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Estimation of gas/liquid and oil/water interface levels in an oil/water/gas separator based on pressure measurements and regression modelling

机译:基于压力测量和回归模型估算油/水/气分离器中的气/液和油/水界面水平

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摘要

Gravity separators are widely used for separation of gas/oil/water/sand from both offshore and onshore oil production facilities. Estimation of the gas/liquid and oil/water interface levels in gravity separators have been a concern since these parameters are important for reliable operation. Most of the instruments on the market today do not provide reliable measurements of both gas/liquid and oil/water interface levels. The few instruments that do provide reliable measurements are however based on radioactive principles. Nevertheless these radioactive instruments possess a strong health, safety and environmental risk. An alternative inexpensive, environmentally friendly, accurate and cost effective way for gas/liquid and oil/water interface level estimation based on pressure measurement is presented. The root mean squared error of prediction (RMSEP) for gas/liquid and oil/water interface level estimation from traversing a pressure sensor based on partial least square regression (PLS-R) were 14.5 mm and 17.7 mm respectively. A comparison of results from models based on PLS-R and ordinary least square regression (OLS-R) techniques proved that the RMSEP from the PLS-R technique was better in estimating the oil/water interface level but in the case of gas/liquid interface level estimation the OLS-R technique was slightly better. It was concluded that the PLS-R technique provided a better overall result and is recommended when pressure measurements in combination with multivariate data analysis is applied for gas/liquid and oil/water interface level estimations in gravity separators.
机译:重力分离器广泛用于从海上和陆上石油生产设施中分离天然气/油/水/砂。重力分离器中的气/液和油/水界面水平的估计一直是一个令人关注的问题,因为这些参数对于可靠的操作很重要。当今市场上的大多数仪器都无法提供对气/液和油/水界面水平的可靠测量。但是,少数提供可靠测量的仪器是基于放射性原理的。然而,这些放射性仪器具有很强的健康,安全和环境风险。提出了一种基于压力测量的气/液和油/水界面液位估算的廉价,环保,准确和成本有效的替代方法。通过基于偏最小二乘回归(PLS-R)遍历压力传感器进行气/液和油/水界面水平估计的预测均方根误差(RMSEP)分别为14.5 mm和17.7 mm。将基于PLS-R和普通最小二乘回归(OLS-R)技术的模型的结果进行比较,结果表明,使用PLS-R技术的RMSEP在估计油/水界面水平时更好,但在气/液情况下接口级别的估计OLS-R技术要好一些。结论是,PLS-R技术可提供更好的总体结果,当压力测量与多元数据分析相结合用于重力分离器中的气/液和油/水界面水平估算时,建议使用PLS-R技术。

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