Locating small-scale heterogeneities with DAS

SUMMARY Distributed Acoustic Sensing (DAS), a photonic technology that converts a fibre-optic cable into a long (tens of kilometres) high-linear-density (every few metres) array of seismo-acoustic sensors, can provide high-density, high-resolution strain measurements along the entire cable. The potential of such a distributed measurement has gained increasing attention in the seismology community for a wide range of applications. It has been shown that DAS has a subwavelength sensitivity to heterogeneities near the fibre-optic cable. This sensitivity is linked to the fact that the DAS measures deformation, as opposed to the displacements that seismometers measure. However, this sensitivity can create difficulties for many DAS applications, such as source location or distant imaging. Regardless, it can be advantageous in obtaining information about the subsurface near the cable. Here we present a method to locate small heterogeneities near the fibre-optic cable by inverting an indicator of the small-scale heterogeneities: the homogenized first-order corrector. We show that this first-order corrector can be used to locate heterogeneities near the fibre-optic cable at the gauge length precision, independent of the wavelength.

Authors

Institutions

Publication Details

Journal
Geophysical Journal International
Published
2025-11-29
DOI
https://doi.org/10.1093/gji/ggaf488
Primary Topic
Neural Networks and Applications
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Locating small-scale heterogeneities with DAS

Kota Mukumoto, Yann Capdeville, D. Leparoux, Tatsunori Ikeda et al.
Geophysical Journal International
Neural Networks and Applications
article

Locating small-scale heterogeneities with DAS

Kota Mukumoto, Yann Capdeville, D. Leparoux, Tatsunori Ikeda, Takeshi Tsuji, Ryohei Naruse
article en

Abstract

SUMMARY Distributed Acoustic Sensing (DAS), a photonic technology that converts a fibre-optic cable into a long (tens of kilometres) high-linear-density (every few metres) array of seismo-acoustic sensors, can provide high-density, high-resolution strain measurements along the entire cable. The potential of such a distributed measurement has gained increasing attention in the seismology community for a wide range of applications. It has been shown that DAS has a subwavelength sensitivity to heterogeneities near the fibre-optic cable. This sensitivity is linked to the fact that the DAS measures deformation, as opposed to the displacements that seismometers measure. However, this sensitivity can create difficulties for many DAS applications, such as source location or distant imaging. Regardless, it can be advantageous in obtaining information about the subsurface near the cable. Here we present a method to locate small heterogeneities near the fibre-optic cable by inverting an indicator of the small-scale heterogeneities: the homogenized first-order corrector. We show that this first-order corrector can be used to locate heterogeneities near the fibre-optic cable at the gauge length precision, independent of the wavelength.

Geophysical Journal InternationalVol. 244(2)
Centre National de la Recherche Scientifique (FR), Japan Agency for Marine-Earth Science and Technology (JP), Kyushu University (JP), Tokyo University of Science (JP), Université Nantes Angers Le Mans (FR), Inpex (Japan) (JP), Institut Català de Ciències del Clima (ES), Laboratoire de Planétologie et Géosciences (FR), Université Gustave Eiffel (FR), The University of Tokyo (JP), Nantes Université (FR)
Openalex Percentile: Top 85%
Neural Networks and Applications
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.