Developments on Microseismic
Monitoring and Risk Assessmentof Large-scale CO2 Storage
Bettina Goertz-Allmann
NORSARCCS Technical Workshop, RITE, Tokyo, January 16, 2019

Outline• Introduction: Induced seismicity & CCS• Two case studies– In Salah, Algeria• Event detection & analysis• Confining event depth– Decatur CCS site
• Microseismic event characterization• Full-waveform modelling• Summary & Conclusions
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Induced Seismicity∆σσ3 - Pp

σN [MPa]

σ1 - Pp• Increasing pore pressure (fluid injection) brings rock closer to failure• Near-critical stress state (typical)  microseismicity• Examples: shale gas fracking, wastewater injection, geothermal
stimulation, CO2 injection
16.01.2019
CCS Technology Workshop, TokyoInduced Seismicity
Example fromBasel geothermal
stimulation(Goertz-Allmannet al., 2011,2012)• Time-distance distribution of seismicity follows
pressure diffusion• Seismicity sometimes induced by very smallpressure perturbations (tides, rain)• At large perturbations (e.g. Basel), source
parameters (stress drop and b-value) appear tocorrelate with pressure or differential stress.
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Induced Seismicity
Seismicity can be induced by a variety of other mechanisms:• Depletion & compaction (e.g. oil production)• Stress transfer in over- and sideburden• Fracture opening (P > fracture pressure, «fracking»)• Fault reactivation

Depletion & compaction
injection

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Induced Seismicity and CCS(Rutqvist, 2013)

 In CCS, we expect a number of the listed mechanisms to contribute toseismicity• Pressure-induced seismicity mainly near injection and at plume front• Stress-induced seismicity and other mechanisms further away
 Goals:
1. Verify seal integrity (risk assessment)
2. Track plume progression (monitoring)
3. Reservoir characterization (management / optimization)

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The In Salah CO2 storage site

 Injection commenced in 2004
via three injection wells.

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The In Salah CO2 storage site

sandstones & mudstones

carboniferous mudstones

20 m carboniferous standstone 4 MT CO2 injected into a naturally fractured
Carboniferous sandstone reservoir at 1.9 km depth.

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Microseismic array at KB-601
2009-2011• Downhole array of 48 3C
geophones between 30-500 m
depth• 6 geophones were connected to3 digitizers• GPS timing problems and strong
electronic noise• Only uppermost geophone
provided reliable data

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Event detection method
Goertz-Allmann et al. (2014)• Master event waveform crosscorrelation method to detect andpick seismic events within
continuous data
• More than 5000 events are detected
between August 2009 and June2011

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Comparison of events and injection data
Goertz-Allmann et al. (2014)

Kaiser effect?

fracture pressure 155 MPa

 High correlation between occurrence of microseismic events andinjection rate Periods of matrix injection and fracture injection
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Event analysis using one geophone Differential S-P wave
onset time gives anestimate of event-toreceiver distance Several clusters withsimilar arrival-timedifferences can be
identifiedP

16.01.2019
CCS Technology Workshop, TokyoSEvent analysis using one geophone Determine event direction fromparticle motion of P-waves.
 Futher separate clusters bycombining S-P, azimuth, andinclination (clusters A-D).
 Overall events are oriented in
the direction of the largest
horizontal stress.
 No seismicity within a radius ofabout 1 km around the injection
well -> Kaiser effect?

(Oye and Ellsworth, 2005 BSSA)

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Possible location of 4 event clusters

 Together with InSAR data the clusters may give an indication on theextent of the CO2 plume in 2010.
Goertz-Allmann et al. (2014)16.01.2019
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Event analysis: example waveforms
Additonalphasearrivals

Shear-wavesplitting
S-P ~ 1s

S-P ~ 0.7s

stack

S-P ~ 0.7s

stack

16.01.2019
CCS Technology Workshop, TokyoMw estimation

16.01.2019
CCS Technology Workshop, TokyoMw estimation

P-waveS-wave16.01.2019
CCS Technology Workshop, Tokyo• Distance and attenuation correction• Determine the low-frequency spectrallevel Ω0 (mean of 10 or 15 Hz to 20 Hz
depending on SNR)
• Compute seismic moment m0 and MW• Most MW estimates are between -1 and0, largest MW is about 1• MW P-wave > Mw S-wave• Effect of the different radiation pattern

b-value analysis of event clusters
 b-value is the slope of the Gutenberg-Richter law
 b-value can be linked to in-situ reservoir stress state: e.g.
high b-value when new fractures open and low b-value
when pre-existing fractures are reactivatedMC16.01.2019
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log10 (N) = a – b M

b-value analysis of event clusters
cluster A

cluster C• Similar b-values for P
and S but significant
variations between
clusters.
cluster B

cluster D• b ~ 1 for cluster A(average tectonic)• Larger b (1.5 to 2) for
clusters B-D

