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Continuous Monitoring of Crosswell Seismic Travel Time: Implications for Stress Monitoring Preliminary Results Tom Daley Lawrence Berkeley National Laboratory.

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Presentation on theme: "Continuous Monitoring of Crosswell Seismic Travel Time: Implications for Stress Monitoring Preliminary Results Tom Daley Lawrence Berkeley National Laboratory."— Presentation transcript:

1 Continuous Monitoring of Crosswell Seismic Travel Time: Implications for Stress Monitoring Preliminary Results Tom Daley Lawrence Berkeley National Laboratory Paul G. Silver Carnegie Institution of Washington, DTM Fenglin Niu Rice University E. L. Majer Lawrence Berkeley National Lab.

2 Outline Motivation Background/History Comparing Experimental Precision Data Acquisition at LBNL Building 64 Site Preliminary results: phase 1 of three-phase program. Demonstrate ability to observe barometric pressure, tidal stresses in travel time and velocity precision of 10 -6. Future Plans: Progressively more realistic geometries, monitor other variables. Phase I 3-meter distance, 15-m depth (LBL facility). Phase II 30m distance 70m depth (LBL/RFS facility). Phase III 100m distance, 2000m depth (Parkfield).

3 Motivation: Why Develop Stress Measurement Methodology? Temporal changes in stress at depth arguably the most important physical property for understanding earthquake occurrence. In principle, can be done with seismology exploiting stress sensitivity of seismic velocity (normally attributed to cracks). We are not the first to propose this:

4 Motivation Continued We are not the first to propose this: Nikolayev(1970)=> Omori (1895-1897!) DeFazio(1973), Reasenberg and Aki(1974), Leary(1979), Yukutake et al.(1988), Sano et al(1999) At Parkfield (LBNL Involvement): Karageorgi, Clymer, McEvilly (1992) Karageorgi, McEvilly, Clymer (1997) : “any future application of these observations would have to be based on a simple, continuous measurement.” Why has this been difficult? Precision, equipment, need for calibration (stress versus velocity) Why are things different now? Improved precision: source and sensor design and electronics recording systems: sampling rates, fast stacking, large storage, precise triggering Can use continuous calibration: Tides and Barometric pressure. Potential access to seismogenic depths via SAFOD

5 Recent Observation of Barometric Pressure (Earthquake Res. Inst., Univ. Tokyo) 450 M depth 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)

6 Recent Observation of Tidal Stresses (ERI, Univ Tokyo) Piezo source offset=12 m, depth=450m, every 30 min for 1 year. Velocity precision 10 -4, Velocity-stress sensitivity 5 x 10 -7 (Yamamura et al., 2003)

7 Delay Time Precision Define  minimum measurable travel time change, T = total travel time, f 0 = center frequency, n = number of wavelengths from source to receiver (n  f    minimum measurable change per period (  f  ) Then the minimum measurable velocity change (“precision”),  V=dV/V=  n,  V=  /n has been measured as 10 -3 – 10 -6 We want to minimize  and/or maximize n For longer distance, n will increase, but f   and  will also increase To minimize , we need to maximize Signal-to-Noise Ratio (SNR); we can show that the standard deviation of  : For random noise, stacking should provide N 1/2 improvement in SNR.

8 Sano(p.c.) Piezo 6 weeks 1 hr 10 6.00E-06 4.00E-05 1.40E-8 BP This study Piezo 160 hrs 1 hr 3 3.00E-06 1.00E-03 1.00E-6 M2, O1/BP Previous Experimental Results Tides/ Barometric pressure

9 Initial Field Test

10 LBNL Bldg. 64 Test Wells Source Well 64-OB-1 Sensor Well 64-OB-2

11 Borehole Source and Sensors Hydrophone Sensor Piezoelectric Source

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

13 Data Acquisition Seismograms Source pulse: 0.08 ms Dominant frequency: 10 kHz. Sample Rate: 48,000 Hz = 20.83  s 30 ms recording Repeated every 100ms. Field stack every 600 ~ 1 stacked record per 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 N 1/2 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 sampling standard error ~50ns. For one-hour sampling, standard error only ~ 6ns. Corresponds to dV of 3x10 -6. DelayTime (ns)

17 2ms Comparison with Barometric Pressure, Dilatation 160 hours of recording: First arrival plus coda (10 cycles) or first arrival only (1.4 cycles). Delay time closely tracks barometric pressure, but at long period. Sensitivity dlnV/stress = 10 -6 /Pa Full scale variation: dlnV = 10 -3 Precision: dlnV = 3x10 -6 SNR = 1000 for pressure.

18 First Arrival vs Coda Delay time based on first arrivals gives longer period signal. But new signal observed. Solid earth tides.

19 Tidal Components All three see long-period barometric response Dilatational strain sees diurnal (O1, K1) and semidiurnal (M2) tides. Same components suggested in first-arrival, and with same relative amplitude, but not coda data.

20 Seno(p.c.) Piezo 6 weeks 1 hr 10 6.00E-06 4.00E-05 1.40E-8 BP This study Piezo 160 hrs 1 hr 3 3.00E-06 1.00E-03 1.00E-6 M2, O1/BP Comparison With Other Experiments Tides/ Barometric pressure

21 Planned Phase 2 and 3 Experiments Longer distance, greater depth Monitor other variables: water level, water pressure, temperature

22 Phase 2: RFS 30m distance, 70m depth

23 Phase 3: SAFOD

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26 30 Years Later. Lets Try Again! 10 -5 !


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