Real-time acoustic monitoring with telemetry to mitigate potential effects of seismic survey sounds on marine mammals: a case study offshore Sakhalin Island

Abstract

Exxon Neftegas Ltd. (ENL) carried out three 4D seismic surveys during the summer of 2015. Seismic operations in two of these fields (Odoptu and Chayvo) ensonified the nearshore feeding area of Korean-Okhotsk (western) gray whales (Eschrichtius robustus), potentially disturbing feeding activities. Following model-based optimization of the source design to minimize its lateral acoustic footprint, pre-season modeling was used to compute the acoustic exposure along each survey line. Real-time acoustic data facilitated implementation of mitigation measures aimed to minimize disturbance of whales. Acoustic data originated from underwater recorders deployed on the seafloor. Two complementary approaches were used to transmit recorded sound data to a computer housed at the Central Post (CP), where decisions regarding mitigation shut downs were made. In the first approach, a limited bandwidth (2–2000 Hz) sampling of the data was transmitted via cable to a surface buoy, which relayed these data to a shore station up to 15 km away via digital VHF telemetry. At the shore station, acoustic impulses from the seismic surveys were processed to compute impulse characteristics in the form of estimates of sound exposure level and peak sound pressure level, as well as one-minute-average 1/3-octave power spectral density coefficients, which were then transmitted to the CP via the internet. In the second, the pulse characteristics were computed through algorithms running on an onboard processor in each recorder’s surface buoy and sent directly to the CP computer via an Iridium satellite uplink. Both methods of data transfer proved viable, but Iridium transmission achieved the goal without the need for any shore based relay stations and is therefore more operationally efficient than VHF transmission. At the CP, analysts used the real-time acoustic data to calibrate and adjust the output of pre-season acoustical model runs. The acoustic footprint for the active seismic source, advancing synchronously with the motion of the seismic vessel and changing as the sound propagation environment changed, was computed from the calibrated and adjusted model output and integrated through the software Pythagoras with locations of gray whales provided by shore-based observers. This enabled analysts to require air gun array shutdowns before whales were exposed to mean square sound pressure levels greater than the behavioral response threshold of 163 dB re 1 μPa2. The method described here provides a realistic means of mitigating the possible effects of air guns at a behavioral response level, whereas most seismic surveys rely on pre-established mitigation radii to manage the risk of injury to a whale.

Seismic surveys near gray whale feeding areas off Sakhalin Island, Russia: assessing impact and mitigation effectiveness

“…During the planning phase, various seismic array configurations were investigated for possible reduction of the size of the 163 dB re 1 µPa 2 SPL isopleth while maintaining the quality of the seismic imaging. This yielded a configuration of 24 air guns in two strings, ranging in volumes from 45 to 290 in 3 , for a total of 2340 in 3 for each of the three seismic vessels (Rutenko et al, 2022a ).…”

“…To facilitate prioritization of operations along seismic survey lines having the highest spatial overlap with the nearshore feeding area, the Odoptu and Chayvo seismic survey areas were divided into mitigation zones based on the 163 dB re 1 μPa 2 SPL footprint of the full air gun array. The 163 dB re 1 μPa 2 SPL footprint of each seismic survey line was estimated through pre-survey acoustic modeling that was calibrated and adjusted during the survey using real-time acoustic data (Rutenko et al, 2022a ). The boundary of the nearshore feeding area, for mitigation purposes, was defined as the 95% kernel of the gray whale density surfaces (whales/km 2 ) using gray whale sighting data from scans at shore-based locations and line transect surveys (vessel and aerial) from June and July 2002–2013 (Fig.…”

“…Data were telemetered to the Central Post by two complementary methods: through digital VHF radio transmission of the acoustic waveform to three receiving stations on shore that analyzed the data and relayed sound levels to the Central Post, and through processing of the acoustic waveform within the RI-AUAR and transmission of sound levels via Iridium satellites. The real-time acoustic data were used to calibrate pre-season modeled 163 dB re 1 µPa 2 SPL footprints by providing a measure of the discrepancy between model predictions and measured levels at the RI-AUARs, from which acousticians stationed at the Central Post estimated a correction factor and applied it to the modeled levels defining the footprint (Rutenko et al, 2022a ). The calibrated 163 dB re 1 µPa 2 SPL footprint of the entire line (the acoustic envelope) and the footprint associated with the air gun array, which moved with the seismic vessel as it progressed along the data acquisition line (the acoustic footprint), were transmitted to the Pythagoras software for display (Fig.…”

“…The insets on the upper right show the mitigation zones for the seismic survey areas. Shore-based acoustic stations received data from the Autonomous Underwater Acoustic Recorders with VHF and Iridium data transmission capability (IR-AUAR) (Rutenko et al, 2022a ) …”

“…The first part of this paper summarizes the mitigation approach, the second part summarizes the implementation of the mitigation measures during ENL’s seismic surveys, and the third part summarizes the overall strategy behind assessment of impacts and mitigation effectiveness. Results of this assessment, including western gray whale behavior and distribution responses to the 2015 seismic survey activities, availability of prey resources, and how a potential decrease of energy intake due to acoustic disturbance could affect reproductive success, are presented in separate papers within this special issue (Blanchard et al, 2022a , b ; Gailey et al, 2022a , b ; Maresh et al, 2022 ; Rutenko et al, 2022a , b ; Schwarz et al, 2022a , b ). It should be noted that ENL and SEIC implemented comparable but not identical mitigation measures; SEIC’s approach is summarized and discussed in IUCN ( 2015a , b , c , 2016 ) and is not part of this paper.…”