CN109188016B - Acoustic-electric bimodal measurement method for phase-splitting flow velocity of oil-gas-water three-phase flow - Google Patents
Acoustic-electric bimodal measurement method for phase-splitting flow velocity of oil-gas-water three-phase flow Download PDFInfo
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Abstract
本发明涉及一种油气水三相流分相流速声电双模态测量方法，包含如下步骤：针对油气水三相水基‑分散流，利用电学传感器采集水相含率信号，利用连续波超声传感器采集多普勒频移信号；根据去噪后的电学传感器的水相含率测量数据，结合特征提取与分类算法实现油气水三相流流型的识别；提取水相含率信号的局部波动特性；利用集合经验模态分解，对连续波超声多普勒频移信号进行分解并选取主分量；采用超声电学联合分析的方法，获得不同流型下水相含率和多普勒频移信号中不同波动尺度的之间的对应关系；对不同流型下、反映分相流速信息的相应本征模态函数进行快速傅里叶变换并计算平均多普勒频移，根据多普勒效应的基本原理，计算分相流速。
The invention relates to a method for measuring the split-phase flow velocity of oil, gas and water three-phase flow, which comprises the following steps: for the three-phase water-based-dispersed flow of oil, gas and water, an electrical sensor is used to collect a water phase holdup signal, and a continuous wave ultrasonic The sensor collects the Doppler frequency shift signal; according to the water phase holdup measurement data of the de-noised electrical sensor, combined with feature extraction and classification algorithms to realize the identification of the three-phase flow pattern of oil, gas and water; extract the local fluctuation of the water phase holdup signal characteristics; using ensemble empirical mode decomposition to decompose the continuous wave ultrasonic Doppler frequency shift signal and select the principal component; using the method of ultrasonic-electrical joint analysis to obtain the water phase holdup and Doppler frequency shift signal under different flow patterns Correspondence between different fluctuation scales; fast Fourier transform is performed on the corresponding eigenmode functions reflecting the information of the split-phase flow velocity under different flow patterns, and the average Doppler frequency shift is calculated. According to the basic Doppler effect The principle is to calculate the split-phase flow rate.
Description
Technical Field
The invention belongs to the technical field of fluid measurement, and relates to a combined measurement method of an ultrasonic sensor and an electrical sensor, which is used for non-disturbance measurement of three-phase flow split-phase flow velocity.
Technical Field
The oil-gas-water three-phase flow is three-component flow in the gas/liquid three-phase flow, and is widely used in the petroleum exploitation and transportation process. In recent years, oil fields enter a high water-cut period, and oil-gas-water three-phase flow mostly takes water as a continuous phase, oil drops and air bubbles as discrete phases to flow together with the continuous phase. The measurement of the flow parameters becomes a hot problem for the research in the field of multiphase flow, and especially the measurement of the phase content and the flow rate has important significance for the accurate estimation of the yield and the guarantee of the production safety. However, compared with single-phase flow, the complex interaction and relative motion characteristics between three phases cause the flow structure to be very complex, the flow pattern to be complex and variable, and great challenges are brought to accurate acquisition of flow parameters.
There are various methods for measuring process parameters of multiphase flow. In the traditional measuring mode, a single-phase instrument is mostly adopted to directly obtain process parameters, and the physical significance is clear. Typical examples are turbine flow meters, differential pressure flow meters, vortex shedding flow meters and the like, but most of the methods belong to invasive measurement, and disturbance is generated to the flow process while flow parameters are obtained, so that the flow structure is influenced, and the measurement accuracy is reduced. Therefore, in scientific research and industrial production processes, the method has important significance for accurately obtaining multiphase flow process parameters by adopting a non-invasive method. Some emerging measurement modes, such as an electrical method, an ultrasonic method, a microwave method, a laser method and the like, are gradually applied to multiphase flow measurement. Among them, the electrical method and the ultrasonic method are of great interest because of their non-invasive, simple sensor structure, easy installation and low cost.
