Electromagnetic Tomography Measuring Device and Method for Gas-liquid Two-phase Flow Content in Downhole Annular Fluid

Abstract

The present invention provides an electromagnetic tomography measurement device and method for the gas-liquid two-phase flow content in the downhole annulus fluid, including an excitation generation module, an electromagnetic sensor array, a signal processing module, a magnetic shielding layer, a channel switching switch, an FPGA processor, an instrument outer wall, an instrument inner wall, an image reconstruction and information extraction module. The FPGA processor is composed of a front-end FPGA processor and a rear-end FPGA processor. The excitation generation module is composed of an excitation signal generator, a D / A conversion, a filter amplification I, and a power amplification circuit. The signal processing module is composed of a data acquisition unit, a filter amplification II, an A / D conversion, and a signal demodulation. The present invention realizes the improvement of the electromagnetic tomography imaging speed and quality for detecting the gas-liquid phase fraction in the downhole annulus flow channel, realizes the extraction and measurement of the gas fraction in the gas-liquid two-phase flow in the annulus flow channel, and is of great significance for preventing overflow in the downhole annulus flow channel.

Description

Technical Field

[0001] The invention relates to the field of pipeline fluid tomography measurement, and in particular to an electromagnetic tomography measurement device and method for gas-liquid two-phase flow content in underground annular fluid. Background Art

[0002] As a traditional energy source, oil and natural gas occupy a very high position and proportion in the field of national economic production. Due to the rapid economic development, the demand for oil and natural gas continues to increase, while domestic oil extraction technology is relatively weak. With the increase in the difficulty of extraction, the underground mining environment has become more severe. Oil exploration and development continues to develop towards complex oil and gas reservoirs with deeper layers, higher temperatures, and more severe environments. Existing extraction technologies face a series of problems such as high comprehensive water content in oil wells, high extraction costs, and great exploration difficulties. The use of old technologies is likely to lead to well invasion, overflow, well gushing, blowout and other accidents during the drilling process, resulting in a waste of oil resources. In order to change this situation, the research of new technologies and new equipment is imminent.

[0003] Electromagnetic tomography is a new type of tomography technology based on the principle of electromagnetic induction. It has the advantages of non-contact, non-invasive, simple and flexible structure, low cost and high sensitivity. It is a direct means to detect multiphase flow in the annular flow channel of the well. The fluid level of the multiphase flow in the annular flow channel of the oil and gas well is constantly changing, and it is impossible to predict the composition of the next second. Electromagnetic tomography usually presents problems of pathology and instability, resulting in irregular edges, blurring and residual images. Summary of the invention

[0004] The purpose of the present invention is to solve the defects of the above-mentioned prior art and provide an electromagnetic tomography measuring device and method for the gas-liquid two-phase flow content in the downhole annular fluid, which can greatly improve the imaging speed and quality, effectively avoid the occurrence of accidents such as well kick, blowout, overflow, and so on, and thus avoid more waste of resources. Through the electromagnetic tomography measuring device and method for the gas-liquid two-phase flow content in the downhole annular fluid, rapid imaging of the fluid in the annular flow channel is achieved, which can buy more time for later well control, thereby reducing the incidence of accidents.

[0005] The present invention adopts the following technical solution:

[0006] An electromagnetic tomography measuring device for gas-liquid two-phase flow content in downhole annular fluid, comprising an excitation generation module, an electromagnetic sensor array, a signal processing module, a magnetic shielding layer, a channel switching switch, an FPGA processor, an instrument outer wall, an instrument inner wall, and an image reconstruction and information extraction module;

[0007] The front-end FPGA processor and the back-end FPGA processor constitute the FPGA processor;

[0008] The excitation signal generator, D / A conversion, filtering and amplification I, and power amplification circuit form the excitation generation module;

[0009] The data acquisition unit, filtering and amplification II, A / D conversion, and signal demodulation form the signal processing module;

