支持向量机算法在地质录井中的应用

在地质录井油气水层识别研究中引入基于统计学习理论的支持向量机算法，对气测录井和地化录井中得到的各项参数及其导出参数之间的关系进行研究，并应用LibSVM软件建立了地质录井的油气水层识别模型，从而提供了一种新的地质录井油气水层识别方法。该方法在新疆某油田的实际应用结果证明，用支持向量机算法进行地质录井油气水层识别具有简单可靠、适应性强和识别精度较高等一系列优点。

Application of Support Vector Machine Arithmetic to Geologic Logging

The support vector machine arithmetic, based on statistical theory, is presented in study of recognition of oil, gas and water zones from geologic logging. The parameters from gasometry logging and geochemistry logging and relations among induced parameters are studied, thus developing a model with help of LibSVM software, by which a novel method for recognizing oil/gas/water zone from geologic logging is proposed. The real application of this method to an oilfield in Xinjiang shows that the support vector machine arithmetic is simple, reliable, more practical and higher accurate for use.