problems devise and carry out world-leading research and share delivery, thus maximising impact. A key priority is supporting the UK economy by driving an integrated research programme and building research capacity that is focused on maximising the contribution of CCS to a low-carbon energy system for the UK. The UKCCSRC is supported by the Engineering and Physical Sciences Research Council (EPSRC) www.epsrc.ac.uk as part of the Research Councils UK Energy Programme, with additional funding from the Department of Energy and Climate Change (DECC) www.decc.gov.uk for the UKCCSRC PACT Facilities www.pact.ac.uk
www.ukccsrc.ac.uk
Pore-scale processes A revolution in describing multiphase flow
Martin Blunt, Matthew Andrew, Branko Bijeljic, Sam Krevor,
Catriona Reynolds, Ali Raeini, Hu Dong, João P. Nunes, Kamaljit Singh
and Hannah Menke
Department of Earth Science and Engineering
Imperial College London and
iRock Technologies, Beijing
Ten-year, $70 million programme: 2008 – 2018. To understand carbon dioxide storage in a Qatari context (carbonates). Major experimental and modelling activity. Based at Imperial College. Work all published in the public domain.
Multidisciplinary (Chem. Eng. / Earth Sci. & Eng.). Three major themes: rocks, fluids and rock-fluid interaction. Four dedicated lecturers, other faculty, post-docs and PhD students (some from Qatar): involves >70 researchers.
3
Nat Geo Oct 2013
Status of Impact – Sea-level rise
4
Abu Dhabi Environment Agency
2009
Abu Dhabi Environment Agency
2009
5
Motivation
Historically high oil prices, even at $40/barrel – peak oil per person in
1979 and current discoveries running at half global production (30 billion
stb/year). Need to produce more of the oil in existing fields.
Exploitation of unconventional oil and gas.
Wise use of groundwater.
Global-scale CO2 storage.
All involve understanding of flow of fluids in porous rocks.
New tools
Multi-scale imaging – particularly ability to image the pore space of rock
and fluids at 10 nm to micron resolution.
Public-domain availability of good-quality software for scientific
computing – changes the way we develop computational models.
What is digital rock analysis? A physically-based model for flow,
based on pore-scale displacement. A nm – cm model (6 orders of
magnitude in scale). A necessary complement and input to a field-scale
geological/reservoir model (cm – km, or another 6 orders of magnitude).
What we can do Original work on 3D X-ray microtomography by Flannery et al. (1987)
states in conclusion: “we believe that it will be possible to study contained
systems under conditions of temperature, pressure, and environment
representative of process conditions.” Can now!
Will discuss imaging and flow simulation: transport, reaction and
multiphase flow.
Flow
Transport
Reaction
Structure
Imperial College multi-scale imaging lab
Start with the fundamentals – understand processes experimentally at the
pore scale. Micron-to-metre imaging with in situ displacement at reservoir
conditions.
Micro-CT – Flow loop
10
Imaging and computing
Bench-top micro-CT scanners are
convenient, no time limitations and
modern systems have optics.
Synchrotron sources. Bright, mono-
chromatic and fast.
Computationally, not interested in
GPU, parallel, but better algorithms.
Availability of excellent public-
domain solvers:
algebraic multigrid,
OpenFoam
Navier-Stokes solver.
Fluid mechanics:
unstructured
adaptive grids.
Blunt et al., Adv. Water Res. 2013
Images and networks for carbonates
Estaillades Ketton Mount Gambier
Represent the pore space topologically and compute displacement semi-
analytically through the network. Also accommodate micro-porosity.
Transport – rocks and people
13
How to get to Imperial from
Heathrow airport?
Direct simulation: use a shallow
seismic image of the subsurface
of London?!
London Underground map (the
macro-pores) plus a local map
(the micro-pores)
Waterflooding and wettability
Complex displacement sequences, shown here for a single idealized
pore. What are the contact angles? Can now measure them in situ.
Altered wettability surfaces after primary drainage:
mixed-wettability.
Relative permeability is
governed by the interplay
of displacement,
structure and wettability,
which can vary across the
field
Water-wet two-phase predictions
Experimental data from Berea sandstone cores (Oak, 1990)
– No tuning of network (Øren and Bakke, 2003) necessary
– The fluids are water and oil
– Water-wet data – predictions made with θa = [50°, 80°]
0 0.2 0.4 0.6 0.8 10
0.2
0.4
0.6
0.8
1
Water Saturation
Rela
tive P
erm
eabili
ty
Primary drainage
0 0.2 0.4 0.6 0.8 10
0.2
0.4
0.6
0.8
1
Water Saturation
Rela
tive P
erm
eabili
ty
ExperimentalPredicted
p
p
rp
p PKk
q
Secondary waterflooding
Valvatne and Blunt, Water Resources Research (2004)
The tyranny of scale
Typically have a million-fold variation in length scale, from 10 nm for
the smallest micro-pores to cms for whole cores.
Need to upscale.
No one method can capture complex displacement processes over
this range of scales.
Whole core – 1 cm Macro pore - 1 mm Micro pore - 10 m
Direct simulation and networks
• Cannot compute multiphase flow directly on images that can
resolve the smallest pores, and processes within them.
• Direct simulation would require of order 1021 grid blocks. No, not
even the fastest in-the-future computer will ever be able to do this.
• Need to combine methods: direct simulation for pore-scale events,
“simple” images; network modelling to upscale behaviour and
capture the correct displacement sequence.
Back to the science - dispersion Direct simulation on the pore-space images.
Stokes solver, streamline tracing, random motion for diffusion.
Sandpack Sandstone (Bentheimer) Carbonate (Portland)
Carbonate images and flow fields
5 mm
Ketton
Mt Gambier
Estaillades Indiana
ME1 Guiting
Particle trajectories in the pore space
Combine analytical
streamline tracing with
a random hop to
represent diffusion.
Solute particles travel
longer distances for
larger Pe number.
𝑃𝑒 =𝑣𝐿
𝐷𝑚= advection
diffusion
v = velocity;
L = grain/pore size;
Dm = molecular diffusion coefficient.
Include reaction by allowing particles within a diffusion distance to react,
including solid. Probability of reaction relates to reaction rate.
Concentration
profiles
Bentheimer
Sandstone
Bead pack Portland
Carbonate
Compare prediction of
concentration vs.
distance for different
times and rock types
against NMR
experiments.
Can make first
principles predictions
once the pore
geometry is imaged.
Bijeljic et al. PRL (2011); PRE
(2013); WRR (2013).
Time
Reaction with the solid: Dissolution regimes
22
Daccord et al.,
Chem. Eng. Sci, (1993)
Maheshwari et al.,
Chem. Eng. Sci, (2013) compact
uniform
wormhole
𝑃𝑒 =𝑣𝐿
𝐷𝑚= advection
diffusion
Da = reaction
advection
Compare pore-scale experiments and models. In the models if a particle
hits solid in the diffusive step, dissolve solid after a given number of hits:
determines reaction rate.
Pore-scale dissolution experiments Flow rate: 0.5 ml/min for 2.5 hrs [Pe ~103; Da ~10-4]
Brine composition: 1% KCl 5% NaCl brine saturated with CO2
at 10 MPa and 50oC [pH=3.1]
Ketton carbonate - homogeneous Portland carbonate - heterogeneous
Menke et al., EST (2015)
Sim
ula
tio
n
Exp
eri
men
tal
Model vs. experiment
Dissolution – parallel to flow direction
Ketton carbonate – chanelling Portland carbonate – compact dissolution
0.05 ml/min [Pe ~102; Da ~10-3]
Three-dimensional results (low flow rate)
1.3
mm
0.67 mm
Small Pe regime only “face dissolution” - Whole grains are being dissolved
No significant impact in permeability.
Simulations: Estaillades Pe, Péclet = 1, slow flow
1.3
mm
0.67 mm
Simulations: Estaillades Pe, Péclet = 50
Simulations: Estaillades Pe, Péclet = 280, fast flow
High Pe regime see more uniform dissolution, as the reactant can penetrate the
rock before reacting. As seen experimentally.
Trapped CO2 clusters – colour indicates size
Pentland et al., Geophysical Research Letters (2011)
How much is trapped and
how much can be stored?
Results in sandstones
(Doddington, Bentheimer
and Berea).
After drainage After waterflooding
20 mm
0.0
0.2
0.4
0.6
0.0 0.5 1.0
Sn
wr
Snwi
C. Pentland (2011)@ 70 C
Rehab results @ 70C
Can study many systems – Bentheimer and Doddington
Can study many systems – Estaillades and Ketton
Can study many systems – Portland
Andrew et al.,
Geophysical Research
Letters (2011); IJGGC (2014)
Curvature, contact angle and validation Can also use high-resolution images to
determine: curvature – capillary pressure,
and local pressure for each ganglion; and
surface contacts to determine contact
angles.
Andrew et al.,
AWR (2014)
Residual oil in a mixed-wet system
Direct simulation (volume of
fluid) of trapping
Measurement of contact angle
Dynamic Tomography at Synchrotron Sources
35
Synchrotron Experimental
Team:
Matthew Andrew
Hannah Menke
Cat Reynolds
Kamal Singh
Branko Bijeljic
Martin Blunt
Connected pathway and ganglia flow
Scan time ≈ 20 s, Time step = 43 s,
10 PV
Interfacial curvature
Equilibrium capillary pressure change
38
Distal (non-local) snap-off
39
3D X-ray Micro-CT imaging of a rock sample
Does it matter?