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Shear-wave splitting analysis• Up to 0.1 s Δt on S arrival.
• Sign of anisotropy• Eigenvalue method(Wüstefeld et al. 2010)
gives anisotropy from Δt:

A = (β Δt)/Rtime delaystack

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A: percentage anisotropy
β : average S velocity
R : source–receiver distanceΔt: time delay

Shear-wave splitting analysis• 83 events with good splitting• 5% of anisotropy for clusters B-D• Less than 2% of anisotropy forcluster A16.01.2019
CCS Technology Workshop, TokyoComparison to injection parameters• No correlation between injection
parameters and cluster A• High correlation with clusters B-D• High activity of cluster C only duringmain injection phase

16.01.2019
CCS Technology Workshop, TokyoConfining microseismic event depthPSP~ 0.5 s• Additional phase on Z
between direct P & S• S-to-P converted phaseat strongest velocity
contrast (850 m).
Cluster A
16.01.2019
CCS Technology Workshop, TokyoSConfining microseismic event depth• Use 3D ray tracing toidentify converted SP.
• Test potential source
locations:• Waveforms at A and A’
have similar S-P
traveltimes but
converted phase only
matches real data atshallower position A.

16.01.2019
CCS Technology Workshop, TokyoConfining microseismic event depth• Cluster A at about 1.7
km (well above thereservoir but still withinlower cap rock).
• No shear-wave splitting
is observed andanisotropy may occur
mainly in deeper layers.
• Inclination angles forcluster A are distinctly
higher than for cluster
B-D also pointing to ashallower source.
 Cluster A: within cap rock!
Goertz-Allmann et al. (2014)16.01.2019CCS Technology Workshop, TokyoSummary of microseismicity at In Salah Over 5000 events detected despite
only one sensor
 Clear dependence on CO2 injection.
 Constrain event depth with later
phase arrivals: we find that onecluster is in the cap rock.
 Two main groups of events areidentified: Type 1: stress-triggered
seismicity (A) Type 2: fracture opening (B-D)
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Outline• Introduction: Induced seismicity & CCS• Two case studies– In Salah, Algeria• Event detection & analysis• Confining event depth– Decatur CCS site
• Microseismic event characterization• Full-waveform modelling• Summary & Conclusions
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The Decatur CCS site•

Inject 1 M tons of CO2 into Mt.
Simon sandstone (460 m thick)at about 1.9 km depth (end2011-2014).

•Borehole & surface sensors.

•About 4,800 microseismic
events were located using
borehole strings.

•

Events occur in distinct clusters
with heterogeneous activity.
Mt. Simon
Lower Mt. Simon
Argenta
Precambrian basement

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The Decatur CCS site
• Most events with Mw < 0.
• Injection at very low pressure (< 1 MPa)
• No obvious correlation with plumemigration – events far from the injection

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Spatial distribution of event clusters and comparison tomodelled CO2 plume
Map view

EW cross section

Cluster centroid locations
Borehole stations
Modeled CO2 plume16 microseismic clusters
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Event characterizationVp [m/s]

Depth [m]Basement
Reservoir
eventsevents events
Basementvs.
reservoir

direct wave
head wave
Precambrian• Theoretical ray diagrams for reservoir & basement events.
• Different waveform signature: head wave and direct wave arrivals
clearly visible for reservoir events
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Event characterization
Reservoir

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Event characterization
Sub-cluster analysis of one cluster
Cross-correlation matrix

Goertz-Allmann et al. (2017)16.01.2019
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Microseismic event characterization
Cluster A
Spatial distribution Temporal migration• Separate eventsoccurring withindifferent layers:
Cold = reservoir
Warm = basement• Migration of eventsfrom the reservoir
into the basement
over the course of100-200 days.
Goertz-Allmann et al. (2017), JGR
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Cluster B
spatialEvent characterization
temporal Separation between  Migration fromthe reservoir
reservoir andinto thebasement events.
basement.

b-valuestress drop

 Decrease ofb-value withdistance.

 Increase of stressdrop with distance.

• Evidence for a fluid-driven process at the cluster level.
• Signs of pressure diffusion.
• Possible punctual hydraulic connection between reservoir andbasement (i.e., confined to faults).
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Relative event locations
Preliminary results of improved relative event locations bydeveloping a modified relocation method.

