›› 2013, Vol. 34 ›› Issue (4): 1-1.

• 论文 •    

基于ARIMA模型的钻井作业风险预测

赵春兰,王 兵,郭 平   

  1. (西南石油大学 理学院,成都 610500)
  • 出版日期:2019-01-01 发布日期:1905-07-12

The Risk Probability Prediction of Drilling Operation Site Using ARIMA Model

ZHAO Chunlan, WANG Bing, GUO Ping   

  1. (College of Technology, Southwest Petroleum University, Chengdu, Sichuan, 610500, China)
  • Online:2019-01-01 Published:1905-07-12

摘要: 钻井作业存在着大量不确定性,具有高投入、高风险的特点,目前尚无针对钻井作业风险概率预测的定量模型。为此,提出ARIMA模型定量预测钻井作业现场未来发生风险概率的方法。以龙岗M井记录的钻井作业现场的风险概率作为时间序列的样本值,提取统计特征,利用SAS软件进行ADF检验、纯随机性检验;并根据ACF和PACF图,结合AIC,SBC准则、标准误差等建立了最终的ARIMA(2,1,3)模型,其拟合误差为4.477 4%. 预测结果表明,该模型对深层碳酸盐岩裂缝性油藏的钻井风险预测效果较好,而且短期预测效果好于长期预测效果。

Abstract: There exist a lot of uncertainties during drilling operation, with high investment and high risks. Up to now, there is no quantitative risk probability prediction model for drilling operation site. This paper proposes the ARIMA model for quantitative prediction of drilling operation risks that may take place in future. Taking the field risk probability recorded from Longgang M well as samples of time sequence, the statistical characteristics are extracted followed by ADF inspection and pure random test with SAS software. Combining the ACF and PACF charts with the criterions of AIC, SBC and standard error, the final ARIMA (2,1,3) model has been developed, with the error of simulation of 4.477 4%. The prediction results show that the model is more suitable for drilling operation site in deep carbonate fractured reservoirs, and the short?term prediction results are better than the long?term prediction ones

中图分类号: