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Application of Online SVR on the Dynamic Liquid Level Soft Sensing

机译：在线SVR在动态液位柔和传感中的应用

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摘要

There exist different kinds of drawbacks and security risks in the measurement methods of dynamic liquid level in oilfield, consequently,each of them can't provide reliable protection to the oilfield for its high efficiency production operations and easily to cause significant economic losses .In order to solve the problems above, soft sensing technology is found as a new way to measure the dynamic liquid level of the oilfield instead of original hardware technology. ANN is a kind of soft sensing technology which is earlier to be used as the way to measure the dynamic liquid level,but there are some problems restricted its use of areas, such as easy to fall into local minimization, slow convergence speed and poor generalization ability.According to the oilfield data's characteristics,Online SVR algorithm is proposed to be a solution to measure the dynamic liquid level in this paper. As a kind of soft sensing technology,Online SVR not only has the same performance of ANN, but also can update the forcast model by online .In addition, it also solve the problems of ANN .Online SVR algorithm is verified by the experiment in this paper and.the result of this experiment shows that Online SVR has higher precision than ANN .The experimental results also show the Online SVR can be used in measuring the dynamic liquid level in oilfield.
机译：在油田的动态液位测量方法中存在不同类型的缺点和安全风险，因此，它们中的每一个都无法为油田提供可靠的保护，以实现其高效生产操作，并且很容易引起重大的经济损失。为了解决上述问题，发现软感应技术作为测量油田动态液位而不是原始硬件技术的新方法。 ANN是一种柔软的传感技术，早期用作测量动态液位的方法，但有一些问题限制了它的使用区域，如易于落入局部最小化，慢会聚速度和差的概率差能够。根据油田数据的特点，在线SVR算法被提出为测量本文测量动态液位的解决方案。作为一种柔和的传感技术，在线SVR不仅具有同样的ANN性能，而且可以通过在线更新城播模型。此外，它还解决了ANN .hine SVR算法的问题通过实验验证了这一点纸张和该实验结果表明，在线SVR具有比ANN更高的精度。实验结果还显示了在线SVR可用于测量油田的动态液位。

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