Real-Time Intelligent Identification Method under Drilling Conditions Based on Support Vector Machine
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摘要:
钻井时效分析通常是依靠人工进行事后分析，具有主观性和随意性，不能及时准确地反映真实的现场情况。为了实时准确地对钻井工况进行自动判别，提高钻井效率，提出了一种基于支持向量机（SVM）的用数据驱动的钻井工况实时识别方法，建立了多个智能识别模型，并对其中的核函数进行分析比较，得出了模型参数的最优值。采用4口井的录井数据验证了模型的准确性，识别结果与实际工况基本一致，6种工况的识别正确率均达到95%以上。钻井时效分析与应用表明，钻井过程中应用工况识别结果，减少了不可见非生产时间。支持向量机实现了钻井工况的实时智能识别，提高了钻井时效，符合油田数字化和智能化发展的要求。
Abstract:At present, the analysis of drilling time-efficiency usually relies on manual post-analysis, which is subjective and arbitrary, and not able to reflect the real field situation in time, with a lot of deviation. In order to identify drilling conditions automatically and accurately in real time and improve drilling efficiency, a data-driven real-time identification method of drilling conditions based on support vector machine (SVM) has been put forward, and established several intelligent identification models. By analyzing and comparing the kernel functions in the models, the optimal model parameters were obtained. Logging data from four wells were used to verify the correctness of the model, and the recognition results were basically consistent with the actual working conditions, and the recognition accuracy under six working conditions was higher than 95%. The analysis of drilling time-efficiency showed that the application of working condition identification result in drilling process shortened the invisible non-production time. Support vector machine has realized real-time intelligent identification of drilling conditions, and improved drilling time-efficiency, which could meet the requirements of digital and intelligent development of oilfields.
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图 7 两层感知器核函数的识别结果
Figure 7. Identification results of kernel functions by two-layer perceptron
表 1 不同核函数计算结果对比
Table 1 Comparisons of calculation results with different kernel functions
核函数 样本
数量准确识别
数量准确
率，%计算用时/s 线性核函数 600 568 94.67 0.511 966 多项式核函数 600 564 94.00 0.670 709 径向基核函数 600 581 96.83 0.581 977 两层感知器核函数 600 242 40.33 2.917 935 
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表 2 不同层位接立柱时间统计
Table 2 Time statistics for making up a stand of drill pip
立柱序号 前期平均接
立柱时间/minSVM实时判断新井接
立柱时间/min现场决策 1—12 2.5 2.7 有待提高 13—24 2.6 有待提高 25—36 2.4 有所提高 37至最后 2.2 显著提高
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