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SEG 76th Annual International Meeting

SEG 76th Annual International Meeting. Continuous Monitoring of Crosswell Seismic Travel Time Thomas M Daley 1 , Paul G. Silver 2 , Fenglin Niu 3 and Ernie Majer 1 1 Lawrence Berkeley National Laboratory 2 Carnegie Institute 3 Rice University. Outline. Background

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SEG 76th Annual International Meeting

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  1. SEG 76th Annual International Meeting Continuous Monitoring of Crosswell Seismic Travel Time Thomas M Daley1, Paul G. Silver2, Fenglin Niu3 and Ernie Majer1 1Lawrence Berkeley National Laboratory 2Carnegie Institute 3Rice University

  2. Outline • Background • Active source stress monitoring • Theory • Limits of travel time measurement accuracy • Optimal frequency of acquisition • Method - Crosswell equipment • Field Experiment Results • Conclusions

  3. Background (1/3) • Goal: In-situ monitoring of stress changes using seismic travel time change • Motivation: • Earthquake ‘Prediction’ • Tectonic stress change • Reservoir Management • Fluid Pressure via effective stress • Subsidence via stress and strain changes Days Source Sensors

  4. Background (2/3) • Lab studies demonstrate stress sensitivity • Stress sensitivity of velocity ~10-9 to 10-6 /Pa • Attempts at field scale measurement date back decades (e.g. Reasenberg and Aki, JGR 1974), with recent work using 4D surface seismic • Crosswell geometry improves repeatability and frequency content (no near surface variations) and gives in-situ result • Continuous monitoring significantly reduces error due to positioning and allows better understanding of time-varying signals (as opposed to time-lapse ‘snapshots’)

  5. Background (3/3) • We need ‘calibration’ signals to understand the stress sensitivity - velocity change itself is not enough • Barometric pressure and Earth tides are ideal calibration signals, but they require high precision • Unambiguous barometric pressure induced change was reported by Yamamura, et al. (2003) and motivated our studies

  6. Recent Observation of Barometric Pressure(Earthquake Res. Inst., Univ. Tokyo) Piezo source offset=12 m every 30 min for 1 year. Velocity precision 10-4 , Velocity-stress sensitivity 5 x 10 -7 (Yamamura et al., 2003) 450 M depth crosswell

  7. Theory (1/3) • For a fixed source-receiver distance with travel time T • Delay time between two measurements =  • Fractional change in velocity = V =  / T • Define dimensionless change per period  =  f0 • We want to measure the minimum V • For data with N wavelengths with center frequency f0 • We want to maximize N (distance and frequency) and minimize Std. Dev.  =  = delay time precision • Theoretical limit on delay time precision given by the Cramer-Rao Lower Bound which predicts 

  8. Theory (2/3): Delay Time Precision • For our crosswell acquisition parameters we can simplify the Cramer-Rao bound (see abstract ) • T=window length, B=fractional bandwidth, SNR=Signal-to-Noise Ratio • Result: • The precision of travel time monitoring is mainly dependent on signal-to-noise ratio • Massive stacking can maximize SNR and minimize e < 10-8 s

  9. Theory (3/3): Optimal Frequency • Attenuation, Q, reduces the signal amplitude as a function of frequency • For a given Q, and a given distance, there is an optimal N and an optimal f0 • For /Q<<1, optimal N ~ Q/ • For Q=60 , N=20, Vp=1.5 km/s then • 3 m, f0 = 10 kHz • 30 m, f0 = 1 kHz • 100 m, f0 = 330 Hz • 1000 m, f0 = 33 Hz

  10. Field Experiment 2003:LBNL Test Wells - 3 m Scale Sensor Well 64-OB-2 Source Well 64-OB-1

  11. Borehole Source and Sensors Hydrophone Sensor Piezoelectric Source

  12. Seismic System Geode Recording System Source Monitor Oscilloscope Source H.V. Pulser Computer (Acq. Program) Shot Monitor Sensor Input Source Output

  13. Data Acquisition Seismograms • Dominant frequency: 10 kHz. • Sample Rate: 48,000 Hz = 20.83 ms • 30 ms record length • Repeated every 100ms. • Field stack 600 ( 1 minute) • 24 channels recorded • 864,000 traces/hr. , ~8 Mb/hr. • Can choose “best” sensor. • Total Time = ~ 8 days

  14. Stacking is Very Effective • Get N1/2 improvement out to at least 10,000 traces!

  15. Delay Time Processing • Data resampled to ~ 2.5 x10-9 s • Each recording cross-correlated with first recording (time and frequency domain compared) • Initial processing for 1 min data and 1 hour data (stack 60)

  16. Precision of One-Minute Measurements • Histogram of differences between adjacent minutes. • For one minute stacking, standard error ~50ns. • For one-hour stacking, standard error only ~ 6ns. • Corresponds to dV of 3x10-6. DelayTime (ns)

  17. LBNL Test Result stress sensitivity of 10-6 /Pa

  18. RFS - 30 m Experiment 2004 • Richmond Field Station Boreholes • Source 25 m deep, 30 m well separation • Attempt to restrain motion Source with hard foam Sensor with centralizer

  19. Instrument Temperature Affects Travel Time ~10 ºC Delay Time (us) Temperature sensitivity ~ 0.1s/ºC Measure and subtract average temperature sensitivity.

  20. RFS Delay Time SNR - 1 minute stack = 600, Std Dev = 40 ns SNR - 1 Hour stack = 3200, Std Dev = 5.2 ns

  21. RFS Results Temperature and linear trend removed stress sensitivity 5 x 10-8 /Pa

  22. Experiment 2005:SAFOD Boreholes Crosswell: 1.1 km deep ~14 m apart

  23. SAFOD Boreholes and Equipment Piezoelectric Source 3C Clamping Sensor

  24. Comparison with Barometric Pressure • Stress sensitivity: 1.3x10-7/Pa • Suggests that we can observe small stress changes at near-seismogenic depth. Delay Time (sec) 1s 10 mbar Bar. Press. (mbar) Elapsed Time(days)

  25. Summary • Submicrosecond precision is achievable with continuous crosswell acquisition • Barometric pressure change can be detected and used for calibration of stress sensitivity • Stress Sensitivity of 1x10-6 (3 m depth), 5x10-8 (30 m depth), 1x10-7 (1.1 km depth) • Permanent emplacement should be even better!

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