首页> 外文期刊>Journal of signal processing systems for signal, image, and video technology >Cloud Computation Processing for Oilfield Block Data and Chain Drive Pumping Unit Polished Rod Motion Model
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Cloud Computation Processing for Oilfield Block Data and Chain Drive Pumping Unit Polished Rod Motion Model

机译:油田区块数据云计算处理与链传动抽油机抛光杆运动模型

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摘要

The oil wells are of similar physical parameters but different production parameters in an oilfield block, but selecting the equipment for every well one by one is unpractical. The measured polished rod load data was taken into account in the Fuzzy Clustering C Means algorithm to work out the typical production data, such as polished rod load on the basis of the cloud computing processing for the vast measured polished rod load data in the test wells in a block. The dynamical equation of the chain pumping unit being constructed, the load data are used to simulate the motion of the pumping unit by means of the numerical iteration algorithm. It is shown that the max acceleration does not occur at the up and down dead points in the stroke but at the position about 5-11 (ay) from the dead points. The combination of the typical production data resulting from the cloud computing processing and the numerical iteration algorithm can solve the practical problem of equipment selection and simulation.
机译:油井具有相似的物理参数,但在一个油田区中的生产参数却不同,但是为每一口井一一选择设备是不切实际的。在模糊聚类C均值算法中考虑了测得的抛光棒载荷数据,以计算出典型的生产数据,例如基于云计算处理的测试井中大量测得的抛光棒载荷数据的抛光棒载荷。在一个街区。构造链式抽油机的动力学方程,通过数值迭代算法,使用载荷数据模拟抽油机的运动。结果表明,最大加速度不在行程的上下死点处发生,而是在距死点约5-11(ay)的位置发生。云计算处理产生的典型生产数据与数值迭代算法的结合,可以解决设备选型和仿真的实际问题。

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