40
Enhanced Oil Recovery
Carbon Storage
http://energy.gov/
Contaminant Transport
http://www.euwfd.com/html/groundwater.html
Shale oil and gas
Conclusions
New tools – both experimentally and numerically allow us to
observe and model flow and transport in great detail from the pore
scale upwards.
Huge practical challenges also drive the science.
We are on the cusp of a revolution.
Acknowledgements
Qatar Petroleum, Shell and the Qatar Science and Technology Park
under the Qatar Carbonates and Carbon Storage Research Centre
Long-term safety of geological CO2 storage:Lessons from Bravo Dome Natural CO2 reservoir
Marc A. Hesse
Department of Geological SciencesInstitute for Computational Engineering & Sciences
October 29, 2015
Marc A. Hesse UKCCSRC Workshop October 29, 2015 1 / 40
Outline
1 IntroductionMotivationBravo Dome natural CO2 field in New Mexico
2 Dissolution trapping at Bravo DomeMagnitude of CO2 dissolutionMechanism of solubility trapping at Bravo DomeRate of CO2 dissolution
3 Pressures in natural CO2 reservoirsReservoir compartmentalizationOrigins of subhydrostatic pressures
4 Implications for geological CO2 storage
Marc A. Hesse UKCCSRC Workshop October 29, 2015 2 / 40
AcknowledgementsFunding:National Science Foundation - Hydrologic SciencesDepartment of Energy - Basic Energy Sciences
Energy Frontier Research Center:Center for Frontiers in Subsurface Energy Security
Bravo Dome collaborators:Kiran Sataye, Daria Ahkbari, Kimberly Lankford, MartinCassidy, Toti Larson, Dani Stoeckli, Changli Yuan, GaryPope, OXY Bravo Dome team
Papers:Sathaye, Hesse, Cassidy & Stockli (2014) PNASSathaye, Larson, & Hesse (201X) EPSL Ahkbari & Hesse(201X) in prep
Marc A. Hesse UKCCSRC Workshop October 29, 2015 3 / 40
Outline
1 IntroductionMotivationBravo Dome natural CO2 field in New Mexico
2 Dissolution trapping at Bravo DomeMagnitude of CO2 dissolutionMechanism of solubility trapping at Bravo DomeRate of CO2 dissolution
3 Pressures in natural CO2 reservoirsReservoir compartmentalizationOrigins of subhydrostatic pressures
4 Implications for geological CO2 storage
Marc A. Hesse UKCCSRC Workshop October 29, 2015 4 / 40
Outline
1 IntroductionMotivationBravo Dome natural CO2 field in New Mexico
2 Dissolution trapping at Bravo DomeMagnitude of CO2 dissolutionMechanism of solubility trapping at Bravo DomeRate of CO2 dissolution
3 Pressures in natural CO2 reservoirsReservoir compartmentalizationOrigins of subhydrostatic pressures
4 Implications for geological CO2 storage
Marc A. Hesse UKCCSRC Workshop October 29, 2015 5 / 40
Trapping contribution and time-scales
IPCC special report Reservoir simulation Theoretical analysis
100 101 102 103 104
100%
80%
60%
40%
20%
0%
Frac
tion
of C
O2 tr
appe
d
Time since injection [yrs]
free CO2
solubility trapping
residual trapping
mineral trapping
100%
80%
60%
40%
20%
0%101 102 103 104
Time since injection [yrs]
Frac
tion
of C
O2 tr
appe
d free CO2
solubility trapping
residual trapping
mineral trapping
100%
80%
60%
40%
20%
0%1 3 9
Injection periods [-]
Frac
tion
of C
O2 tr
appe
d
solubility trapping
residual trapping
free CO2
Benson et al. (2005)IPCC Special Report
Kumar et al. (2005)SPE Journal, 10(3)
MacMinn et al. (2011)J. Fluid Mech., 688
Constrain trapping rates at Bravo Dome using field observations!
Marc A. Hesse UKCCSRC Workshop October 29, 2015 6 / 40
Trapping contribution and time-scales
IPCC special report Reservoir simulation Theoretical analysis
100 101 102 103 104
100%
80%
60%
40%
20%
0%
Frac
tion
of C
O2 tr
appe
d
Time since injection [yrs]
free CO2
solubility trapping
residual trapping
mineral trapping
100%
80%
60%
40%
20%
0%101 102 103 104
Time since injection [yrs]
Frac
tion
of C
O2 tr
appe
d free CO2
solubility trapping
residual trapping
mineral trapping
100%
80%
60%
40%
20%
0%1 3 9
Injection periods [-]
Frac
tion
of C
O2 tr
appe
d
solubility trapping
residual trapping
free CO2
Benson et al. (2005)IPCC Special Report
Kumar et al. (2005)SPE Journal, 10(3)
MacMinn et al. (2011)J. Fluid Mech., 688
Constrain trapping rates at Bravo Dome using field observations!
Marc A. Hesse UKCCSRC Workshop October 29, 2015 6 / 40
Outline
1 IntroductionMotivationBravo Dome natural CO2 field in New Mexico
2 Dissolution trapping at Bravo DomeMagnitude of CO2 dissolutionMechanism of solubility trapping at Bravo DomeRate of CO2 dissolution
3 Pressures in natural CO2 reservoirsReservoir compartmentalizationOrigins of subhydrostatic pressures
4 Implications for geological CO2 storage
Marc A. Hesse UKCCSRC Workshop October 29, 2015 7 / 40
Bravo Dome natural gas field, New Mexico
Marc A. Hesse UKCCSRC Workshop October 29, 2015 8 / 40
Introduction Bravo Dome, NM
The numbers:Area: 3600 km2
Gas-water contact: 1700 km2
Reserves: 22 tcf (10 tcf)Largest CO2 field.Top 20 natural gas fields.Essentially pure CO2
Origin: volcanic gas(very high 3He/4He)
Marc A. Hesse UKCCSRC Workshop October 29, 2015 9 / 40
Introduction Bravo Dome, NM
The numbers:Area: 3600 km2
Gas-water contact: 1700 km2
Reserves: 22 tcf (10 tcf)Largest CO2 field.Top 20 natural gas fields.Essentially pure CO2
Origin: volcanic gas(very high 3He/4He)
20 km
Marc A. Hesse UKCCSRC Workshop October 29, 2015 9 / 40
Introduction Bravo Dome, NM
The numbers:Area: 3600 km2
Gas-water contact: 1700 km2
Reserves: 22 tcf (10 tcf)Largest CO2 field.Top 20 natural gas fields.Essentially pure CO2
Origin: volcanic gas(very high 3He/4He)
Marc A. Hesse UKCCSRC Workshop October 29, 2015 9 / 40
Introduction Bravo Dome, NM
The numbers:Area: 3600 km2
Gas-water contact: 1700 km2
Reserves: 22 tcf (10 tcf)Largest CO2 field.Top 20 natural gas fields.
Essentially pure CO2
Origin: volcanic gas(very high 3He/4He)
Marc A. Hesse UKCCSRC Workshop October 29, 2015 9 / 40
Introduction Bravo Dome, NM
The numbers:Area: 3600 km2
Gas-water contact: 1700 km2
Reserves: 22 tcf (10 tcf)Largest CO2 field.Top 20 natural gas fields.Essentially pure CO2
Origin: volcanic gas(very high 3He/4He)
Marc A. Hesse UKCCSRC Workshop October 29, 2015 9 / 40
Introduction Bravo Dome, NM
The numbers:Area: 3600 km2
Gas-water contact: 1700 km2
Reserves: 22 tcf (10 tcf)Largest CO2 field.Top 20 natural gas fields.Essentially pure CO2
Origin: volcanic gas(very high 3He/4He)
Marc A. Hesse UKCCSRC Workshop October 29, 2015 9 / 40
Data available at Bravo Dome, NM
788 wells150 wells with digitized logs42 cored wells10 wells with stratigraphic logs18 wells with noble gas/isotope data3645 permeability and porositymeasurements21 drainage capillary pressure curves40 2D seismic lines
Best data set to constrain the magnitude and rate of solubility trapping.
