.png){kind=icon}
返回
pyGrav, a Python-based program for handling and processing relative gravity data
.png){kind=icon}
PRE
AI
DOI：10.1016/j.cageo.2016.03.010.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
pyGrav is a Python-based open-source software dedicated to the complete processing of relative-gravity data. It is particularly suited for time-lapse gravity surveys where high precision is sought. Its purpose is to bind together single-task processing codes in a user-friendly interface for handy and fast treatment of raw gravity data from many stations of a network. The intuitive object-based implementation allows to easily integrate additional functions (reading/writing routines, processing schemes, data plots) related to the appropriate object (a station, a loop, or a survey). This makes pyGrav an evolving tool. Raw data can be corrected for tides and air pressure effects. The data selection step features a double table-plot graphical window with either manual or automatic selection according to specific thresholds on data channels (tilts, gravity values, gravity standard deviation, duration of measurements, etc.). Instrumental drifts and gravity residuals are obtained by least square analysis of the dataset. This first step leads to the gravity simple differences between a reference point and any point of the network. When different repetitions of the network are done, the software computes then the gravity double differences and associated errors. The program has been tested on two specific case studies: a large dataset acquired for the study of water storage changes on a small catchment in West Africa, and a dataset operated and processed by several different users for geothermal studies in northern Alsace, France. In both cases, pyGrav proved to be an efficient and easy-to-use solution for the effective processing of relative-gravity data. (C) 2016 Elsevier Ltd. All rights reserved.
Keyword:
Relative-gravity
Time-variable gravity
Object-oriented
Python
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
C
IF:
4.4
论文数:
5.0K
被引数:
1.5W
机构
引用论文
Demonstration of 4H-SiC JFET Digital ICs Across 1000°C Temperature Range without Change to Input Voltages在1000°C温度范围内演示4H-SiC JFET数字IC，且输入电压无变化
PREAI
分享收藏分享收藏The Influence of Extended Defects in 4H-SiC Epitaxial Layers on Gate Oxide Performance and Reliability4H-SiC外延层中扩展缺陷对栅氧化物性能和可靠性的影响
OAAI
OAAI分享收藏Enhanced Hole Transport in Ni/Y₂O₃/n-4H-SiC MOS for Self-Biased Radiation DetectionNi/Y₂O₃/n-4H-SiC MOS中增强的空穴输运用于自偏置辐射检测OAAI
OAAI分享收藏Measuring gravity change caused by water storage variations: Performance assessment under controlled conditions.png)
JOURNAL OF HYDROLOGY
JOURNAL OF HYDROLOGYIF6.3
PREAI
分享收藏
查看更多内容