Research for full-term forecasting model of production rate with multiple life cycle

3rd International Conference on Energy Materials and Environment Engineering

能源学;生态环境科学

Wende, Yan^1 ; Yingzhong, Yuan^1 ; Jun, Liu^2 ; Zhilin, Qi^1 ; Jiqiang, Li^1 ; Qianhua, Xiao^1

Chongqing Key Laboratory of Complex Oil and Gas Fields Exploration and Development, Chongqing University of Science and Technology, Shapingba, Chongqing, China^1

Petro China Southwest Oil and Gas Field Company, Chengdu, China^2

关键词: Binary regression;    Correlation factors;    Cumulative production;    Forecasting modeling;    Production forecasting;    Production peaks;    Regression method;    Trial-and-error method;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/61/1/012006/pdf
DOI  :  10.1088/1755-1315/61/1/012006

学科分类：环境科学（综合）

来源: IOP

【 摘 要 】

Based on generalized production forecasting model, in the case of oil production with multiple production peak value and multiple life cycle, a multi-peak forecasting model is proposed, which can describe full course of rise, growth, maturity and decline for every life cycle. Linear trial-and-error method, binary regression method and ternary regression method are used to resolve the parameters of production forecasting model. The results indicate that parameters in linear trial-and-error method are not resolved simultaneously and the solutions are usually not the best matching. Parameters in multi-variant regression method are resolved simultaneously with the best correlation factor, and the solution is more accurate than linear trial-and-error method. Growth factor including cumulative production rate term and exponential function term of time are considered simultaneously in ternary regression method, and the solution is more accurate than binary regression method. For actual example with three-peak production, ternary regression method are used to resolve the parameters of multi-peak production forecasting model, and matching accuracy is greatly improved.