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基于复阻抗法的水平井流体持率测量初步研究OA

Preliminary Study on Measurement of Fluid Holdup in Horizontal Wells Based on the Complex Impedance Method

中文摘要英文摘要

为了克服电学法在水平井流体持率测量中存在的测量参数单一、测量装置结构复杂等局限性,提出了一种基于复阻抗法的新型水平井流体持率测量方法,并对其可行性进行了系统研究.采用复阻抗频谱法作为测量原理,以 2N序列伪随机信号作为多频同步激励源,通过理论分析与数值仿真相结合的方式,深入探讨了复阻抗法持率测量的理论基础.利用 COMSOL 有限元仿真软件开展了正演研究,获取了不同持率条件下油水两相流分层流的复阻抗频谱响应特征;从频谱数据中提取了复阻抗实部比值与虚部斜率比值作为反映持水率的关键无量纲特征参数.引入径向基函数(Radial Basis Function,RBF)神经网络建立了特征参数与持水率之间的非线性反演拟合模型;初步设计了基于复阻抗法的流体持率测量系统,并开展了油水两相流分层流室内模拟实验,以验证该方法的实际测量可行性.研究结果表明:①油水两相流的复阻抗频谱能够有效反映其持率信息,提取的实部比值与虚部斜率比值特征参数与持水率之间存在显著的非线性映射关系,能够有效消除不同矿化度水相对测量结果的影响;②相较于多项式拟合方法,RBF 神经网络在持水率反演中展现出更优异的非线性逼近能力,其误差平方和降低了 93.7%,决定系数达到 0.999 9,均方根误差仅为 0.113 2,预测精度大幅提升;③室内模拟实验条件下,所设计的测量系统对不同持水率油水两相流的识别结果与实际持水率基本吻合,分层流油水识别平均符合率大于 90%,最大相对误差为 12%.结论认为,基于复阻抗法的水平井流体持率测量方法在理论上可行,初步设计基于复阻抗法的测量系统能够有效识别流体中的持水率,验证了复阻抗法在水平井持率测量领域的实际应用潜力,为后续进一步发展多流型、复杂工况下的复阻抗持率测量技术奠定了理论基础.

To overcome the limitations of the current electrical method in measuring the fluid holdup in horizontal wells,such as the single measurement parameter and the complex structure of the measurement device,a new method for measuring the fluid holdup in horizontal wells based on the complex impedance method is proposed,and its feasibility is systematically studied.The complex impedance spectrum method is adopted as the measurement principle,and a 2N sequence pseudo-random signal is used as the multi-frequency synchronous excitation source.Through a combination of theoretical analysis and numerical simulation,the theoretical basis of the complex impedance method for holdup measurement is deeply explored.The COMSOL finite element simulation software is used to conduct forward research and obtain the complex impedance spectrum response characteristics of oil-water two-phase flow stratified flow under different holdup conditions.The real part ratio and the imaginary part slope ratio of the complex impedance are extracted from the spectrum data as key dimensionless characteristic parameters reflecting the water holdup.The radial basis function(RBF)neural network is introduced to establish a nonlinear inversion fitting model between the characteristic parameters and the water holdup.A preliminary design of the fluid holdup measurement system based on the complex impedance method is carried out,and indoor simulation experiments of oil-water two-phase flow stratified flow are conducted to verify the actual measurement feasibility of this method.The research results show that:①The complex impedance spectrum of oil-water two-phase flow can effectively reflect its holdup information,and the extracted real part ratio and imaginary part slope ratio characteristic parameters have a significant nonlinear mapping relationship with the water holdup,which can effectively eliminate the influence of different salinity water on the measurement results.②Compared with the polynomial fitting method,the RBF neural network shows better nonlinear approximation ability in the inversion of water holdup,with the sum of squared errors reduced by 93.7%,the coefficient of determination R2 reaching 0.999 9,and the root mean square error being only 0.113 2,significantly improving the prediction accuracy.③Under the indoor simulation experiment conditions,the recognition results of the designed measurement system for oil-water two-phase flow with different water holdups are basically consistent with the actual water holdup,and the average coincidence rate of oil-water identification in stratified flow is greater than 90%,with the maximum relative error being 12%.The conclusion is that the complex impedance method for measuring the fluid holdup in horizontal wells is feasible in theory.The preliminary designed measurement system based on the complex impedance method can effectively identify the water holdup in the fluid,verifying the practical application potential of the complex impedance method in the field of holdup measurement in horizontal wells,and laying a theoretical foundation for the subsequent development of complex impedance holdup measurement technology under multi-flow patterns and complex working conditions.

彭川;方铎平;齐真真;李志华;李健伟;杜娟;于鹏

中石化经纬有限公司华北测控公司,河南 郑州 450000||中国地质大学(武汉)资源学院,湖北 武汉 430074中国地质大学(武汉)人工智能与自动化学院,湖北 武汉 430074中石化经纬有限公司华北测控公司,河南 郑州 450000中国地质大学(武汉)人工智能与自动化学院,湖北 武汉 430074中石化经纬有限公司华北测控公司,河南 郑州 450000中石化经纬有限公司华北测控公司,河南 郑州 450000中石化经纬有限公司华北测控公司,河南 郑州 450000

天文与地球科学

复阻抗法持率测量油水两相流分层流径向基函数神经网络模拟实验水平井非线性反演

complex impedance methodholdup measurementoil-water two-phase flowstratified flowradial basis function neural networksimulation experimenthorizontal wellnonlinear inversion

《测井技术》 2026 (3)

439-450,12

湖北省重点研发计划项目"基于人工智能和数字孪生的井下作业实时可视化跟踪和智能控制"(2023BAB099)

10.16489/j.issn.1004-1338.2026.03.006

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