English / 正體中文
研究人員研究技術人員駐所、訪問學者博士後研究學術諮詢委員合聘、兼任及通信研究人員研究助理行政人員TIGP研究生退休研究人員地球所友
古進上

古進上 Ku, Chin-Shang

研究助技師
研究領域:地震學、地球物理、地球科學

研究簡介

My research mainly focuses on observational seismology and concentrates on analyzing the seismic data to image the subsurface structure. The ambient noise records and earthquake seismograms are used to explore the crustal and uppermost mantle structure. For example, I was in charge of installing a seismic network deployed in the western Solomon Islands. From setting up the instrument to the final scientific studies, I completed works with the research team and eventually published the seismic velocity models for the study region.

I also assisted in designing and establishing the telemetry system for real-time seismic data transmissions since 2009. Moreover, I managed the virtual private network (VPN) for data acquisition from remote stations and data exchange between IES and other institutions. Besides, I am operating several servers for different services in data transmissions (some for importing and others for exporting data) and providing stations' information (maintenance history, transmit latency, data quality control, and state of health of instrument). To extract the event data to become more accessible from the continuous database, I have designed the customized data extraction system by utilizing different software and programming languages (e.g., SeisComP, SEISAN, and Python). Most of the missions above were accomplished independently and adjustable according to the specific purpose of principal investigators.

In the near future, I will work on managing the data of distributed acoustic sensing (DAS), a very novel observation technology in seismology. DAS can detect the vibration changes at each optical fiber distance (at intervals of several meters). With high resolution in space and time, it can provide more information for monitoring microseismic events. At the same time, because every few meters of the optical fiber can be used as a sensor, a few kilometers long of optical fiber can accumulate a large amount of observation data in a short time, new data processing techniques are required. Thus, I will focus on developing the processing procedures using the new programming language (e.g., Julia).
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