万庭辉, 邱海峻, 陆敬安, 李占钊, 马超, 王静丽. 天然气水合物试采中分布式光纤测温(DTS)数据现场处理及可视化[J]. 海洋地质前沿, 2020, 36(2): 59-64. DOI: 10.16028/j.1009-2722.2019.019
    引用本文: 万庭辉, 邱海峻, 陆敬安, 李占钊, 马超, 王静丽. 天然气水合物试采中分布式光纤测温(DTS)数据现场处理及可视化[J]. 海洋地质前沿, 2020, 36(2): 59-64. DOI: 10.16028/j.1009-2722.2019.019
    WAN Tinghui, QIU Haijun, LU Jingan, LI Zhanzhao, MA Chao, WANG Jingli. Study of On-Site Processing and Visualization of DTS Datafrom China's First Offshore Natural Gas Hydrate Production Testin South China Sea[J]. Marine Geology Frontiers, 2020, 36(2): 59-64. DOI: 10.16028/j.1009-2722.2019.019
    Citation: WAN Tinghui, QIU Haijun, LU Jingan, LI Zhanzhao, MA Chao, WANG Jingli. Study of On-Site Processing and Visualization of DTS Datafrom China's First Offshore Natural Gas Hydrate Production Testin South China Sea[J]. Marine Geology Frontiers, 2020, 36(2): 59-64. DOI: 10.16028/j.1009-2722.2019.019

    天然气水合物试采中分布式光纤测温(DTS)数据现场处理及可视化

    Study of On-Site Processing and Visualization of DTS Datafrom China's First Offshore Natural Gas Hydrate Production Testin South China Sea

    • 摘要: 综合运用Matlab和Origin的优势功能,实现了海域天然气水合物试采过程中DTS现场数据的快速处理和可视化。相较于传统的二维温度数据成图,采用DTS(Distributed Fiber Optical Temperature Sensor)数据可视化方法高效直观,可综合分析全井或局部温度随时间变化的趋势,有助于了解井筒内生产情况,进一步结合地温梯度曲线,可辅助判断井筒附近水合物的分解和形成,有效提高生产优化和预测的分析效率。

       

      Abstract: This paper synthesizes the advantages and functions of using Matlab and Origin to realizing rapid processing and visualization of DTS field data in Offshore Natural Gas Hydrate Production Test by China in the South China Sea. Compared with the traditional two-dimensional temperature data mapping, the DTS (Distributed Fiber Optical Temperature Sensor) data visualization method used in this paper is more efficient and intuitive, and can comprehensively analyze the trend of the whole well or the local temperature with time, which is helpful to know the production in the wellbore. The situation, combined with the geothermal gradient curve, can assist in judging the decomposition and formation of hydrates near the wellbore, effectively improving the efficiency of production optimization and prediction.

       

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