An Integrated Approach to Locating Undetected Off-Shore Small Magnitude Seismic Sources

Abstract

The publicly available earthquake record contains a plethora of information regarding seismic sources across the globe. However, smaller magnitude seismic sources are generally not kept on record. Small magnitude seismic sources can indicate many different occurrences such as earthquakes, landslides, ordnance, or commercial human interaction. An integrated method, using the existing Automated Event Location Using a Mesh of Arrays (AELUMA) scheme combined with a multi-layered deep neural network machine learning algorithm, can allow for more accurate seismic source location with lower uncertainty. More accurate low magnitude seismic source locations can be directly applied to seabed instability, where off-shore landslides, for instance, create obstacles for subsurface naval warfare. Additionally, accurate seismic source locations can affect decision making with respect to seafloor infrastructure and commercial interests.

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Document Details

Document Type
Technical Report
Publication Date
Nov 13, 2023
Accession Number
AD1214779

Entities

People

  • Jordan H. Graw

Organizations

  • United States Naval Research Laboratory

Tags

Communities of Interest

  • Autonomy

DTIC Thesaurus Topics

  • Algorithms
  • Arrays
  • Artificial Intelligence Software
  • Deep Learning
  • Earthquakes
  • Information Processing
  • Information Science
  • Information Systems
  • Latitude
  • Learning
  • Longitude
  • Machine Learning
  • Naval Warfare
  • Neural Networks
  • Seabed
  • Seismic Arrays
  • Seismic Detection
  • Surface Waves
  • Training
  • Uncertainty
  • Validation

Fields of Study

  • Environmental science

Readers

  • Coastal Oceanography
  • Geotechnical Engineering.
  • Sensor Fusion and Tracking Systems.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference