Proceedings of Meetings on Acoustics

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1 Proceedings of Meetings on Acoustics Volume 19, ICA 2013 Montreal Montreal, Canada 2-7 June 2013 Underwater Acoustics Session 2pUWb: Arctic Acoustics and Applications 2pUWb3. Comparing modeled and measured sound levels from a seismic survey in the Canadian Beaufort Sea Marie-Noël R. Matthews* and Alexander O. MacGillivray *Corresponding author's address: JASCO Applied Sciences, Dartmouth, B3B 1Z1, Nova Scotia, Canada, Marie- Noel.Matthews@jasco.com In this paper, we compare airgun sound levels measured during an offshore seismic survey to acoustic model predictions. The survey occurred in deep water (>650 m), on and beyond the continental slope in the Canadian Beaufort Sea. The modeling was performed with JASCO Applied Sciences' Marine Operations Noise Model, which uses a parabolic-equation-based algorithm to predict N 2 D sound propagation in ocean environments. Sound levels were measured with up to five calibrated Autonomous Multichannel Acoustic Recorders at distances of 50 to 50,000 m from the airgun array in water depths between 50 and 1,500 m. The sound levels were measured in both the broadside (across-track) and endfire (along-track) directions. The high-resolution digital recordings of seismic sounds were analyzed to determine peak and root-meansquare sound pressure levels and sound exposure levels as functions of range from the airgun array, and compared to the model results. Although the modeled sound levels were generally conservative, the model results accurately predicted the existence of a shadow zone and the overall transmission loss trend. Published by the Acoustical Society of America through the American Institute of Physics 2013 Acoustical Society of America [DOI: / ] Received 22 Jan 2013; published 2 Jun 2013 Proceedings of Meetings on Acoustics, Vol. 19, (2013) Page 1

2 INTRODUCTION This paper compares modeled and measured sound exposure levels (SELs) and root-mean-square (rms) sound pressure levels (SPLs) in two water depth regimes for a seismic survey conducted in the Canadian Beaufort Sea in summer JASCO Applied Sciences (JASCO) performed a modeling study to predict underwater sound levels propagating from a 5085 in 3 airgun array in preparation for the Chevron Canada Limited 2012 Sirluaq 3-D seismic program. The directional source level of the airgun array was predicted with JASCO s Airgun Array Source Model (AASM). Received SELs were predicted with JASCO s Marine Operations Noise Model (MONM) in conjunction with the modeled source level. JASCO s Full Waveform Range-dependent Acoustic Model (FWRAM) was used to determine the range-dependent relationship between rms SPL and SEL. JASCO measured sound levels during the Sirluaq program to verify and adjust, if necessary, the predicted maximum distances to sound level thresholds of relevance to marine mammal exclusion zones. Autonomous Multichannel Acoustic Recorders (AMARs) were deployed in a layout that captured sound levels in both the broadside (perpendicular to survey line) and endfire (along the survey line) directions. Here, modeled and measured sound levels are compared for an intermediate ( m, continental shelf) and a deep (>1000 m, ocean basin) ocean environment. METHOD Predictive Acoustic Modeling Frequency-dependent source levels and directivity of the seismic airgun array were predicted with JASCO s AASM (MacGillivray 2006). This model computes a set of pressure waveforms for the individual airguns, at the standard reference distance of 1 m, based on the array layout and each airgun s volume, tow depth, and firing pressure. These notional signatures account for the interactions with other airguns in the array. The signatures are summed with the appropriate phase delays to obtain the directional far-field acoustic signature of the array. This farfield signature is filtered into 1/3-octave passbands to compute the source levels, in db re 1 µpa 2 s, as a function of frequency band and azimuth. Underwater sound propagation was predicted with MONM. This model s predictions for various airgun array sizes have been compared to experimental data in several difference environments (Hannay and Racca 2005, Aerts et al. 2008, Funk et al. 2008, Ireland et al. 2009, O Neill et al. 2010, Warner et al. 2010, Austin et al. 2012, Racca et al. 2012a, 2012b). MONM treats sound propagation through a wide-angled parabolic equation solution based on a version of