[0010] The structure of the traditional electromagnetic tomography device has been adjusted. The adjustment includes the stable output of the excitation signal of the excitation generation module, the excitation signal of the electromagnetic sensor array, the noise interference of the signal processing module, and the system signal transmission part. The front-end FPGA processor controls the excitation signal generator to generate an excitation signal. The excitation signal generates a digital sine signal after passing through the D / A converter. The digital sine signal passes through filtering and amplification I and the power amplification circuit, and then is distributed to the electromagnetic sensor array through the channel switching switch. After the detection signal passes through the channel switching switch, the signal acquisition unit collects the detection signal, and then enters the A / D conversion after passing through filtering and amplification II. The processed signal has anti-interference ability. The signal is further preprocessed through signal demodulation and transmitted to the image reconstruction and information extraction module through the back-end FPGA processor.

[0011] The coil skeleton direction of the electromagnetic sensor array faces one side of the outer wall. A kind of skeleton with an arc is selected, and the electromagnetic sensor array is arranged between the outer wall and the inner wall of the instrument to generate a uniform magnetic field in the detection area; an iron core is inserted into the center of the coil skeleton to enhance the magnetic field strength in the imaging area. The magnetic shielding layer of the electromagnetic sensor array is made of an iron-aluminum alloy material with a thickness of 50 - 250 microns, and the magnetic shielding layer is wrapped outside the inner flow channel.

[0012] After the structure of the device is optimized, the original data is preprocessed through the signal processing module to improve the imaging speed and quality. The specific processing method is as follows:

[0013] Step 1. Improve the transformation speed of the sensitivity matrix. The rapid conversion of sensitivity is the key to improving the imaging speed of the system. Use the fast coefficient matrix generation method to change the local sparse matrix of the permeability change unit. If the annulus imaging area is divided into unit grids, then when detecting the gas-liquid two-phase flow in the annulus flow channel area, the permeability of some cells in the imaging area will change, and the elements of its local sparse matrix will change, thus generating a new total coefficient matrix. The expression of the local sparse matrix is shown in Equation (1):

[0014]

[0015] In the formula, e is the unit coefficient matrix, μ1 and μ2 are the permeabilities of the phase flow changes, N i , N j are the unit shape functions, and t is a positive integer.

[0016] Step 2. Process the original data of the image. The main processing method is to use the sensitivity matrix dimensionality reduction algorithm for processing, so as to improve the image edge blur and afterimage of the electromagnetic tomography. The corresponding sensitivity is:

[0017]

[0018] In the formula, the current I is the excitation condition, and the vector magnetic potential distributions of the detection coil and the excitation coil are A j and A i , the induced voltage is V, τ is the conductivity, the perturbation volume is C, and the operating frequency is W.

[0019] Step 3. Normalize the measured change values detected and the sensitivity matrix of the local unit to reduce the influence of noise interference. The specific processing expression is:

[0020] U = Sg (3)

[0021] In the formula, U is the normalized measured value vector, S is the normalized sensitivity matrix, and g is the conductivity gray value vector of the substance in the fluid.

[0022] Step 4. Eliminate the abnormal areas existing in the electromagnetic tomography through image subtraction, and then perform gray processing of the image.

[0023] Step 5. Introduce the gamma correction algorithm to perform non-linear tone editing on the image, detect the dark part and the light part in the image signal, and increase the brightness difference between the two to improve the image contrast effect, so as to eliminate the blurred area and afterimage in the electromagnetic tomography. The gamma correction algorithm expression is:

[0024] F(I) = I γ (4)

[0025] In the formula, F(I) is the image output value, I is the image input value, and γ is the gamma value of different gray images.

[0026] Step 6. Linearly expand or compress the gray range through the linear gray transformation of the image, and selectively enhance or reduce the contrast within a specific gray value range.

