石油勘探与开发2012，Vol.39Issue(4)：500-504,5.
西非及亚太地区海上油田钻井完井投资估算模型
A model for estimating the drilling and completion investment in offshore oilfields in West Africa and the Asia-Pacific region
摘要
Abstract
A BP neural network model for estimating the drilling and completion investment is built based on the BP neural network method with 86 representative offshore oilfields in West Africa and Asia-Pacific as samples. The model uses five factors, including oil price, water depth, well number, well depth and geologic condition, as the input parameters, and outputs the drilling and completion investment parameters. Comparison of the model with a regression analysis model shows that the established model is reasonable and valuable because the BP neural network is an active learning process, able to effectively describe the non-linear relationship between variables and solve complicated problems. The established BP neural network model has high fitting accuracy and the errors of most samples are within 30%, satisfying the requirements for engineering development, and are much smaller than that of regression analysis.关键词
西非/亚太地区/海上油田/钻井完井投资估算/BP神经网络Key words
West Africa/ Asia-Pacific/ offshore oilfield/ drilling and completion investment estimate/ BP neural network分类
能源科技引用本文复制引用
汪东进,李秀生,张海颖,王震..西非及亚太地区海上油田钻井完井投资估算模型[J].石油勘探与开发,2012,39(4):500-504,5.基金项目
教育部哲学社会科学研究重大课题攻关项目"中国与全球油气资源重点区域合作研究"(09JZD0038) （09JZD0038）
