油气田采出水结垢趋势评价方法与展望  

Evaluation method and prospect of production water scaling trend in oil and gas fields

作　　者：高家朋 鱼涛 屈撑囤[1,2] 郭志强 单巧丽 GAO Jiapeng;YU Tao;QU Chengtun;GUO Zhiqiang;SHAN Qiaoli(College of Chemistry and Chemical Engineering,Xi'an Shiyou University,Xi'an Shaanxi 710065,China;Shaanxi Oil and Gas Pollution Control and Reservoir Protection Key Laboratory,Xi'an Shaanxi 710065,China;Changqing Engineering Design Co.,Ltd.,Xi'an Shaanxi 710065,China)

机构地区：[1]西安石油大学化学化工学院,陕西西安710065 [2]陕西省油气田环境污染控制技术与储层保护重点实验室,陕西西安710065 [3]长庆工程设计有限公司,陕西西安710065

出　　处：《石油化工应用》2022年第11期14-19,共6页Petrochemical Industry Application

基　　金：陕西省教育厅服务地方专项计划项目:陕北区域油气田措施返排液回用技术研究,项目编号:22JC054。

摘　　要：作为油气田生产过程中的主要影响之一,采出水结垢的问题引起了研究者们的广泛关注。其中结垢预测方法对油气田生产过程具有很大的影响。现今大多结垢预测公式主要多为实验室环境下通过静态实验而得出,不一定能完全适应油田实际生产过程,而近年来随着大数据的兴起以及神经网络的发展,在结垢趋势预测以及模型的建立方面有了长足的发展。本文通过对机理性结垢预测以及相关软件开发应用和现代数值分析两种方法进行梳理与总结,最后结合当前结垢预测发展情况,对其做出展望。As one of the main effects in the production process of oil and gas fields, the problem of produced water scaling has attracted wide attention of researchers. The scaling prediction method has a great influence on the production process of oil and gas fields. At present, most of the scaling prediction formulas are obtained by static experiments in the laboratory environment, which may not be suitable for the actual production process of oilfield. However, with the rise of big data and the development of neural network, it has made great progress in the prediction of scaling trend and the establishment of models. In this paper, the mechanism of scaling prediction and related software development and application and modern numerical analysis methods are carded and summarized, and finally combined with the current scale prediction development, the prospects are made.

关 键 词：油田结垢 结垢预测 软件模拟 神经网络 

分 类 号：TE319[石油与天然气工程—油气田开发工程]