the U.S. Naval Research Laboratory s Range-dependent Acoustic Model (RAM; Collins 1996) that has been modified to account for an elastic seabed (Zhang and Tindle 1995). MONM computes three-dimensional acoustic transmission loss by modeling acoustic propagation along radial traverses covering a 360 swath around the source, an approach known as N 2-D. MONM accounts for range and/or depth variation of multiple environmental parameters, including bathymetry, sound speed in the water column, and sub-bottom geoacoustic properties. MONM also accounts for bottom loss due to shear wave conversion at the seabed and for compressional wave attenuation in all layers. The frequency-dependent sound field is modeled by computing the transmission loss at the center frequencies of successive 1/3-octave bands. Received levels are computed by subtracting the modeled transmission loss from the directional source levels in each frequency band. These received band levels are then summed to calculate the broadband sound field. In this study, 1/3-octave bands of 10 to 2000 Hz were predicted with MONM. This frequency range includes the important bandwidth of noise emissions from seismic airgun arrays. Both rms SPL and SEL were computed from synthetic pressure waveforms modeled with FWRAM along one transect at each site. The range-dependent offsets between the rms SPL and SEL were used to convert the MONMmodeled sound fields from SEL to rms SPL. This approach combines the computational efficiency of MONM with the pulse length estimates provided by FWRAM. FWRAM computes synthetic pressure waveforms versus range and depth with the same parabolic equation algorithm as MONM and uses the same environmental inputs (bathymetry, sound speed in the water column, and sub-bottom geoacoustic properties). FWRAM uses Fourier synthesis of the acoustic transfer function in closely spaced frequency bands to compute pressure waveforms. FWRAM is appropriate for computing time-averaged rms SPLs for impulsive sources since the calculations are conducted in the time domain. Proceedings of Meetings on Acoustics, Vol. 19, (2013) Page 2

3 Model Parameters At the time of modeling, the Sirluaq program s survey area was not finalized, so sound propagation was modeled at five sites chosen to represent the full range of water depths within the proposed survey area. The final survey lines were, however, within a smaller area, for which two of the modeled sites apply based on the water depth: the intermediate ( m) and deep (>1000 m) regimes (Figure 1). FIGURE 1. Location of the modeled sites, the acoustic recorders (AMARs), and the recorded survey lines in the Canadian Beaufort Sea. The array tow direction was unknown at the time of modeling, so it was modeled at a true bearing of 315. Based on bathymetry in the area and directionality of the source signature, this tow direction likely produces the longest distances to sound level thresholds for establishing marine mammal exclusion zones. The bathymetry for the modeled area was extracted from the SRTM30+ (v6.0) data grid. This dataset is a 30 arcsecond grid (~ m at the studied latitude), rendered for the entire globe (Rodriguez et al. 2005). The bathymetry data were re-gridded to cover a km region with a horizontal resolution of m. Several detailed well logs containing comprehensive descriptions of sediments along with porosity and some density data are available for the Beaufort Sea continental shelf; however, no data were available at deeper depths off the shelf where the 2012 survey occurred. Based on the well log data and considering the extensive size of the modeled area, the geoacoustic profiles were generalized to reflect the major features of the sediment column at the modeled sites. The geoacoustic properties were estimated using the grain-shearing model of Buckingham (2005), assuming the average porosity and density profiles of those measured at nearby wells (Table 1). TABLE 1. Geoacoustic profile representing a deep clay bottom for the modeled intermediate and deep sites. Within the range of depths, the parameters increase linearly within their stated range. Depth below seafloor (m) Density (g/cm 3 ) Compressionalwave speed (m/s) Compressional-wave attenuation (db/λ) Shear-wave speed (m/s) Shear-wave attenuation (db/λ) > Sound speed profiles in the water column near the modeled sites were obtained from the U.S. Naval Oceanographic Office s Generalized Digital Environmental Model V 3.0 (GDEM; Teague et al. 1990, Carnes 2009). GDEM provides ocean climatology of monthly temperature and salinity for the world s oceans on a latitudelongitude grid with 0.25 resolution. The GDEM temperature-salinity profiles for the month of August were converted to sound speed profiles according to the equations from Coppens (1981). Proceedings of Meetings on Acoustics, Vol. 19, (2013) Page 3

