What Could Controlled Releases Do Better?

IEAGHG Modeling & Monitoring Combined Meeting

Morgantown Aug. 2014

Lee SpanglerDirector, Energy Research Institute

Big Sky Carbon Sequestration Partnership (BSCSP)Zero Emission Research & Technology Collaborative (ZERT)

Montana State University

1

Monitoring Zones

• Atmosphere– Ultimate Integrator

– Dynamic

– Monitoring & Modeling

• Biosphere – dynamic

– requires protection

– opportunity for wide area monitoring but indirect methods

• Soil – Integrates

– dynamic

• Aquifers – Integrates

– Requires protection

2

Injection Zone

Caprock & Deep Overburden

Soil(Vadose & Shallow

Saturated Zones

Biosphere

Atmosphere

How We Have Learned

Natural Analogs• Mammoth Mountain• Laacher See• Latera• Soda Springs, ID• Crystal Geyser, UT• Others

How analogous is the analog?Flow through significant overburdenFluxes may be much higher than leaky engineered system

3

Controlled Releases• ASGARD (Nottingham)• ZERT (Montana State)• Australia• Norway• Crystal Geyser, UT• Brazil Ressacada• Others

Source term knownAbility to establish detection limitsCan measure recoveryRelatively little overburden

What Is the Monitoring Purpose?

• Climate change mitigation?

– 1% over 1000 yrs – climate models?

• Retention in the reservoir?

– Subsurface techniques typically do not measure properties directly proportional to concentration / quantity

• Overall storage security?

• HSE, Resource protection (USDW)?

– Measure to ensure levels are below impact levels

• Public assurance?

• Verification and accounting?

– Mass flow meters only accurate to ~1%4

Methods

• Soil Gas Monitoring• In-situ soil gas probes• Soil Flux chambers• Open path FTIR, Differential Absorption LIDAR• Cavity ring-down, other isotopic measurements• Water chemistry• Tracers• Hyperspectral / mutispectral imaging• Resistivity• Many more

5

What Are Relevant Release Rates?

6

0.1

1

10

100

1000

10000

0 20 40 60 80 100

Years

Leakag

e (

t C

O2 / d

ay)

• 4 Mt/year injection from 500 MW power plant

• 50 years injection

• Four Leakage rates– 1% / year

– 0.1% / year

– 0.01% / year

– 0.001% / year

0

10

20

30

40

50

60

0 20 40 60 80 100

Years

Em

pla

ce

me

nt

(Mt

CO

2)

0.01%

0.1%

1.0%

0.001%

• 1% over 1000 yrs = 0.001% / yr = 0.00001

• Daily leakage = 6 Tonnes / day

• Equivalent to ~92 idling cars

0.01

0.1

1

10

100

0 20 40 60 80 100

Years

Sc

ale

d L

ea

ka

ge

Ra

te (

t/d

ay

)

0.001

0.01

0.1

1

10

0 20 40 60 80 100

Years

Sc

ale

d L

ea

ka

ge

Ra

te (

t/d

ay

)

Injection Rate

Scale to 1000 m leak

1,000 kg/day: 1 tonne/day

100 m

1,000 m

1,000 m

10 m100 m 100 m

Sally Benson

Lee Spangler

0.01%

0.1%

0.001% 0.01%

0.1%

0.001%

Experiment Site

MSU Agricultural lands

Route

Experiment Site

MSU Agricultural lands

Route

Field Test Facility

Horizontal Well Installation

Packer

Pressure

transducer

Electric cable

Packer inflation line

CO2 delivery lines

Strength line

240 ft

40 ft

16 in

Packer Packer

Ray Solbau, Sally Benson

Large Number of Participants / MethodsInvestigator Institution Monitoring

Technology

Number of Sensors

Arthur Wells

Rod Diehl

Brian Strasizar

National Energy

Technology Laboratory

Atmospheric tracer

plume measurements

1 tower (4m)

Blimp (Apogee

Scientific) with 3 tether

line samplers

Bee hive monitoring for

tracer with sorption tube

and pollen trap

2 hives

Automated Soil CO2

flux system

4 chambers

William Pickles

Eli Silver

Erin Male

University of

California- Santa Cruz

Hand held hyperspectral

measurements (plant

health)

1 instrument

Yousif Kharaka

James ThordsenGil

AmbatsSarah Beers

United States

Geological Survey*

Ground water

monitoring

1 EC and temperature

probe, Dissolved

oxygen probe, lab

analysis of water

samples

Henry Rauch West Virginia

University

Water monitoring well

headspace gas sampling

1 sensor

Lucian Wielopolski

Sudeep MitraBrookhaven National

Laboratory*

Ineleastic neutron

scattering (total soil

carbon)

1 instrument

Martha Apple

Xiaobing Zhou

Venkata Lakkaraju

Bablu Sharma

+2 students

Montana Tech* Soil moisture, temp.

