SH Exploitation induced Risks - SHEER project 2/8 WP4... · Analysis of fluid-induced seismicity...

SHale gas E l ti dExploration and Exploitation induced RisksRisks

Seismic hazard assessment considering fluid-induced seismicity:Seismic hazard assessment considering fluid-induced seismicity:

Inter-event time distribution of seismicity induced by hydraulic fracturing operationsfracturing operations

Alexander Garcia-Aristizabal(AMRA)

Second Annual MeetingBlackpool - June 5-7, 2017

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 640896.

Introduction: IS seismic hazard assessment

Time

SpaceAccurate estimation ofAccurate estimation of

distribution parametersdescribing the statistical

properties (in time) of the Analysis of the Size

p p ( )seismic processes and the eventual relationships with

industrial activity

yspatial

distribution of IS, accounting for

ph sical constraintsAnalysis of the

Propagation

physical constraints (environment and

industrial parameters)

size distribution accounting for

physical constraintspa a e e s)

Integrating detailed subsurface

constraints (environment and

industrial parameters) subsurface

information to reduce the variability

observed in GMPEs

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Characterizing fluid-induced seismicityg yIn time

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Analysis of fluid-induced seismicity Obseervations

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- Analysis in the time domainRelations ith ind strial acti it- Relations with industrial activity

- Analysis in the spatial domain

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Proxy case study

Geothermal fieldCooper basin, Australia

High pressure injection into granitic rockThe well (Habanero 1) was completed in granite from 4135 to 4421m and stimulated twice (2003 & 2005)In 2003, over 20000m3 were injectedIn 2005, over 25000m3 were injectedTemperature at the botomhole: ~250°C

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Proxy case study

Geothermal fieldCooper basin, Australia

8 Olympic pools

High pressure injection into granitic rockThe well (Habanero 1) was completed in granite from 4135 to 4421m and stimulated twice (2003 & 2005)In 2003, over 20000m3 were injectedIn 2005, over 25000m3 were injectedTemperature at the botomhole: ~250°C

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Analysis of fluid-induced seismicity

Cooper basin, 2003

FIP → Fracture initiation testLTI L t i j ti t tLTI → Long-term injection test

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Cooper basin, 2003

FIP-1

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Cooper basin, 2003

FIP-1

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Analysis of fluid-induced seismicity Cooper basin, 2003

FIP-1 – Injection periodFIP 1 Injection period

During injection periods,

seismicit rateseismicity rateseems to correlatewith injection ratet ject o ate

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Analysis of fluid-induced seismicity Cooper basin, 2003

FIP-1 – 'Free response' periodFIP-1 – Free response period

During the free response periods,seismicity rate decays with timeseismicity rate decays with time

following a decay function7/20


Summary of models frequently used for analyzing fluid-induced seismicity in the time domain:

The Reasenberg & Jones model (1989, 1990, 1994)

The Epidemic-type aftershock model, ETAS (Hainzl & Ogata 2005)

The Σ-based (seismogenic index) model of Shapiro et al., 2010.

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Summary of models frequently used for analyzing fluid-induced seismicity in the time domain:

The Reasenberg & Jones model (1989, 1990, 1994)

The Epidemic-type aftershock model, ETAS (Hainzl & Ogata 2005)

The Σ-based (seismogenic index) model of Shapiro et al., 2010.

W i l t 'h b id' (I FR) d li hWe implement a 'hybrid' (I-FR) modeling approach:

Th i j ti /f (I FR) d li h→ The injection/free-response (I-FR) modeling approach

Analysis of injection periods in the time domain

Analysis of free-response periods in the time domainAnalysis of free-response periods in the time domain

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Analysis of fluid-induced seismicity I-FR approach – Injection periods


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dt

Study of the Distributionh t i i i t t ticharacterizing inter-event times

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t → inter-event timesDifferent modeling hypotheses:Different modeling hypotheses:

Non-homogeneous Poisson processprocess

Homogeneous Poisson process

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Modelparameter

determination

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Modelparameter

determination

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Modelparameter

determination

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Modelparameter

determination

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Modelparameter

determination

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Exponential(μ parameter)

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3.2 bbl/min


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9 bbl/min


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19 bbl/min


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Model testing: Forecasting injection-related seismicity (exponential model for Cooper Basin)

Where:

Parameter of the Exponential distribution: Ir_t : Injection rate at

ti twhere:

time t

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Model testing I-FR approach – Injection periods

a) Forecasting injection-related seismicity (from injection rate data)

→ Given (scheduled) injection rates and volumes, can be used to forecast expected seismicity

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a) Forecasting injection-related seismicity (from injection rate data)

13/20→ Given (scheduled) injection rates and volumes, can be used to forecast expected seismicity