The method for measuring the electric phase content is divided into methods such as an annular conductance array, a conductance probe, electric process tomography and the like according to the difference of the structure, the shape and the excitation mode of the sensor. The conductivity method is based on a ring-shaped electrical impedance measuring sensor, is a common phase content measuring method, and has the advantages of no disturbance, no radiation, quick response and the like. It requires that the object to be measured is a mixture with a conductive medium as a continuous phase. The method establishes an electrical sensitive field by applying constant excitation voltage on an excitation electrode pair, when the phase content of the measured fluid changes, the impedance characteristic of the sensitive field changes, the measurement of the phase content of the measured fluid is realized by acquiring the potential difference on a measurement electrode pair, and the method has wide application in multiphase flow measurement.
The ultrasonic flow velocity measurement method measures the flow velocity of the fluid by reflecting, refracting, scattering and other phenomena when the ultrasonic wave is transmitted in the fluid, and has the advantages of no disturbance, simple sensor structure, low cost and the like. According to different measurement principles, the method is mainly classified into a correlation method, a time difference method, a doppler method and the like. The time difference method utilizes the relation between the propagation speed of ultrasonic waves in fluid and the flowing speed of the fluid to realize flow measurement, and is mostly used for the condition that the discrete phase content is high. The correlation method utilizes the transit time of a fluid noise signal when the fluid noise signal passes from one sensor to another sensor to obtain the flow, is based on a cross-correlation algorithm, is suitable for various fluids, but the physical and practical significance of cross-correlation flow rate is not clear so far. The Doppler method utilizes the Doppler effect of ultrasound to realize the measurement of the flow velocity of the discrete phase, and has clear physical significance. Ultrasonic waves are emitted into the fluid by the ultrasonic transducer, and are received by the ultrasonic transducer after being reflected or scattered by moving discrete phases (liquid drops or air bubbles) in the multiphase fluid. According to the doppler effect, the frequency difference between the incident sound wave and the received sound wave is proportional to the average flow velocity of the discrete phase scattering particles in the measurement region. When the ultrasonic Doppler is used for measuring the flow velocity, the ultrasonic Doppler method mainly comprises a pulse wave ultrasonic Doppler method and a continuous wave ultrasonic Doppler method. The pulse wave ultrasonic Doppler method intermittently transmits ultrasonic waves into fluid in a pulse mode, receives an acoustic signal in each pulse interval time, has the range gating capacity, and can obtain the position information of a scatterer while obtaining the flow velocity. But its furthest measurement distance and maximum measurable flow rate are limited due to the limitation of the nyquist sampling frequency. The continuous wave Doppler technology continuously transmits and receives ultrasonic waves, generally has a fixed measuring area, can obtain the average flow velocity of scattering particles in the measuring area, and has the advantages of generally simpler structure, lower cost and no limitation of the maximum measurable flow velocity. When the continuous wave ultrasonic Doppler technology is used for measuring the flow velocity of oil-gas-water three-phase flow, discrete phases of the continuous wave ultrasonic Doppler technology comprise liquid drops and air bubbles, and the reflection and scattering effects can be generated on the ultrasonic waves in the flowing process. And because the slip between the gas and liquid phases is not negligible, the doppler shift caused by droplets and bubbles is different. The doppler shift signal is thus a superposition of the ultrasonic doppler effect by scatterers with different flow velocities at different locations, and is a complex signal containing fluctuations of multiple frequency scales, some of which reflect the flow velocity information of different phases. Therefore, the electric sensor and the continuous wave ultrasonic Doppler sensor are combined for use to obtain the water phase content and flow velocity information of the oil-gas-water three-phase flow. The acquisition of the oil-gas-water three-phase flow split-phase flow velocity is realized through the establishment of a time-frequency analysis method and a model.
