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Early Kick Detection Using Adaptive Analytics with Downhole Accelerometer Data

机译:利用井下加速度计数据使用自适应分析进行早期踢球检测

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High frequency downhole vibration data includes more hidden information than low frequency surface data.This paper discusses monitoring high frequency acceleration data for early kick detection because the accelerator sensor values’trend is monitored rather than processed.When gas,fluid,or oil kick occurs,fluid influx reduces fluid viscosity in the annulus,causing degradation of the damping factor.The sensor installed on the drillpipe detects the velocity/acceleration modification,resulting in the damping factor modification and includes an analytical model to calculate the effect of the damping ratio on the acceleration calculations.Fluid influx and migration in the wellbore strongly affects the damping factor.This paper discusses a method of deconvoluting sensor values that use a combination of minimum entropy deconvolution and the Teager-Kaiser energy operator to remove the noise,unwanted sensor values,and the likelihood of false predictions.The trend of the final intrinsic mode functions(IMFs)at each depth is continuously monitored to predict formation influx,if any.A novel concept of monitoring incremental IMF and IMF energy at each depth is introduced,revealing a wealth of information and simplifying the process of monitoring and analyzing the vast amount of available data.The methodology developed extracts essential information from high frequency vibration data to make real-time data monitoring straightforward,reliable,and fast.
机译:高频井下振动数据包括除低频表面数据。本文讨论了由于加速传感器values'trend被监测而不是processed.When气体,流体,或油踢发生监视高频加速度数据进行早期检测踢更多隐藏信息,流体流入降低了流体的粘度在环形空间中,导致安装在钻杆阻尼factor.The传感器的劣化检测速度/加速度变形,从而导致衰减因子修改,并且包括一个分析模型来计算在阻尼比的效果加速度calculations.Fluid涌入和迁移在井筒强烈影响阻尼factor.This论述去卷积使用最小熵解卷积和Teager-凯瑟能量算子的组合来去除噪声,不想要的传感器值的传感器值的方法,和最终固有模式的乐趣假predictions.The趋势的可能性在每个深度ctions(IMF分量)被连续监测来预测形成涌入,如果引入在每个深度监控增量IMF和IMF的能量any.A新颖的概念,揭示了丰富的信息,并简化监测和分析的大量的处理可data.The方法编制的提取物对高频振动数据的重要信息进行实时数据监控简单,可靠和快速。

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