[0027] Step 7. Use the Otsu algorithm to perform image binarization processing, and finally obtain a relatively clear image. The Otsu algorithm expression is:

[0028] σ 2 = P1(m1 - M) 2 + P2(m2 - M) 2 (5)

[0029] Wherein, σ is the average value of the background image, m1 and m2 are the gray values of different parts of the image, P1 and P2 are the occurrence probabilities of the gray values of different parts, and M is the global average threshold. After obtaining the image of the effective annulus flow channel imaging area, first extract the bubbles in the annulus cross-section, and use the morphological image processing two-dimensional derivative method Canny operator to extract the tomography bubble boundary in the image, realizing high positioning accuracy of the bubbles and simultaneously suppressing false edges.

[0030] After extracting the bubbles in the imaging cross-section, by obtaining the gas holdup parameter of the annulus cross-section, the phase holdup in the gas-liquid two-phase flow is obtained. The extracted bubble boundary is processed by the erosion and dilation algorithm, and the inside of the bubble is filled by using the hole filling technology. The image is calibrated, and the corresponding relationship between the image pixel points and the geometric dimensions is obtained after calibration, so as to obtain parameters such as the area, perimeter, and standard diameter of the bubbles.

[0031] The specific steps for obtaining parameters are as follows:

[0032] S1. After counting the number of pixels of the same mark by scanning the image, multiplying it by the actual area represented by a unit pixel can obtain the actual area of the bubble.

[0033] Step 2. After obtaining the contour lines of each bubble through edge detection, using the regionprops function to obtain the total number of image pixels of each bubble contour line, and then multiplying it by the actual length represented by a unit pixel, so as to obtain the actual boundary perimeter L of each bubble.

[0034] Step 3. In the study of two-phase flow, since the projected area of the bubble is measured by the image, the standard diameter of the bubble is defined by the diameter of a circle with the same area as it, that is

[0035]

[0036] In the formula, d is the bubble diameter and s is the cross-sectional area of the bubble;

[0037] After obtaining the above bubble parameters, the gas holdup can be directly obtained through the ratio between the gas content and the fluid content in the downhole annulus flow channel.

[0038] The beneficial effects of the present invention:

[0039] 1. The present invention optimizes the electromagnetic tomography imaging device in the traditional downhole annulus flow channel, improves the data acquisition rate, and enhances the real-time performance of the image.

[0040] 2. The present invention performs preprocessing of sensitivity matrix optimization and sensitivity normalization on the original image data. By means of gray processing, gamma correction, and linear enhancement of image gray level, etc., the problems of image edge blurring and edge afterimage are solved, and the imaging accuracy and quality are greatly improved, which is of great significance for the rapid measurement of multiphase flow in the fluid of the downhole annulus flow channel and for preventing downhole overflow.

[0041] 3. The present invention realizes the acquisition of the cross-sectional gas holdup parameter in the annulus flow channel and realizes the non-contact measurement of the gas-liquid two-phase flow content in the downhole annulus fluid. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 It is a schematic structural diagram of an electromagnetic tomography measurement device for the gas-liquid two-phase flow content in the downhole annulus fluid;

[0043] Figure 2 It is a schematic principle diagram of an electromagnetic tomography measurement device for the gas-liquid two-phase flow content in the downhole annulus fluid;

[0044] Figure 3 It is a side view of the electromagnetic sensor array in the electromagnetic tomography measurement device for the gas-liquid two-phase flow content in the downhole annulus fluid;

[0045] Figure 4 It is a diagram of the annulus imaging area of the electromagnetic tomography measurement device for the gas-liquid two-phase flow content in the downhole annulus fluid;

[0046] FIG. 5(a), FIG. 5(b), and FIG. 5(c) are the image processing effect diagrams of the electromagnetic tomography measurement method for the gas-liquid two-phase flow content in the downhole annulus fluid;

[0047] FIG. 6(a) and FIG. 6(b) are the bubble extraction diagrams of the electromagnetic tomography measurement method for the gas-liquid two-phase flow content in the downhole annulus fluid.