Chlorophyll Content

Meter , Fluorescence

Meter , LI-COR 2000 to

measure leaf area index

Leaf Porometer to

measure stomatal

conductance

5 sensors

Infrared radiometry

(plant health)

2 instruments

Atmospheric humidity

and temperature,

accumulated rainfall

1 sensor each

Plant root imaging 1 camera

Soil conductivity 1 sensor

Handheld hyperspectral

measurements (plant

health)

1 instrument

William Holben

Sergio Morales

University of Montana* Microbial studies Lab analysis

47 investigators

31 instruments / sensor arrays

5 univ. 6 DOE labs, 4 companies

Investigator Institution Monitoring

Technology

Number of Sensors

Lee Spangler

Laura Dobeck

Kadie Gullickson

Montana State

University

Water content

reflectometers (soil

moisture)

15 sensors

Automated soil CO2

flux system

5 long term

chambers, 1 portable

survey chamber

CO2 soil gas

concentration

6 sensors

Kevin Repasky (PI)

Jamie Barr

Montana State

University

Underground fiber

sensor array (CO2 soil

gas concentration)

4 sensors

Rand Swanson Resonon* Flight based

hyperspectral

imaging system

1instrument

Joseph Shaw (PI)

Justin Hogan

Nathan Kaufman

Montana State

University

Multi-spectral

imaging system (plant

health)

1instrument

Meteorological

measurements

1 tower

Julianna Fessenden

+3 students

Los Alamos National

Laboratory

In situ (closed path)

stable carbon isotope

detection system

1 instrument

Flask sampling for in

situ isotope detection

Lab analysis

Sam Clegg

Seth Humphries

Los Alamos National

Laboratory

Frequency-modulated

spectroscopy (FMS)

open-air path

1 instrument

Thom Rahn Los Alamos National

Laboratory

Eddy covariance 1 tower

James Amonette

Jon Barr

Pacific Northwest

National Laboratory

Soil CO2 flux

(steady-state)

27 chambers

Sally Benson (PI)

Sam Krevor

Jean-Christophe

Perin

Ariel Esposito

Chris Rella (Picarro)

Stanford University*

/ Picarro

Instruments*

Commercial cavity

ringdown real-time

measurements of δ13C

and CO2 in air

1 instrument

Greg Rau

Ian McAlexander

(LGR)

Lawrence Livermore

National Laboratory

/Los Gatos Research*

Commercial cavity

ringdown real-time

measurements of δ13C

and CO2 in air

1 instrument

Jennifer Lewicki Lawrence Berkeley

National Laboratory

CO2 soil gas

concentration

8 sensors

CO2 atmospheric

concentration

2 sensors

Chamber soil CO2

flux measurements

1 instrument

Meteorological

measurements

1 tower

Large Number of

Participants / Methods

J.L. Lewicki

Flux Chamber

13

Eddy covariance net CO2 flux monitoring

An eddy covariance (EC) station was

deployed ~30 m NW of the release

well in 2006, 2007, and 2008.

J. Lewicki (LBNL)

In 2008 (0.3 t CO2 d-1 for 1 month)

leakage signal was detected in raw

EC CO2 flux (Fc) data. Ecosystem

CO2 fluxes were modeled and

removed from Fc to improve signal

detection in residual flux (Fcr) data.

A least-squares inversion of

measured residual CO2

fluxes and corresponding

modeled footprint functions

during the 2008 release

modeled the distribution of

surface CO2 fluxes, allowing

us to locate and quantify (to

within 7%) the leakage

signal.

Spectral Imaging System:

Imaging Spectrometer,

Data Logger/System Control,

IMU/GPS/Communications

Spectral Imaging System:

Imaging Spectrometer,

Data Logger/System Control,

IMU/GPS/Communications

Hyperspectral Imaging

True Color Analyzed Image

Kevin Repasky

Hyperspectral Imaging Unsupervised Classification

What We Have Learned?• Many near surface methods are quantitative but

– Diurnal, seasonal, annual variations in ecosystem background flux affect detection limits

– Appropriate area integrated, mass balance is a challenge

• Nearly all methods could detect 0.15 tonnes / day release at ZERT site.

