SHale gas Exploration l and Exploitation induced Risks Seismic hazard assessment considering fluid-induced seismicity: Inter-event time distribution of seismicity induced by hydraulic fracturing operations Alexander Garcia-Aristizabal (AMRA) Second Annual Meeting Blackpool - 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.
3/20 Introduction: IS seismic hazard assessment Time Accurate estimation of distribution parameters describing the statistical properties p (in time) ) of the seismic processes and the eventual relationships with industrial activity Space Analysis of the spatial distribution of IS, accounting for physical constraints (environment and industrial parameters) a e Size Analysis of the size distribution accounting for physical constraints (environment and industrial parameters) Propagation Integrating detailed subsurface information to reduce the variability observed in GMPEs
Characterizing fluid-induced seismicity In time 4/20
Analysis of fluid-induced seismicity Observations 4/20
Analysis of fluid-induced seismicity Observations 4/20
Analysis of fluid-induced seismicity Observations 4/20
Analysis of fluid-induced seismicity Observations - Analysis in the time domain - Relations with industrial activity it - Analysis in the spatial domain 4/20
Proxy case study Geothermal field Cooper basin, Australia High pressure injection into granitic rock The well (Habanero 1) was completed in granite from 4135 to 4421m and stimulated twice (2003 & 2005) In 2003, over 20000m 3 were injected In 2005, over 25000m 3 were injected Temperature at the botomhole: ~250 C 5/20
Proxy case study Geothermal field Cooper basin, Australia 8 Olympic pools High pressure injection into granitic rock The well (Habanero 1) was completed in granite from 4135 to 4421m and stimulated twice (2003 & 2005) In 2003, over 20000m 3 were injected In 2005, over 25000m 3 were injected Temperature at the botomhole: ~250 C 5/20
Analysis of fluid-induced seismicity Cooper basin, 2003 FIP Fracture initiation test LTI Long-term injection testt 6/20
Analysis of fluid-induced seismicity Cooper basin, 2003 FIP-1 6/20
Analysis of fluid-induced seismicity Cooper basin, 2003 FIP-1 6/20
Analysis of fluid-induced seismicity Cooper basin, 2003 FIP-1 Injection period During injection periods, seismicity rate seems to correlate with injection rate 7/20
Analysis of fluid-induced seismicity Cooper basin, 2003 FIP-1 'Free response' period During the free response periods, seismicity rate decays with time following a decay function 7/20
Analysis of fluid-induced seismicity 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. 8/20
Analysis of fluid-induced seismicity 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. We implement a 'hybrid' (I-FR) modeling approach: The injection/free-response (I-FR) modeling approach Analysis of injection periods in the time domain Analysis of free-response periods in the time domain 8/20
Analysis of fluid-induced seismicity I-FR approach Injection periods Analysis of injection periods in the time domain 9/20
Analysis of fluid-induced seismicity I-FR approach Injection periods Analysis of injection periods in the time domain dt Study of the Distribution characterizing i inter-event ttimes 9/20
Analysis of fluid-induced seismicity I-FR approach Injection periods t inter-event times Different modeling hypotheses: Non-homogeneous Poisson process Homogeneous Poisson process 9/20
10/20 Analysis of fluid-induced seismicity I-FR approach Injection periods Model parameter determination
10/20 Analysis of fluid-induced seismicity I-FR approach Injection periods Model parameter determination
10/20 Analysis of fluid-induced seismicity I-FR approach Injection periods Model parameter determination
10/20 Analysis of fluid-induced seismicity I-FR approach Injection periods Model parameter determination
10/20 Analysis of fluid-induced seismicity I-FR approach Injection periods Model parameter determination
11/20 Analysis of fluid-induced seismicity I-FR approach Injection periods Exponential (μ parameter)
11/20 Analysis of fluid-induced seismicity I-FR approach Injection periods 3.2 bbl/min Exponential (μ parameter)
11/20 Analysis of fluid-induced seismicity I-FR approach Injection periods 9 bbl/min Exponential (μ parameter)
11/20 Analysis of fluid-induced seismicity I-FR approach Injection periods 19 bbl/min Exponential (μ parameter)
Analysis of fluid-induced seismicity I-FR approach Injection periods Model testing: Forecasting injection-related seismicity (exponential model for Cooper Basin) Where: Parameter of the Exponential distribution: where: Ir_t : Injection rate at time t 12/20
13/20 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
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 13/20
13/20 Model testing I-FR approach Injection periods Model testing: Forecasting injection-related seismicity Model parameters: determined using data from the FIP-1 Target period: FIP-3
13/20 Model testing I-FR approach Injection periods Model testing: Forecasting injection-related seismicity
13/20 Model testing I-FR approach Injection periods Model testing: Forecasting injection-related seismicity Model parameters: determined using data from the FIP-1 Target period: Extended injection 1
