A system and method for interpreting oil well production profiles based on distributed fiber optic acoustic wave monitoring

Abstract

The present invention belongs to the technical field of oil and gas production, and specifically relates to a system and method for interpreting oil well production profiles based on distributed fiber optic acoustic wave monitoring. Since the water cut and flow rate corresponding to the measured FBE data are uncertain, the present invention establishes an FBE-flow interpretation chart that shows the change of formation fluid flow rate at different water cuts. When the number of production layers, wellhead water cut, and wellhead flow rate are known, the water cut of each production layer is assumed, and the flow rate corresponding to the assumed water cut is calculated based on the measured FBE data under the corresponding FBE-flow interpretation chart. The wellhead water cut and flow rate under the assumed water cut conditions are then obtained. By controlling the error between the calculated wellhead flow rate and the actual wellhead flow rate detected, the flow rate and water cut parameters of each production well section are determined, thereby realizing downhole production profile monitoring and interpretation.

Description

Technical Field

[0001] The invention relates to the technical field of oil and gas exploitation, and is a system and method for explaining oil well production profiles based on distributed optical fiber acoustic wave monitoring. Background Art

[0002] Currently, confirming oil well production profiles primarily relies on traditional measurement techniques and sensors, such as mechanical samplers, rotary sidetracking samplers, temperature and pressure measurements, tracer testing, and various types of flowmeters (such as turbine flowmeters, electromagnetic flowmeters, and ultrasonic flowmeters). However, traditional electronic logging instruments have technical limitations, including low spatial resolution and an inability to continuously acquire data; susceptibility to interference from complex downhole environments; complex and error-prone technical operations; and difficulty interpreting data, requiring specialized knowledge. These limitations make it difficult to obtain accurate profile information in real time, hindering the monitoring and adjustment of oil well production status.

[0003] With the continuous development of technology, distributed acoustic monitoring (DAS) technology is playing an increasingly important role in oil well production profile monitoring. This technology enables real-time and continuous acquisition of acoustic signals during the oil well production process, enabling distributed monitoring of the entire wellbore. This opens up new possibilities for obtaining real-time and accurate oil well production profile information.

[0004] However, the current methods for interpreting oil well production profiles based on distributed fiber optic acoustic sensing are still very limited. For example, Chinese patent document CN117266832A (202311488486.3) discloses a method and system for inverting the two-phase flow production profile of oil and gas wells using DAS. According to the raw data measured by optical fiber processing, Fourier transform (FFT) is performed in the depth direction and time direction to obtain the frequency wavenumber slope. According to the slope, the sound velocity can be obtained. In different mixtures, the proportion of oil or water can be obtained according to the empirical formula, and then the oil-water two-phase flow production profile can be obtained. However, if the quality of the field data is not high enough, the above method cannot solve the sound velocity in the frequency wavenumber domain converted from the raw data; For example, the oil well production profile inversion method based on low-frequency acoustic wave signals and temperature signals disclosed in Chinese patent document CN116677371A (202310817136.0) is complex in technical operation and difficult in data analysis, and there is a problem that the results cannot be obtained in a short time.

[0005] Chinese patent document CN112240196A (201910640705.2) discloses a wellbore production profile monitoring simulation experimental device based on distributed fiber optic sound and temperature monitoring, comprising: a distributed fiber optic sound and temperature monitoring integrated system, a wellbore and reservoir simulation system, a fluid supply and control system, and a fluid collection system; the distributed fiber optic sound and temperature monitoring integrated system is connected to the wellbore and reservoir simulation system via an external optical cable and an internal optical cable; a left fluid inlet and a right fluid inlet are symmetrically arranged on the axial outer wall of the wellbore and reservoir simulation system, respectively connected to the fluid supply system; the fluid collection system is connected to the wellbore and reservoir simulation system via a drainage pipeline. The above patent can achieve continuous and real-time fluid production status monitoring of the production profiles of simulated multi-layer vertical wells, horizontal wells, multi-branch wells, and inclined wells. It can also simulate the temperature and sound response of wellbore production under different liquid volumes, different water cuts, different temperatures, and different production layers, providing technical ideas for wellbore production profile testing. The above patent requires a large number of formation parameters (such as formation thermal diffusivity, specific heat capacity, formation density, etc.) and physical parameters (including viscosity, density, water content, etc.), and the calculation process is complicated.

[0006] Therefore, the present invention provides a new reliable, simple and efficient method to meet the demand for rapid and accurate confirmation of oil well production status. Summary of the Invention

[0007] The main purpose of the present invention is to provide an oil well production profile interpretation system and method based on distributed fiber optic acoustic wave monitoring. This application can calculate the production profile by simply obtaining the wellhead water content, wellhead flow rate and the number of production layer sections. It has low dependence on parameters and low computational complexity. It is a new flow interpretation method that solves the problems of large computational complexity and low accuracy in the existing technology of distributed fiber optic production profile interpretation.

