基于数据融合技术的水下油气井计量方法研究
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摘要
虚拟流量计系统具有成本低、精度高等优点,逐渐成为水下油气井生产计量的一种新方式,其核心是依托多相流模拟技术的油气井流量算法。为了提高虚拟流量计系统在线应用时的可靠性和精度,基于数据融合技术和多个物理流量模型,设计了分别基于D-S证据理论、不确定度理论和神经网络理论的3种融合流量估计方法。现场生产数据测试结果表明,数据融合流量估计方法的平均误差维持在5%以内,且当单个物理流量模型失效时,融合技术仍能给出最优的计量结果,保证了整个虚拟流量计系统的可靠性。
Virtual flowmeter system based on oil and gas well flow algorithm of the multi-phase flow simulation technology,has become a new measurement method for underwater oil and gas well production by its low costs and high precision. In order to improve the reliability and accuracy of this online system,three methods of fusion flow evaluation based on the theory of D-S evidence,uncertainty and neutral network were designed from the data fusion technology and multiple physical flow models. The verification results of field production data show that the average error of fusion flow estimation methods could be kept within 5% and the fusion flow estimation method can provide the optimal measurement results even at single physical flow model failure.
Virtual flowmeter system based on oil and gas well flow algorithm of the multi-phase flow simulation technology,has become a new measurement method for underwater oil and gas well production by its low costs and high precision. In order to improve the reliability and accuracy of this online system,three methods of fusion flow evaluation based on the theory of D-S evidence,uncertainty and neutral network were designed from the data fusion technology and multiple physical flow models. The verification results of field production data show that the average error of fusion flow estimation methods could be kept within 5% and the fusion flow estimation method can provide the optimal measurement results even at single physical flow model failure.
引文
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[3] 王珏,李清平,王凯,等.水下油气田虚拟计量技术应用[J].舰船科学技术,2013,35(9):118-122.WANG J,LI Q P,WANG K,et al.Virtual metering technology for subsea fields[J].Ship science and technology,2013,35(9):118-122.
[4] 刘卫萍,王宁,周晓磊.数据融合技术在环境监测领域的应用[J].计算机系统应用,2016,25(6):88-93.LIU W P,WANG N,ZHOU X L,et al.Application of data fusion to environment monitoring[J].Computer systems and applications,2016,25(6):88-93.
[5] 高琪.无线传感器网络中数据融合技术研究[D].兰州:西北师范大学,2015.GAO Q.Research of data aggregation in wireless sensor networks[D].Lanzhou:Northwest Normal University,2015.
[6] 刘兴斌,卢静,王延军,等.多传感器数据融合技术在多相流领域研究进展[J].石油管材与仪器,2016(1):6-9.LIU X B,LU J,WANG Y J,et al.Research progress of multi-sensor data fusion technology in multi-phase flow[J].Petroleum tubular goods & instruments,2016(1):6-9.
[7] 莫荣强,艾萍,吴礼福,等.一种支持大数据的水利数据中心基础框架[J].水利信息化,2013(3):16-20.MO R Q,AI P,WU L F,et al.A fundamental frame of water resources data center supporting big data[J].Water resources informatization,2013(3):16-20.
[8] 王智,宫敬,尹铁男,等.天然气凝析液长距离管道稳态水力热力计算[J].东北石油大学学报,2013,37(4):60-66.WANG Z,GONG J,YIN T N,et al.Steady-state hydraulic thermal dynamic calculation algorithm in long gas-condensate pipeline[J].Journal of northeast petroleum university,2013,37(4):60-66.
[9] 王智.深海天然气集输系统在线模拟方法研究[D].北京:中国石油大学(北京),2015.WANG Z.Online simulation study for subsea oil-gas gathering and transportation system[D].Beijing:China University of Petroleum(Beijing),2015.
[10] Schüller R B,Munaweera S,Selmer-Olsen S,et al.Critical and subcritical oil/gas/water mass flow rate experiments and predictions for chokes[J].Spe production & operations,2003(21):372-380.
[11] 王艳芝,吴海浩,宫敬.基于D-S理论的多模型凝析气井流量算法研究[J].北京石油化工学院学报,2016,24(2):31-36.WANG Y Z,WU H H,GONG J.Research on flow algorithm of multi-model condensate gas wells based on D-S theory[J].Journal of Beijing institute of petro-chemical technology,2016,24(2):31-36.
[12] 毛开翼.关于组合预测中的权重确定及应用[D].成都:成都理工大学,2007.MAO K Y.Combination forecast in weight determination and application[D].Chengdu:Chengdu University of Technology,2007.
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[14] 康健.基于多传感器信息融合关键技术的研究[D]:哈尔滨:哈尔滨工程大学,2013.KANG J.The key technology research of multi-sensors information fusion[D].Harbin:Harbin Engineering University,2013.
[15] 刘英爽.基于神经网络的多模型融合金融时间序列分析方法[D].哈尔滨:哈尔滨工业大学,2011.LIU Y S.Neutral network based multi-model fusion method for financial time series analysis[D].Harbin:Harbin Institute of Technology,2011.