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Real-Time Intelligent Recognition Method for Horizontal Well Marker Bed

机译:水平井标记床的实时智能识别方法

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The accurate identification of the horizontal well marker bed is to guarantee the soft landing of the well trajectory. With the intelligent development of the petroleum industry, it is feasible to apply computers to identify the marker bed automatically. In case-based reasoning technology, the data of well logging while drilling (LWD) as characteristic parameters are compared with those of adjacent well. By taking the depth sequence of LWD data as time series and using Dynamic Time Warping (DTW) similarity measure algorithm, the similarity index of each drilling depth is calculated corresponding to the marker bed in the adjacent well. The total similarity curve is obtained by giving different weights of different feature parameters. Selecting natural gamma, deep resistivity, and shallow resistivity LWD curves as characteristic parameters, two horizontal wells in JL block of Junggar basin are analysed by this method. The result of similarity curve indicates the location of the marker bed and the total similarity value reaches 78%. The research shows that the method based on case-based reasoning can identify the marker bed of the horizontal well accurately and effectively, assist the geologist to carry out formation correlation of multiple wells at the same time, reduce the cost of human labour force, and improve work efficiency.
机译:水平井标记床的精确识别是保证井轨迹的软着陆。随着石油工业的智能发展,应用计算机自动识别标记床是可行的。在基于案例的推理技术中,将钻井(LWD)作为特征参数进行良好的记录数据与相邻井的井。通过将LWD数据的深度序列作为时间序列和使用动态时间翘曲(DTW)相似度测量算法,计算每个钻孔深度的相似性指数对应于相邻井中的标记床。通过给出不同特征参数的不同权重获得总相似性曲线。选择天然伽马,深度电阻率和浅电阻率LWD曲线作为特征参数,通过该方法分析Junggar盆地JL块中的两个水平孔。相似性曲线的结果表示标记床的位置,总相似性值达到78%。该研究表明,基于案例推理的方法可以准确且有效地识别水平井的标记床,帮助地质学家同时进行多孔的形成相关性,降低人力劳动力的成本,以及提高工作效率。

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