Application of Chaotic Theory to Oil Production Rate Time Series Prediction
Time series analysis of oil production rate is performed using chaos theory. And based on phase space reconstruction, oil production rate prediction model was established, through which oil production rate was predicted directly and after smoothing respectively for each well. The analysis indicates that oil production rate shows chaotic behaviors for some wells, for which the average largest Lyaunov Exponent is about 0.063, while for the others, its obscure because the minimum embedding dimension couldnt be obtained through Cao Method. The prediction model provides a reliable result, and the prediction after smoothing works even better. The average relative errors of direct prediction and smoothing-prediction are 13.02％ and 1.58％ respectively for wells in Tahe Oilfield, which indicates that its promising to develop a predictive model based on the previous oil production rate for wells.
Chaotic Prediction Model Oil Production Rate Time Series
Zheng Songqing Zhang Hongfang Bao Jingwei
China University of Petroleum (Hua Dong)CUP Dongying,China Petroleum Exploration & Production Research Institute Sinopec Beijing,China PetroChina Research Institute of Petroleum Exploration & Development Beijing,China
国际会议
上海
英文
2505-2508
2009-11-20（万方平台首次上网日期，不代表论文的发表时间）