Disclosure of Invention
The invention aims to provide an accurate and undisturbed oil-gas-water three-phase flow split-phase flow velocity extraction method by utilizing multi-sensor information. The sensor and the measuring method of the invention combine the ultrasonic Doppler sensor and the electric sensor and are respectively used for acquiring the flow velocity and the water phase content information of the oil-gas-water three-phase flow. Processing multi-source information by using a signal processing technology: the characteristics of the water phase content data are extracted, the flow characteristic analysis of oil-gas-water three-phase flow and the correct identification of the flow pattern can be realized by combining a classification algorithm, the ultrasonic Doppler measurement data are subjected to collective empirical mode decomposition on the basis, and the undisturbed accurate acquisition of the phase-splitting flow velocity of the oil-gas-water under different flow patterns can be realized by adopting a sound-electricity combined analysis method. The technical scheme of the invention is as follows:
an acoustoelectric bimodal measurement method for split-phase flow velocity of oil-gas-water three-phase flow adopts a bicrystal ultrasonic transducer and an electrical sensor; the bicrystal ultrasonic transducer is used for acquiring an ultrasonic Doppler frequency shift signal, adopts a structure of transmitting and receiving an integral body at the same side, comprises a receiving piezoelectric ceramic wafer and a transmitting piezoelectric ceramic wafer inside, and is respectively used for receiving and transmitting ultrasonic waves; the electrical sensor is used for acquiring a water phase content signal and is arranged in the horizontal pipeline together with the ultrasonic transducer; the measuring method comprises the following steps:
1) aiming at oil-gas-water three-phase water-based-dispersed flow, an electrical sensor is utilized to acquire a water phase content signal H (T), T belongs to (0, T), and a continuous wave ultrasonic sensor is utilized to acquire a Doppler frequency shift signal fd(T), T belongs to (0, T), wherein T is sampling time, and high-frequency noise in the two signals is removed;
2) according to the denoised water phase content measurement data of the electrical sensor, recognition of an oil-gas-water three-phase flow pattern is realized by combining a feature extraction and classification algorithm;
3) extracting local fluctuation characteristics of the aqueous phase content signal: continuous wavelet transform is carried out on water phase content signals under different flow patterns to obtain continuous wave wavelet transform coefficients at a given scale a and a given moment b
And calculating local wavelet energy coefficients
Wherein psi (t) is a mother wavelet function, Daubechies4 wavelet is adopted, and the total scale is 500; drawing a local wavelet energy coefficient spectrogram on a time-scale axis to obtain the local fluctuation characteristic of the water phase content signal;
4) decomposing the continuous wave ultrasonic Doppler frequency shift signal by using ensemble empirical mode decomposition and selecting a principal component: using a method of ensemble empirical mode decomposition to convert the ultrasonic Doppler signal f into an ultrasonic Doppler signald(T), the T epsilon (0, T) is decomposed into a plurality of intrinsic mode functions IMF step by stepj(t) (j ═ 1, 2.. times, n) and a trend function rnSum of (t):
wherein n is the number of the intrinsic mode functions obtained by decomposition, and the first 3-level intrinsic mode functions IMF are selectedi(t) (i ═ 1,2,3) as the principal component of the flow rate extraction;
5) obtaining the corresponding relation between the water phase content and different fluctuation scales in Doppler frequency shift signals in different flow patterns by adopting an ultrasonic-electric combined analysis method according to the decomposition results in the steps 3) and 4), selecting different components from the main components obtained in the step 4) for extracting the split-phase flow velocity, and performing large scale, namely scale in a local wavelet energy coefficient spectrogram of the water-based-dispersed-bubble-like flow and the water-based-dispersed-elastic-like flow and the water phase content signals>50, the fluctuation component of which has a corresponding relation and is a first-stage intrinsic mode function IMF obtained by decomposing a Doppler frequency shift signal1(t), which is a high frequency component and has a discontinuity in time, reflecting the velocity of discrete-phase bubbles intermittently present during flowDegree information; and the small scale (scale) in the local wavelet energy coefficient spectrogram of the water phase occupancy signal<50) The fluctuation components have corresponding relations and are second-stage and third-stage intrinsic mode functions IMF obtained by Doppler frequency shift signal decomposition2(t)&IMF3(t), which are low frequency components and continuous in time, reflecting the velocity information of the completely dispersed oil droplets during the flow; for water-based-dispersed-plug flow, large scale, namely scale, in local wavelet energy coefficient spectrogram of water phase occupancy signal>50, the fluctuation components of which have corresponding relations and are first-stage and second-stage intrinsic mode functions IMF obtained by Doppler frequency shift signal decomposition1(t)&IMF2(t) which are high frequency components and have a discontinuity in time reflecting information on the velocity of discrete phase gas plugs intermittently present in the flow process; and the small scale, namely the scale, in the local wavelet energy coefficient spectrogram of the water phase occupancy signal<50, the fluctuation component of the Doppler frequency shift signal is in corresponding relation with a third-level intrinsic mode function IMF obtained by decomposing the Doppler frequency shift signal3(t), which is a low frequency component and continuous in time, reflects the velocity information of the fully dispersed oil droplets during flow.
