scholarly journals Effect of ocean sound speed uncertainty on matched-field geoacoustic inversion

2008 ◽  
Vol 123 (6) ◽  
pp. EL162-EL168 ◽  
Author(s):  
Chen-Fen Huang ◽  
Peter Gerstoft ◽  
William S. Hodgkiss
Keyword(s):  
Sound Speed ◽  
Geoacoustic Inversion

scholarly journals A Volunteer Computing Project for Solving Geoacoustic Inversion Problems

2017 ◽  
Vol 7 (1) ◽  
pp. 363-370
Author(s):  
Oleg Zaikin ◽  
Pavel Petrov ◽  
Mikhail Posypkin ◽  
Vadim Bulavintsev ◽  
Ilya Kurochkin
Keyword(s):  
Inverse Problems ◽  
Shallow Water ◽  
Sound Speed ◽  
Underwater Acoustics ◽  
Volunteer Computing ◽  
Speed Profile ◽  
Geoacoustic Inversion ◽  
Sound Speed Profile ◽  
Profile Reconstruction ◽  
Discretization Grid

AbstractA volunteer computing project aimed at solving computationally hard inverse problems in underwater acoustics is described. This project was used to study the possibilities of the sound speed profile reconstruction in a shallow-water waveguide using a dispersion-based geoacoustic inversion scheme. The computational capabilities provided by the project allowed us to investigate the accuracy of the inversion for different mesh sizes of the sound speed profile discretization grid. This problem suits well for volunteer computing because it can be easily decomposed into independent simpler subproblems.

scholarly journals Geoacoustic inversion for acoustic parameters of sediment layer with low sound speed

2019 ◽  
Vol 68 (9) ◽  
pp. 094301
Author(s):  
Meng-Zhu Li ◽  
Zheng-Lin Li ◽  
Ji-Xun Zhou ◽  
Ren-He Zhang
Keyword(s):  
Sound Speed ◽  
Sediment Layer ◽  
Acoustic Parameters ◽  
Geoacoustic Inversion

MFP Benchmark Inversions via the RIGS Method

1998 ◽  
Vol 06 (01n02) ◽  
pp. 185-203 ◽  
Author(s):  
A. Tolstoy
Keyword(s):  
Half Space ◽  
Source Localization ◽  
Sound Speed ◽  
Original Method ◽  
Grid Search ◽  
Sediment Thickness ◽  
Geoacoustic Inversion ◽  
Benchmark Data ◽  
Method Formulation ◽  
Test Scenarios

This paper discusses the geoacoustic inversion results obtained on the Workshop '97 benchmark data via the Refined Iterated Grid Search (RIGS) method. We find that the method can be highly accurate in estimating geoacoustic and source localization unknowns for the ten test scenarios attempted. The original method formulation using KRAKEN as the embedded propagation code produced the results presented at the workshop where we found that some parameters are extremely well determined, i.e. sediment attenuationα sed (within 1% in all 3 cases: ATa, ATb, ATc), sediment densityρ sed (within 5% in all ten subcases: SD, AT, SO, WAa), source ranger sou to within 40 m and source depthz sou to within 2 m (in all four subcases SO and WAa). Moreover, sediment sound-speed gradients γ were also well determined (within 8%) except for very thin sediments/subcase ATb where sediment thickness h sed ≈ 13 m). However, more recent, post-workshop results using ORCA embedded in the RIGS inversion software has resulted in even better results. Five of the original ten subcases have been re-done, and those results are also shown in this paper. In particular, we find that for the new results: r sou is now accurate to within 11 m, z sou to within 0.2 m, and all geoacoustic properties (except for half-space density ρ hsp ) are accurate to within 5%.

PROPAGATION MODEL ACCURACY FOR MFP

2000 ◽  
Vol 08 (03) ◽  
pp. 389-399 ◽  
Author(s):  
A. TOLSTOY
Keyword(s):  
High Resolution ◽  
Sound Speed ◽  
High Accuracy ◽  
Propagation Model ◽  
Model Accuracy ◽  
Geoacoustic Inversion ◽  
Propagation Models ◽  
Matched Field Processing ◽  
Selection Of ◽  
Excellent Accuracy

The selection of a propagation model for use in many underwater acoustic applications has been understood to be highly important for quite some time. However, it has not previously been understood how various models might actually degrade Matched Field Processing (MFP) performance even when input parameters are known exactly. That is, acoustic propagation models have not previously been benchmarked within the context of MFP where acoustic amplitudes and phases need to be highly accurate depending on the nature of the processor of interest, such as for a high resolution Capon processor. This paper discusses the SCOOTER, ORCA, and KRAKEN models, and a high angle PE model within the context of MFP. These models are compared to the SAFARI data generated for the Workshop97 geoacoustic inversion CAL case. In general it seems that all the abovementioned models show excellent accuracy for use with the Linear Processor. However, it is found that KRAKEN may experience unexpected difficulties at unpredictable frequencies where these errors can affect high resolution processing (as demonstrated by geoacoustic inversions via the RIGS method),14 that SCOOTER and PE require relatively long CPU times for high accuracy, and that how accurately parameters are interpolated, e.g., sound-speed profiles, can also be important. It should be noted that all of the models discussed in this work may be considered to be very accurate in the context of most applications, particularly those involving data.

scholarly journals Geoacoustic Estimation of the Seafloor Sound Speed Profile in Deep Passive Margin Setting Using Standard Multichannel Seismic Data

2021 ◽  
Vol 9 (12) ◽  
pp. 1423
Author(s):  
Ernst Uzhansky ◽  
Omri Gadol ◽  
Guy Lang ◽  
Boris Katsnelson ◽  
Shelly Copel ◽  
...  
Keyword(s):  
Deep Water ◽  
Seismic Data ◽  
Sound Speed ◽  
Sound Propagation ◽  
Passive Margin ◽  
Seismic Profiles ◽  
Geoacoustic Inversion ◽  
Margin Setting ◽  
Receiver Array ◽  
Head Waves

Seafloor geoacoustic properties are important in determining sound propagation in the marine environment, which broadly affects sub-sea activities. However, geoacoustic investigation of the deep seafloor, which is required by the recent expansion of deep-water operations, is challenging. This paper presents a methodology for estimating the seafloor sound speed, c0, and a sub-bottom velocity gradient, K, in a relatively deep-water-compacting (~1000 m) passive-margin setting, based on standard commercial 2D seismic data. Here we study the seafloor of the southeastern Mediterranean margin based on data from three commercial seismic profiles, which were acquired using a 7.2 km-long horizontal receiver array. The estimation applies a geoacoustic inversion of the wide-angle reflections and the travel times of the head waves of bending rays. Under the assumption of a constant positive K, the geoacoustic inversion converges to a unique set of parameters that best satisfy the data. The analysis of 24 measurement locations revealed an increase in the average estimates of c0 from 1537 ± 13 m s−1 to 1613 ± 12 m s−1 for seafloor depths between ~1150 m and ~1350 m. K ranged between 0.75 and 0.85 m s−1 with an average of 0.80 ± 0.035 s−1. The parameters were consistent across the different locations and seismic lines and they match the values that were obtained through depth-migration-velocity analysis and empiric relations, thereby validating our estimation methodology.

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