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IEAGHG CCS Summer School Regina, Sask., Canada, 17-22 July, 2016

Storage 4 - Modeling for CO2 Storage

Professor John Kaldi Chief Scientist, CO2CRC Australian School of Petroleum, University of Adelaide, Australia

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Modelling

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On Models .…

• There is no substitute for: • Critical independent evaluation on the part of

the geoscientists and engineers to assure the success of a modeling project.

Most failures occur because a basic assumption was found to be wrong.

“All models are wrong…. some are useful” George Box

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Modelling for CO2 Storage • Modeling is used to: – Design injection (location and number of wells,

– Forecast the migration of injected carbon dioxide

– Simulate fluid flow

– Estimate storage capacity

– Predict reservoir response

– Know when and where to monitor

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• Modeling can include: – coupled geochemistry;

– coupled geomechanics;

– tracer migration.

• Other benefits of modeling – Ascertain uncertainty

– Impress stakeholders: communication tool

• Most modelling uses computer models

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Modelling for CO2 Storage


Computer models for CO2 Storage

• Computer models usually: – solve the multiphase equations for fluid flow in porous

media;

– use finite-difference techniques for solving flow equations;

– require the simulated region to be broken up into grid blocks

– are based on techniques and code developed in the petroleum industry over the past 4 decades.

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Simulation grid

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Discretisation & parameterisation

Each grid block only has one value for porosity, permeability, saturation, composition etc. This has two important consequences:

• We cannot resolve anything in the results below the size of a grid block, i.e. may need to refine grid in areas of interest.

• Geological data measured on different scales e.g. core data, has to be “upscaled” or averaged in an intelligent way.

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Upscaling

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3D representation(s) of the subsurface

Each cell contains values for geographic position, depth, volume, rock type, poro/perm, and other “static” properties. Size and complexity important

Grid resolution a key decision: trade-off between detail vs. computational limits.

The 3D static geological model

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The Basics: Static (Geological) Modelling Aim: Capture effects of structure, stratigraphy, sedimentary architecture

– Reservoirs and seals – Lateral and vertical scale & heterogeneity – Faults & fractures – petrophysical properties (porosity, permeability, seismic) – Fluid properties

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Input data types Hard Data: Direct measurement from the subsurface: • Cores (metres), • cuttings (a few mms), • Plugs (10s cms) • fluid samples…

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Integrated data for reservoir characterisation & modelling

-Dep. Env. - Poro/Perm - Stratigraphy

Core data

Outcrop Analogs - Stratigraphy - Geometry

Seismic

Static model

Wireline log data (correlate between wells)

Dynamic (Res Sim) model

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Reservoir Simulation: Dynamic Models

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Simulation input and output

• Input: – Static model (permeability, porosity, fault boundaries…) – Dynamic properties (relative permeability, capillary

pressure) – Initial conditions (pressure, temperature,…) – Boundary conditions (aquifer drive, …) – Flow rates at wells

• Output: – Maps of pressure, fluid saturation, …. – Tracer concentration (if implemented) – Dissolved components (if implemented) – Chemical reaction products (if implemented) – Stress and strain (if implemented in a geomechanical

model)

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Dealing with uncertainty: requirement for Probabilistic Modelling

Multiple Interpretations

Data Scarcity

Reservoir Heterogeneity

Data “Fuzziness”

Stochastic Model

Need Probabilistic Approach

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Uncertainty


Models should be fit for purpose

1. To address scientific questions in a generic context e.g.:

– the effect of shale barriers on vertical migration of CO2

– the effect of a hydrodynamic gradient on CO2 migration

– Dissolution of CO2

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40 yr

130 yr

330 yr

From: J. Ennis-King

Modelling the dissolution of injected CO2

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900 yr

1300 yr

2400yr From: J. Ennis-King

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Modelling the dissolution of injected CO2


Models should be fit for purpose

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2. To make technical predictions in a site-specific context to support decisions e.g.:

- What is CO2 breakthrough time in a deep injection EOR project?

- What is effect of well-spacing on maximum injectivity?

- What is the predicted seismic response? Image source: http://www.iogsolutions.com

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Models can be simple...

rc,max

h

h(r,t)

q

Nordbotten et al. (2005)

e.g. Analytical models

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…or more complex

Reference: Flett, M. A., et al. (2008) SPEdoi:10.2118/116372-MS

Example from Gorgon Project:

• Inject and store 3-4 MT PA

• Long-term modelling and monitoring

Solves a large set of linear equations at a number of given time-steps for a large number of cells

•Computationally demanding

•“Coupled” geochem / geomech

e.g. 3D Numerical Models

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Anderson & Woessner (1992)

Basin-scale vs Small-scale (pilot) projects

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Solve a large set of linear equations at multiple time-steps for a large number of cells in a broad geographic area -Computationally demanding

Make technical predictions in a site-specific context to aid decision-making -Computationally manageable

500m


CO2 injection

well

Image from: C. Gibson-Poole

Modelling injection and migration of CO2 Kingfish Field, Gippsland Basin, Austtralia

Lakes Entrance Formation

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CO2CRC Otway Project

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The CO2CRC Otway Project

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• Geological model: incorporates structure (faults) & fluid contacts

• Static model

- based on: facies (rock-type) grid parameterization

- Stochastic: multiple realisations of properties (eg porosity, permeability)

• Dynamic model:

upscaled; simulates various injection / migration scenarios


CRC-1 Injector Naylor-1 Monitor well

Naylor South-1

0 300m

Pre-production gas spill point

-2140 -2120 -2100 -2080 -2060 -2040 -2020 -2000 -1980

Depth mSS

T.Dance

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T.Dance

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Screen grab of 3D model looking West.

Naylor South Fault Injection zone in contact with Timboon Aquifer

Geo-cellular model Details: •10x10m lateral cell size •Layers ~1m

•Total cells: 132,396

•Layers follow top

•5 Realisations of sands and shale •Poro/perm conditioned to facies

CRC-2 Naylor-1

CRC-1

Porosity T.Dance

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Screen grab of 3D model looking West.

Naylor South Fault Injection zone in contact with Timboon Aquifer

Geo-cellular model Details: •10x10m lateral cell size •Layers ~1m

•Total cells: 132,396

•Layers follow top

•5 Realisations of sands and shale •Poro/perm conditioned to facies

CRC-2 Naylor-1

CRC-1

Permeability T.Dance

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CO2 injection well

Monitoring well

CO2 accumulation

Upscaled Reservoir Model

Y.Cinar

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CO2CRC Otway project: CO2 mass fraction

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Carbon dioxide mass fraction: 18 Sept Carbon dioxide mass fraction: 31 Dec


CO2CRC Otway project: pressure difference

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Pressure difference: 18 Sept – 31 Dec Pressure difference: 18 Sept – 31 Dec (NW – SE slice)


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Modelling Time and effort

(from Tyson, 2008)


Modelling Conclusions

• Modelling is a useful tool in the design of carbon dioxide storage projects.

• Modelling depends on the quality of the data and the skill of the user (old saying: garbage in, garbage out).

• Most effort and time in modelling is in data gathering and grid parameterization

• In the right hands with correct questions it can provide powerful answers.

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