[0048] In the figures: 1 - excitation generation module, 2 - electromagnetic sensor array, 3 - signal processing module, 4 - inner wall of the instrument, 5 - channel switch, 6 - FPGA processor, 7 - well wall, 8 - outer wall of the instrument, 9 - magnetic shielding layer, 10 - image reconstruction and information extraction module. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0049] To make the objectives, technical solutions, and advantages of the present invention clearer, the technical solutions in the present invention will be described clearly and completely below. Apparently, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without making creative efforts shall fall within the protection scope of the present invention.

[0050] As Figure 1As shown in the figure, the electromagnetic tomography measurement device for the gas-liquid two-phase flow content in the downhole annulus fluid of the present invention includes an excitation generation module 1, an electromagnetic sensor array 2, a signal processing module 3, a magnetic shielding layer 9, a channel switching switch 5, an FPGA processor 6, an instrument outer wall 8, an instrument inner wall 4, and an image reconstruction and information extraction module 10. The present invention has a complete electromagnetic tomography imaging system. Except for the image reconstruction and information extraction module, all other modules are in the downhole instrument, and each module is powered by the downhole system power supply.

[0051] As Figure 2 shown in the figure, the electromagnetic sensor array 2 consists of 8 coils to form a single-layer annular array. The coil skeleton is closely attached to the instrument inner wall 4 to form a uniform magnetic field in the detection area. An iron core is inserted into the center of the coil skeleton to enhance the magnetic field strength in the imaging area. The magnetic shielding layer 9 of the electromagnetic sensor array 2 is made of a relatively thick iron-aluminum alloy material, and the magnetic shielding layer 9 is arranged to wrap the inner flow channel pipe wall (on the outside).

[0052] As Figure 3 shown in the figure, the front-end FPGA processor controls the excitation signal generator to generate an excitation signal. After passing through the D / A converter, the excitation signal generates a digital sine signal with high precision, high resolution, and a wide output frequency range. The digital signal then passes through the filter amplification I and power amplification circuits, and is distributed to the electromagnetic sensor array 2 through the channel switching switch 5. Then, through the channel switching switch 5, the signal acquisition unit acquires the detection signal, and then enters the A / D converter after passing through the filter amplification II. The processed signal has good anti-interference ability. After a series of preprocessings such as demodulation, the signal is finally transmitted to the image reconstruction and information extraction module 10 through the back-end FPGA processor. By adopting the parallel working mode of the FPGA dual processors, each module in the device can work simultaneously, improving the data acquisition rate and enhancing the real-time performance of the image.

[0053] The front-end FPGA processor and the back-end FPGA processor form the FPGA processor 6. The excitation signal generator, D / A conversion, filter amplification I, and power amplification circuits form the excitation generation module 1. The data acquisition unit, filter amplification II, A / D conversion, and signal demodulation form the signal processing module 3.

[0054] When using this device to measure the gas-liquid two-phase flow content in the annulus flow channel, in order to obtain high-quality imaging effects, the key lies in preprocessing the original data and optimizing the imaging method. The specific implementation steps are as follows:

[0055] Step 1. Improve the transformation speed of the sensitivity matrix. The rapid conversion of sensitivity is the key to improving the imaging speed of the system. The local sparse matrix of the permeability change unit is changed by using the fast coefficient matrix generation method. If the annulus imaging area is divided into unit grids, then when detecting gas-liquid two-phase flow in the annulus flow channel area, the permeability of some cells in the imaging area will change, thus generating a new total coefficient matrix. The expression of the local coefficient matrix is shown in Equation (1):

[0056]

[0057] In the formula, e is the unit coefficient matrix, μ1 and μ2 are the permeabilities of the phase flow changes, N i , N j are both unit shape functions, and t is a positive integer.

[0058] Step 2. Process the original data of the image. The main processing method is to use the sensitivity matrix dimensionality reduction algorithm for processing to improve the image edge blur and afterimage of the electromagnetic tomography imaging.