4 Sound Level Measurements JASCO measured sound levels using multiple AMARs deployed between 40 m and 90 m depth. Each AMAR continuously recorded 24-bit acoustic data with a GeoSpectrum M8E or M8K hydrophone ( 164 or 201 db re 1 V/µPa sensitivity, respectively). Before deployment, all AMARs were calibrated with a Pistonphone Type 42AC (G.R.A.S. Sound & Vibration A/S). The pressure sensitivities obtained from the calibrations were used in the data analysis to determine received sound levels. During the survey, the seismic array was towed along parallel survey lines with a true bearing of 272 /092. Sound levels from the airgun array in intermediate water depths ( m) were measured on 8 10 Aug Five AMARs (I1 through I5) were positioned to capture sound levels in both the broadside and endfire directions (Figure 2). The AMARs were moored to the seabed so that the hydrophone sensor was suspended at approximately 60 m depth (Figure 3). Pressure sensors mounted on the AMARs recorded the actual measurement depth. Tandem 111 Acoustic Releases (InterOcean Systems, Inc.) connected the floating instrument package to the anchor weight for instrument retrieval. Before retrieval, the AMAR locations were triangulated with a Model 1100E Acoustic Command and Ranging Unit (InterOcean Systems, Inc.). AMARs I1 through I4 were deployed in water depths between 475 and 685 m. Due to a failure of the tandem release system, AMAR I5 at 50 km range was not recovered. Thus, no data were acquired at 50 km broadside. FIGURE 2. Geometry of the survey line and the five AMARs (I1 through I5) for the intermediate depth measurement (not to scale). AMAR I5 was not recovered. FIGURE 3. (a) The AMAR mooring with tandem acoustic releases for AMARS I1 through I5 and D5 (not to scale). The anchor lines were sufficiently long to suspend hydrophones at approximately 60 m depth. (b) The AMAR suspension system for drift measurements (not to scale). The main line was sufficiently long to suspend the hydrophones at approximately 60 m depth. Proceedings of Meetings on Acoustics, Vol. 19, (2013) Page 4

5 Sound levels from the airgun array in deep water (>1000 m) were measured on Aug One AMAR was deployed at 50 km broadside (AMAR D5 in Figure 1) in 53 m of water using the same mooring as the intermediate water measurements (Figure 3). Within 10 km of the airgun array, the water was too deep (>800 m) to moor AMARs to the seabed, so an AMAR was suspended from a drifting vessel at various ranges from the survey tracks (drift measurements in Figure 1). A GPS receiver (Garmin GPSMAP 78s) affixed to a surface float recorded the coordinates as close to the AMAR as possible, and a depth sensor mounted on the AMAR recorded the depth, which depended on wind and ocean currents. Since the deployment vessel could not safely venture into the path of the seismic vessel s streamers, the closest measurement range was 650 m. These drift measurements were obtained over three days as the seismic vessel surveyed three lines. The geographic separation of the survey lines is unlikely to influence the measurements, since the variation in the bathymetry along the propagation paths was negligible relative to the water depth. The bathymetry used for the predictive modeling was found to match the deployment depths on the deployment vessel s echosounder and was deemed accurate. Sound speed profiles were measured with Expendable Sound Velocimeter probes (XSV, Lockheed Martin Sippican). The XSV probes provide sing-around sound velocity measurements (±0.25 m/s) to depths up to 2000 m. The acoustic data were analyzed to determine received sound levels as functions of range from the airgun array in both the broadside and endfire directions. Seismic pulses in the recordings were identified by manual picks and automated detection. The waveform data were converted to micropascals according to the calibrated hydrophone sensitivity of each AMAR. For each pulse, distance to the source array was computed from triangulated coordinates of the AMAR and time-referenced navigation logs of the acoustic center of the airgun array provided by the seismic