Field seismic and geospatial sensor data integration and visualization
现场地震和地理空间传感器数据集成和可视化
基本信息
- 批准号:507080-2016
- 负责人:
- 金额:$ 1.82万
- 依托单位:
- 依托单位国家:加拿大
- 项目类别:Engage Grants Program
- 财政年份:2016
- 资助国家:加拿大
- 起止时间:2016-01-01 至 2017-12-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
The dynamic nature of today's industry requires new technology and ways of conducting seismic and geomatics survey continuously. The current seismic equipment and systems have limited frequency bandwidth, and lack of lower range frequency signals and higher frequency range result in lower resolution and restricts capability for analysis. The geophone developed by Symroc has large data capacity and make continuous data collection and monitoring viable. However, the acquired seismic data and geospatial information by the new geophone is currently processed in a batched mode and over a long period of time. The final seismic visual and analytical results cannot be available to users for months due to the complexity and size of the data collected. The objective of this proposed project is to develop efficient and accurate data-driven integration methods on the continuously collected seismic sensor data together with their geospatial information. The project offers innovative approaches and distinctive solutions that can lead to more energy-efficient, low cost and reliable seismic data collection and analytical process. The project will provide better understanding of how to process wide range of frequency seismic data. The developed system can potentially be used to help natural earthquake studies and researches, resource industry operations, live monitoring, and other real time environmental monitoring. Benefits of the proposed research to the industry and economy of Alberta and Canada are significant. Additionally, the expertise and research experience provides unique opportunities to train HQP.
当今工业的动态性质要求不断地进行地震和地质测量的新技术和方法。现有的地震仪器和系统频带宽度有限,缺乏低频信号和高频信号,导致分辨率较低,限制了分析能力。Symroc公司研制的检波器数据容量大,可实现连续数据采集和监测。然而,新的地震检波器所采集的地震数据和地理空间信息目前是以批处理方式并在很长一段时间内处理的。由于所收集数据的复杂性和规模,最终的地震视觉和分析结果在几个月内无法提供给用户。本拟议项目的目标是就不断收集的地震传感器数据及其地理空间信息制定有效和准确的数据驱动整合方法。该项目提供了创新的方法和独特的解决方案,可以实现更节能,更低成本和更可靠的地震数据收集和分析过程。该项目将使人们更好地了解如何处理各种频率的地震数据。该系统可用于自然地震研究、资源工业运营、现场监测和其他真实的实时环境监测。拟议的研究对阿尔伯塔和加拿大的工业和经济的好处是显着的。此外,专业知识和研究经验为培训HQP提供了独特的机会。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Wang, Xin其他文献
Preparation of lignin-based porous carbon with hierarchical oxygen-enriched structure for high-performance supercapacitors
- DOI:
10.1016/j.jcis.2019.01.058 - 发表时间:
2019-03-22 - 期刊:
- 影响因子:9.9
- 作者:
Chen, Weimin;Wang, Xin;Zhou, Xiaoyan - 通讯作者:
Zhou, Xiaoyan
A note on instanton effects in ABJM theory
ABJM理论中瞬子效应的注记
- DOI:
10.1007/jhep11(2014)100 - 发表时间:
2014-09 - 期刊:
- 影响因子:5.4
- 作者:
Wang, Xian-fu;Wang, Xin;Huang, Min-xin - 通讯作者:
Huang, Min-xin
Train duration and inter-train interval determine the direction and intensity of high-frequency rTMS after-effects.