[0059] The corresponding sensitivity is:[[]]

[0060]

[0061] In the formula, the current I is the excitation condition, and the vector magnetic potential distributions of the detection coil and the excitation coil are A j and A i respectively, the induced voltage is V, τ is the conductivity, the perturbation volume is C, and the operating frequency is W.

[0062] Step 3. Normalize the measured change value and the sensitivity matrix of the local unit detected to reduce the influence of noise interference. The specific processing expression is:[[]]

[0063] U = Sg (3)

[0064] In the formula, U is the normalized measured value vector, S is the normalized sensitivity matrix, and g is the conductivity gray value vector of the substance in the fluid.

[0065] Step 4. Eliminate the abnormal areas existing in the electromagnetic tomography imaging through image subtraction, and then perform gray processing on the image.

[0066] Step 5. Introduce the gamma correction algorithm to perform non-linear tone editing on the image, detect the dark and light parts of the image signal, and increase the brightness difference between the two to improve the image contrast effect, so as to eliminate the blurred area and afterimage in the electromagnetic tomography imaging. The expression of the gamma correction algorithm is:[[]]

[0067] F(I) = I γ (4)

[0068] Wherein, F(I) is the image output value, I is the image input value, and γ is the gamma value of different grayscale images.

[0069] Step 6. Linearly expand or compress the grayscale range through the linear grayscale transformation of the image, and selectively enhance or reduce the contrast within a specific grayscale value range.

[0070] Step 7. Use the Otsu algorithm for image binarization processing to finally obtain a relatively clear image. The expression of the Otsu algorithm is:

[0071] σ 2 = P1(m1 - M) 2 + P2(m2 - M) 2 (5)

[0072] Wherein, σ is the average value of the background image, m1 and m2 are the grayscale values of different parts of the image, P1 and P2 are the occurrence probabilities of the grayscale values of different parts, and M is the global average threshold.

[0073] As Figure 4 shown, after obtaining the image of the imaging area of the effective annulus flow channel, first extract the bubbles in the annulus cross-section, and extract the tomography bubble boundaries in the image through the morphological image processing two-dimensional derivative method Canny operator to achieve high positioning accuracy of the bubbles and simultaneously suppress false edges.

[0074] After extracting the bubbles in the imaging cross-section, obtain the gas holdup parameter of the annulus cross-section to obtain the phase holdup in the gas-liquid two-phase flow. Process the extracted bubble boundaries through the erosion and dilation algorithm, fill the inside of the bubbles using the hole filling technique, calibrate the image, and obtain the corresponding relationship between the image pixel points and the geometric dimensions after calibration, so as to obtain parameters such as the area, perimeter, and standard diameter of the bubbles. The specific steps for parameter acquisition are as follows:

[0075] S1. After counting the number of the same marked pixel points by scanning the image, multiply it by the actual area represented by a unit pixel point to obtain the actual area S of the bubble.

[0076] S2. After obtaining the contour lines of each bubble through edge detection, use the regionprops function to obtain the total number of pixel points of each bubble contour line, and then multiply it by the actual length represented by a unit pixel point to obtain the actual boundary perimeter L of each bubble.

[0077] S3. In the study of two-phase flow, since the image measurement obtains the projected area of the bubble, the standard diameter of the bubble is defined by the diameter of a circle with the same area as it, that is

[0078]

[0079] where d is the bubble diameter and s is the cross-sectional area of the bubble;

[0080] After obtaining the above bubble parameters, the gas holdup can be obtained directly from the ratio between the gas content and the fluid content in the downhole annulus flow channel.

[0081] Embodiment

[0082] For the electromagnetic sensor array with 1 - 8 coils, the channel switching switch controls one coil as the input coil and the remaining coils as output coils. Based on the simulation software, the output signals of 56 groups of coils with a cross-section containing bubbles are calculated as shown in Table 1. Then, after preprocessing these original output signals, they are input into the image information reconstruction module to generate an annulus cross-section image containing bubbles.

