支持向量机回归在油气钻井成本预测中的应用

钻井成本是钻井公司成本的重要组成部分,对钻井成本进行准确预测,有利于提高钻井成本的控制和计划管理水平.应用作业成本法分析影响钻井成本的主要因素,结合某钻井公司钻井成本数据,运用支持向量机回归建立预测模型,同多元回归与BP神经网络回归进行对比,验证了支持向量机模型具有较高的预测精度.

Application of support vector machine regression in the forecast of oil-gas drilling cost

Oil-gas drilling cost is a vital part in the cost of a drilling engineering company.The accurate forecast of the drilling cost will be helpful to the cost controlling and project planning of a drilling engineering company.The factors of influencing the drilling cost are analyzed using activity-based costing,according to the practical drilling cost data of a drilling engineering company,the drilling cost forecasting model is established using support vector machine regression.Compared with multi-variable linear regression and BP neural network,the support vector machine regression has higher forecasting accuracy.