基于含砂液流振动信号特征分析的出砂监测实验研究

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振动与冲击 ›› 2019, Vol. 38 ›› Issue (14) : 112-117.

论文

王锴，刘刚，李祎宸，王刚，冯凯

作者信息 +

Experimental research on sand production monitoring based on the vibration signal features analysis of sand-carrying flow

WANG Kai，LIU Gang，LI Yichen，WANG Gang，FENG Kai

Author information +

文章历史 +

摘要

针对高含水期油田出砂监测问题，本文提出一种利用安装在管线上的振动传感器，结合信号采集系统，通过分析含砂液流冲击管线产生的振动信号时-频特征，实时监测出砂量变化的方法。本文以水-砂两相流振动信号特征为研究对象，设计室内出砂监测实验，基于STFT时-频分析方法，研究携砂流的速度、砂粒粒径大小、含砂量与出砂振动信号时-频特征关系。通过设计出砂信号校准方法，进一步建立了出砂量监测数学模型。结果表明基于携砂流振动信号时-频分析的振动监测方法可以有效检测砂粒信息，水-砂两相流中，砂粒激发的特征频段为10.5-12.5KHz, 含砂量监测模型的误差在14%以内，该方法为更复杂的多相流出砂监测研究奠定了基础，为油井安全生产提供了技术保障。

Abstract

Aiming at the sand production monitoring during the high water-cut oil field production period, a method with the help of vibration sensors installed on the pipeline and a signal acquisition system was proposed to monitor the change of sand content.In the method, the time-frequency characteristics of vibration signals caused by the sand-carrying flow impacting on the pipeline were analysed.By this indoor experiment, the relationships between sand-carrying flow, sand size, sand content and sand production signals were investigated using the STFT time-frequency method.Furthermore, a sand calibration method was presented and the corresponding sand production monitoring model was established.The results show that the vibration method can effectively detect the sand content in the sand characteristic band of 10.5—12.5 kHz, and the error is within 14%.The method lays a foundation for the sand production monitoring in more complex multiphase flow to ensure the safety of oil production.
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导出引用

王锴，刘刚，李祎宸，王刚，冯凯. 基于含砂液流振动信号特征分析的出砂监测实验研究[J]. 振动与冲击, 2019, 38(14): 112-117

WANG Kai，LIU Gang，LI Yichen，WANG Gang，FENG Kai. Experimental research on sand production monitoring based on the vibration signal features analysis of sand-carrying flow[J]. Journal of Vibration and Shock, 2019, 38(14): 112-117

参考文献

［1］ RANJITHA P G, PERERAA M S A, PERERAA W K G, et al. Sand production during the extrusion of hydrocarbons from geological formations: A review[J]. Journal of Petroleum Science & Engineering, 2014, 124:72-82.
［2］ WANG Z Z, TIAN H, DENG J G, et al. Improving well productivity through sand management[J]. Oil Drilling & Production Technology, 2006, 28:59–63.
［3］ BIANCO L C B, HALLECK P M. Mechanisms of Arch Instability and Sand Production in Two-Phase Saturated Poorly Consolidated Sandstones[C]. SPE European Formation Damage (2001) Conference, The Hague, Netherlands.
［4］ GAO G W, DANG R R, NOURI A, et al. Sand rate model and data processing method for non-intrusive ultrasonic sand monitoring in flow pipeline[J]. Journal of Petroleum Science & Engineering, 2015, 134:30-39.
［5］ PERERA M S A, RANJITH P G, RATHNAWEERA T D, et al. An experimental study to quantify sand production during oil recovery from unconsolidated quicksand formations. Petroleum Exploration and Development, 2017, 44(5): 811-816.
［6］ ZHAI L S, JIN N D, GAO Z K, et al. The ultrasonic measurement of high water volume fraction in dispersed oil-in-water flows[J]. Chemical Engineering Science, 2013, 94(5):271-283.
［7］ ADEKOMAYA O A. Modelling of solid flow effect on pressure drop in a vertical gas well[J]. Petroleum Exploration and Development, 2012, 39(2):245-249.
［8］ GUO M, YAN Y, HU Y, et al. On-line measurement of the size distribution of particles in a gas–solid two-phase flow through acoustic sensing and advanced signal analysis[J]. Flow Measurement & Instrumentation, 2014, 40:169-177.
［9］ Lelu He, Yefeng Zhou, Zhengliang Huang, et al. Acoustic analysis of particle-wall interaction and detection of particle mass flow rate in vertical pneumatic conveying. Industrial & Engineering Chemistry Research, 2014, 53(23):9938-9948.
［10］ XU C, WANG S, TANG G, et al. Sensing characteristics of electrostatic inductive sensor for flow parameters measurement of pneumatically conveyed particles[J]. Journal of Electrostatics, 2007, 65(9):582-592.
［11］ HII N C, TAN C K, WILCOX S J, et al. An investigation of the generation of Acoustic Emission from the flow of particulate solids in pipelines[J]. Powder Technology, 2013, 243(1):120-129.
［12］ EL-ALEJ M, MBA D, YAN T H, et al. Investigation on Sand Particle Impingement on Steel Pipe in Two Phase Flow Using Acoustic Emission Technology[J]. Applied Mechanics & Materials, 2013, 315:540-544.
［13］ Ong.F, Uecker. M, Tariq.U. Robust 4D Flow Denoising Using Divergence-Free Wavelet Transform,MAGNETIC RESONANCE IN MEDICINE, 2015,73(2): 828-842.
［14］ Aghdam. B. H, Vahdati. M, Sadeghi, et al. Vibration-based estimation of tool major flank wear in a turning process using ARMA models, International Journal of Advanced Manufacturing Technology, 2015,76: 1631-1642.
［15］ Liu, W. Y. Auto term window method and its parameter selection, Measurement, 2013, 9(46):3113-3118.
［16］ WANG K, LIU Z G, JIE W, et al. Acoustic sensor approaches for sand detection in sand–water two-phase flows [J]. Powder Technology, 2017, 320:739-747.
［17］ HE Q B, Wang J, Hu F, et al. Wayside acoustic diagnosis of defective train bearings based on signal resampling and information enhancement[J]. Journal of Sound & Vibration ,2013, 332(21): 5635-5649.
［18］ Wang K, Liu Z, Liu G, et al. Vibration sensor approaches for sand detection in oil–water–sand multiphase flow[J]. Powder Technology, 2015, 276:183-192.
［19］崔明根，吴勃英，王德明，等. 数值分析原理[M]. 北京：科学出版社，2003.
CUI Minggen, WU Boying, WANG Deming, et al. Principle of numerical analysis[M]. BeiJing: Sciences Press, 2003