• Accurate event locations are necessary for any kind of interpretation• Change of cluster orientation• Planar feature
Old event locations→ Fracture?
Relocated eventsFull-waveform modelling
Observed waveform example
PS

PS3_2
PnSn

PS3_1

16.01.2019
CCS Technology Workshop, Tokyo• Different phase arrivals with head wave
and direct wave arrivals.
• Pn/Sn phase arrives first at deeper
sensor (PS3_1).
• P/S phase arrives first at shallower
sensor (PS3_2).
• Waveform modelling can help us tobetter understand the observed
waveform characteristics.
• Gain a complete picture of the travel
path of an event and helps us to select
events and phases, which best sample
the target area.

Full-waveform modelling• 3D FD modelling using 1D velocity model• 30 Hz Ricker wavelet.
• Compare sources placed at 1600 m, 2040m, and 2200 m depth.
Synthetic receivers
Real receivers
Sources at 1600 m,2040 m and 2200 m

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Full-waveform modelling
Source at 2040 m depth

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Full-waveform modelling
Sequential snap-shots of full waveform modelling (from A to F)

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Full-waveform modellingobserved

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modelled

Full-waveform modellingmodelled
Source 1600 m

Source 2040 m

Source 2200 m

observed

16.01.2019
CCS Technology Workshop, Tokyo• Different source depths show different
signatures.
• Best match between observed and modelleddata at 2040 m (reservoir/basement interface).
• Different phases can only be distinguished atlarger source-receiver distances (> 1200 m).

Summary of microseismicity at Decatur• Type 1: mainly stress-triggered seismicity• A seismicity migration pattern from the sediment into basement isobserved.
• Seismicity within a cluster exhibits signs of pressure diffusion, boththrough the spatio-temporal evolution of seismicity but also throughsource parameters such as b-value and stress drop.
• Eventually, a punctual hydraulic connection (such as, e.g., abasement-connected fault) causes migration into the basement. may explain clustering of seismicity (i.e., weak crust around thoseareas).
• Finite-difference modelling helps to correctly identify seismic phases
sampling the CO2 plume and can confirm a source at thereservoir/basement interface.

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Comparison In Salah and Decatur• Depth resolution of microseismicity was critical to support reservoir
characterization• Obtained by exploiting information contained in later arrivals /multipathing• Requires waveform modelling for hypothesis testing and confirmation• In Salah:– Information on caprock integrity– Variations in b-value between (pressure-driven?) reservoir eventsand (stress-driven?) caprock events– Despite very inadequate network coverage• Decatur:– Connection between reservoir and basement– Overall stress-driven seismicity/ fracture reactivation– But fluid-driven characteristics within cluster
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More general insight• During CCS operations: most important is event depth resolution toverify seal integrity.
– Reservoirs are generally thinner than depth uncertainty fromstandard seismological methods. Therefore, additional constraints
need to be exploited to improve depth resolution.
• Integration of reservoir engineering data is important for meaningful
microseismic interpretation:– Need pressure, pumping & fluid flow data densely sampled in timewith accurate time stamp.
– Source parameters (b, ∆σ) can provide hints of reservoir hydraulics,
but require good calibration• Accurate moment magnitudes are important for risk assessment (event
discrimination and forecast with b value):– Ensure sufficient bandwidth of recording– Good prior knowledge of noise environment (particularly problematicoffshore)
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More general insight• Good network planning:– Vertical aperture with borehole array(s) for depth resolution– Azimuthal coverage for location accuracy and source parameter
inversion including moment tensor• Real-time data stream and automatic processing can provide “trafficlight” feedback to operations.
• In most cases I have seen, microseismicity can NOT be used to track
CO2 plume because of often lack of brittle deformation.
Therefore a complementary method needs to be used for that (4Dseismic, InSAR (deserts!), microgravity (offshore), geochemical
sampling, …. ).

16.01.2019
CCS Technology Workshop, TokyoThank you for your attention!
Contact: Bettina Goertz-Allmann
Email: bettina@norsar.noThanks to my collegues: D. Kühn, V. Oye, K. Iranpour, B. Dando, E. Aker, B. Bohloli,R. Bauer, S. Greenberg,Acknowledgements
The partners in the In Salah CO2 Storage Joint Industry Project - BP, Equinor (formerly Statoil), and Sonatrach.

Part of this work on Decatur was supported as part of the Center of Geological Storage of CO2, an Energy Frontier
Research Center funded by the U.S. Department of Energy, Office of Science.
Data for this project were provided, in part, by work supported by the U.S. Department of Energy under award number
DE-FC26-05NT42588 and the Illinois Department of Commerce and Economic Opportunity.
We are grateful for support through the Climit program of GASSNOVA project No. 616065.
Data provided by the Midwest Geological Sequestration Consortium (MGSC), funded through the U.S. DoE National
Energy Technology Laboratory (NETL) and the State of Illinois.

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