6) Carrying out fast Fourier transform on corresponding intrinsic mode functions reflecting split-phase flow velocity information under different flow patterns, calculating average Doppler frequency shift, and calculating split-phase flow velocity according to the basic principle of Doppler effect: for water-based-dispersed-bubbly and water-based-dispersed-elastotic flows, the average true flow rates of the gas phase are:
the average true flow rate of the droplets is
For water-based-dispersed-plug flow, the mean true flow rate of the gas phase is
The average true flow rate of the droplets is:
wherein f is0Is the excitation frequency of the ultrasonic transmitting probe, theta is the included angle between the ultrasonic beam direction and the horizontal direction, c is the sound velocity in the fluid,
for the average Doppler shift obtained by fast Fourier transform of different eigenmode functions, Sd*(fd*) To correspond to a frequency shift fd*Is the corresponding main component reflecting the information of the phase-separated flow velocity under different flow patterns determined in the step 5).
The invention has the substantive characteristics that: in the oil-gas-water three-phase water-based-dispersed flow, the dispersed phase comprises oil drops and bubbles, and different flow patterns can be formed according to the relation between different gas liquids. Under different flow patterns, different discrete phases have different distribution and size differences in the flowing process, so that different fluctuation forms of water content can be caused. The phase content information detection technology based on the electrical sensitivity principle can accurately acquire the fluctuation sequence of the water phase content when the phase content distribution of the fluid to be detected changes. Based on the ultrasonic Doppler effect, when a continuous wave ultrasonic signal propagates in an oil-gas-water three-phase flow, reflection and scattering phenomena occur on the surfaces of oil drops and bubbles, and the slip between a gas phase and a liquid phase is not negligible, so that the oil drops and the bubbles can cause different Doppler frequency shifts. A doppler shifted signal is therefore a complex signal containing fluctuations in multiple frequency scales, where fluctuations in some frequency scales reflect flow velocity information in different phases. Therefore, the combination of an electrical phase content measuring sensor and a continuous wave ultrasonic Doppler sensor is used for measuring the three-phase water-based-dispersed flow of oil, gas and water: acquiring a fluctuation time sequence of the water phase content by using an electrical sensor, acquiring a local wavelet energy coefficient spectrogram by using a continuous wavelet transform technology, acquiring local fluctuation characteristics of a water phase content signal, and identifying a three-phase flow pattern by combining a characteristic extraction and classification identification algorithm; acquiring a Doppler frequency shift signal by using a continuous wave ultrasonic Doppler sensor, and decomposing the signal based on ensemble empirical mode decomposition to obtain a main component capable of reflecting split-phase flow velocity; the electric signals and the ultrasonic signals are subjected to combined analysis, components capable of reflecting different discrete phase flow information in the main components are determined under different flow patterns, the average Doppler frequency shift of the corresponding components is calculated through fast Fourier transform of the main components, and finally the acquisition of the split-phase flow velocity is achieved. The invention has the following beneficial effects and advantages:
1. the method is a non-disturbance type measuring means, and does not generate any disturbance to the fluid;
2. the method adopts an electrical and ultrasonic bimodal measurement mode, and can obtain more comprehensive description on the flow process;
3. the method adopts ultrasonic-electric combined analysis, can accurately extract the split-phase flow velocity of the oil-gas-water three-phase flow from the continuous wave ultrasonic Doppler frequency shift signal, and is simple and easy to implement;
4. the method has the advantages of convenient measurement, high speed and low cost.
Drawings
The following drawings depict selected embodiments of the present invention, all by way of example and not by way of exhaustive or limiting example, and are presented in the figures of the accompanying drawings:
FIG. 1 is a schematic structural diagram of an ultrasonic and electrical bimodal measurement system in the measurement method of the present invention;
FIG. 2 is a schematic diagram of an ultrasonic Doppler sensor in the measurement method of the present invention;
FIG. 3 is a schematic diagram of a conductive loop sensor structure in the measuring method of the present invention;
FIG. 4 is a flow chart of empirical mode decomposition integrated into the measurement method of the present invention;
FIG. 5 is a step of calculating the split-phase flow rate of oil-gas-water three-phase flow in the measurement method of the present invention;
FIG. 6 validation results of apparent flow rates of the liquid phase;
FIG. 7 gas phase superficial flow velocity verification results;
fig. 8 summarizes the flow rate verification results.
