辽宁石油化工大学学报

辽宁石油化工大学学报 ›› 2018, Vol. 38 ›› Issue (06): 54-58.DOI: 10.3969/j.issn.1672-6952.2018.06.010

• 石油与天然气工程 • 上一篇    下一篇

基于正交实验的水源井水腐蚀影响因素及腐蚀预测

黄丽1陈昱铭2韩鑫1曾庆恒1   

  1. 1.重庆科技学院 石油与天然气工程学院, 重庆 401331; 2.吉林油田油气工程研究院 三次采油研究所,吉林 松原 138000
  • 收稿日期:2018-07-18 修回日期:2018-09-05 出版日期:2018-12-01 发布日期:2018-12-11
  • 通讯作者: 曾庆恒(1956-),男,教授,从事采油采气工程研究;E-mail:zengqingheng@163.com。
  • 作者简介:黄丽(1991-),女,硕士研究生,从事采气工程研究;E-mail:973609052@qq.com。
  • 基金资助:
    重庆科技学院研究生科技创新计划项目(YKJCX1620132)。

Influence Factors and Corrosion Prediction of Water Source Well Corrosion based on Orthogonal Experiment

Huang Li1Chen Yuming2Han Xin1Zeng Qingheng1   

  1. 1.School of Petroleum Engineering,Chongqing University of Science &Technology,Chongqing 401331,China; [JP2]2.Research Institute Three Mining, PetroChina Jilin Oilfield Company Petroleum Engineering,Songyuan Jilin 138000,China
  • Received:2018-07-18 Revised:2018-09-05 Online:2018-12-01 Published:2018-12-11

摘要: 针对SZ36-1油田水源井水对油管腐蚀穿孔的影响日益严重的问题,在现场工况下研究了管材的腐蚀规律并对腐蚀进行了预测。设计5因素4水平的正交实验,分析了温度、压力、流速、CO2质量浓度和矿化度等5个因素对腐蚀速率的影响,确定了SZ36-1油田水源井腐蚀环境下的主控因素是温度和CO2质量浓度。通过多元线性回归分析方法和BP神经网络方法,建立腐蚀预测模型并进行了对比分析。对比分析结果表明,基于多元线性回归方法的腐蚀预测模型预测精度更高,更适合目前油田水源井水的腐蚀预测。

关键词: 水源井腐蚀, 腐蚀因素, 正交实验, 腐蚀预测

Abstract: In view of the increasingly serious problem of corrosion and perforation of the oil pipe caused by water source well in the SZ36-1 oilfield, the corrosion law of the pipe is studied under field conditions and the corrosion is predicted. The Orthogonal experiment of five factors and four levels is designed to analyze the effects of temperature, pressure, flow rate, CO2 concentration and salinity on the corrosion rate.The main controlling factors in the corrosion environment of the water source well of SZ36-1 oilfield are temperature and CO2 concentration. The corrosion prediction model is established and compared by multiple linear regression analysis and BP neural network. The comparative analysis results show that the corrosion prediction model based on multiple linear regression method has higher prediction accuracy and is more suitable for corrosion prediction of oilfield water source well.

Key words: Water source well corrosion, Corrosion factor, Orthogonal experiment, Corrosion prediction