Title of article :
A model for estimating the drilling and completion investment in offshore oilfields in West Africa and the Asia-Pacific region
Author/Authors :
WANG، نويسنده , , Dongjin and LI، نويسنده , , Xiusheng and ZHANG، نويسنده , , Haiying and Wang، نويسنده , , Zhen، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2012
Pages :
5
From page :
534
To page :
538
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.
Keywords :
West Africa , offshore oilfields , Asia-Pacific , BP neural network , drilling and completion investment estimate
Journal title :
Petroleum Exploration and Development
Serial Year :
2012
Journal title :
Petroleum Exploration and Development
Record number :
2300666
Link To Document :
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