14/20 Analysis of fluid-induced seismicity I-FR approach Free response periods Analysis of free-response periods in the time domain
14/20 Analysis of fluid-induced seismicity I-FR approach Free response periods Considering the so-called trigger models (Vere-Jones and Davies 1966), it is assumed dthat tthe probability bilit 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 law, Etas model,
15/20 Analysis of fluid-induced seismicity I-FR approach Free response periods Modified Omori law, t -> time from the end of injection Free-response response after FIP-1
15/20 Analysis of fluid-induced seismicity I-FR approach Free response periods Modified Omori law, t -> time from the end of injection Free-response response Free-response response Free-response response Free-response response after FIP-1 after FIP-2 after LTI-1 after FIP-3
15/20 Analysis of fluid-induced seismicity I-FR approach Free response periods Modified Omori law,
16/20 Analysis of fluid-induced seismicity I-FR approach: Analysis in the time domain Summary Injection period 'Free-response' response period
16/20 Analysis of fluid-induced seismicity I-FR approach: Analysis in the time domain Summary Injection period 'Free-response' response period Rate of events follows a Poisson process HPP / NHPP Model parameter(s) are a function of the fluid injection rate
16/20 Analysis of fluid-induced seismicity I-FR approach: Analysis in the time domain Summary Injection period 'Free-response' response period Rate of events follows a Poisson process HPP / NHPP The rate of events after the end of injection modeled using an adequate decay function λ(t) Model parameter(s) are a function of the fluid injection rate p (and k) of MOL are a function of the injected volume (or mass)
Analysis of fluid-induced seismicity I-FR approach: Analysis in the time domain Summary Injection period 'Free-response' response period HPP / NHPP Decay function λ(t) Model parameter(s) are a function of the fluid injection rate Analysis in the time domain p (and k) of MOL are a function of the injected volume (or mass) Forecasting induced seismicity rates 16/20
17/20 Analysis of fluid-induced seismicity I-FR approach: Analysis in the time domain Summary I-FR model for Copper Basin Exponential Modif. Omori Seismicity rate:
17/20 Analysis of fluid-induced seismicity I-FR approach: Analysis in the time domain Summary I-FR model for Copper Basin Exponential Modif. Omori Seismicity rate: Where: Parameter of the Exponential distribution: where: Ir_t : Injection rate at time t
17/20 Analysis of fluid-induced seismicity I-FR approach: Analysis in the time domain Summary I-FR model for Copper Basin Exponential Modif. Omori Seismicity rate: Where: Parameter of the Exponential distribution: where: Ir_t : Injection rate at time t Exponent of the modified d Omori: V* : Volume Injected (preceding the FR period)
17/20 Analysis of fluid-induced seismicity I-FR approach: Forecasting seismicity for a full stage (Injection & Free response periods) Injection Free-response
18/20 Back to IS seismic hazard assessment Forecasting seismicity rates in time and space Frequency-size distribution (Gutenberg-Richter) Analysis in the time domain GMPE Analysis in the spatial domain IS seismic hazard assessment
Analysis considering development by multi-stage/well, multi-well/pad, and multi-pad Next steps Updating procedure as the site development progresses in time
18/20 IS Seismic hazard assessment: Output I-FR approach Next steps Integration ti with regional PSHA? Regional context EGS site IS seismic hazard assessment Time-d dependen nt, Ind dustrial ac ctivity de ependent Updated hazard assessment (?)
19/20 Conclusions Identifying parameters that control seismicity rates is a key element for evaluating the seismic hazard of fluid injections
19/20 Conclusions Identifying parameters that control seismicity rates is a key element for evaluating the seismic hazard of fluid injections Similar il to the tectonic t activity, it the statistics ti ti of induced seismicity can be rather well described by relatively simple models well known in statistical seismology
Conclusions A modeling framework for describing fluid induced seismicity in time has been presented. It is based in two main modeling tools: 20/20
Conclusions A modeling framework for describing fluid induced seismicity in time has been presented. It is based in two main modeling tools: During injection periods: Seismicity rates are modeled as a (homogeneous or non-homogeneous) Poisson process, whose parameters are a function of the rate of fluid injection. 20/20
Conclusions A modeling framework for describing fluid induced seismicity in time has been presented. It is based in two main modeling tools: During injection periods: Seismicity rates are modeled as a (homogeneous or non-homogeneous) Poisson process, whose parameters are a function of the rate of fluid injection. During free-response response periods (Ir = 0), seismicity rates are modeled using a decay function (e.g., Omori law). The decay rate is mainly controlled by the total volume of fluid injected 20/20
Thanks alexander.garcia@amracenter.com