Verification of Predictions of Magnitude of Completeness Using an Earthquake Catalog

Transcription

1 Verification of Predictions of Magnitude of Completeness Using an Earthquake Catalog Designing induced seismic monitoring networks to meet regulations Dario Baturan Presented at GeoConvention 2015

2 Introduction Magnitude of completeness (Mc) lowest magnitude at which all the earthquakes in a space-time volume are detected Gutenberg-Richter (G-R) law 10 Along with location accuracy, Mc is considered a fundamental measure of seismic network performance How do we design a seismic network to meet monitoring objectives without a pre-existing earthquake catalog?

3 Motivation Model and asses the performance to meet monitoring requirements Report all M1.5 earthquakes or higher (BC OGC dense array directive) Compare different network designs Optimize # of stations and their distribution to minimize monitoring costs Consider site noise Build robust monitoring protocols Impact of each station on network performance Redundancy and design for 24/7 operation Select appropriate instrumentation Consider the instrument noise floor in the frequency range of interest Application in enforcing induced seismic monitoring regulations Earthquake magnitude-based traffic light protocols Ensure seismic networks meet their monitoring objectives on day 1

4 Alberta Energy Regulator Subsurface Order No. 2 Nanometrics Before conducting hydraulic fracturing operations in the DuvernayZone, the licensee must assess the potential for induced seismicity and adopt, and be immediately prepared to implement, a response plan to address potential seismic events Monitor for seismic activity in the vicinity of the hydraulic fracturing operations and follow a traffic light process with staged action thresholds The order requires licensees to immediately report to the AER observed seismic events of 2.0 ML or greater The licensees must be able to detect, report and cease operations in case of an event of 4.0Ml or greater in the vicinity of their well In summary Implement a response plan based on seismicity Induced seismic monitoring network Traffic light process operation Real-time 24/7 operation and notifications Reportingand action thresholds triggered by M2 and M4 earthquakes respectively Networkdesign for Mc ~ 1.8

5 Methodology 1. Define the monitoring region of interest and divide it into a grid 2. Overlay a starting point seismic station array 3. Determine noise floor for each station 4. Estimate event spectra using generalized Brune modelling 5. Evaluate minimum magnitude event that exceeds threshold SNR at a minimum of 4 stations within each grid point 6. Refine the distribution and the number of stations

6 Array Modelling Inputs Event Spectra Utilize classic Brune (1970) seismic event displacement spectrum model generalized by Abercombie (1995) to account for Effective anelastic attenuation (Q) High frequency roll-off rate (n) Corner frequency degree of sharpness (γ)

7 Velocity model Array Modelling Inputs Source and receiver velocity and medium density required for Brune event spectra modelling Seismic station distribution in the region of interest Target earthquake depths Minimum detection SNR

8 Array Modelling Inputs Station Noise Instrument noise Published digitizer and seismometer self-noise specifications Important to chose the right instrument for the job Site noise PSD PDF of existing or survey stations in the region of interest Compute noise map across the frequency range of interest

9 Verification Central United States New Madrid seismic zone predicted performance using Array Modelling Existing 51-station seismic network

10 Verification Central United States Catalogue of almost 2500 events clustered around several known faults in the region Choose only grid squares with more than 50 earthquakes in them

11 Verification Methodology Plot frequency magnitude distribution for each grid square Find maximum curvature of the frequency magnitude distribution Bootstrap sample the catalogue for stability and estimate uncertainty

12 Verification Central United States Observed and predicted Mc similar The difference in predicted and observed Mc is on average ~ 0.3

13 Verification Central United States Low uncertainty in observed Mc (~ 0.1 or less) Predicted and observed Mc discrepancies appear spatially unbiased

14 Discussion Potential sources of discrepancy Mc computation method - Woesnner & Weimer, S Discretization of catalogue SNR assumes optimally-tuned trigger algorithm Much better agreement observed in induced seismic data sets

15 Case Study Brazeau, Dam Traffic light thresholds set at M1.0 and M2.0 within the exclusion zone All events of M >1.0 MUST be detected Desired network performance obtained with 8 stations Consider adding more stations for redundancy Currently only 1 event detected within exclusion zone M0.8, did not trigger traffic light

16 Case Study Duvernay, Alberta Alberta Energy Regulator Subsurface Order No. 2 Traffic light threshold set at M2.0 and M4.0 Model network performance for Mc ~ stations required to ensure compliance

17 Summary Developed seismic array design/performance modeling methodology Mc predictions agree reasonably well with observations from the case study catalogue Method allows objective comparison of network designs Application in design of regulation-driven induced seismic monitoring networks Traffic light protocols usually triggered by event magnitude thresholds

18 Key references: Questions? Abercrombie, R., (1995), Earthquake source scaling relationships from -1 to 5 ML, using seismograms recorded at 2.5 km depth, J. Geophys. Res., Vol. 100, pp Ackerley, N. (2012). Poster Presentation: Estimating the Spectra of Small Events for the Purpose of Evaluating Microseismic Detectability Threshholds. GeoConvention. Calgary. Brune, J. (1970). Tectonic Stress and the Spectra of Seismic Shear Waves from Earthquakes. J. Geophys. Res., Vol. 75, No. 26, McNamara, D. E., & Buland, R. P. (2004). Ambient Noise Levels in the Continental United States. Bull. Seism. Soc. Am., Vol. 94, No. 4, Ogata, Y. & Katsura, K. (1993) Analysis of temporal and spatial heterogeneity of magnitude frequency distribution inferred from earthquake catalogues. Geophys. J. Int., 113, Peters, D. & Crosson, R. (1972) Application of prediction analysis to hypocenter determination using a local array. Bull. Seism. Soc. Am., 62 (3), Stabile, T. A., Iannaccone, G., Zollo, A., Lomax, A., Ferulano, M. F., Vetri, M. L., et al. (2013). A comprehensive approach for evaluating network performance in surface and borehole seismic monitoring. Geophys. J. Int., 192, Wiemer, S. & Wyss, M. (2000) Minimum Magnitude of Completeness in Earthquake Catalogs: Examples from Alaska, the Western United States, and Japan. Bull. Seism. Soc. Am., 90 (4), Woesnner, J., & Weimer, S. (2005). Assessing the Quality of Earthquake Catalogues: Estimating the Magnitude of Completeness and Its Uncertainty. Bull. Seism. Soc. Am., 95 (2),

19 Thank You Dario Baturan Director, Technical Operations