西南石油大学学报（社会科学版）2019，Vol.21Issue(1)：8-13,6.DOI:10.11885/j.issn.1674 5094.2018.09.26.03
基于偏最小二乘回归分析的油田操作成本预测——以DX油田为例
Prediction of Oilfield Operation Cost Through Partial Least Squares Regression——A Case Study on DX Oilfield
摘要
Abstract
Partial least squares regression analysis establishes a regression model by extracting the components containing the original data variation information from the independent variable and dependent variable data table, which can solve the problem of multiple collinearity due to the high correlation between the independent variables in the regression modeling process.With oil field operation cost as the research object, and operating cost as the dependent variable, we analyze the partial data of the DX Oilfield's variables through partial least squares regression analysis by using SIMCA-P software.The regression prediction model is established and tested.The results show that the independent variable index has an explanatory power of 0.99902, and the model has very high reliability.This research shows that partial least squares regression method is applicable to the prediction of oilfield operation cost, and can be used for reference in other research objects.关键词
偏最小二乘回归/回归模型/回归预测模型/油田操作成本/SIMCA-P软件Key words
partial least squares regression/regression model/regression prediction model/oilfield operating cost/SIMCA-P software分类
管理科学引用本文复制引用
陈武,吴焘宏,陈尘,马梦晓..基于偏最小二乘回归分析的油田操作成本预测——以DX油田为例[J].西南石油大学学报（社会科学版）,2019,21(1):8-13,6.基金项目
国家科技重大专项"特高含水后期整装油田延长经济寿命期开发技术" (2016ZX0511-001) （2016ZX0511-001）
四川省软科学研究计划项目"多重视域下四川天然气产业可持续发展研究" (2018ZR0072) （2018ZR0072）