• Scaling, 6 tonnes per day would be detectable over an area 40 times as large

• Surface expression was “patchy” – 6 areas of ~5m radius

• Natural analogs also seem to have “patchy” surface expression

• Will engineered systems that leak have similar properties?

• Measurable changes in aqueous geochemistry can occur quickly depending on soil

• Isotopes / tracers / measurement of interdependent species gives greater sensitivity or discriminaiton against background variability 16

ZERT Pre-Release Planning

Soils

Tim HolleyTopsoil:

• USCS- CL , low plasticity clay

• AASHTO- A-6, Clay

Intermediate Layer:

• USCS- ML, Low plasticity silt

• AASHTO- A-4, Silt

Moisture Content: 10-15%

Grain Size (Sieve) Analysis: >60% fines (Passing No. 200 Sieve)

Atterberg Limits (Liquid and Plastic Limit)

Topsoil: LL 37, PI 14 Intermediate layer: LL 37, PI 10

Organic Content by Ignition: Topsoil: 7.5%, Intermediate layer: 5.3%

Visual In-Field Classification: Clayey silt or silty clay

C la y T o p so il

A llu via l S a n d y G ra vel

C la yey S ilt

C la y T o p so il

A llu via l S a n d y G ra vel

C la yey S ilt

C la y T o p so il

A llu via l S a n d y G ra vel

C la yey S ilt

A llu via l S a n d y G ra vel

C la yey S iltC la yey S ilt

Site Soil Characteristics

706050403020100

cm

roots cobblesandred claybrown clay

sampling sites wet

Soil core @ MW3 (0 to 32.5 in)

Soil Core taken from MW3 (upper 32 “)

Julianna Fessenden

Percolation Testing: Results

Cole S. PeeblesPercolation Test #1,

Perc Rate = 43.05 min/inch y = 1.5931x0.4533

R2 = 0.9983

1.00

10.00

100.00

1.00 10.00 100.00 1000.00 10000.00

Total Cumulative Time (min)

dT

/dH

(m

inu

tes

/in

ch

)

Typically only represent horizontal hydraulic conductivity.- Upper Silty Topsoil: k = 2.79 ft/day. - Clayey Silt Zone: k = 2.18 ft/day. - Silt/Sandy Gravel Interface: k = 4.70 ft/day. - Average Conductivity: k = 3.22 ft/day.

** This is between 2 and 3 orders of magnitude less than alluvial gravels.

Grid and BCs of Radial Model

Full domain, vertical exaggeration ~ 10x. Domain for plotting results.

Curt Oldenburg

Injection Rate Notes

For the horizontal well case, pore volume was used to derive a first-guess

injection rate (this was discussed in earlier telecons).

PVg = LWH f Sg

L = 100 m

W = 3 m

H = 3 m

f = 0.3

Sg = 0.5

PVg = 900 m3 . 0.3 . 0.5 = 135 m3

At 1 bar, 20 oC,

rair = 1.2 kg/m3

rCO2 = 1.8 kg/m3

massCO2 = 135 m3 x 1.8 kg/m3 = 243 kg CO2

If inject 10 pore volumes over 10 days,

QCO2 = 2430 kg CO2/10d * 1 d/86400 s

QCO2 = 2.81 x 10-3 kg CO2/s

In the conference call of 28 August, the suggested rate of injection for the vertical

well was 1/300th that in the horizontal well.

QCO2 = 1/300 (2430 kg CO2/10days)

QCO2 = 0.81 kg CO2/day

For the Cases 1 and 2 presented below, injection rates of 1 kg/day and 10 kg/day

are used for comparison purposes.

Curt Oldenburg

Results for 1 kg/day at 1 day Results for 1 kg/day at 10 days

Injection Calculations for Low Perm Silt

Curt Oldenburg

But we didn’t see a large lateral spread. Why?

Likely due to root

penetrations (> 1 m depth)

through the silty layer

providing macroporous

channels for CO2

transport

Some other locations are seeing spreading

Ginninderra Joint CO2CRC-Geoscience Australia projectLocated on CSIRO Plant Industry Ginninderra Experiment Station (Canberra);

deep yellow podzolic soils; sandy loam to heavy clay; gravel to 1cm.