[0083] The image information of the annulus cross-section tomography is processed step by step according to the method. Figure 5(a) - Figure 5(c) They are, in sequence, the differential effect diagram of the bubble image of the experimental processing cross-section, the image enhancement effect diagram, and the Otsu binary image; the optimal effect diagram is obtained through the above processing. The Canny operator detection and hole filling method are used to extract the bubbles. Figures 6(a) and 6(b) are, in sequence, the Canny operator edge detection diagram and the hole filling result diagram; finally, through the acquisition of the gas holdup parameter of the annulus cross-section, the phase holdup in the gas-liquid two-phase flow is obtained.

[0084] Table 1 Output voltage values of the measuring coils

[0085] Energizing coil Coil 1 - 2 Coil 1 - 3 Coil 1 - 4 Coil 1 - 5 Coil 1 - 6 Coil 1 - 7 Coil 1 - 8 Output voltage (V) 0.26709 0.27179 0.27137 0.2712 0.27137 0.27181 0.26711 Energizing coil Coil 2 - 1 Coil 2 - 3 Coil 2 - 4 Coil 2 - 5 Coil 2 - 6 Coil 2 - 7 Coil 2 - 8 Output voltage (V) 0.26709 0.26716 0.27188 0.27144 0.27128 0.27145 0.27173 Energizing coil Coil 3 - 1 Coil 3 - 2 Coil 3 - 4 Coil 3 - 5 Coil 3 - 6 Coil 3 - 7 Coil 3 - 8 Output voltage (V) 0.2716 0.26695 0.26705 0.27157 0.27117 0.27101 0.27118 Energizing coil Coil 4 - 1 Coil 4 - 2 Coil 4 - 3 Coil 4 - 5 Coil 4 - 6 Coil 4 - 7 Coil 4 - 8 Output voltage (V) 0.2714 0.27183 0.26714 0.26709 0.27183 0.2714 0.27123 Energizing coil Coil 5 - 1 Coil 5 - 2 Coil 5 - 3 Coil 5 - 4 Coil 5 - 6 Coil 5 - 7 Coil 5 - 8 Output voltage (V) 0.27094 0.27111 0.27151 0.267 0.26693 0.27155 0.27111 Energizing coil Coil 6 - 1 Coil 6 - 2 Coil 6 - 3 Coil 6 - 4 Coil 6 - 5 Coil 6 - 7 Coil 6 - 8 Output voltage (V) 0.27116 0.271 0.27115 0.27159 0.26696 0.26701 0.27158 Energizing coil Coil 7 - 1 Coil 7 - 2 Coil 7 - 3 Coil 7 - 4 Coil 7 - 5 Coil 7 - 6 Coil 7 - 8 Output voltage (V) 0.27182 0.27138 0.2712 0.27137 0.27181 0.2671 0.26711 Energizing coil Coil 8 - 1 Coil 8 - 2 Coil 8 - 3 Coil 8 - 4 Coil 8 - 5 Coil 8 - 6 Coil 8 - 7 Output voltage (V) 0.26706 0.27173 0.27128 0.27111 0.27128 0.2717 0.26705

[0086] The present invention uses an electromagnetic tomography measurement device and method for the gas-liquid two-phase flow content in downhole annulus fluid. By optimizing the structure of the electromagnetic tomography device and the preprocessing method of image information, problems such as the ill-posedness and instability of electromagnetic tomography are solved. The rapid imaging and high-quality imaging of the gas-liquid two-phase flow content detection by electromagnetic tomography in the downhole annulus flow channel are realized, and the non-contact measurement of the gas-liquid two-phase flow content in the downhole annulus flow channel fluid is realized.