Model testing: Forecasting injection-related seismicityModel testing: Forecasting injection-related seismicity

Model parameters: determined using data fromdetermined using data from

the FIP-1

Target period: FIP-3

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Model testing: Forecasting injection-related seismicity

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Model testing: Forecasting injection-related seismicityModel testing: Forecasting injection-related seismicity

Model parameters: determined using data fromdetermined using data from

the FIP-1

Target period: Extended injection 1

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Analysis of fluid-induced seismicity I-FR approach – Free response periods

Analysis of free-response periods in the time domain

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Considering the so-called “trigger models” (Vere-Jones and Davies 1966), it is d th t th b bilit f h k i t ti t ft iassumed that the probability of a shock occurring at a time t after a given

triggering event is proportional to a decay function λ(t).

Regarding the nature of λ(t), different functions can be considered:

An exponential decay,

An inverse power-law decay,

Modified Omori lawModified Omori law,

Etas model,

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t -> time from the end of injection

→ Modified Omori law,

Free-responseFree response after FIP-1

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t -> time from the end of injection


Free-response Free-response Free-response Free-responseFree response after FIP-1

Free response after FIP-2

Free response after LTI-1

Free response after FIP-3

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Analysis of fluid-induced seismicity I-FR approach: Analysis in the time domain

Summary

'Free-response'Injection period Free response period

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Summary


Rate of eventsRate of events follows a Poisson

processHPP / NHPPHPP / NHPP

Model parameter(s)Model parameter(s)are a function of the fluid injection rate

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Summary


Rate of events The rate of events after theRate of events follows a Poisson

processHPP / NHPP

The rate of events after the end of injection modeled using an adequate decay

function λ(t)HPP / NHPP

Model parameter(s) p (and k) of MOL are a f ti f th i j t dModel parameter(s)

are a function of the fluid injection rate

function of the injected volume (or mass)

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Summary


HPP / NHPP Decay function λ(t)

Model parameter(s)f ti f th

p (and k) of MOL are a f ti f th i j t dAnalysis in the timeare a function of the

fluid injection ratefunction of the injected

volume (or mass)

Analysis in the time domain

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Forecasting induced seismicity rates


Summary I-FR model for Copper Basin

Exponential – Modif. Omori

Seismicity rate:

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Seismicity rate:

Where:Where:

Parameter of the Exponential distribution:Exponential distribution:

where:

Ir_t : Injection rate attime t

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Seismicity rate:

Where:Where:

Parameter of the Exponential distribution:Exponential distribution:

where:

Ir_t : Injection rate attime t

Exponent of the difi d O i

V* : Volume Injected( di th FR i d)modified Omori:

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(preceding the FR period)

Analysis of fluid-induced seismicity I-FR approach:

Forecasting seismicity for a full stage (Injection & Free response periods)

Injection Free-responseInjection Free-response

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Back to IS seismic hazard assessment…

Forecasting seismicity Frequency-size distributiong yrates in time and space (Gutenberg-Richter)

Analysis in the time domain

GMPE

IS seismic hazardassessment

Analysis in the spatial domainassessment

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Analysis considering development by multi-stage/well, multi-well/pad, and multi-pad

Next steps

Updating procedure as the site development progresses in time

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I-FR approach IS Seismic hazard assessment: Output

Next steps

I t ti ith i l PSHA?IS seismic hazard

assessment

Integration with regional PSHA?

Regional context

nt,

epen

dent

depe

nden

ctiv

ity d

e

EGS site Tim

e-d

dust

rial a

cIn

d

Updated hazard assessment (?)( )

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ConclusionsConclusions

Identifying parameters that control seismicity rates is a key element for evaluating the y gseismic hazard of fluid injections

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ConclusionsConclusions

Identifying parameters that control seismicity rates is a key element for evaluating the y gseismic hazard of fluid injections

Si il t th t t i ti it th t ti ti fSimilar to the tectonic activity, the statistics of induced seismicity can be rather well described by relatively simple models well known in statistical seismologystatistical seismology

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ConclusionsConclusionsA modeling framework for describing fluid induced seismicity in time has g g ybeen presented. It is based in two main modeling tools:

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During injection periods:During injection periods:

Seismicity rates are modeled as a (homogeneous or non-homogeneous) Poisson process, whose

t f ti f th t f fl idparameters are a function of the rate of fluid injection.

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During injection periods:During injection periods:

Seismicity rates are modeled as a (homogeneous or non-homogeneous) Poisson process, whose

t f ti f th t f fl idparameters are a function of the rate of fluid injection.

During free response periods (Ir = 0)During free-response periods (Ir = 0),

seismicity rates are modeled using a decay function (e.g., Omori law). The decay rate is mainly

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controlled by the total volume of fluid injected

Th kThanks

[email protected]

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