基于过程支持向量回归机的油田开发指标预测模型

A Model of Oilfield Development Index Forecast Base on Process Support Vector Regression Machine

针对传统支持向量回归机在机制上难以直接对时变信号进行处理，提出了一种用于时间序列预测的过程支持向量回归模型，面向油田开发指标综合分析预测等问题，提出了一种过程支持向量回归机模型，建立了基于涡流搜索的优化学习算法，方法可综合历史数据和开发条件，实现对油田开发指标的预测。

Aiming at the traditional support vector regression machine on the mechanism can＇t to solute dynamic time-varying signal pattern classification, proposes a process support vector regression time series prediction model. For the comprehensive analysis and prediction of oilfield development indexes, proposed a process support vector regression model. The learning algorithm based on vortex search algorithm is established, it can be used to realize the forecast of oil field development index with the comprehensive historical data and development conditions.