- DOI:
10.3389/fnins.2023.1157080 - 发表时间:
2023 - 期刊:
- 影响因子:4.3
- 作者:
Jin, Jingna;Wang, Xin;Wang, He;Li, Ying;Liu, Zhipeng;Yin, Tao - 通讯作者:
Yin, Tao
Arabidopsis Floral Initiator SKB1 Confers High Salt Tolerance by Regulating Transcription and Pre-mRNA Splicing through Altering Histone H4R3 and Small Nuclear Ribonucleoprotein LSM4 Methylation
拟南芥花引发剂 SKB1 通过改变组蛋白 H4R3 和小核核糖核蛋白 LSM4 甲基化来调节转录和前 mRNA 剪接,从而赋予高盐耐受性
- DOI:
- 发表时间:
2011 - 期刊:
- 影响因子:11.6
- 作者:
Bao, Shilai;Zhang, Shupei;Zhang, Ya;Wang, Xin;Li, Dan;Li, Qiuling;Yue, Minghui;Li, Qun;Zhang, Yu-e - 通讯作者:
Zhang, Yu-e
Catalytic hydrogenation of nitrophenols and nitrotoluenes over a palladium/graphene nanocomposite
钯/石墨烯纳米复合材料上硝基苯酚和硝基甲苯的催化氢化
- DOI:
10.1039/c4cy00048j - 发表时间:
2014-05 - 期刊:
- 影响因子:0
- 作者:
Fu, Yongsheng;He, Guangyu;Sun, Xiaoqiang;Wang, Xin - 通讯作者:
Wang, Xin
Wang, Xin的其他文献
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{{ truncateString('Wang, Xin', 18)}}的其他基金
Personalized Location Recommendation on Location-Based Social Networks by Efficiently Utilizing Spatio-Temporal Information
有效利用时空信息的基于位置的社交网络的个性化位置推荐
- 批准号:
RGPIN-2018-03916 - 财政年份:2022
- 资助金额:
$ 1.82万 - 项目类别:
Discovery Grants Program - Individual
Three-Dimensional Mixed-Mode Fracture Mechanics Methodologies for Structural Integrity Assessments of Welded Structures
用于焊接结构结构完整性评估的三维混合模式断裂力学方法
- 批准号:
RGPIN-2020-06550 - 财政年份:2022
- 资助金额:
$ 1.82万 - 项目类别:
Discovery Grants Program - Individual
Personalized Location Recommendation on Location-Based Social Networks by Efficiently Utilizing Spatio-Temporal Information
有效利用时空信息的基于位置的社交网络的个性化位置推荐
- 批准号:
RGPIN-2018-03916 - 财政年份:2021
- 资助金额:
$ 1.82万 - 项目类别:
Discovery Grants Program - Individual
Three-Dimensional Mixed-Mode Fracture Mechanics Methodologies for Structural Integrity Assessments of Welded Structures
用于焊接结构结构完整性评估的三维混合模式断裂力学方法
- 批准号:
RGPIN-2020-06550 - 财政年份:2021
- 资助金额:
$ 1.82万 - 项目类别:
Discovery Grants Program - Individual
Personalized Location Recommendation on Location-Based Social Networks by Efficiently Utilizing Spatio-Temporal Information
有效利用时空信息的基于位置的社交网络的个性化位置推荐
- 批准号:
RGPIN-2018-03916 - 财政年份:2020
- 资助金额:
$ 1.82万 - 项目类别:
Discovery Grants Program - Individual
Three-Dimensional Mixed-Mode Fracture Mechanics Methodologies for Structural Integrity Assessments of Welded Structures
用于焊接结构结构完整性评估的三维混合模式断裂力学方法
- 批准号:
RGPIN-2020-06550 - 财政年份:2020
- 资助金额:
$ 1.82万 - 项目类别:
Discovery Grants Program - Individual
Fracture Mechanics Methodologies for Structural Integrity Assessments and Fatigue Life Predictions under Multi-axial Non-proportional Loading
多轴非比例载荷下结构完整性评估和疲劳寿命预测的断裂力学方法
- 批准号:
RGPIN-2015-03994 - 财政年份:2019
- 资助金额:
$ 1.82万 - 项目类别:
Discovery Grants Program - Individual
Development of geospatial clustering methods for broadband seismic-facies analysis
宽带地震相分析的地理空间聚类方法的开发
- 批准号:
514549-2017 - 财政年份:2019
- 资助金额:
$ 1.82万 - 项目类别:
Collaborative Research and Development Grants
Personalized Location Recommendation on Location-Based Social Networks by Efficiently Utilizing Spatio-Temporal Information
有效利用时空信息的基于位置的社交网络的个性化位置推荐
- 批准号:
RGPIN-2018-03916 - 财政年份:2019
- 资助金额:
$ 1.82万 - 项目类别:
Discovery Grants Program - Individual
Development of geospatial clustering methods for broadband seismic-facies analysis
宽带地震相分析的地理空间聚类方法的开发
- 批准号:
514549-2017 - 财政年份:2018
- 资助金额:
$ 1.82万 - 项目类别:
Collaborative Research and Development Grants
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