Marc A. Hesse UKCCSRC Workshop October 29, 2015 10 / 40
Outline
1 IntroductionMotivationBravo Dome natural CO2 field in New Mexico
2 Dissolution trapping at Bravo DomeMagnitude of CO2 dissolutionMechanism of solubility trapping at Bravo DomeRate of CO2 dissolution
3 Pressures in natural CO2 reservoirsReservoir compartmentalizationOrigins of subhydrostatic pressures
4 Implications for geological CO2 storage
Marc A. Hesse UKCCSRC Workshop October 29, 2015 11 / 40
Outline
1 IntroductionMotivationBravo Dome natural CO2 field in New Mexico
2 Dissolution trapping at Bravo DomeMagnitude of CO2 dissolutionMechanism of solubility trapping at Bravo DomeRate of CO2 dissolution
3 Pressures in natural CO2 reservoirsReservoir compartmentalizationOrigins of subhydrostatic pressures
4 Implications for geological CO2 storage
Marc A. Hesse UKCCSRC Workshop October 29, 2015 12 / 40
Estimating dissolution from gas composition
Convective dissolution of CO2
CO2/3He-ratio in the gas
CO2CO2
He HeCO2 CO2
Fraction dissolved: F = 1− [CO2/He]final[CO2/He]initial
≈ 1− 216 ≈ 0.9
Marc A. Hesse UKCCSRC Workshop October 29, 2015 13 / 40
Estimating dissolution from gas composition
Convective dissolution of CO2 CO2/3He-ratio in the gas
CO2CO2
He HeCO2 CO2
0 5 10 15 20 25 30 350
2
4
6
8
10
12
14
16
18
time [hrs]
CO
2/He
in g
as [m
ol/m
ol]
Fraction dissolved: F = 1− [CO2/He]final[CO2/He]initial
≈ 1− 216 ≈ 0.9
Marc A. Hesse UKCCSRC Workshop October 29, 2015 13 / 40
Mapping geochemistry into the reservoir
Gas geochemistry:
Compositional variation in the reservoir
Gilfillan et al. (2009) Nature, 458Lollar & Ballentine (2009) Nature Geosci, 2(8)Cassidy (2006) PhD Thesis U. Houston
Marc A. Hesse UKCCSRC Workshop October 29, 2015 14 / 40
Mapping geochemistry into the reservoir
Gas geochemistry: Compositional variation in the reservoir
2.5
3
3.5
4
4.5
5
0 10 20 30 40 50 60 70Easting (km)
0
10
20
30
40
50
60
70
Nor
thin
g (k
m)
CO2/3 H
109 [-
]
8 MPa
Gilfillan et al. (2009) Nature, 458Lollar & Ballentine (2009) Nature Geosci, 2(8)Cassidy (2006) PhD Thesis U. Houston
Marc A. Hesse UKCCSRC Workshop October 29, 2015 14 / 40
Mapping geochemistry into the reservoir
Gas geochemistry: Compositional variation in the reservoir
10%
20%
30%
40%
50%
0 10 20 30 40 50 60 70Easting (km)
0
10
20
30
40
50
60
70
Nor
thin
g (k
m)
60%
0%
loca
l fra
ctio
n of
gas
dis
solv
ed
Gilfillan et al. (2009) Nature, 458Lollar & Ballentine (2009) Nature Geosci, 2(8)Cassidy (2006) PhD Thesis U. Houston
Marc A. Hesse UKCCSRC Workshop October 29, 2015 14 / 40
Gas mass per area: m = φ̄S̄ρ(p̄)h
Thickness
Volume fraction Density Mass
0 10 20 30 40 50 60 70Easting (km)
0
10
20
30
40
50
60
70
Nor
thin
g (k
m)
20
40
60
80
100
120
thic
knes
s of
gas
col
umn:
h [m
]
Large spatial variations that need to be accounted for in mass balance.
Marc A. Hesse UKCCSRC Workshop October 29, 2015 15 / 40
Gas mass per area: m = φ̄S̄ρ(p̄)h
Thickness Volume fraction
Density Mass
0 10 20 30 40 50 60 70Easting (km)
0
10
20
30
40
50
60
70
Nor
thin
g (k
m)
20
40
60
80
100
120
thic
knes
s of
gas
col
umn:
h [m
]
0
10
20
30
40
50
60
70
Nor
thin
g (k
m)
4%
6%
8%
10%
12%
14%
16%
0 10 20 30 40 50 60 70Easting (km)
gas
volu
me
frac
tion:
φS
Large spatial variations that need to be accounted for in mass balance.
Marc A. Hesse UKCCSRC Workshop October 29, 2015 15 / 40
Gas mass per area: m = φ̄S̄ρ(p̄)h
Thickness Volume fraction Density
Mass
0 10 20 30 40 50 60 70Easting (km)
0
10
20
30
40
50
60
70
Nor
thin
g (k
m)
20
40
60
80
100
120
thic
knes
s of
gas
col
umn:
h [m
]
0
10
20
30
40
50
60
70
Nor
thin
g (k
m)
4%
6%
8%
10%
12%
14%
16%
0 10 20 30 40 50 60 70Easting (km)
gas
volu
me
frac
tion:
φS
0 10 20 30 40 50 60 700
10
20
30
40
50
60
70
Easting (km)
Nor
thin
g (k
m)
100
200
300
400
500
600
700
800
gas
dens
ity [k
g/m
3 ]
Large spatial variations that need to be accounted for in mass balance.
Marc A. Hesse UKCCSRC Workshop October 29, 2015 15 / 40
Gas mass per area: m = φ̄S̄ρ(p̄)h
Thickness Volume fraction Density Mass
0 10 20 30 40 50 60 70Easting (km)
0
10
20
30
40
50
60
70
Nor
thin
g (k
m)
20
40
60
80
100
120
thic
knes
s of
gas
col
umn:
h [m
]
0
10
20
30
40
50
60
70
Nor
thin
g (k
m)
4%
6%
8%
10%
12%
14%
16%
0 10 20 30 40 50 60 70Easting (km)
gas
volu
me
frac
tion:
φS
0 10 20 30 40 50 60 700
10
20
30
40
50
60
70
Easting (km)
Nor
thin
g (k
m)
100
200
300
400
500
600
700
800
gas
dens
ity [k
g/m
3 ]
0 10 20 30 40 50 60 700
10
20
30
40
50
60
70
Easting (km)
Nor
thin
g (k
m)
100
200
300
400
500
600
700
800
900
1000
1100
0
gas
mas
s pe
r uni
t are
a [k
g/m
2 ]
Large spatial variations that need to be accounted for in mass balance.
Marc A. Hesse UKCCSRC Workshop October 29, 2015 15 / 40
Gas mass per area: m = φ̄S̄ρ(p̄)h
Thickness Volume fraction Density Mass
0 10 20 30 40 50 60 70Easting (km)
0
10
20
30
40
50
60
70
Nor
thin
g (k
m)
20
40
60
80
100
120
thic
knes
s of
gas
col
umn:
h [m
]
0
10
20
30
40
50
60
70
Nor
thin
g (k
m)
4%
6%
8%
10%
12%
14%
16%
0 10 20 30 40 50 60 70Easting (km)
gas
volu
me
frac
tion:
φS
0 10 20 30 40 50 60 700
10
20
30
40
50
60
70
Easting (km)
Nor
thin
g (k
m)
100
200
300
400
500
600
700
800
gas
dens
ity [k
g/m
3 ]
0 10 20 30 40 50 60 700
10
20
30
40
50
60
70
Easting (km)
Nor
thin
g (k
m)
100
200
300
400
500
600
700
800
900
1000
1100
0
gas
mas
s pe
r uni
t are
a [k
g/m
2 ]
Large spatial variations that need to be accounted for in mass balance.
Marc A. Hesse UKCCSRC Workshop October 29, 2015 15 / 40
Estimate of the local change in mass: ∆m
∆M =
∫∫∆m dxdy ≈
∫∫(1/F − 1)mf dxdy.
Mass/area: mf Fraction dissolved: F
Change in mass, ∆m
0 10 20 30 40 50 60 700
10
20
30
40
50
60
70
Easting (km)
Nor
thin
g (k
m)
100
200
300
400
500
600
700
800
900
1000
1100
0
gas
mas
s pe
r uni
t are
a [k
g/m
2 ]
10%
20%
30%
40%
50%
0 10 20 30 40 50 60 70Easting (km)
0
10
20
30
40
50
60
70
Nor
thin
g (k
m)
60%
0%
loca
l fra
ctio
n of
gas
dis
solv
ed
As expected, mf is low where F is high → global fraction dissolved is less!
Marc A. Hesse UKCCSRC Workshop October 29, 2015 16 / 40
Estimate of the local change in mass: ∆m
∆M =
∫∫∆m dxdy ≈
∫∫(1/F − 1)mf dxdy.
Mass/area: mf Fraction dissolved: F Change in mass, ∆m
0 10 20 30 40 50 60 700
10
20
30
40
50
60
70
Easting (km)
Nor
thin
g (k
m)
100
200
300
400
500
600
700
800
900
1000
1100
0
gas
mas
s pe
r uni
t are
a [k
g/m
2 ]
10%
20%
30%
40%
50%
0 10 20 30 40 50 60 70Easting (km)
0
10
20
30
40
50
60
70
Nor
thin
g (k
m)
60%
0%
loca
l fra
ctio
n of
gas
dis
solv
ed
50
100
150
200
250
300
350
400
450
00 10 20 30 40 50 60 70
Easting (km)
0
10
20
30
40
50
60
70
Nor
thin
g (k
m)
mas
s lo
ss p
er u
nit a
rea
[kg/
m2 ]
As expected, mf is low where F is high → global fraction dissolved is less!
Marc A. Hesse UKCCSRC Workshop October 29, 2015 16 / 40
Estimate of the local change in mass: ∆m
∆M =
∫∫∆m dxdy ≈
∫∫(1/F − 1)mf dxdy.
Mass/area: mf Fraction dissolved: F Change in mass, ∆m
0 10 20 30 40 50 60 700
10
20
30
40
50
60
70
Easting (km)
Nor
thin
g (k
m)
100
200
300
400
500
600
700
800
900
1000
1100
0
gas
mas
s pe
r uni
t are
a [k
g/m
2 ]
10%
20%
30%
40%
50%
0 10 20 30 40 50 60 70Easting (km)
0
10
20
30
40
50
60
70
Nor
thin
g (k
m)
60%
0%
loca
l fra
ctio
n of
gas
dis
solv
ed
50
100
150
200
250
300
350
400
450
00 10 20 30 40 50 60 70
Easting (km)
0
10
20
30
40
50
60
70
Nor
thin
g (k
m)
mas
s lo
ss p
er u
nit a
rea
[kg/
m2 ]
As expected, mf is low where F is high → global fraction dissolved is less!
