摘要
准确预测油田产量对油田开发调整部署有重要意义.依据油田产量变化特征与油田产量数据丰富的特点,引入产量变化系数修正传统灰色模型,并运用中心差商改进了传统灰导数离散过程,减小灰导数离散误差,再结合PSO算法,最终建立了PSO-改进GM（1,1）模型.运用PSO-改进GM（1,1）模型进行油田产量预测,对比传统灰色模型与PSO-改进GM（1,1）模型的产量预测结果可知,与传统灰色模型预测结果相比,应用PSO-改进GM（1,1）模型进行油田产量预测具有更高的准确性.
Accurate prediction of oilfield production is of great significance to oilfield de- velopment. In this paper, Based on the traditional gray model, the PSO-modified GM （1,1） model is established by the production decline coefficient and central difference to discretiza- tion of traditional gray derivation. The PSO-modified GM （1,1） model is used to predict the production. By comparing the result of traditional grey model with the PSO-modified GM （1,1） model, it is known that the result of the PSO-modified GM （1,1） model is more accurate than traditional grey model.
作者
崔传智
吴忠维
李昱东
黄广庆
李荣涛
金超林
CUI Chuan-zhi1, WU Zhong-wei1, LI Yu-dong2, HUANG Guang-qing3, LI Rong-tao1, JIN Chao-lin1(1. College of Petroleum Engineering China University of Petroleum （East China）, Qingdao 266580, China） （2. Yumen Oilfield Exploration and Development Research Institute, Yumen 735000, China） （3. PetroChina the Creat Wall Drilling International Logging Company, Beijing 100101, China)
出处
《数学的实践与认识》
北大核心
2018年第17期119-123,共5页
Mathematics in Practice and Theory
基金
国家重大科技专项“大型油气田及煤层气开发”资助项目(2016ZX05010-002-007)
关键词
产量递减系数
中心差商
灰色模型
油田产量预测
Production decline coefficient
central difference
grey model
oilfield production prediction
