Derrick Chambers, Ge Jin, Ahmad Tourei, Abdul Hafiz Saeed Issah, Ariel Lellouch, Eileen R Martin, Donglin Zhu, Aaron J Girard, Shihao Yuan, Thomas Cullison, Tomas Snyder, Seunghoo Kim, Nicholas Danes, Nikhil Punithan, M Shawn Boltz, Manuel M Mendoza
{"title":"DASCore: a Python Library for Distributed Fiber Optic Sensing.","authors":"Derrick Chambers, Ge Jin, Ahmad Tourei, Abdul Hafiz Saeed Issah, Ariel Lellouch, Eileen R Martin, Donglin Zhu, Aaron J Girard, Shihao Yuan, Thomas Cullison, Tomas Snyder, Seunghoo Kim, Nicholas Danes, Nikhil Punithan, M Shawn Boltz, Manuel M Mendoza","doi":"10.26443/seismica.v3i2.1184","DOIUrl":null,"url":null,"abstract":"<p><p>In the past decade, distributed acoustic sensing (DAS) has enabled many new monitoring applications in diverse fields including hydrocarbon exploration and extraction; induced, local, regional, and global seismology; infrastructure and urban monitoring; and several others. However, to date, the open-source software ecosystem for handling DAS data is relatively immature. Here we introduce DASCore, a Python library for analyzing, visualizing, and managing DAS data. DASCore implements an object-oriented interface for performing common data processing and transformations, reading and writing various DAS file types, creating simple visualizations, and managing file system-based DAS archives. DASCore also integrates with other Python-based tools which enable the processing of massive data sets in cloud environments. DASCore is the foundational package for the broader DAS data analysis ecosystem (DASDAE), and as such its main goal is to facilitate the development of other DAS libraries and applications.</p>","PeriodicalId":520237,"journal":{"name":"Seismica","volume":"3 2","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11440623/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Seismica","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.26443/seismica.v3i2.1184","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In the past decade, distributed acoustic sensing (DAS) has enabled many new monitoring applications in diverse fields including hydrocarbon exploration and extraction; induced, local, regional, and global seismology; infrastructure and urban monitoring; and several others. However, to date, the open-source software ecosystem for handling DAS data is relatively immature. Here we introduce DASCore, a Python library for analyzing, visualizing, and managing DAS data. DASCore implements an object-oriented interface for performing common data processing and transformations, reading and writing various DAS file types, creating simple visualizations, and managing file system-based DAS archives. DASCore also integrates with other Python-based tools which enable the processing of massive data sets in cloud environments. DASCore is the foundational package for the broader DAS data analysis ecosystem (DASDAE), and as such its main goal is to facilitate the development of other DAS libraries and applications.
在过去十年中,分布式声学传感(DAS)在不同领域实现了许多新的监测应用,包括碳氢化合物勘探和开采;诱发、局部、区域和全球地震学;基础设施和城市监测;以及其他一些领域。然而,到目前为止,处理 DAS 数据的开源软件生态系统还相对不成熟。我们在此介绍 DASCore,这是一个用于分析、可视化和管理 DAS 数据的 Python 库。DASCore 实现了一个面向对象的接口,用于执行常见的数据处理和转换、读写各种 DAS 文件类型、创建简单的可视化以及管理基于文件系统的 DAS 存档。DASCore 还与其他基于 Python 的工具集成,从而能够在云环境中处理海量数据集。DASCore 是更广泛的 DAS 数据分析生态系统 (DASDAE) 的基础软件包,因此其主要目标是促进其他 DAS 库和应用程序的开发。