Marc A. Hesse UKCCSRC Workshop October 29, 2015 16 / 40
Magnitude of CO2 dissolution at Bravo Dome
1 Mass of gas dissolved at Bravo Dome:∆M = 366± 122 MtCO2.Equivalent to 65 years of emissionsfrom US coal power plant.
2 Total mass of CO2 emplaced at BravoDome is Mt = 1.6± 0.7GtCO2.Equivalent to annual global volcanicCO2 emissions.
3 At Bravo Dome only 22%±7% ofthe emplaced CO2 have dissolved.Much less than the maximum localdissolution in NE.
free CO2 77%
dissolved CO2 23%
Uncertainty is mainly due to variations in height of gas column!
Marc A. Hesse UKCCSRC Workshop October 29, 2015 17 / 40
Magnitude of CO2 dissolution at Bravo Dome
1 Mass of gas dissolved at Bravo Dome:∆M = 366± 122 MtCO2.Equivalent to 65 years of emissionsfrom US coal power plant.
2 Total mass of CO2 emplaced at BravoDome is Mt = 1.6± 0.7GtCO2.Equivalent to annual global volcanicCO2 emissions.
3 At Bravo Dome only 22%±7% ofthe emplaced CO2 have dissolved.Much less than the maximum localdissolution in NE.
free CO2 77%
dissolved CO2 23%
Uncertainty is mainly due to variations in height of gas column!
Marc A. Hesse UKCCSRC Workshop October 29, 2015 17 / 40
Outline
1 IntroductionMotivationBravo Dome natural CO2 field in New Mexico
2 Dissolution trapping at Bravo DomeMagnitude of CO2 dissolutionMechanism of solubility trapping at Bravo DomeRate of CO2 dissolution
3 Pressures in natural CO2 reservoirsReservoir compartmentalizationOrigins of subhydrostatic pressures
4 Implications for geological CO2 storage
Marc A. Hesse UKCCSRC Workshop October 29, 2015 18 / 40
Stratigraphic architecture of reservoir
Porosity and permeability
Capillary entry pressure
10-2 10-1 100 101 102 1030
100
200
[mD]
n = 35460 0.1 0.2 0.30
100
200
[-]
High capillary entry pressure prevents CO2 entry into the siltstone.
Marc A. Hesse UKCCSRC Workshop October 29, 2015 19 / 40
Stratigraphic architecture of reservoir
Porosity and permeability
Capillary entry pressure
10-2 10-1 100 101 102 1030
100
200
[mD]
n = 35460 0.1 0.2 0.30
100
200
[-]
sandsilt
High capillary entry pressure prevents CO2 entry into the siltstone.
Marc A. Hesse UKCCSRC Workshop October 29, 2015 19 / 40
Stratigraphic architecture of reservoir
Porosity and permeability
Capillary entry pressure
10-2 10-1 100 101 102 1030
100
200
[mD]
n = 35460 0.1 0.2 0.30
100
200
[-]42 mD
High capillary entry pressure prevents CO2 entry into the siltstone.
Marc A. Hesse UKCCSRC Workshop October 29, 2015 19 / 40
Stratigraphic architecture of reservoir
Porosity and permeability Capillary entry pressure
10-2 10-1 100 101 102 1030
100
200
[mD]
n = 35460 0.1 0.2 0.30
100
200
[-]42 mD
0.0 0.2 0.4 0.6 0.8 1.00.0
0.5
1.0
1.5
2.0
2.5
[MPa
]
[-]
siltstone
sandstone
High capillary entry pressure prevents CO2 entry into the siltstone.
Marc A. Hesse UKCCSRC Workshop October 29, 2015 19 / 40
Stratigraphic architecture of reservoir
Porosity and permeability Capillary entry pressure
10-2 10-1 100 101 102 1030
100
200
[mD]
n = 35460 0.1 0.2 0.30
100
200
[-]42 mD
0.0 0.2 0.4 0.6 0.8 1.00.0
0.5
1.0
1.5
2.0
2.5
[MPa
]
[-]
siltstone
sandstone
High capillary entry pressure prevents CO2 entry into the siltstone.
Marc A. Hesse UKCCSRC Workshop October 29, 2015 19 / 40
Dissolution into residual brine during emplacement
0 0.1 0.25695
705
715
725
735
745
φ, φg [-]
silt}} sand
B 5 15 25 35 45 55 65 B’500
600
700
800
900
granitic basementbrine
elev
atio
n [m
]
source
distance along cross-section [km]
anhydrite
0 20 40 60 80 100 1200
0.2
0.4
0.6
0.8
1
1.2
Pressure [bar]
CO
2so
lubility[m
ol
kg]
Bravo Dome MeasurmentsDuan et al. (2003): pure waterDuan et al. (2003): 2 molal NaCl
Easting (km)
No
rth
ing
(km
)
0 25 50 750
25
50
75
0
50
100
150CO
2(aq)
[kg/m2]
Marc A. Hesse UKCCSRC Workshop October 29, 2015 20 / 40
Dissolution into residual brine during emplacement
0 0.1 0.25695
705
715
725
735
745
φ, φg [-]
silt}} sand
B 5 15 25 35 45 55 65 B’500
600
700
800
900
granitic basementbrine
elev
atio
n [m
]
source
distance along cross-section [km]
anhydrite
0 20 40 60 80 100 1200
0.2
0.4
0.6
0.8
1
1.2
Pressure [bar]
CO
2so
lubility[m
ol
kg]
Bravo Dome MeasurmentsDuan et al. (2003): pure waterDuan et al. (2003): 2 molal NaCl
Easting (km)
No
rth
ing
(km
)
0 25 50 750
25
50
75
0
50
100
150CO
2(aq)
[kg/m2]
Marc A. Hesse UKCCSRC Workshop October 29, 2015 20 / 40
Dissolution into residual brine during emplacement
0 0.1 0.25695
705
715
725
735
745
φ, φg [-]
silt}} sand
B 5 15 25 35 45 55 65 B’500
600
700
800
900
granitic basementbrine
elev
atio
n [m
]
source
distance along cross-section [km]
anhydrite
0 20 40 60 80 100 1200
0.2
0.4
0.6
0.8
1
1.2
Pressure [bar]
CO
2so
lubility[m
ol
kg]
Bravo Dome MeasurmentsDuan et al. (2003): pure waterDuan et al. (2003): 2 molal NaCl
Easting (km)
No
rth
ing
(km
)
0 25 50 750
25
50
75
0
50
100
150CO
2(aq)
[kg/m2]
Marc A. Hesse UKCCSRC Workshop October 29, 2015 20 / 40
Dissolution into residual brine during emplacement
0 0.1 0.25695
705
715
725
735
745
φ, φg [-]
silt}} sand
B 5 15 25 35 45 55 65 B’500
600
700
800
900
granitic basementbrine
elev
atio
n [m
]
source
distance along cross-section [km]
anhydrite
0 20 40 60 80 100 1200
0.2
0.4
0.6
0.8
1
1.2
Pressure [bar]
CO
2so
lubility[m
ol
kg]
Bravo Dome MeasurmentsDuan et al. (2003): pure waterDuan et al. (2003): 2 molal NaCl
Easting (km)
No
rth
ing
(km
)
0 25 50 750
25
50
75
0
50
100
150CO
2(aq)
[kg/m2]
Marc A. Hesse UKCCSRC Workshop October 29, 2015 20 / 40
Dissolution into residual brine during emplacement
0 0.1 0.25695
705
715
725
735
745
φ, φg [-]
silt}} sand
B 5 15 25 35 45 55 65 B’500
600
700
800
900
granitic basementbrine
elev
atio
n [m
]
source
distance along cross-section [km]
anhydrite
0 20 40 60 80 100 1200
0.2
0.4
0.6
0.8
1
1.2
Pressure [bar]
CO
2so
lubility[m
ol
kg]
Bravo Dome MeasurmentsDuan et al. (2003): pure waterDuan et al. (2003): 2 molal NaCl
Easting (km)
No
rth
ing
(km
)
0 25 50 750
25
50
75
0
50
100
150CO
2(aq)
[kg/m2]
Marc A. Hesse UKCCSRC Workshop October 29, 2015 20 / 40
Dissolution into residual brine during emplacement
0 0.1 0.25695
705
715
725
735
745
φ, φg [-]
silt}} sand
B 5 15 25 35 45 55 65 B’500
600
700
800
900
granitic basementbrine
elev
atio
n [m
]
source
distance along cross-section [km]
anhydrite
0 20 40 60 80 100 1200
0.2
0.4
0.6
0.8
1
1.2
Pressure [bar]
CO
2so
lubility[m
ol
kg]
Bravo Dome MeasurmentsDuan et al. (2003): pure waterDuan et al. (2003): 2 molal NaCl
Easting (km)
No
rth
ing
(km
)
0 25 50 750
25
50
75
0
50
100
150CO
2(aq)
[kg/m2]
Marc A. Hesse UKCCSRC Workshop October 29, 2015 20 / 40
How much dissolved during emplacementMain reservoir segment Map of Bravo Dome: NE reservoir segment:
residual brine 53%
aquifer 47%
10%
20%
30%
40%
50%
0 10 20 30 40 50 60 70Easting (km)
0
10
20
30
40
50
60
70
Nor
thin
g (k
m)
60%
0%
loca
l fra
ctio
n of
gas
dis
solv
ed
residualbrine 14%
aquifer 86%
1 Significant amounts dissolved into ’residual brine’ during emplacement.Highlights positive effect of heterogeneity on dissolution!
2 Significant amounts dissolved into underlying aquifer after emplacement.Provides field evidence for enhanced dissolution due to brine flow.