[0008] The technical problem to be solved by the present invention is achieved by the following technical solution: an oil well production profile interpretation system based on distributed fiber optic acoustic wave monitoring, comprising a casing, an oil pipe, an optical cable, and a DAS production profile monitor installed on the ground. The oil pipe is located within the casing, and the optical cable is installed within the oil pipe or on the outer wall of the oil pipe or on the outer wall of the casing. The optical cable is lowered into the oil pipe for a single measurement, and can be lowered outside the oil pipe or casing in a permanent manner, with a flexible lowering position. The permanent type requires that the optical cable and the pipe be tightly fitted.

[0009] The DAS production profile monitor is connected to the optical cable, and the DAS production profile monitor includes a DAS oil well production profile interpretation module;

[0010] The DAS oil well production profile interpretation module is used to process the oil well DAS data acquired in real time by the optical cable to obtain the real-time flow rate and water content of each production layer section of the oil well;

[0011] The DAS oil well production profile interpretation module includes an FBE-flow chart module, a data pre-processing module and an oil well production profile interpretation module;

[0012] The FBE-flow chart module is used to set an FBE-flow interpretation chart showing the relationship between FBE data related to formation fluid flow and flow rate as the flow rate changes under different water content ratios. When establishing the FBE-flow interpretation chart, the water content ratio interval between two adjacent charts is the same; the formation fluid is a two-phase oil-water phase.

[0013] The data preprocessing module is used to convert the sound data related to the flow of formation fluid entering the wellbore collected during the production process into FBE data to obtain FBE data of each production layer;

[0014] The oil well production profile interpretation module is used to utilize the sound data processed by the data preprocessing module and, based on the FBE-flow interpretation plate in the FBE-flow plate module, assume the water cut of each production layer under the condition that the number of production layers, the wellhead water cut and the wellhead flow rate are known. Based on the FBE data of each production layer calculated by the data preprocessing module under the corresponding FBE-flow interpretation plate, the flow rate corresponding to the assumed water cut is calculated, and then the wellhead water cut and flow rate under the assumed water cut conditions are obtained. By controlling the error between the obtained wellhead flow rate and the detected actual wellhead flow rate, the flow rate and water cut parameters of each production well section are determined.

[0015] Preferably, the oil well production profile interpretation module, based on the FBE data of each production layer calculated by the data preprocessing module, assumes the water cut of each section, and interpolates the flow rate corresponding to each section in the FBE-flow chart. The detailed steps are as follows: based on the wellhead water cut, arbitrarily assume the water cut of each layer section, and based on the assumed water cut of each layer section, use the FBE data of each section calculated by the data preprocessing module to query the corresponding flow value in the FBE-flow chart corresponding to the assumed water cut of each layer section, that is, search the FBE-flow chart with the same FBE data to determine the corresponding flow value, or use the flow values ​​of two adjacent FBE-flow interpretation charts corresponding to the water cut to linearly interpolate the flow value corresponding to the assumed water cut in the middle position, that is, use the flow rate of the shallow layer minus the flow rate of the deep layer in the two layers to obtain the flow rate of each layer section under the assumed water cut; the wellhead water cut is obtained by separating oil, water and impurities on the ground through a centrifuge, measuring the volume of oil and water respectively, and calculating the water cut. Assuming the water content of each layer based on the wellhead water content can converge to the results faster;

[0016] The wellhead flow rate Q' under the assumed water cut is obtained by decreasing the flow rate layer by layer to obtain the inflow flow rate q for each layer. i ;

[0017] The built-in algorithm is used to calculate the water content of each layer and the inflow rate q of each layer. i Verification includes the following steps:

[0018] 2-1) Calculate the error ΔQ = QQ′ between the actual wellhead flow rate and the wellhead flow rate under the current assumed water cut. In each layer, assume the water cut f′ w and the actual moisture content f w The error between them is x i , the change in flow rate when the water content increases or decreases by 1% under the FBE data in the corresponding FBE-flow chart is Δq i ;

[0019] Δq i The calculation method is as follows: select the flow rate with the minimum water content and the maximum water content under the corresponding FBE data in the FBE-flow chart, perform linear interpolation, and calculate the change in flow rate under unit water content change;

[0020] 2-2) Establish the assumed flow error equation and water content error equation, which are equations (2) and (3) respectively:

[0021]

[0022] Where n is the number of production intervals, f w0 is the wellhead water content, f wi The water content assumed for each interval;

[0023] 2-3) Combine equations (2) and (3) and solve to obtain the error x of each segment. i , further calculate the corrected moisture content f′ of each layer wi =f wi +x i Then, according to the corrected water content, the FBE-flow chart is queried to obtain the sum of the flow rates of each layer, and compared with the actual flow rate at the wellhead, and the flow error ΔQ is recalculated; the actual flow rate at the wellhead is obtained through measurement;

