摘要
为准确预测油气生产过程中的能源消耗,通过对油气生产过程分析,确定了过程的主要能耗指标,提出了一种机理模型与最小二乘支持向量机(LS-SVM)相结合的混合建模方法.通过对油气生产过程及各子过程之间关系的分析,建立了该过程综合能耗的机理模型,并利用LS-SVM对机理模型不能描述的误差特性进行补偿.仿真结果表明,该方法能够准确地预测油气生产过程的综合能耗,其预测性能优于机理模型和LS-SVM构建的数据模型,且具有较好的稳定性和可靠性,将其应用到某采油作业区的实际生产过程,取得了满意的效果.
In order to accurately predict the energy consumption in the oil and gas production process, the primary energy consumption indicator was determined through the analysis of the oil and gas production process. A hybrid modeling method was proposed, in which the mechanism model was combined with LS-SVM to predict the comprehensive energy consumption of oil and gas production process. Based on the analysis of the whole production process and the relationship between sub-processes, the mechanistic model of the energy consumption was established, and then LS-SVM was applied to compensate the error which could not be described using the mechanism model. The simulation results showed that the energy consumption of oil and gas production process could be accurately predicted with the proposed method, and the performance was better than those of mechanistic model and the model established by LS-SVM. It could be also concluded that the hybrid model has better stability and reliability. When the model was applied to the actual production process in some oil recovery operation area, satisfactory results could be received.
出处
《东北大学学报(自然科学版)》
EI
CAS
CSCD
北大核心
2013年第11期1525-1528,共4页
Journal of Northeastern University(Natural Science)
基金
国家自然科学基金资助项目(61034005)