元坝高酸性气田地面管道内腐蚀预测  

Internal corrosion prediction of ground pipeline of Yuanba high-sour gasfield

作　　者：孙天礼[1] 韩雪 黄仕林[1] 赵春兰[2] 何欢 曾德智[2] SUN Tianli;HAN Xue;HUANG Shilin;ZHAO Chunlan;HE Huan;ZENG Dezhi(No.2 Gas Production Plant,SINOPEC Southwest Oil&Gas Company;Southwest Petroleum University//State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation)

机构地区：[1]中国石化西南油气分公司采气二厂,四川省阆中市634700 [2]西南石油大学·油气藏地质及开发工程国家重点实验室,四川省成都市610500

出　　处：《油气储运》2023年第1期40-45,共6页Oil & Gas Storage and Transportation

基　　金：国家自然科学基金资助项目“静载、振动与腐蚀作用下H_(2)S和CO_(2)气井完井管柱螺纹密封面的力化学损伤机制研究”,51774249;四川省科技计划资助项目“页岩气水平井大规模加砂压裂井筒固液两相流动模拟及冲蚀规律研究”,21JCQN0066。

摘　　要：针对元坝高酸性气田地面管道的内腐蚀问题,提出了一种考虑多因素的BP神经网络腐蚀预测模型。该模型以温度、CO_(2)分压、H2S分压、p H值、Cl-含量、总矿化度、液气比、缓蚀剂残余量8种影响因素的数据作为输入量,再将腐蚀速率作为输出量,通过现场实测获得大量历史样本数据,对BP神经网络进行训练,实现了地面管道的腐蚀速率预测,并利用该模型对元坝高酸性气田地面管道各腐蚀因素的重要程度进行评判。结果表明:随机抽取工况参数,模型预测值与实测值的平均绝对误差在10%以内,预测模型具有较高的准确性和可靠性;影响元坝高酸性气田地面管道腐蚀速率的主控因素为H2S分压,CO_(2)分压、缓蚀剂残余量次之。研究成果可为类似气田地面管道的内腐蚀评估提供技术借鉴。(图2,表3,参22)To study the internal corrosion of ground pipelines in Yuanba high-sour gasfield,a corrosion prediction model based on BP neural network was proposed with consideration to multiple factors.In the model,the input was 8 types of working condition data,i.e.,the temperature,CO_(2)partial pressure,H2S partial pressure,pH value,Cl-concentration,total salinity,liquid-to-gas ratio and the residue of corrosion inhibitor,while the output was the corrosion rate.Specifically,the BP neural network was trained with a large amount of historical sample data from field measurement to realize the prediction of the corrosion rate of ground pipelines.Besides,the model was used to evaluate the importance of various factors affecting the corrosion of ground pipelines in Yuanba high-sour gasfield.As shown in the results,the predicted model is highly accurate and reliable,as the average absolute error between the predicted value of the model and the measured value is within 10%for random working condition parameters.In addition,H2S partial pressure is the main control factor of the corrosion rate of ground pipelines in Yuanba high-sour gasfield,followed by CO_(2)partial pressure and corrosion inhibitor.Generally,the research results could provide technical reference for the internal corrosion assessment of ground pipelines in similar gas fields.(2 Figures,3 Tables,22 References)

关 键 词：高含硫气田 站内管道 腐蚀速率预测 BP神经网络 主控因素 

分 类 号：TE88[石油与天然气工程—油气储运工程]