Marc A. Hesse UKCCSRC Workshop October 29, 2015 21 / 40
Outline
1 IntroductionMotivationBravo Dome natural CO2 field in New Mexico
2 Dissolution trapping at Bravo DomeMagnitude of CO2 dissolutionMechanism of solubility trapping at Bravo DomeRate of CO2 dissolution
3 Pressures in natural CO2 reservoirsReservoir compartmentalizationOrigins of subhydrostatic pressures
4 Implications for geological CO2 storage
Marc A. Hesse UKCCSRC Workshop October 29, 2015 22 / 40
CO2 emplacement and regional volcanismDistribution of regional volcanism Age of regional volcanism
[MPa]2 4 6 8 10 12 14
−60 −40 −20 0 20 40 60 80
20
40
60
80
100
120
140
160
1.7Ma−56ka9Ma−2.2Ma
easting [km]
north
ing
[km
]
TexasO
klahoma
Colorado
T1
095
Folsom SiteFolsom SiteCapulin volcanoCapulin volcano
New Mexico
volcanic ages:
T2
Assumed age of Bravo Dome is 10ka.
Three major volcanic phases:1 Raton phase: 9.0 - 3.5 Ma2 Clayton phase: 3.0 -2.25 Ma3 Capulin phase: 1.7 - 0.04 Ma
Independent estimate of CO2 age!
Stroud (1996) M.S. Thesis, NM Tech
Marc A. Hesse UKCCSRC Workshop October 29, 2015 23 / 40
Dating CO2 emplacment with thermochronologyCore sample with Apatite crystal
(U-Th)/He thermochronology
Apatite accumulates He from radioactive decay below T = 75◦C.Current reservoir conditions T = 35◦C → heating by ∆T ≈ 40◦C
Hot volcanic CO2 entered Bravo Dome 1.2-1.5 Ma ago.
Marc A. Hesse UKCCSRC Workshop October 29, 2015 24 / 40
Dating CO2 emplacment with thermochronologyCore sample with Apatite crystal (U-Th)/He thermochronology
Apatite accumulates He from radioactive decay below T = 75◦C.Current reservoir conditions T = 35◦C → heating by ∆T ≈ 40◦C
Hot volcanic CO2 entered Bravo Dome 1.2-1.5 Ma ago.
Marc A. Hesse UKCCSRC Workshop October 29, 2015 24 / 40
Dating CO2 emplacment with thermochronologyCore sample with Apatite crystal (U-Th)/He thermochronology
Apatite accumulates He from radioactive decay below T = 75◦C.Current reservoir conditions T = 35◦C → heating by ∆T ≈ 40◦C
Hot volcanic CO2 entered Bravo Dome 1.2-1.5 Ma ago.
Marc A. Hesse UKCCSRC Workshop October 29, 2015 24 / 40
Estimate IPCC–diagram for Bravo Dome
100 101 102 103 104
100%
80%
60%
40%
20%
0%
Frac
tion
of C
O2 tr
appe
d
Time since injection [yrs]
free CO2
solubility trapping
residual trapping
mineral trapping
Marc A. Hesse UKCCSRC Workshop October 29, 2015 25 / 40
Estimate IPCC–diagram for Bravo Dome
Bravo Dome
100%
80%
60%
40%
20%
0%
Frac
tion
of C
O2 tr
appe
d
100 101 102 103 104
Time since emplacement [yrs]105 106 107
free CO2
solubility trapping
Marc A. Hesse UKCCSRC Workshop October 29, 2015 25 / 40
Outline
1 IntroductionMotivationBravo Dome natural CO2 field in New Mexico
2 Dissolution trapping at Bravo DomeMagnitude of CO2 dissolutionMechanism of solubility trapping at Bravo DomeRate of CO2 dissolution
3 Pressures in natural CO2 reservoirsReservoir compartmentalizationOrigins of subhydrostatic pressures
4 Implications for geological CO2 storage
Marc A. Hesse UKCCSRC Workshop October 29, 2015 26 / 40
Outline
1 IntroductionMotivationBravo Dome natural CO2 field in New Mexico
2 Dissolution trapping at Bravo DomeMagnitude of CO2 dissolutionMechanism of solubility trapping at Bravo DomeRate of CO2 dissolution
3 Pressures in natural CO2 reservoirsReservoir compartmentalizationOrigins of subhydrostatic pressures
4 Implications for geological CO2 storage
Marc A. Hesse UKCCSRC Workshop October 29, 2015 27 / 40
Pressures gradients at Bravo Dome
[MPa]2 4 6 8 10 12 14
−60 −40 −20 0 20 40 60 80
20
40
60
80
100
1.7Ma−56ka9Ma−2.2Ma
easting [km]
north
ing
[km
]
Texas
095
volcanic ages:
?
?
??
?
?
Is the reservoir still filling?If not, why didn’t the pressure gradient relax?
Marc A. Hesse UKCCSRC Workshop October 29, 2015 28 / 40
Sub-hydrostatic gas pressures at Bravo Dome
Bravo Dome gas pressure
Pressure compartments
0 2 4 6 8 10
600
650
700
750
800
850
900
Gas Pressure (MPa)
Dep
th (m
)
AB
C
D
EF
ρwg
ρgg
pe
Marc A. Hesse UKCCSRC Workshop October 29, 2015 29 / 40
Sub-hydrostatic gas pressures at Bravo Dome
Bravo Dome gas pressure Pressure compartments
0 2 4 6 8 10
600
650
700
750
800
850
900
Gas Pressure (MPa)
Dep
th (m
)
AB
C
D
EF
ρwg
ρgg
pe
103103.2103.4103.6103.835.6
35.8
36
36.2
36.4
Longitude (°W)La
titud
e (°
N)
A
BC
DE
F
S
T
Marc A. Hesse UKCCSRC Workshop October 29, 2015 29 / 40
Stratigraphic controls on compartmentalization
Pressure compartments
Gas volume fraction s̃and fraction
103103.2103.4103.6103.835.6
35.8
36
36.2
36.4
Longitude (°W)
Latit
ude
(°N
)
A
BC
DE
F
S
T
Marc A. Hesse UKCCSRC Workshop October 29, 2015 30 / 40
Stratigraphic controls on compartmentalization
Pressure compartments Gas volume fraction s̃and fraction
103103.2103.4103.6103.835.6
35.8
36
36.2
36.4
Longitude (°W)
Latit
ude
(°N
)
A
BC
DE
F
S
T
0
10
20
30
40
50
60
70
Nor
thin
g (k
m)
4%
6%
8%
10%
12%
14%
16%
0 10 20 30 40 50 60 70Easting (km)
gas
volu
me
frac
tion:
φS
Marc A. Hesse UKCCSRC Workshop October 29, 2015 30 / 40
Stratigraphic controls on compartmentalization
B 5 15 25 35 45 55 65 B’500
600
700
800
900
granitic basementbrine
elev
atio
n [m
]
source
distance along cross-section [km]
compartment 1
compartment 2
compartment 3
CO2 is stored in a number of closed compartments?
Marc A. Hesse UKCCSRC Workshop October 29, 2015 31 / 40
Stratigraphic controls on compartmentalization
B 5 15 25 35 45 55 65 B’500
600
700
800
900
granitic basementbrine
elev
atio
n [m
]
source
distance along cross-section [km]
compartment 1
compartment 2
compartment 3
CO2 is stored in a number of closed compartments?
Marc A. Hesse UKCCSRC Workshop October 29, 2015 31 / 40
Outline
1 IntroductionMotivationBravo Dome natural CO2 field in New Mexico
2 Dissolution trapping at Bravo DomeMagnitude of CO2 dissolutionMechanism of solubility trapping at Bravo DomeRate of CO2 dissolution
3 Pressures in natural CO2 reservoirsReservoir compartmentalizationOrigins of subhydrostatic pressures
4 Implications for geological CO2 storage
Marc A. Hesse UKCCSRC Workshop October 29, 2015 32 / 40
Sub-hydrostatic gas pressures at Bravo Dome
14 ± 3%
5%
16%
Total Subhydrostatic Pressure = 6.3 MPa
Regional Subhydrostatic
Ogallala Depletion
Erosional Unloading
Cooling of Volcanic CO2
Dissolution of CO2into Brine
Un-Explained
41 ± 30%
10 ± 5%
14 ± 4%
Marc A. Hesse UKCCSRC Workshop October 29, 2015 33 / 40
Sub-hydrostatic gas pressures at Bravo Dome
14 ± 3%
5%
16%
Total Subhydrostatic Pressure = 6.3 MPa
Regional Subhydrostatic
Ogallala Depletion
Erosional Unloading
Cooling of Volcanic CO2
Dissolution of CO2into Brine
Un-Explained
41 ± 30%
10 ± 5%
14 ± 4%
250 300 350 400 450 5000
2
4
6
8
10
12
Temperature (K)P
ressu
re (
Mp
a)
CO2 Isodensity Diagram
Dissolution Effect
∆P = 0.7 - 1.1 MPa
Marc A. Hesse UKCCSRC Workshop October 29, 2015 33 / 40
Regional underpressure
33˚ N
34˚ N
35˚ N
36˚ N
37˚ N
38˚ N
Latit
ude
Langitude100˚ W101˚ W102˚ W103˚ W104˚ W105˚ W106˚ W
A A’
Marc A. Hesse UKCCSRC Workshop October 29, 2015 34 / 40
Regional underpressure
33˚ N
34˚ N
35˚ N
36˚ N
37˚ N
38˚ N
Latit
ude
Langitude100˚ W101˚ W102˚ W103˚ W104˚ W105˚ W106˚ W
A A’
Elev
atio
n (ft
)
-6000
-4000
-2000
0
2000
4000
6000
100˚ W101˚ W102˚ W103˚ W104˚ W
Langitude
A’A
Precambrian Basement
TXNMAnadarko
DalhartBasin
Wolfcampion
Marc A. Hesse UKCCSRC Workshop October 29, 2015 34 / 40
Underpressure due to regional evaporite
Marc A. Hesse UKCCSRC Workshop October 29, 2015 35 / 40
Underpressure due to regional evaporite
Permian Evaporite
Marc A. Hesse UKCCSRC Workshop October 29, 2015 35 / 40
Underpressure is normal in natural CO2 reservoirs
Gas Pressure (MPa)
De
pth
(m
)
0
4000
3000
2000
1000
0 302010
SJE
DMMD
KD
GC
MC
MD
L
GC
KD
MC
GCL
MD
SJ E
DM
B1
B5
B4
B2
B3
BD
DM: Des Moines
E: Estancia
GC: Gordon Creek
KD: Kevin Dome
L: Lisbon
MC: Mc Callum
MD: McElmo Dome
SJ: St. Johns
B1: Denver Basin
B2: Anadarko Basin
B3: Arkoma Basin
B4 Palo Duro Basin
B5: San Juan Basin
ρw g
Marc A. Hesse UKCCSRC Workshop October 29, 2015 36 / 40
Outline
1 IntroductionMotivationBravo Dome natural CO2 field in New Mexico
2 Dissolution trapping at Bravo DomeMagnitude of CO2 dissolutionMechanism of solubility trapping at Bravo DomeRate of CO2 dissolution
3 Pressures in natural CO2 reservoirsReservoir compartmentalizationOrigins of subhydrostatic pressures
4 Implications for geological CO2 storage
Marc A. Hesse UKCCSRC Workshop October 29, 2015 37 / 40
Summary and conclusionNatural analogs for geological CO2 storage
1 Large amounts of data are freely available.2 Provide constraints in long-term fate of geological CO2 storage
Dissolution at Bravo Dome1 Estimate that 366 MtCO2 have dissolved.2 50% dissolves into residual brine during emplacement.3 50% dissolves after emplacement into aquifer.4 Emplacement of CO2 1.2-1.4 Ma ago.
