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当前的测井资料质量标准基于人工验收制定,其中包含大量的定性标准,如何依据定性标准进行测井资料质量自动验收,是目前面临的一个难题,将支持向量机方法应用于测井资料幅度异常预测,在资料中挑选可疑样本,依据已有的专家验收结论建立预测模型,对测井资料幅度异常进行预测,避免了自动验收中必须将定性标准定量化的问题,在实际应用中有较好的效果,对同类工程问题的解决有一定的借鉴意义。
The current logging data quality standards are based on manual acceptance, which contains a large number of qualitative criteria. How to automatically check the logging data quality according to the qualitative criteria is a difficult problem that we now face. The application of SVM to logging data anomalies Prediction, the selection of suspicious samples in the data, based on the existing expert acceptance conclusion to establish a prediction model to predict the anomalies of the logging data to avoid the need for automatic acceptance must quantify the qualitative criteria, in practical application is better The effect of similar projects to solve some of the reference.