DASPy: A Python Toolbox for DAS Seismology

DOI number:10.1785/0220240124

Affiliation of Author(s):中国科学技术大学地球和空间科学学院

Journal:Seismological Research Letters

Place of Publication:美国

Abstract:Distributed acoustic sensing (DAS) has emerged as a novel technology in geophysics, owing to its high-sensing density, cost effectiveness, and adaptability to extreme environments. Nonetheless, DAS differs from traditional seismic acquisition technologies in many aspects: big data volume, equidistant sensing, measurement of axial strain (strain rate), and noise characteristics. These differences make DAS data processing challenging for new hands. To lower the bar of DAS data processing, we develop an open-source Python toolbox called DASPy, which encompasses classic seismic data processing tec

First Author:Minzhe Hu

Co-author:Zefeng Li

Indexed by:Journal paper

Correspondence Author:Zefeng Li

Document Code:34

Discipline:Natural Science

First-Level Discipline:Geophysics

Document Type:SCI

Volume:95

Issue:5

Page Number:3055-3066

ISSN No.:0895-0695

Translation or Not:no

Date of Publication:2024-07-26

Links to published journals:https://doi.org/10.1785/0220240124