Pressures at Bravo Dome1 Pressure is significantly below hydrostatic (common).2 CO2 dissolution can reduce pressure in compartmentalized reservoir.3 Permian evaporites are associated with large regional underpressure.
Marc A. Hesse UKCCSRC Workshop October 29, 2015 38 / 40
Summary and conclusionNatural analogs for geological CO2 storage
1 Large amounts of data are freely available.2 Provide constraints in long-term fate of geological CO2 storage
Dissolution at Bravo Dome1 Estimate that 366 MtCO2 have dissolved.2 50% dissolves into residual brine during emplacement.3 50% dissolves after emplacement into aquifer.4 Emplacement of CO2 1.2-1.4 Ma ago.
Pressures at Bravo Dome1 Pressure is significantly below hydrostatic (common).2 CO2 dissolution can reduce pressure in compartmentalized reservoir.3 Permian evaporites are associated with large regional underpressure.
Marc A. Hesse UKCCSRC Workshop October 29, 2015 38 / 40
Summary and conclusionNatural analogs for geological CO2 storage
1 Large amounts of data are freely available.2 Provide constraints in long-term fate of geological CO2 storage
Dissolution at Bravo Dome1 Estimate that 366 MtCO2 have dissolved.2 50% dissolves into residual brine during emplacement.3 50% dissolves after emplacement into aquifer.4 Emplacement of CO2 1.2-1.4 Ma ago.
Pressures at Bravo Dome1 Pressure is significantly below hydrostatic (common).2 CO2 dissolution can reduce pressure in compartmentalized reservoir.3 Permian evaporites are associated with large regional underpressure.
Marc A. Hesse UKCCSRC Workshop October 29, 2015 38 / 40
Implications for CO2 storageTrapping and safety
1 Structural trapping contained large volume over millenial timescales.2 Dissolution trapping is slower then expected.3 Dissolution trapping is nice, but not strictly necessary.
Geological CO2 storage on a scale large enough to matter?1 Sleipner is an example of successful storage in an optimal formation.2 Bravo Dome is an example if successful storage in a formation
that would not be considered optimal.
Low-pem & low-pressure formations as CO2 storage targets1 Previously considered for hazardous waste injection.2 CO2 is less mobile than in high perm formations.3 Inject large amounts before reaching hydrostatic pressure.4 CO2 dissolution reduces pressure over time.
Marc A. Hesse UKCCSRC Workshop October 29, 2015 39 / 40
Implications for CO2 storageTrapping and safety
1 Structural trapping contained large volume over millenial timescales.2 Dissolution trapping is slower then expected.3 Dissolution trapping is nice, but not strictly necessary.
Geological CO2 storage on a scale large enough to matter?1 Sleipner is an example of successful storage in an optimal formation.2 Bravo Dome is an example if successful storage in a formation
that would not be considered optimal.
Low-pem & low-pressure formations as CO2 storage targets1 Previously considered for hazardous waste injection.2 CO2 is less mobile than in high perm formations.3 Inject large amounts before reaching hydrostatic pressure.4 CO2 dissolution reduces pressure over time.
Marc A. Hesse UKCCSRC Workshop October 29, 2015 39 / 40
Implications for CO2 storageTrapping and safety
1 Structural trapping contained large volume over millenial timescales.2 Dissolution trapping is slower then expected.3 Dissolution trapping is nice, but not strictly necessary.
Geological CO2 storage on a scale large enough to matter?1 Sleipner is an example of successful storage in an optimal formation.2 Bravo Dome is an example if successful storage in a formation
that would not be considered optimal.
Low-pem & low-pressure formations as CO2 storage targets1 Previously considered for hazardous waste injection.2 CO2 is less mobile than in high perm formations.3 Inject large amounts before reaching hydrostatic pressure.4 CO2 dissolution reduces pressure over time.
Marc A. Hesse UKCCSRC Workshop October 29, 2015 39 / 40
Implications for CO2 storageTrapping and safety
1 Structural trapping contained large volume over millenial timescales.2 Dissolution trapping is slower then expected.3 Dissolution trapping is nice, but not strictly necessary.
Geological CO2 storage on a scale large enough to matter?1 Sleipner is an example of successful storage in an optimal formation.2 Bravo Dome is an example if successful storage in a formation
that would not be considered optimal.
Low-pem & low-pressure formations as CO2 storage targets1 Previously considered for hazardous waste injection.2 CO2 is less mobile than in high perm formations.3 Inject large amounts before reaching hydrostatic pressure.4 CO2 dissolution reduces pressure over time.
Marc A. Hesse UKCCSRC Workshop October 29, 2015 39 / 40
Thank you for your attention.
Marc A. Hesse UKCCSRC Workshop October 29, 2015 40 / 40
Copyright of Shell Global Solutions International B.V.
MULTIPHASE FLOW MODELLING OF CALCITE DISSOLUTION PATTERNS FROM CORE SCALE TO RESERVOIR SCALE
Jeroen Snippe, Holger Ott Shell Global Solutions International B.V.
1 October 2015
Presentation for UKCCSRC Specialist Meeting on Flow and Transport for CO2 Storage
Imperial College London,
30th October 2015
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DEFINITIONS & CAUTIONARY NOTE
Reserves: Our use of the term “reserves” in this presentation means SEC proved oil and gas reserves.
Resources: Our use of the term “resources” in this presentation includes quantities of oil and gas not yet classified as SEC proved oil and gas reserves. Resources are consistent with the Society of Petroleum Engineers 2P and 2C definitions.
Organic: Our use of the term Organic includes SEC proved oil and gas reserves excluding changes resulting from acquisitions, divestments and year-average pricing impact.
Resources plays: Our use of the term ‘resources plays’ refers to tight, shale and coal bed methane oil and gas acreage.
The companies in which Royal Dutch Shell plc directly and indirectly owns investments are separate entities. In this presentation “Shell”, “Shell group” and “Royal Dutch Shell” are sometimes used for convenience where references are made to Royal Dutch Shell plc and its subsidiaries in general. Likewise, the words “we”, “us” and “our” are also used to refer to subsidiaries in general or to those who work for them. These expressions are also used where no useful purpose is served by identifying the particular company or companies. ‘‘Subsidiaries’’, “Shell subsidiaries” and “Shell companies” as used in this presentation refer to companies in which Royal Dutch Shell either directly or indirectly has control. Companies over which Shell has joint control are generally referred to as “joint ventures” and companies over which Shell has significant influence but neither control nor joint control are referred to as “associates”. The term “Shell interest” is used for convenience to indicate the direct and/or indirect ownership interest held by Shell in a venture, partnership or company, after exclusion of all third-party interest.