Detailed Description
The following describes embodiments of the present invention in detail with reference to the drawings.
FIG. 1 is a schematic structural diagram of an ultrasonic and electrical bimodal measurement system in the measurement method of the present invention. The electrical sensor is illustrated as a conductive loop sensor. The measuring system is composed of a group of electric sensor arrays 2 arranged on an experimental pipe section 1, an electric signal generating and acquiring unit 4 connected with the electric sensor arrays, a group of ultrasonic sensor arrays 3 and an ultrasonic signal generating and acquiring unit 6 connected with the ultrasonic sensor arrays. The electric sensor array 2 consists of four annular metal electrodes which are embedded in the inner wall of the pipeline at certain intervals; the ultrasonic sensor array 3 is composed of a group of integrated transmitting and receiving bicrystal ultrasonic transducers which are arranged on the same side of the pipeline. The electric sensor array 2 and the ultrasonic sensor array 3 are arranged on the measured pipeline 1 at certain intervals (the installation sequence is not limited) to form a dual-mode sensor array, and work simultaneously. When the measured flow multiphase flow enters a measured pipeline from the flow direction 0, the electrical sensor array 2 obtains measurement data reflecting the water content fluctuation information of the measured fluid through the electrical signal generating and collecting unit 4, and the data is sent to the phase content data processing unit 5 for data processing to complete flow characteristic analysis and flow pattern recognition; meanwhile, the ultrasonic sensor array 3 obtains measurement data of Doppler frequency shift reflecting flow velocity information of the measured fluid through the ultrasonic signal generating and collecting unit 6, and sends the data into the Doppler frequency shift data processing unit 7 for data processing to finish the decomposition of different fluctuation scales in the data; and sending the flow characteristic analysis, the flow pattern recognition result and the frequency shift data decomposition result into a phase separation flow velocity calculation unit 8 to complete the acquisition of the phase separation flow velocity of the oil-gas-water three-phase flow.
Fig. 2 is a schematic structural diagram of an ultrasonic doppler sensor in the measurement method of the present invention. The ultrasonic Doppler probe used in the invention is a double-crystal ultrasonic transducer integrating transmitting and receiving at the same side, and the internal part of the ultrasonic Doppler probe comprises a transmitting piezoelectric ceramic wafer 3a and a receiving piezoelectric ceramic wafer 3b which are respectively attached to an acoustoelectric coupling material 3c and a receiving piezoelectric ceramic wafer 3 d. The acoustic- electric coupling materials 3c and 3d are directly contacted with the measured fluid 2 and form an included angle theta with the test pipeline 10The ultrasonic beam path is installed to maintain an angle theta with the incoming flow direction 0 of the fluid 2 to be measured. A sound insulating material 4 is added between the acoustic- electric coupling materials 3c and 3d to prevent interference between the transmitted and received sound waves. The double-crystal ultrasonic transducer is arranged at the bottom of the test pipeline 1. Emission pressureThe electric ceramic wafer 3a emits ultrasonic waves, and the acoustic waves propagate in the fluid 2, are reflected and scattered by the discrete phases (bubbles 6, droplets 7) in the measurement space 5, and are received by the receiving piezoelectric ceramic wafer 3 b. The frequency difference between the received sound wave and the transmitted sound wave reflects the flow rate information of the fluid in the measurement space 5.
Fig. 3 is a schematic structural diagram of a conductive loop sensor in the measurement method of the present invention. The electric sensor is composed of four annular metal electrodes (1, 2,3, 4) which are arranged along the axial direction and are embedded in the inner wall 0 of the pipeline, wherein the electrodes 1 and 4 are excitation electrode pairs and used for generating a stable electric sensitive field between the excitation electrode pairs, and the electrodes 2 and 3 are measurement electrode pairs and used for measuring the potential difference between the excitation electrode pairs and the measurement electrode pairs. By injecting a constant square wave excitation current into the electrode 1 and grounding the electrode 4, a stable electrically sensitive field can be formed between the electrodes 1 and 4, using the current excitation voltage measurement mode. When the measured fluid flows through the sensitive field, the medium phase content and distribution change to cause the corresponding change of the potential difference between the electrode 2 and the electrode 3, and the measurement of the fluid water content can be realized by measuring the potential difference.
