Internal microseismic event pattern revealed by waveform cross-correlation analysis

Transcription

1 Internal microseismic event pattern revealed by waveform cross-correlation analysis Bettina P. Goertz-Allmann, Volker Oye, Steven J. Gibbons, Robert Bauer, and Robert Will MGSC annual meeting September 20, 2017

2 Outline Microseismic activity at IBDP CCS site Event characterization using waveform cross-correlation Formation distinction Spatial & temporal sub-cluster analysis Statistical & physical source parameter variations Conclusions 2/17

3 Microseismic activity at IBDP CCS site Over 17,000 events detected (4,800 located). Events occur in distinct clusters. Heterogeneous cluster activity. Analysis based on deep borehole data. Mt. Simon Lower Mt. Simon Argenta Precambrian basement 3/17

4 4/17 Microseismic activity at IBDP CCS site

5 Event characterization using waveform cross-correlation Distinguish between events in the reservoir and in the basement: Triggered by different mechanisms (pressure-driven versus stress-driven) Hydraulic connection between reservoir & basement? Need better depth resolution to identify basement and reservoir events à waveform x-correlation technique Ø Increased relative depth resolution Ø Formation distinction possible R=0.92 Master 5/17

6 Event characterization using waveform cross-correlation Master 1 Reservoir events Master 2 Basement events 6/17

7 Event characterization using waveform cross-correlation Basement Reservoir vs. events reservoir events events Vp [m/s] direct wave head wave Depth [m] Precambrian Theoretical ray diagrams for reservoir & basement events. Different waveform signature: head wave and direct wave arrivals clearly visible for reservoir events 7/17

8 Event characterization using waveform cross-correlation Reservoir Basement Basement events Reservoir events 8/17

9 Event characterization using waveform cross-correlation Sub-cluster analysis of cluster A and B Cross-correlation matrix for cluster B 9/17

10 Event characterization using waveform cross-correlation Cluster B Spatial distribution Temporal migration Strong degree of spatial clustering. Separate events occurring within different layers with much more confidence. Migration of events from the reservoir into the basement over the course of days. 10/17

11 Event characterization using waveform cross-correlation Cluster A Spatial distribution Temporal migration Strong degree of spatial clustering. Separate events occurring within different layers with much more confidence. Migration of events from the reservoir into the basement over the course of days. 11/17

12 Statistical & physical source parameter variations b-value b-value is the slope of the Gutenberg- Richter law. Cluster A Cluster B stress drop Δσ The difference between the state of stress before and after the earthquake is called the stress drop. W 0 corner frequency f c Average b-value points to reactivation of pre-existing fractures rather than creation of new fractures. æ f Ds = M c ö 0 ç è 0.42b ø 3 b-value & stress drop can be linked to in-situ reservoir stress state 12/17

13 Statistical & physical source parameter variations Spatial b-value variations High b-values at the cluster nucleation point. Decrease of b-value with distance. 13/17

14 Statistical & physical source parameter variations Spatial stress drop variations Lower stress drops around nucleation point and increase towards the Northeast. 14/17

15 Statistical & physical source parameter variations b-value stress drop Decrease/increase of b-value/stress drop with distance. Could suggest some fluid percolation process. 15/17

16 Statistical & physical source parameter variations r = 4πDt 16/17 Signs of pressure diffusion in the seismicity of cluster B. Strongly simplifying assumptions with a hydraulically isotropic and homogeneous medium. Possible punctual hydraulic connection between reservoir and basement i.e., confined to faults.

17 Conclusions We achieve high relative depth resolution using waveform cross-correlation, which reveals seismicity migration patterns from sediment into basement. Seismicity within a cluster exhibits signs of pressure diffusion, both through the spatio-temporal evolution of seismicity but also through source parameters such as b-value and stress drop. Eventually, a punctual hydraulic connection (such as, e.g., a basement-connected fault) causes migration into the basement. à may explain clustering of seismicity (i.e., weak crust around those areas). Results have been published in : Goertz-Allmann, B. P., et al. (2017) "Characterization of induced seismicity patterns derived from internal structure in event clusters." JGR. 17/17

18 Thank you for your attention! Contact: Bettina Goertz-Allmann This work 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.