Geoacoustic inversions using Combustive Sound Sources (CSS)

Transcription

1 Geoacoustic inversions using Combustive Sound Sources (CSS) Gopu Potty, James Miller (URI) James Lynch, Arthur Newhall (WHOI) Preston Wilson, David Knobles (UT, Austin) Work supported by Office of Naval Research

2 Source Receiver Locations CSS 20 to SHRU km CSS 20 to SHRU km Grab samples In situ probes Short core- station AHC 800 Core

3 From David Knobles

4 Potty, G., Miller, J. H., and Lynch, J. F., Newhall, A., Wilson, P., Geoacoustic inversions using combustive sound source signals, J. Acoust. Soc. Am. (EL), 2008 Inversion Results- Compressional Wave Speed Compressional wave speed (top 40 m) compared with Jiang et al. model (JASA- 2007) Standard deviation ~ 20 m/sec. The R- reflector is approx. around 20 m Sea floor R - Reflector

5 Potty, Miller, Wilson, Lynch and Newhall, Geoacoustic inversion using combustive sound source signals, J. Acoust. Soc. Am., 124(3), Inversion Results- Compressional Wave Speed Sediments in top 15 m generally sandy interbedded with mud and shells. Inversion captures the trend in core data; but lower in magnitude Resolution not sufficient to capture high-speed layers at 8 m and at 11 m.

6 Attenuation - Modal Amplitude Ratios Mode 1 and 2 ratios in the frequency range 20 Hz to 80 Hz used for inversion Inversion for attenuation using the dominant modes modes 1 and 2

7 Depth below seafloor Relative Sensitivity of modes 0-2 m 2-4 m High 4-6 m 6-10 m m m m m m >30 m Low Mode #

8 Attenuation Inversion Results Mode 1 and 2 Published data all types of sediments (Stoll- 85) Freq. exponent ~ 1.86 (deep) 1.89 (shallow) Primer study SW 06 SW 06 (Biot Model) ECS data Primer data (Biot model) Inversions compare well with earlier (Primer) inversions Frequency exponent agrees with Holmes et al. (JASA-EL;2007) value of 1.8 +/- 0.2

9 Attenuation Estimates Mode 3 Different colors indicate attenuation at different depths Mode 3 data at frequencies 70 to 100 Hz Mode 1 and 2 strong > 20 m Mode 3 strong depth< 20 m Deeper sediments (red) very different (depends on modes 1 and 2; mode 3 not very sensitive at this depth Sediments at depths< 20 m more reliable (mode 3 sensitive at this depth)

10 SHRU 1 SHRU 2 From David Knobles

11 From David Knobles

12 From David Knobles

13 Time Frequency Analysis of the CSS signal SWAMI Data HRU Data

14 depth below seafloor (m) source receiver Mode Arrival Times Calculated based on SHRU data Mode 2 fit not very good Mode shapes _ Modes 1,2 and 3 Mode 2 has a peak at the sedimentwater interface. Mode 3 has a null both at the source and receiver location. Mode 3 could help to get better sediment information

15 Inversion Initial Result Mode 2 fit good except at the Airy Phase Mode 2 sensitive to near surface sediment Inversions range independent

16 Future Work Use more modes (mode 3 use another receiver) Attenuation inversions using CSS 26 and CSS 18. Focus on the Airy phase (mode 2) include range dependency Investigate the depth resolution are sediment layers visible to the inversion?

17 Acoustic Intensity Variability in the Presence of Shallow Water Internal Waves near a Shelfbreak Front Georges Dossot, James H. Miller, Gopu R. Potty, Dept. of Ocean Engineering, URI James F. Lynch, Arthur E. Newhall, WHOI Mohsen Badiey, University of Delaware SW06 Workshop at UT Austin February 10-12, 2009

18 Research Overview This study will attempt to verify the hypothesis that ISWs and the front cause complex multimode and multipath interference patterns which result in intensity variations of received acoustic signals Benefits: Provide a better understanding of acoustic variability in the complex shallow-water environment Provide a better understanding of ocean processes and properties Calculate and characterize intensity metrics based upon the R/V Sharp Transmissions

19 R/V Sharp Event 44 Compiled environmental data is useful for visualizing the event and for acoustic modeling Radar data determines the orientation of the wave front R/V Sharp ADCP shows internal wave structure SHARK soundspeed shows internal wave front arrives at SHARK array one hour prior to location of R/V Sharp

20 180 Hours of Acoustic Transmissions

21 Research Tasks Develop and maintain a web-based data archival system Currently operational, continued updates Preliminary data processing and automation Example of chirp automatic handling of chirp sequences Intensity metrics Example of chirp sequences transmitted on 13 Aug 06 Statistical characterization Some preliminary figures from calculated intensity metrics Modeling Future, most likely R/V Sharp Event 44 Inverse Problem Future, use statistics as part of model

22 Web-based data archival Information posted includes: Initial data results Misc Documents & Presentations References I am using Matlab code Simple way of sharing my work not meant to steal thunder from primary SW06 websites Password protected with standard SW06 username & password

23 Example Data from Event 44

24 Data processing & automation Automatic signal detection & automation is a must for this data

25 Statistical Measurements Integrated Energy: I z l dz d I, z, l Temporally Integrated Energy: I z, l d I, z, l Point Observations of Broadband Intensity: I, z, l Point Observations of Point Scintillations: Point Observations of Peak Intensity: SI I I I P z, l max I, z, l

26 I z (l) Number of arrivals 5 Integrated Energy Integrated Energy Integrated Energy Distribution Transmission number I z l dz d I, z, l I z (l) Total acoustic energy detected at the array, as a function of transmission number Intensity integrated over depth and arrival time Depth is integrated over entire array Time integral done over τ, the energetic region of the signal Corrected for ambient noise by subtracting average noise levels before and after energetic region of signal

27 I (z,l) I (z,l) Temporally Integrated Energy Temporally Integrated Energy (deepest hydrophone) 5 4 Temporally Integrated Energy Distribution (deepest hydrophone) Transmission number I z, l d I, z, l Number of arrivals Time integral done over τ, the energetic region of the signal Energy Detector mode of a sonar system Corrected for ambient noise by subtracting average noise levels before and after energetic region of signal Shows depth dependence not seen in Integrated Energy, I zτ (l) Energy redistribution due to mode coupling Energy redistribution due to ray scattering

28 I P (z,l) Number of arrivals Peak Intensity 5 Peak Intensity 30 Peak Intensity Distribution Transmission number I P (z,l) I P z, l max I, z, l

29 I(,z,l) Number of arrivals Point Observations Intensity "Point" Observations Intensity "Point" Observations Distribution Transmission number I(,z,l) I, z, l

30 I(,z,l) Number of arrivals Event Correlation Intensity "Point" Observations Intensity "Point" Observations Distribution 600 Research 500 Vessel Transmission number SHARK0 Array Propagating Internal 0 5 Wave10 I(,z,l)

31 Research Tasks Develop and maintain a web-based data archival system Currently operational, continued updates Preliminary data processing and automation Example of chirp automatic handling of chirp sequences Intensity metrics Example of chirp sequences transmitted on 13 Aug 06 Statistical characterization Some preliminary figures from calculated intensity metrics Modeling Future, most likely R/V Sharp Event 44 Inverse Problem Future, use statistics as part of model

32 Thank you! Questions?

33 Chirp detector Performance

34 Chirp detector Performance

35 Chirp detector Performance

36 Chirp detector Performance Automatic signal detection & automation is a must for this data

37 Chirp detector Performance