FIG. 4 is a flow chart of the ensemble empirical mode decomposition used in the measurement method of the present invention. The ensemble empirical mode decomposition is proposed for solving the mode aliasing problem in the traditional empirical mode decomposition, and the main idea is that the measurement accuracy can be improved by averaging multiple measurements of a certain classification in statistics. Ensemble empirical mode decomposition by adding m different sets of white noise ω to the signal x (t) to be decomposed multiple timesi(t), (i ═ 1, 2.., m) composite signals X which are different in m groupsi(t), (i ═ 1, 2.., m), and then performing empirical mode decomposition on each set of composite signals. Empirical mode decomposition the composite signal X described above is passed through a screening processi(t), (i ═ 1, 2.. times, m) the differently sized undulations present are progressively separated, producing a series of eigenmode functions IMF of different sizesij( i 1, 2.. multidot.m; j 1, 2.. multidot.n) to a sequence of residual values rinAnd (t) stopping decomposition by a monotonic function, wherein n is the number of the eigenmode functions generated by each decomposition. Finally averaging all groups of intrinsic mode function components obtained by all empirical mode decomposition to obtain a set of experienceEigenmode function of modal decomposition
FIG. 5 is a flow chart of the calculation steps for obtaining the phase-separated flow rate of oil-gas-water three-phase flow by the ultrasonic and electric combined sensor of the present invention. Aiming at oil-gas-water three-phase water-based-dispersed flow, the calculation steps for obtaining the split-phase flow velocity by the electricity and ultrasonic data combined analysis method provided by the invention are as follows:
step 1: collecting water phase content signals H (T), T epsilon (0, T) of the electric sensor and Doppler frequency shift signals f of the ultrasonic sensord(T), T belongs to (0, T), and removing high-frequency noise in the two signals (the denoising method is not limited), wherein T is sampling time;
step 2: according to the denoised water phase content measurement data of the electrical sensor, the recognition of an oil-gas-water three-phase flow pattern (water-based-dispersed-bubbly flow, water-based-dispersed-plug flow, water-based-dispersed-bullet flow) is realized by combining a feature extraction and classification algorithm;
the general steps of flow pattern identification are: firstly, extracting characteristic values capable of reflecting flow pattern change characteristics from measurement data, such as a statistical method, a time-frequency analysis method, a nonlinear analysis method and the like; and then classifying and identifying the characteristic values by using classification algorithms such as a support vector machine, an artificial neural network and the like. Taking a continuous wavelet transform method as an example, firstly, performing continuous wavelet transform on denoised water phase content measurement data H (t) (mother wavelet is Daubechies4 wavelet, and total scale is 500):
wherein wa,bFor successive wavelet transform coefficients at a given scale a and a given time instant b ψ (t) is the mother wavelet function. Because the water phase content fluctuation characteristics under different flow patterns are different, the time-wavelet-energy spectrum parameters are calculated:
this parameter can reflect the energy variation of the water fraction sequence along the time axis. The calculated mean value and variance of the step E (b) can be used as the characteristics of flow pattern recognition to be input into a trained artificial neural network, and the recognition of the typical flow pattern of the oil-gas-water three-phase water-based-dispersed flow can be completed.