This presentation contains forward-looking statements concerning the financial condition, results of operations and businesses of Royal Dutch Shell. All statements other than statements of historical fact are, or may be deemed to be, forward-looking statements. Forward-looking statements are statements of future expectations that are based on management’s current expectations and assumptions and involve known and unknown risks and uncertainties that could cause actual results, performance or events to differ materially from those expressed or implied in these statements. Forward-looking statements include, among other things, statements concerning the potential exposure of Royal Dutch Shell to market risks and statements expressing management’s expectations, beliefs, estimates, forecasts, projections and assumptions. These forward-looking statements are identified by their use of terms and phrases such as ‘‘anticipate’’, ‘‘believe’’, ‘‘could’’, ‘‘estimate’’, ‘‘expect’’, ‘‘intend’’, ‘‘may’’, ‘‘plan’’, ‘‘objectives’’, ‘‘outlook’’, ‘‘probably’’, ‘‘project’’, ‘‘will’’, ‘‘seek’’, ‘‘target’’, ‘‘risks’’, ‘‘goals’’, ‘‘should’’ and similar terms and phrases. There are a number of factors that could affect the future operations of Royal Dutch Shell and could cause those results to differ materially from those expressed in the forward-looking statements included in this presentation, including (without limitation): (a) price fluctuations in crude oil and natural gas; (b) changes in demand for Shell’s products; (c) currency fluctuations; (d) drilling and production results; (e) reserves estimates; (f) loss of market share and industry competition; (g) environmental and physical risks; (h) risks associated with the identification of suitable potential acquisition properties and targets, and successful negotiation and completion of such transactions; (i) the risk of doing business in developing countries and countries subject to international sanctions; (j) legislative, fiscal and regulatory developments including potential litigation and regulatory measures as a result of climate changes; (k) economic and financial market conditions in various countries and regions; (l) political risks, including the risks of expropriation and renegotiation of the terms of contracts with governmental entities, delays or advancements in the approval of projects and delays in the reimbursement for shared costs; and (m) changes in trading conditions. All forward-looking statements contained in this presentation are expressly qualified in their entirety by the cautionary statements contained or referred to in this section. Readers should not place undue reliance on forward-looking statements. Additional factors that may affect future results are contained in Royal Dutch Shell’s 20-F for the year ended 31 December, 2014 (available at www.shell.com/investor and www.sec.gov ). These factors also should be considered by the reader. Each forward-looking statement speaks only as of the date of this presentation, 2 October, 2015. Neither Royal Dutch Shell nor any of its subsidiaries undertake any obligation to publicly update or revise any forward-looking statement as a result of new information, future events or other information. In light of these risks, results could differ materially from those stated, implied or inferred from the forward-looking statements contained in this presentation. There can be no assurance that dividend payments will match or exceed those set out in this presentation in the future, or that they will be made at all.
We use certain terms in this presentation, such as discovery potential, that the United States Securities and Exchange Commission (SEC) guidelines strictly prohibit us from including in filings with the SEC. U.S. Investors are urged to consider closely the disclosure in our Form 20-F, File No 1-32575, available on the SEC website www.sec.gov. You can also obtain this form from the SEC by calling 1-800-SEC-0330.
October 2015
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INTRO: CALCITE DISSOLUTION DURING CO2 INJECTION
Context: CO2 storage/EOR
CO2 injection → acidification →
carbonate dissolution
3 October 2015
Fred and Fogler (1999), SPE 56995
Experiments show ‘wormholing’ for CO2 -saturated brine injection
Similar to patterns in extensive acid stimulation literature
Very limited experimental work done with gas/SC CO2 injection
Model investigation
Impact of gas phase
Upscaling to field scale
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MODELLING APPROACH
Using in-house dynamic multiphase reservoir flow simulator (MoReS) coupled to open-source geochemical package (PHREEQC v3)
4 October 2015
Detailed model (core scale)
Explicit representation of WH patterns
Grid resolution << WH diameter
Chemistry including kinetics (phreeqc.dat, Palandri & Kharaka)
2-phase flow description including capillary effects and diffusion
Permeability, capillary pressure, relperms modified during dissolution
Continuum scale (Darcy) model → flow within WH approximate
Effective model (core scale to well/reservoir scale) [2nd part of presentation]
Implicit representation of WH patterns
Generalised to 2-phase case with CO2
Parameters tuned to detailed model and experiments
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DETAILED MODEL
5 October 2015
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3D
SOME MODEL RESULTS (SINGLE PHASE)
6 October 2015
WH competition 5mm…
Most of fine-scale simulations done in 2D
Compact dissolution Conical dissolution Conical wormhole
Ramified wormholes Homogeneous dissol. Dominant wormhole
2D
WH width 2 mm
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MODEL VALIDATION (SINGLE PHASE)
7 October 2015
Ramified wormholes
Uniform dissolution
Dominant wormhole
Con
ical
w
orm
hole
Com
pact
di
ssol
utio
n
Dah
mko
hler
num
ber
(rea
ctio
n ra
te/c
onve
ctio
n ra
te)
Peclet number (convection rate/diffusion rate)
MoReS results (colour) plotted on domain boundaries from Golfier et al., J. Fluid Mech. (2002), vol. 457, pp. 213-254 with experimental patterns from Fred and Fogler (1999), SPE 56995
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TWO-PHASE EXPERIMENT/MODEL RATIONALE
Experiment
Two experiments were done at Shell with CO2 + brine co-injection
This is ~representative for the conditions somewhat behind the CO2 plume front in CCS
Pure CO2 injection WH experiment would be more challenging
longer core to resolve profiles (gas saturation, calcite dissolution)
high CT signal:noise to resolve subtle calcite dissolution patterns
Model:
Model experiment with CO2 + brine co-injection and compare results
Derive upscaled (effective) model description
Apply effective model to pure CO2 injection (larger model dimensions)
8 October 2015
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2-PHASE RELPERM AND CAPILLARY PRESSURE
9 October 2015
During dissolution
Interpolation between curves (linear in porosity)
Power law scaling of permeability with porosity
0.0
1.5
3.0
0.00
0.25
0.50
0.75
1.00
0.00 0.25 0.50 0.75 1.00
Cap
illar
y p
ress
ure
(G
as-W
ate
r) [
bar
]
Re
lati
ve p
erm
eab
ility
Gas saturation
krw matrix
krg matrix
krw cavity
krg cavity
Pc matrix
Pc cavity
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TWO-PHASE MODEL RESULTS (CO-INJECTION)
10 October 2015
The gas phase slightly suppresses WH velocity
260 PV
single-phase two-phase co-injection (same rate)
720 PV
560 PV
760 PV
760 PV
2000 PV
260 PV
880 PV
760 PV
880 PV
760 PV
2000 PV
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1
10
100
1000
10000
0.001 0.010 0.100 1.000 10.000 100.000
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Interstitial Water Velocity (cm/min)
Brine + gas
Observed
TWO-PHASE MODEL RESULTS (CO-INJECTION)
11 October 2015
Most suppression around optimal flow rates (~dominant WH regime)
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TWO-PHASE MODEL RESULTS: ANALYSIS/COMPARISON
12 October 2015
2-phase, 1+1 ml/min co-inj. 1-phase, 1ml/min
Porosity
Experiment (Shell) (Porosity)
Ott et al. (2013) SCA2013-029
Gas saturation
Water flux (log scale)
760 PV 880 PV
Copyright of Shell Global Solutions International B.V.
Ott, H., and S. Oedai (2015) Geophys. Res. Lett., 42, 2270–2276 doi:10.1002/2015GL063582
2ND SHELL EXPERIMENT: WH SUPPRESSION
In this experiment gas co-injection seems to trigger transition from dominant WH into conical WH/compact dissolution
Slumping reproduced in model runs with gravity (only investigated on small diameter core)
13 October 2015
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EFFECTIVE MODEL APPROACH
14 October 2015
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LEARNINGS FROM ACID STIMULATION LITERATURE
15 August 2015
Acid stimulation literature (single phase): Universally shaped curve #PVBT vs vi (or vWH vs vi)
Location of curve depends on phi, perm, aspect ratio, HCl strength, …
‘Global Wormholing Model’ (GWM), Talbot&Gdanski (2008), SPE 113042, offers ~universal parameterisation
~predictive vWH vs vi for given phi, perm, HCl strength, etc.
Buijse & Glasbergen (2005), SPE 96892
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GWM CHARACTERISTICS
16 October 2015
Talbot&Gdanski (2008), SPE 113042
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10
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Interstitial Water Velocity (cm/min)
Brine + gas Observed
compact dissolution limit Model (fit)
Model (solubility-equivalent HCl) Model (pH-equivalent HCl)
GWM APPLICATION TO CO2-BRINE
17 August 2015
Deviation in single WH regime because Poiseuille flow profile
in model poorly resolved or grid
resolution too coarse
Model was run in 2D, for which GWM
model is overshooting in face dissolution
regime
GWM model fitted by tuning HCl strength
Resulting GWM model also fits available experimental data well (next slides)
GWM model applied to dynamic flow simulations by locally accounting for calcite saturation index through HCl strength parameter
For 2-phase use same GWM parameters – use the water vi as input velocity
Copyright of Shell Global Solutions International B.V.
