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注水开发集输管道腐蚀因素分析及预测模型建立
Corrosion factors and prediction model of water injection-associated gathering and transportation pipelines
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- DOI:
- 10.3969/j.issn.1001-2206.2026.01.013
- 作者:
- 孙晓光
SUN Xiaoguang
- 作者单位:
- 中国石油华北油田分公司第四采油厂, 河北廊坊 065000
The Fourth Oil Production Plant of Huabei Oilfield Branch, PetroChina, Langfang 065000, China
- 关键词:
- 注水; 集输管道; 腐蚀因素; 预测模型; 敏感区域
water injection;gathering and transportation pipelines;corrosion factors;prediction models;sensitive areas
- 摘要:
为降低注水开发油田集输管道的失效风险，将数值模拟与室内实验方法相结合，开展管道腐蚀因素分析。以某油田6条在役管道为研究对象，利用OLGA软件模拟沿线温度、压力及流型变化，依据相关标准识别出15处腐蚀敏感区，并针对敏感区工况参数开展室内失重实验及腐蚀产物表征分析，并建立腐蚀速率预测模型。结果表明：管道低洼段易形成段塞流和固相沉积，导致局部腐蚀加剧；压力对腐蚀速率的影响最大，其次为H2S分压、温度、Cl-质量浓度、HCO3-质量浓度、Ca2+质量浓度，Mg2+只有在质量浓度较高时才对腐蚀速率产生影响，CO2分压对腐蚀速率几乎无影响；腐蚀速率预测模型的相对误差为±5%，相关系数为0.936 4。研究结果对管道腐蚀防护有参考价值，预测模型可为高敏感管段防腐选材及维护提供理论依据。
To reduce the failure risk of water injection-associated gathering and transportation pipelines, this study combines numerical simulation and laboratory experimental methods. Six in-service pipelines in an oilfield were taken as the research objects. The OLGA software was used to simulate the changes of temperature, pressure, and flow pattern along the line. Combined with relevant standards, 15 corrosion-sensitive areas were identified. Laboratory weight loss experiments and characterization analysis of corrosion products were carried out under parameters of the working conditions in the sensitive areas, and a corrosion rate prediction model was established. The results show that the low-lying sections of the pipelines are prone to the formation of slug flow and solid phase deposition, leading to the intensification of local corrosion. Pressure has the greatest impact on the corrosion rate, followed by H2S partial pressure, temperature, Cl- concentration, HCO3- concentration, and Ca2+ concentration. Mg2+ only influences the corrosion rate at high concentrations, while CO2 partial pressure has almost no effect on the corrosion rate. The corrosion rate prediction model has a relative error of ±5% with a correlation coefficient of 0.936 4. The results are of reference value for pipeline corrosion prevention. The model can provide precise theoretical support for the selection of anti-corrosion materials and maintenance of highly sensitive pipe sections.