And step 3: processing the water phase content sequence by adopting a time-frequency decomposition and characteristic extraction method to obtain local fluctuation characteristics caused by different discrete phases in water phase content signals under different flow patterns;
in an oil-gas-water three-phase water-based-dispersed flow, the discrete phase comprises oil drops and air bubbles. Due to the discreteness and size differences of the different discrete phases during flow: the size of the oil drops of the discrete phase is smaller than that of the bubbles of the discrete phase, and the oil drops are completely dispersed in the water and flow together with the water phase, and the bubbles are intermittently generated, which causes a fluctuation mode with different water phase content. The fluctuation characteristic of the water phase content measurement data of the denoised electric sensor is decomposed by adopting a time-frequency decomposition method, and meanwhile, different fluctuation characteristics of the water phase content caused by different discrete phases can be determined by combining a characteristic parameter extraction method, so that the flow characteristics of the different discrete phases in the flow process are disclosed. In the case of the continuous wavelet transform, the local wavelet energy coefficients of the water occupancy signal at a given scale a and a given time b are calculated on the basis of the continuous wavelet transform in step 2:
the local wavelet energy coefficient can be used for reflecting the fluctuation amplitude of the signal under a given scale and time, and the local fluctuation characteristic of the water phase content signal can be obtained by drawing a spectrogram of the local wavelet energy coefficient on a time-scale axis: the fluctuation component of the large scale (the scale is more than 50) mainly reflects the low-frequency large fluctuation of the water phase content caused by the discrete-phase bubbles, and the fluctuation component of the small scale (the scale is less than 50) mainly reflects the high-frequency small fluctuation of the water phase content caused by the discrete-phase oil drops.
And 4, step 4: decomposing the continuous wave ultrasonic Doppler frequency shift signal by using ensemble empirical mode decomposition;
based on the method of ensemble empirical mode decomposition, the ultrasonic Doppler signal f is processed by a screening processd(T), the T epsilon (0, T) is decomposed into a plurality of intrinsic mode functions IMF step by stepj(t) (j ═ 1, 2.. times, n) and a trend function rnSum of (t):
wherein n is the number of intrinsic mode functions obtained by decomposition. In general, the high-frequency components with large energy among the components obtained through the screening process often include the most significant and dominant information in the signal, and are the most dominant components. Therefore, the first 3-level intrinsic mode function IMF is selectedi(t) (i ═ 1,2,3) as the principal component of the flow rate extraction;
and 5: and respectively selecting different main components for calculating the split-phase flow rate under different flow patterns by adopting ultrasonic-electrical joint analysis according to the flow pattern recognition result and the decomposition result.
1) And (4) obtaining the corresponding relation between the water phase content and different fluctuation scales in the Doppler frequency shift signals in different flow patterns by adopting an ultrasonic-electric combined analysis method, and selecting different components from the main components obtained in the step (4) for extracting the split-phase flow velocity. For water-based-dispersed-bubbly flow and water-based-dispersed-elastic flow, the first-stage intrinsic mode function IMF obtained by decomposing Doppler frequency shift signals and corresponding to large-scale fluctuation components in a local wavelet energy coefficient spectrogram of a water phase content signal1(t) which is a high-frequency component and has discontinuity in time, reflecting information on the velocity of discrete-phase bubbles intermittently appearing during the flow; the second-level and third-level intrinsic mode functions IMF obtained by decomposing Doppler frequency shift signals have corresponding relation with small-scale fluctuation components in a local wavelet energy coefficient spectrogram of the water phase content signals2(t)&IMF3(t), which are low frequency components and are continuous in time, reflecting the velocity information of the fully dispersed oil droplets during the flow. For water-based-dispersive-plug flow, the large-scale fluctuation component in the local wavelet energy coefficient spectrogram of the water phase content signal is in pairThe corresponding relation is the first stage and the second stage intrinsic mode function IMF obtained by Doppler frequency shift signal decomposition1(t)&IMF2(t) which are high frequency components and have a discontinuity in time reflecting information on the velocity of discrete phase gas plugs intermittently present in the flow process; the third-level intrinsic mode function IMF which is obtained by decomposing Doppler frequency shift signals and has a corresponding relation with small-scale fluctuation components in a local wavelet energy coefficient spectrogram of the water phase content signals3(t), which is a low frequency component and continuous in time, reflects the velocity information of the fully dispersed oil droplets during flow.
2) And (3) carrying out fast Fourier transform on corresponding intrinsic mode functions reflecting split-phase flow velocity information under different flow patterns and calculating the average Doppler frequency shift: performing fast Fourier transform on the first stage eigenmode function and sampling Doppler average frequency shift in time:
performing fast Fourier transform on the sum of the first and second stage eigenmode function components and calculating the Doppler mean frequency shift over the sampling time:
performing fast Fourier transform on the sum of the second and third stage eigenmode function components and calculating the Doppler mean frequency shift in the liquid film time range
Performing fast Fourier transform on the third-stage eigenmode function and sampling Doppler average frequency shift in time:
wherein f isd1，fd2，fd3，fd4Are respectively IMF1(t)，IMF1(t)+IMF2(t)，IMF2(t)+IMF3(t)，IMF3(t) corresponding Doppler shift, Sd1(fd1)，Sd2(fd2)，Sd3(fd3)，Sd4(fd4) Respectively, the energy spectral intensity of its corresponding doppler shift.