vessel. The peak SPL, 90% energy rms SPL, and SEL were calculated for each seismic pulse. RESULTS: MODELED VS. MEASURED SOUND LEVELS Intermediate Water Depth Regime Sound levels were measured at ranges of up to 50 km in the endfire direction and up to 10 km in the broadside direction. The modeled levels were extracted at 60 m depth along true bearings of 315 and 225 (modeled endfire and broadside directions, respectively), up to a range of 140 km. Figures 4 and 5 compare the modeled and measured SELs and rms SPLs, respectively, in the endfire direction for the airgun array approaching and receding from AMAR I1, which was located directly on the survey track. Results for the broadside directions were similar to results from the endfire so they are not presented here. FIGURE 4. Intermediate water depth regime ( m): Comparison between modeled and measured (AMAR I1) levels at 60 m depth along the endfire direction (parallel to the survey track); (a) sound exposure levels (SELs), (b) root-mean-square (rms) sound pressure levels (SPLs). Proceedings of Meetings on Acoustics, Vol. 19, (2013) Page 5

6 Deep Water Regime Sound levels were measured at ranges of up to 50 km in both the endfire and broadside directions with a minimum range of about 650 m in the broadside direction and 1500 m in the endfire direction. The modeled levels were extracted at 40 m depth along true bearings of 315 and 225 (modeled endfire and broadside directions, respectively), up to a range of 140 km. Figures 6 and 7 compare the modeled SELs and rms SPLs, respectively, in the endfire direction for the airgun array approaching the AMAR suspended from a drifting vessel. The results for the broadside directions were similar to results from the endfire so they are not presented here. FIGURE 5. Deep water depth regime (>1000 m): Comparison between modeled and measured (AMAR I1) levels at 60 m depth along the endfire direction (parallel to the survey track); (a) sound exposure levels (SELs), (b) root-mean-square (rms) sound pressure levels (SPLs). DISCUSSION The modeled and measured sound levels are in agreement in both water depth regimes, especially in the intermediate ( m) regime. The model accurately predicted the existence of shadow and conversion zones (significant increase in sound levels seen between 1 and 10 km in Figures 4 7) as well as the overall transmission loss trend. In deep water, the transmission loss inside the shadow zone was stronger than modeled, and the distance to the minima was poorly predicted by the model. The model overestimated sound levels in the near field (<100 m range). This is expected since the propagation model applies the far-field approximation. The differences in location and sound speed profile between the modeling and the measurements are the main sources of error in the modeled sound levels. The actual survey lines for the Sirluaq program were within a smaller and deeper area than was modeled. In the intermediate water depth regime, the measured survey line had water depths between 650 and 800 m and was 65 to 115 km from the modeled site, where the water depth was 648 m. In the deep water regime, the monitored survey lines had water depths between 1200 and 1700 m and were 10 to 50 km from the modeled site, where the water depth was 1375 m. The measured sound speed profiles had a stronger gradient in the top 50 m of water than the modeled profile (Figure 8). This gradient resulted in increased downward refraction which contributed to the observed difference between modeled and measured sound levels. Proceedings of Meetings on Acoustics, Vol. 19, (2013) Page 6

7 FIGURE 6. Comparison between modeled and measured sound speed profiles in the water column for the intermediate ( m; left) and deep (>1000 m; right) water regimes. Agreement between the modeled and measured sound levels was better for the SEL metric than for the rms SPL metric. This difference shows that the modeling of SEL is more robust against environmental error than rms SPL. Future research by JASCO will focus on improved methods for estimating underwater sound levels from impulsive sources, like airgun arrays. ACKNOWLEDGMENTS We thank the crew of M.V. Jim Kilabuk, as well as the staff at Chevron Canada Limited and WesternGeco for support in acquiring sound level measurements. REFERENCES Aerts, L., M. Blees, S. Blackwell, C. Greene, K. Kim, D. Hannay, and M. Austin. (2008). Marine mammal monitoring and mitigation during BP Liberty OBC seismic survey