Scale prediction of water injection pipeline in Wangjiawan Dwastrict of Xingzichuan Oilfield
In order to facilitate the maintenance of oilfield surface water injection pipelines,it is necessary to make realistic predictions about the scaling inside the pipelines.In response to the serious scaling of water injection pipelines in Wangjiawan District and the frequent replacement of pipelines due to scaling,the water injection pipeline in this block was taken as the research object.Based on the ion concentration of the injected water along a certain joint station,scaling software was used to predict the scaling trend of the injected water,and which was validated through indoor static experiments.The effects of different temperatures,pH values,and pressures on the scaling type and the trend of scaling amount were analyzed.Based on the water injection flow and the heat loss process along the pipeline,a mathematical model for the variation of water temperature along the pipeline was established to predict the thickness of scaling along the pipeline.The results show that the theoretically predicted scaling amount increases by 106.75 mg/L when the temperature increases from 10 ℃ to 50 ℃.The amount of scaling increases by 166.7 mg/L when the pH value increases from 6 to 8.As the pipeline pressure increased from 0.5 MPa to 10.5 MPa,the amount of scaling decreased by 18.68 mg/L,indicating that pH value is the main factor affecting pipeline scaling,followed by temperature,and pressure has little effect on scaling.By comparing the predicted values of scaling software with experimental data,it was found that the two were basically consistent,with a relative error of 5％～10％.This indicates that the software can predict the trend and thickness of pipeline scaling and can more accurately simulate the scaling situation in the oil field.The mathematical model prediction of thermodynamic changes shows that the thickness of pipeline scaling increases with the increase of water injection time,and the scaling thickness reaches 20.8 mm after 3 years.The predicted results are consistent with the actual on-site conditions,indicating that the prediction model also meets the on-site requirements and has certain applicability.Accurate prediction of scaling trends is beneficial for slowing down pipeline scaling,improving water injection quality,and providing important guidance for the selection of effective cleaning and anti-scaling methods and processes in the future.
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