Research on CCL Signal Recognition Method for Coupling Based on SVM Algorithm

Unconventional oil and gas resources are currently being produced on a massive scale in key domestic oil and gas fields, and the identification of oil and gas well coupling locations has become a research hotspot in the field of petroleum technology. The investigation of CCL signals is made more inventive by the use of data mining and machine learning approaches. This work employs signal signature-based signal selection and sliding window feature selection. After a series of tests, the SVM model outperformed the AUC model in classifying performance evaluation measures. In addition, when compared to CCL signal measurements, the model prediction results were better.