RessacadaPETROBRAS Research Center (CENPES), Federal University of

Santa Catarina (UFSC), Pontifical Catholic University of Rio

Grande do Sul (PUCRS), São Paulo State University (UNESP)

Coarse sand with clay layers

Resistivity measurements show significant spread

Surface Topology

Surface Topology

36

37

Resistivity Measurements

Rick Hammack

Garret Veloski

What Remains to be Learned from Controlled Releases?

39

More obvious

• Ecosystem specific responses

• Test / prove new detection technologies

More Interesting

• Detection methods at greater depths

• Transport properties through varying soil types

– How much transport in dissolved phase?

• CO2 physical and chemical distribution

• Breakthrough times for deeper releases

• Influence of topology on surface expression

Injection well at 55 m on both profiles

ZERT EW POST INJECTION

ZERT EW PRE INJECTION Rick Hammack

Garret Veloski

Resistivity Measurements

Injection well at 52 m

NS POST INJECTION

NS PRE INJECTION

Resistivity Measurements

Rick Hammack

Garret Veloski

42

Class VI Regulations§ 146.90 Testing and monitoring requirements.

(h) The Director may require surface air monitoring and/or soil gas monitoring

to detect movement of carbon dioxide that could endanger a USDW.

• (1) Design of Class VI surface air and/ or soil gas monitoring must be based on

potential risks to USDWs within the area of review;

• (2) The monitoring frequency and spatial distribution of surface air

monitoring and/or soil gas monitoring must be decided using baseline data,

and the monitoring plan must describe how the proposed monitoring will yield

useful information on the area of review delineation and/or compliance with

standards under § 144.12 of this chapter;

• (3) If an owner or operator demonstrates that monitoring employed under

§§ 98.440 to 98.449 of this chapter (Clean Air Act, 42 U.S.C. 7401 et seq.)

accomplishes the goals of paragraphs (h)(1) and (2) of this section, and meets

the requirements pursuant to § 146.91(c)(5), a Director that requires surface

air/soil gas monitoring must approve the use of monitoring employed under §§

98.440 to 98.449 of this chapter. Compliance with §§ 98.440 to 98.449 of this

chapter pursuant to this provision is considered a condition of the Class VI

permit;

(i) Any additional monitoring, as required by the Director, necessary to support,

upgrade, and improve computational modeling of the area of review evaluation43

Class VI Regulations(j) The owner or operator shall periodically review the testing and monitoring

plan to incorporate monitoring data collected under this subpart, operational data

collected under § 146.88, and the most recent area of review reevaluation

performed under § 146.84(e). In no case shall the owner or operator review the

testing and monitoring plan less often than once every five years. Based on this

review, the owner or operator shall submit an amended testing and monitoring

plan or demonstrate to the Director that no amendment to the testing and

monitoring plan is needed. Any amendments to the testing and monitoring plan

must be approved by the Director, must be incorporated into the permit, and are

subject to the permit modification requirements at §§ 144.39 or 144.41 of this

chapter, as appropriate. Amended plans or demonstrations shall be submitted

to the Director as follows:

• (1) Within one year of an area of review reevaluation;

• (2) Following any significant changes to the facility, such as addition of

monitoring wells or newly permitted injection wells within the area of

review, on a schedule determined by the Director; or

• (3) When required by the Director.

(k) A quality assurance and surveillance plan for all testing and monitoring

requirements.

44

Subpart RR – Reporting Requirements for Geologic Sequestration

• No threshold

• Research & Development exemption (must apply)

• Report (quarterly)

– Mass received

– Type of source

– Mass produced

– Mass leaked by equipment at surface

– Mass emitted by surface leakage

45

RR – Measurement, Reporting & Verification

Contents of MRV plan

• Delineation of the maximum monitoring area and the active monitoring areas.

• Identification of potential surface leakage pathways for CO2 in the maximum monitoring area and the likelihood, magnitude, and timing, of surface leakage of CO2 through these pathways.

• A strategy for detecting and quantifying any surface leakage of CO2.

• A strategy for establishing the expected baselines for monitoring CO2 surface leakage.

• MRV plan revisions required if material changes made to monitoring or operational parameters (large changes in volume injected, addition of injection wells, unpredicted plume development, etc.) 46

MVA Discussion Questions• Is current monitoring technology sufficient to meet EPA MVA

requirements for Class VI and GHG reporting?

• Is technology sufficient to monitor pressure and plume migration?

• Is technology sufficient to monitor for leaks? In wells? In the subsurface? At the surface?

• Is technology sufficient to monitor for induced seismicity?

