Broadband Geo-Acoustic Inversion from Sparse Data Using Genetic Algorithms: Results from the 1997 Geo-Acoustic Inversion Workshop

Abstract

Matched field acoustic inversion techniques were investigated using data from sparsely populated, vertical receiving arrays and a single receiver element. The purpose of considering sparse data sets is to investigate, by simulation, the feasibility of reducing the number and complexity of acoustic measurements needed for geo-acoustic inversion. The entire bandwidth of the1997 G-Acoustic Inversion Workshop data (25-500 Hz) was used to compensates for the lack of spatial information when a limited number of receivers is considered. Forward model PROSIM and inversion code SAGA were applied to benchmark cases: sd , wa, and n. The inversion results generally showed good agreement with the ground truth, for full arrays, sparse arrays and single receiver elements. With a simple two layer model, an effective sound speed profile in the bottom was determined, which produced a good fit between model and observed pressure fields for the multi-layer case n.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 1998
Accession Number
AD1113465

Entities

People

  • M. Siderius
  • P. Gerstoft
  • P. Nielsen

Organizations

  • SACLANT ASW Research Centre

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Acoustic Fields
  • Acoustic Measurement
  • Acoustic Properties
  • Acoustics
  • Algorithms
  • Broadband
  • Computational Science
  • Computations
  • Data Sets
  • Eigenvalues
  • Frequency
  • Frequency Bands
  • Frequency Domain
  • Genetic Algorithms
  • Measurement
  • Nato
  • Probability
  • Probability Distributions
  • Seabed
  • Shallow Water
  • Simulations
  • Thickness
  • Time Domain
  • Transmission Loss

Readers

  • Computational Modeling and Simulation
  • Distributed Systems and Data Platform Development
  • Military/Explosive Ordnance Disposal (EOD) Technology

Technology Areas

  • AI & ML
  • Biotechnology