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0.001 0.01 0.1 1 10 100 1000
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Interstitial Fluid Velocity (cm/min)
Model Observed
FITTED MODEL COMPARISON TO EXPERIMENTS OTT ET AL. (SHELL) 2013 – SCA 2013-029
18 October 2015
L=5.91”, d=2.95”
q=1 mL/min
Estaillades limestone
φ=0.278, k=270 mD
T=50 °C, p=100 bar
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Interstitial Fluid Velocity (cm/min)
Model Observed
FITTED MODEL COMPARISON TO EXPERIMENTS CAROLL ET AL. (LLNL) 2013 - IJGHGC 16S (2013) S185–S193
19 October 2015
L=1.18”, d=0.59”
q=0.05 mL/min
Calculated HCl equivalent based on undersaturated CO2 molality
Weyburn limestone (59% calcite)
φ=0.15, k=0.032 mD
T=60 °C, p=248 bar, p_CO2 = 30 bar
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Interstitial Fluid Velocity (cm/min)
Model Observed
FITTED MODEL COMPARISON TO EXPERIMENTS VIALLE ET AL. 2014 - J. GEOPHYS. RES. SOLID EARTH, 119, 2828–2847
20 October 2015
L=0.13.8”, d=3.94”
q=5 mL/min
Salinity = 25000 ppm
Calculated HCl equivalent based on undersaturated CO2 molality
Estaillades limestone
φ=0.286, k=120 mD
T=20 °C, p_CO2 = 1 bar
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Interstitial Fluid Velocity (cm/min)
Model Observed
FITTED MODEL COMPARISON TO EXPERIMENTS LUQUOT ET AL. 2011 - TRANSP POROUS MED (2014) 101:507–532
21 October 2015
L=0.71”, d=0.35”
q=0.08 mL/min
Calculated HCl equivalent based on undersaturated CO2 molality
Alcobaa limestone
φ=0.15, k=0.24 mD
T=100 °C, p=120 bar, p_CO2 = 34 bar
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Interstitial Fluid Velocity (cm/min)
Model Observed
FITTED MODEL COMPARISON TO EXPERIMENTS SVEC & GRIGG 2001 - SPE 71496
22 October 2015
L=20.3”, d=1.98”
q=17 mL/min
Indiana limestone
φ=0.123, k=35.7 mD
T=38 °C, p=138 bar
Salinity=86950 ppm
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Interstitial Fluid Velocity (cm/min)
Model Observed
FITTED MODEL COMPARISON TO EXPERIMENTS LUQUOT & GOUZE 2009 - CHEMICAL GEOLOGY 265 (2009) 148–159
23 October 2015
L=0.71”, d=0.35”
q=1.14 mL/min
Mondeville limestone
φ=0.075, k=35.7 mD
T=100 °C, p=120 bar, p_CO2 = 100 bar
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Interstitial Fluid Velocity (cm/min)
Model Observed
FITTED MODEL COMPARISON TO EXPERIMENTS MENKE 2015 - IMPERIAL COLLEGE LONDON – PRIVATE COMM
24 October 2015
L=0.47”, d=0.16”
q=0.5 mL/min
Salinity = 60000 ppm
Portland limestone
φ=0.045, k=0.096 mD
T=50 °C, p=100 bar
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∆ Pressure
Reference case: no WH’s
EFFECTIVE MODEL RESULTS (LINEAR MODEL, 1METER)
CO2-saturated brine injection: Potential for large injectivity increase
Pure CO2 injection: Short/no wormholes. Negligible impact on injectivity 25 October 2015
Pure CO2 injection (1cm/min) CO2-sat brine injection (1cm/min)
WH velocity
Gas saturation
WH length
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EFFECTIVE MODEL RESULTS (RADIAL MODEL, R=50 METER)
26 October 2015
Pure CO2 injection (0.5 MT/year) CO2-sat brine injection (0.5 MT/year)
Gas saturation
Injection pressure
Reference case: no WH’s
WH length
Same conclusions as for linear model Note for pure CO2 injection: WH length decreases with distance (cf. linear: ~constant)
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ANALYSIS OF RESULTS (RADIAL MODEL)
27 October 2015
0.000001
0.000010
0.000100
0.001000
0.010000
0.100000
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
0 100 200 300 400 500 600
WH
ve
loci
ty (
cm/m
in),
WH
len
gth
(cm
),
po
rosi
ty c
han
ge (
m3
/m3
), p
erm
mu
lt -
1
gas
satu
rati
on
(m
3/m
3)
Radial distance (cm)
SAT_GAS
Vwh
Lwh
DPHI
PERMX_MULT -1
0.000001
0.000010
0.000100
0.001000
0.010000
0.100000
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
300 320 340 360 380 400
WH
ve
loci
ty (
cm/m
in),
WH
len
gth
(cm
),
po
rosi
ty c
han
ge (
m3
/m3
), p
erm
mu
lt -
1
gas
satu
rati
on
(m
3/m
3)
Radial distance (cm)
SAT_GAS
Vwh
Lwh
DPHI
PERMX_MULT -1
Only thin region in which conditions are favourable for WH growth
Far ahead of gas front gradual increase in acidity → always close to calcite equillibrium → outside WH regime (too low Da#)
Note: calcite solubility in CO2-saturated brine controls final porosity change
Copyright of Shell Global Solutions International B.V.
1
10
100
1000
10000
0.001 0.01 0.1 1 10 100 1000
Po
re V
olu
me
s to
Bre
akth
rou
gh
Interstitial Fluid Velocity (cm/min)
Base caseVi -> 0 (ideal compact dissol)L/A=2L/A = .67T=-65T=30T=50HCl=.002617HCl=.05HCl=.238Estaillades exp (L/A = .34)Model 2D (L/A=15)best fit to 9.8 cm2/g MoReS
SENSITIVITY TO GWM PARAMETER UNCERTAINTY RANGE
28 October 2015
Parameter ranges based on (wide) envelope around experimental and model results
For radial application, base case L/A ≈1cm-1 based on acid stimulation radial corefloods and field application experience
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SENSITIVITY RESULTS: IMPACT ON WH LENGTH (1-PHASE)
29 October 2015
0
100
200
300
400
500
600
700
800
900
1,000
0 20 40 60 80 100
Wo
rmh
ole
len
gth
(cm
)
Distance from sandface (cm)
ref case HCld238 HCld005 LdAd67
LdA2 Tm30 T50
Strong sensitivity, especially to acid strength parameter
In all cases strong wormhole growth initiating at sandface
Hypothetical WH’s initiating ahead of sandface overtaken (shock front)
After several months of injection
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Weaker sensitivities than in 1-phase case
Conclusions from reference case run appear robust, i.e.: short/no wormholes (LWH < 0.05 cm)
perm multiplier < 1.01 for LWH < 5cm (2D) or 2cm (3D) [next slides]
SENSITIVITY RESULTS: IMPACT ON WH LENGTH (2-PHASE)
30 October 2015
0.000
0.010
0.020
0.030
0.040
0.050
0.060
0 100 200 300 400 500
Wo
rmh
ole
len
gth
(cm
)
Distance from sandface (cm)
ref case HCld238 HCld005 LdAd67
LdA2 Tm30 T50
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REMARK ON EFFECTIVE PERMEABILITY MULTIPLIER
In pure CO2 injection case WH’s would initiate away from sandface
Q: how assign effective perm?
Matrix background and high perm WH channels
Assume random WH initiation pattern
Assume idealised dominant WH’s
Straight channel WH = 2mm
From Poiseuille flow, kWH ≈ 105 D
Control parameters ∆φ and LWH
Considered both 2D and 3D
Considered enhanced connectivity case (~ WH angle distribution/bifurcations)
31 October 2015
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Numerical upscaling
Simple formula gives good fit, for all ∆φ , all LWH, all perm contrasts
𝑘𝑒𝑓𝑓
𝑘𝑚− 1 =
𝑘𝑔𝑒𝑜𝑚(∆φ)
𝑘𝑚− 1
𝐿𝑊𝐻
𝑐1
𝑐2 (+bounded by harm and arithm)
REMARK ON EFFECTIVE PERMEABILITY MULTIPLIER
32 October 2015
1.E-06
1.E-05
1.E-04
1.E-03
1.E-02
1.E-01
1.E+00
1.E+01
1.E+02
1.E+03
1.E+04
1.E+05
1.E+06
1.E-06 1.E-05 1.E-04 1.E-03 1.E-02 1.E-01 1.E+00
k_mult_harm - 1
k_mult_geom - 1
k_mult_arithm - 1
WH_kmult1Min1
WH_kmult2Min1
Fit
1.E-06
1.E-05
1.E-04
1.E-03
1.E-02
1.E-01
1.E+00
1.E+01
1.E+02
1.E+03
1.E+04
1.E+05
1.E+06
1.E-06 1.E-05 1.E-04 1.E-03 1.E-02 1.E-01 1.E+00
k_mult_harm - 1
k_mult_geom - 1
k_mult_arithm - 1
WH_kmult1Min1
WH_kmult2Min1
Fit
1.E-06
1.E-05
1.E-04
1.E-03
1.E-02
1.E-01
1.E+00
1.E+01
1.E+02
1.E+03
1.E+04
1.E+05
1.E+06
1.E-06 1.E-05 1.E-04 1.E-03 1.E-02 1.E-01 1.E+00
k_mult_harm - 1
k_mult_geom - 1
k_mult_arithm - 1
WH_kmult1Min1
WH_kmult2Min1
Series7
Example - perm contrast 𝑘𝑊𝐻
𝑘𝑚= 400, LWH =100mm
log(∆φ)
log
𝐤𝐖
𝐇
𝐤𝐦
−𝟏
10-6 1 10-6
10+6
Note: for pure CO2 injection: ∆φ≈10-4
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CONCLUSIONS
At fixed brine rate, gas co-injection causes some suppression of calcite dissolution patterns.
Modelling indicates limited suppression for any flow rate
Experiment: limited to strong suppression in dominant/conical WH regime
33 October 2015
Successfully applied effective GWM model (from acid stimulation literature) to CO2-brine system (matches fine-scale model and experiments)
Effective model predicts WH can be significant in carbonate reservoirs on operational timescale (days-years) for CO2 & water co-injection
Good for injectivity
Potentially problematic for well/rock stability (depending on WH pattern)
Effective model predicts negligible wormhole formation for pure CO2 injection (at any scale from core scale to reservoir scale)
WH formation irrelevant for pure CO2 injection projects (‘standard’ CCS)
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REMARK ON REACTION KINETICS VS GWM PARAMETERS
35 August 2015