• Is technology sufficient for all depositional environments, including those containing oil and gas?

• Is technology sufficient to establish baselines? In the subsurface? At the surface?

• Are additional small and/or large scale field tests needed to validate MVA technologies?

• Is technology sufficient for post-injection monitoring?

• Is current technology sufficiently cost-effective? Are there opportunities for significant cost reductions?

• Are there opportunities for MVA advances which would enable improved storage performance?

47

What Is the Monitoring Purpose?• Climate change mitigation?

– 1% over 1000 yrs – climate models?

• Retention in the reservoir?– Subsurface techniques typically do not measure properties directly

proportional to concentration / quantity

• Overall storage security?

• HSE, Resource protection (USDW)?– Measure to ensure levels are below impact levels

• Public assurance?

• Verification and accounting?– Mass flow meters only accurate to ~1%

48

If we had a better understanding of realistic leakage mechanisms, rates, and fluxes we

could develop better monitoring strategies.

What Are Relevant Fluxes?

49

k3

k2

k1

Mechanisms, their transport rates and relative rates will affect:

• Residence times and quantities

• Induction periods

• Flux (both area and rate)

What Are Relevant Fluxes?

50

• Simple model assumes 1st order rates (exp functional form) and solves three coupled differential equations.

• GHG mitigation relevant rates are used so effective time constant is very large (rates small)

• Under these conditions, most functional forms should be quasi-linear and qualitative results would be similar

• Allows support for “thought experiments” concerning induction periods, secondary accumulation, etc.

k3

k2

k1

5120 40 60 80 100

50000

100000

150000

200000

200 400 600 800 1000

250000

500000

750000

1 ´ 10 6

1.25 ´ 10 6

1.5 ´ 10 6

1.75 ´ 10 6

2 ´ 10 6

Years

Ton

ne

s

Years

Ton

ne

s

k3

k2

k1

1% over 1000 yrs

Fast subsequent processes

200 Megatonnesin place

Mathematica“Intuitive Interface”

Test Case One Excellent Seal

Two Good Sealsk1 = 0.0001 (10 x faster than default of 1% per 1000 yrs)k2 = 0.0001 (10 x faster)k3 = 0.01

Ton

ne

s

Ton

nes

200 400 600 800 1000

250000

500000

750000

1 ´ 10 6

1.25 ´ 10 6

1.5 ´ 10 6

1.75 ´ 10 6

2 ´ 10 6

20 40 60 80 100

50000

100000

150000

200000

Years

Years

k3

k2

k1

Induction Period

53

k3

k2

k1

20 40 60 80 100

50000

100000

150000

200000

Years

Ton

ne

s

k1 = 0.0005 (50 x faster than default of 1% per 1000 yrs)k2 = 0.0002 (50 x faster)k3 = 0.01

Near Surface Monitoring seems to Indicate Good Performance

200 400 600 800 1000

250000

500000

750000

1 ´ 106

1.25 ´ 106

1.5 ´ 106

1.75 ´ 106

2 ´ 106

Induction Period

Poor Atmospheric Performance

Years

Ton

ne

s

But there is a large and rapid accumulation under secondary seal that should be detectable

54

Underground Fiber Sensor

Hollow core where the light interacts with the carbon dioxide

20 40 60 80 100 120 140

0

5000

10000

15000

20000

25000

30000 0 .3 m C e ll O ve r P ipe

1 m F ibe r O ver P ipe

CO

2 C

on

ce

ntr

ati

on

(p

pm

)

T im e (h r)

Jamie Barr Kevin Repasky

Near-surface monitoring technologies were tested at the MSU field site.

• Surface flux monitoring, soil gas sampling, and perfluorocarbon tracers were tested at the MSU site

• All methods were able to detect plumes at both wells out to 5m

• PFC tracers were most sensitive for detection

Surface flux measurements

Soil gas measurementsPFC tracer measurements

0

10

20

30

40

50

60

70

-15 -5 5 15surface distance from pipe (m)

CO

2 c

on

ce

ntr

ati

on

(%

vo

l) 100 cm

60 cm

30 cm

What Are Relevant Fluxes?

57

k3

k2

k1

• Simple model assumes 1st order rates (exp functional form) and solves three coupled differential equations. Residence times and volumes

• GHG mitigation relevant rates are used so effective time constant is very large (rates small)

• Under these conditions, most functional forms should be quasi-linear and qualitative results similar

• Allows support for “thought experiments” concerning induction periods, secondary accumulation, etc.