| 肖浩汉,曹瑞琅,王玉杰,赵宇飞,孙彦鹏.随钻监测数据预处理方法研究[J].水利学报,2024,55(11):1379-1390 |
| 随钻监测数据预处理方法研究 |
| Research on preprocessing methods for monitoring drilling data |
| 投稿时间：2023-12-30 |
| DOI：10.13243/j.cnki.slxb.20230816 |
| 中文关键词: 随钻钻进(探) 数据预处理 机器学习 缺失插补 滤波降噪 |
| 英文关键词: digital drilling data preprocessing machine learning missing data interpolation noise reduction |
| 基金项目:国家电网公司总部科技项目(5200-202322135A-1-1-ZN);国家自然科学基金项目(52079150) |
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| 中文摘要: |
| 为攻克多维异构随钻监测数据处理难题，本研究分析多钻孔钻进数据特征，采用统计分析和机器学习方法，提出了一种数据预处理方法。该方法首先对原始钻进数据特征进行分析，确定了稳定钻进阶段数据提取判断标准，提出识别异常钻进数据的准则，并评估了多种方法在钻进数据缺失修补和滤波降噪方面的适用性。结果表明：两点线性插补方法取得了最低的误差指标和最佳的缺失插补效果;巴特沃斯滤波器在不同噪声类型下均取得了最优的滤波效果。最后，开发了轻量化钻进数据自动预处理软件，并在工程案例中验证了其快速完成数据提取、分类、修补和降噪的能力。研究结果为工程实践提供了可靠的理论依据和数据支持。 |
| 英文摘要: |
| To address challenges associated with processing multi-dimensional heterogeneous monitoring drilling data，this study conducts an analysis of the characteristics of multi-borehole drilling data and introduces a data preprocessing method leveraging statistical analysis and machine learning techniques.This methodology begins with an examination of the original drilling data’s features，establishes criteria for extracting stable drilling stage data，defines parameters for identifying abnormal drilling data，and assesses the effectiveness of various methods for repairing missing drilling data and reducing noise.The results indicate that the two-point linear interpolation method achieved the lowest error index and the most effective missing data interpolation.Additionally，the Butterworth filter demonstrated optimal filtering performance across various types of noise.Subsequently，a lightweight automatic preprocessing software for drilling data is developed，and its efficacy in swiftly completing tasks such as data extraction，classification，repair，and noise reduction is validated through engineering case studies.This endeavor furnishes a dependable theoretical framework and empirical data support for practical applications in engineering. |
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