in Foggy Island Bay, Beaufort Sea, July-August 2008: 90-day report, LGL Rep. P Prepared by LGL Alaska Research Associates Inc., LGL Ltd., Greeneridge Sciences Inc. and JASCO Applied Sciences Ltd. for BP Exploration Alaska. Austin, M., A. O. MacGillivray, and N. R. Chapman. (2012). Acoustic transmission loss measurements in Queen Charlotte Basin, Canadian Acoustics 40, Buckingham, M. J. (2005). Compressional and shear wave properties of marine sediments: Comparisons between theory and data, J. Acoust. Soc. Am. 117, Carnes, M. R. (2009). Description and Evaluation of GDEM-V 3.0. NRL Memorandum Report US Naval Research Laboratory, Stennis Space Center, MS. 21 p. Collins, M. D. (1996). User s Guide for RAM Version 1.0 and 1.0p Naval Research Laboratory, Washington, DC Coppens, A. B. (1981). Simple equations for the speed of sound in Neptunian waters, J. Acoust. Soc. Am. 69, Funk, D., D. Hannay, D. Ireland, R. Rodrigues, and W. Koski. (2008). Marine mammal monitoring and mitigation during open water seismic exploration by Shell Offshore Inc. in the Chukchi and Beaufort Seas, July November 2007: 90-day report, LGL Rep. P Prepared by LGL Alaska Research Associates Inc., LGL Ltd., and JASCO Research Ltd. for Shell Offshore Inc, Nat. Mar. Fish. Serv., and U.S. Fish and Wild. Serv. 218p, plus appendices. Hannay, D. E. and R. Racca. (2005). Acoustic Model Validation, Technical report for Sakhalin Energy Investment Company by JASCO Research Ltd. Ireland, D. S., R. Rodrigues, D. Funk, W. Koski, and D. Hannay. (2009). Marine mammal monitoring and mitigation during open water seismic exploration by Shell Offshore Inc. in the Chukchi and Beaufort Seas, July October 2008: 90-day report, LGL Rep. P Prepared by LGL Alaska Research Associates Inc., LGL Ltd., and JASCO Applied Sciences Ltd. for Shell Offshore Inc, Nat. Mar. Fish. Serv., and U.S. Fish and Wild. Serv. 277p, plus appendices. Lurton, X. (2002). An Introduction to Underwater Acoustics: Principles and Applications. (Springer, Chichester, U.K.), 347 p. Proceedings of Meetings on Acoustics, Vol. 19, (2013) Page 7

8 MacGillivray, A. O. (2006). Acoustic Modelling Study of Seismic Airgun Noise in Queen Charlotte Basin. MSc Thesis. (University of Victoria, Victoria, BC), 98 p. O Neill, C., D. Leary, and A. McCrodan. (2010). Sound Source Verification. (Chapter 3) In Blees, M. K., K. G. Hartin, D. S. Ireland, and D. Hannay. (eds.) Marine mammal monitoring and mitigation during open water seismic exploration by Statoil USA E&P Inc. in the Chukchi Sea, August October 2010: 90-day report. LGL Report P1119. Prepared by LGL Alaska Research Associates Inc., LGL Ltd., and JASCO Applied Sciences Ltd. for Statoil USA E&P Inc., Nat. Mar. Fish. Serv., and U.S. Fish and Wild. Serv. 3-1, 3-34 p. Racca, R., A. Rutenko, K. Bröker, and M. Austin. (2012a). A line in the water - design and enactment of a closed loop, model based sound level boundary estimation strategy for mitigation of behavioural impacts from a seismic survey. 11th European Conference on Underwater Acoustics Volume 34(3), Edinburgh, United Kingdom. Racca, R., A. Rutenko, K. Bröker, and G. Gailey. (2012b). Model based sound level estimation and in-field adjustment for realtime mitigation of behavioural impacts from a seismic survey and post-event evaluation of sound exposure for individual whales. Acoustics 2012 Fremantle: Acoustics, Development and the Environment, Fremantle, Australia. Rodriguez, E., C. S. Morris, Y. J. E. Belz, E. C. Chapin, J. M. Martin, W. Daffer, and S. Hensley. (2005) An Assessment of the SRTM Topographic Products. JPL D Jet Propulsion Laboratory, Pasadena, CA. Teague, W. J., M. J. Carron, and P. J. Hogan. (1990). A comparison between the Generalized Digital Environmental Model and Levitus climatologies. Journal of Geophysical Research 95(C5): Warner, G., C. Erbe, and D. Hannay. (2010). Underwater sound measurements. (Chapter 3) In: Reiser, C. M, D. W. Funk, Rodrigues, and D. Hannay. (eds.) Marine mammal monitoring and mitigation during open water seismic exploration by Shell Offshore, Inc. in the Alaskan Chukchi Sea, July October 2009: 90-day report. LGL Report P LGL Alaska Research Associates Inc. and JASCO Applied Sciences Ltd. for Shell Offshore Inc, Nat. Mar. Fish. Serv., and U.S. Fish and Wild. Serv. 3-1, 3-54 p. Zhang, Y. and C. Tindle. (1995). Improved equivalent fluid approximations for a low shear speed ocean bottom, J. Acoust. Soc. Am. 98, Proceedings of Meetings on Acoustics, Vol. 19, (2013) Page 8