3) From the basic principle of the doppler effect, the split-phase flow velocity is calculated: for water-based-dispersed-bubbly and water-based-dispersed-elastotic flows, the average true flow rates of the gas phase are:
the average true flow rate of the droplets is
For water-based-dispersed-plug flow, the mean true flow rate of the gas phase is
The average true flow rate of the droplets is:
wherein f is0Is the excitation frequency of the ultrasonic transmitting probe, theta is the included angle between the ultrasonic beam direction and the horizontal direction, c is the sound velocity in the fluid,
the average Doppler shift obtained by fast Fourier transform of different intrinsic mode functions in step 5 2) is the corresponding principal component reflecting the split-phase flow velocity information under different flow patterns determined in step 5 1).
The experiment verifies as follows:
the dynamic experiment is completed on an oil-gas-water three-phase flow experimental device. The fluid conveying pipeline of the experimental device is a stainless steel pipe with the inner diameter of 50mm, and the distance from the inlet to the outlet of the multiphase flow is about 16.6 m. The combined electrical and ultrasonic sensor was mounted in the test pipe section about 13m from the inlet of the multiphase flow so that the flow pattern developed sufficiently. Meanwhile, a pressure gauge and a temperature gauge are arranged on the test pipe section so as to record working conditions, and a camera is used for observing and recording the flow pattern. The fluids used in the experiment were tap water (density 998kg/m3, kinematic viscosity 1.01X 10-3 Pa.s), No. 15 technical white oil (density 790kg/m3, kinematic viscosity 3.9X 10-2 Pa.s) and dry respectivelyAir (density 1.2kg/m3, dynamic viscosity 1.81X 10-5 pas). The phases are mixed at the inlet by a T-mixer and the flow of each phase is measured by a standard single phase flow meter prior to mixing. By changing the flow ratio of different phases, different flow forms are generated. In each set of experiments, the flow rates of the oil phase and the water phase are fixed, and the flow rate of the gas phase is gradually increased to form different flow patterns (water-based-dispersed-bubble flow, water-based-dispersed-plug flow and water-based-dispersed-bullet flow). In the experiment, the total flow range of the three-phase flow under the standard condition is 6.66m3H to 14.97m3The total apparent flow rate varies from 0.92m/s to 1.76 m/s. The continuous measurement time in each flow state is 10s, and the acquisition of the fluctuation time sequence of the water phase content and the Doppler frequency shift signal is completed.
The processing of the fluctuation time sequence and the Doppler frequency shift signal of the water phase content is completed according to the steps in the specific implementation mode, and the phase separation real average flow velocity of the oil-gas-water three-phase water-based dispersed flow under different flow patterns can be obtained. In order to verify the effectiveness of the method, the real-time gas phase content and the real-time total liquid phase content can be calculated by using the real-time water phase content measured by the conductance ring under the assumption that no slip exists between oil and water.
Wherein phiwβ is the real-time water phase content in the liquid phasel，βg，βwβ for real-time total liquid phase content, real-time gas phase content and real-time water phase contentwObtained by means of an electrical phase fraction sensor, due to the absence of slip phi between oil and waterwCan be obtained by the inlet content. The split-phase apparent flow rate is further calculated:
wherein Jl，JgAnd J is the liquid phase superficial flow rate, the gas phase superficial flow rate and the total superficial flow rate, respectively. This was verified in comparison to the inlet reference superficial flow rate. The verification result is as shown in the figure6-8, taking root mean square error as an evaluation index: the root mean square errors of the liquid phase appearance, the gas phase appearance and the total gauge pipe are respectively 0.06m/s, 0.06m/s and 0.07 m/s. Therefore, the method can accurately obtain the phase separation flow rate of the oil-gas-water three-phase flow.
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