[0087] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. An electromagnetic tomography measurement method for the gas-liquid two-phase flow content in the downhole annulus fluid, characterized in that, The specific processing method of the image reconstruction and information extraction module is as follows: Step 1. Use the fast coefficient matrix generation method to change the local sparse matrix of the permeability change unit, and divide the annulus imaging area into unit grids. When detecting gas-liquid two-phase flow in the annulus flow channel area, the permeability of some unit grids in the imaging area will change, and the elements of its local sparse matrix will change, thus generating a new total coefficient matrix. The expression of the local sparse matrix is shown in Equation (1): where e is the unit coefficient matrix, μ1 and μ2 are the permeabilities of the phase flow changes; N i and N j are the element shape functions, and t is a positive integer; Step 2. Process the original data of the image. The processing method is to use the sensitivity matrix dimensionality reduction algorithm to improve the image edge blur and afterimage of the electrical capacitance tomography. The corresponding sensitivity is: Wherein, the current I is the excitation condition, and the vector magnetic potential distributions of the detection coil and the excitation coil are A j and A i , the induced voltage is V, τ is the conductivity, the perturbation volume is C, and the operating frequency is W; Step 3. Normalize the measured change value and the sensitivity matrix of the local unit. The specific processing expression is: U = Sg (3) In the formula, U is the vector of the normalized measured value, S is the normalized sensitivity matrix, and g is the vector of the conductivity gray value of the substance in the fluid; Step 4. Eliminate the abnormal area in the electrical capacitance tomography by subtracting the images, and then perform gray processing on the images; Step 5. Introduce the gamma correction algorithm to perform non-linear tone editing on the images, detect the dark and light parts in the image signal, and increase the brightness difference between the two to improve the image contrast effect, so as to eliminate the blurred area and afterimage in the electrical capacitance tomography. The expression of the gamma correction algorithm is: F(I) = I γ (4) In the formula, F(I) is the image output value, I is the image input value, and γ is the gamma value of different gray images; Step 6. Linearly expand or compress the gray range through the linear gray transformation of the images, and selectively enhance or reduce the contrast within a specific gray value range; Step 7. Use the Otsu algorithm to perform image binarization processing, and finally obtain a relatively clear image. The expression of the Otsu algorithm is: σ 2 = P1(m1 - M) 2 + P2(m2 - M) 2 (5) In the formula, σ is the average value of the background image, m1 and m2 are the gray values of different parts of the image, P1 and P2 are the occurrence probabilities of the gray values of different parts, and M is the global average threshold. After obtaining the image of the effective annulus flow channel imaging area, first extract the bubbles in the annulus cross-section, and extract the tomography bubble boundary in the image through the morphological image processing two-dimensional derivative method Canny operator to achieve high positioning accuracy of the bubbles and suppress false edges at the same time; After extracting the bubbles in the imaging cross-section, obtain the gas holdup parameter in the annulus cross-section to get the phase holdup in the gas-liquid two-phase flow. Process the extracted bubble boundary through the erosion and dilation algorithm, fill the inside of the bubbles using the hole filling method, calibrate the image, and obtain the corresponding relationship between the image pixel points and the geometric dimensions after calibration, so as to obtain the area, perimeter, and standard diameter parameters of the bubbles.

2. The method according to claim 1, wherein The specific steps for obtaining the area, perimeter, and standard diameter parameters of the bubbles are as follows: S1. After counting the number of the same marked pixel points by scanning the image, multiply it by the actual area represented by a unit pixel point to obtain the actual area of the bubbles; Step 2. After obtaining the contour lines of each bubble through edge detection, use the regionprops function to calculate the total number of image pixels of each bubble contour line, and then multiply it by the actual length represented by a unit pixel to obtain the actual boundary perimeter L of each bubble; Step 3. In the study of two-phase flow, since the image measurement obtains the projected area of the bubble, the standard diameter of the bubble is defined by the diameter of a circle with the same area, that is where d is the bubble diameter and s is the cross-sectional area of the bubble; After obtaining the bubble parameters, the gas holdup can be directly obtained through the ratio between the gas content and the fluid content in the downhole annulus flow channel.

Images