[0024] If ΔQ / Q<ε, the accuracy is met and the iteration is stopped and the corrected moisture content f′ of each layer is output. wi , or when the water content selection range is the water content interval Δf% corresponding to the establishment of the FBE-flow interpretation chart, stop the iteration, otherwise update Δq i , and return to step 2-1) to continue to correct the moisture content, the precision ε is pre-set and can be selected arbitrarily;

[0025] Δq iThe updating method is as follows: by narrowing the selection range between the minimum and maximum water cuts of the FBE-flow chart, a more refined linear interpolation of the flow is performed under the corresponding FBE data to calculate the change in flow under unit water cut change; that is, the water cut selection range is gradually reduced during correction, and the subsequent selection ensures that the assumed water cut is within the selected range, and the assumed value is as close to the midpoint of the selection range as possible; preferably, when the water cut selection range is the corresponding water cut interval Δf% when establishing the FBE-flow interpretation chart, When the water cut interval is less than Δf%, the FBE-flow interpretation chart is used to re-update Δq i ;

[0026] 2-4) Based on the FBE data calculated for each segment and the corrected moisture content f′ wi , find the corresponding flow in the FBE-flow chart;

[0027] If there is no FBE-flow chart for the corresponding water content, the flow corresponding to the adjacent water content is used to interpolate and calculate the flow at this water content, and the flow rate of each layer is calculated by decreasing the flow rate layer by layer. i ;

[0028] 2-5) Output the inflow flow rate q of each layer segment i and the corrected moisture content f′ wi .

[0029] A preferred method for establishing an FBE-flow interpretation chart in the present invention is to conduct simulated oil well fluid flow experiments at different flow rates and water cuts in a distributed optical fiber flow monitoring experimental device. The experiments are performed at intervals of N% water cut, where N is a preset value. The flow rate at each water cut is compared with the FBE data extracted from the DAS signal, and a curve corresponding to the FBE data and flow rate at a specific water cut is fitted. Based on the large amount of experimental data, an FBE-flow interpretation chart is established, i.e., one FBE-flow interpretation chart is associated with each water cut. This method of establishing the chart by fitting is conventional technology and will not be described in detail here.

[0030] Preferably, the distributed optical fiber flow monitoring experimental device includes a simulated oil pipe, an inner-tube optical fiber arranged in the simulated oil pipe, an outer-tube optical fiber arranged outside the simulated oil pipe, a liquid supply module, and a DAS monitor, wherein the inner-tube optical fiber and the outer-tube optical fiber are connected to each other;

[0031] The DAS monitor is connected to the optical fiber inside the pipe or the optical fiber outside the pipe;

[0032] The side wall of the simulated oil pipe is provided with a plurality of production layer simulation holes;

[0033] The liquid supply module is connected to the production layer simulation hole and is used to inject oil well simulation fluids with different flow rates and different water contents into the simulation oil pipe.

[0034] Preferably, the liquid supply module of the present invention includes a water storage tank, an oil storage tank, a first pump body, a second pump body and a valve group;

[0035] The water tank is connected to the valve block inlet via a first pump body, while the oil tank is connected to the valve block inlet via a second pump body. The valve block outlets are each connected to a simulated well in the production layer. The first and second pump bodies adjust the water content to achieve uniform mixing of oil and water within the valve body.

[0036] In addition, an air supply module can also be set up to connect the air source to the valve group inlet through the pump body. By setting a flow meter, the flow of the air supply can be detected and controlled to perform a proportioned mixing of the water and gas phases or a proportioned mixing of the oil, gas and water phases.

[0037] Preferably, the distributed optical fiber flow monitoring experimental device of the present invention further comprises a waste liquid bucket, and the waste liquid bucket is connected to the outlet of the simulated oil pipe.

[0038] Preferably, the data preprocessing module converts the sound data related to the flow of formation fluid entering the wellbore collected during the production process into FBE data in the following detailed steps:

[0039] 1-1) The collected raw DAS signal is filtered to remove noise. This is accomplished by applying a bandpass filter to select a specific frequency range for analysis. The bandpass filter described herein is an algorithm that allows signals within a specific frequency range to pass while blocking (attenuating) signals at other frequencies. This is a prior art technique and will not be described in detail here.

[0040] 1-2) Convert the time series data into frequency domain data through fast Fourier transform and determine the signal strength at different frequencies;

[0041] 1-3) Select the appropriate frequency band based on the problem to be analyzed;

[0042] 1-4) Within the selected frequency band, the sum of the energies of all frequency components calculated as formula (1) is the frequency band energy FBE:

[0043]

[0044] where E(t) represents the energy of a frequency band with duration t, a and b are the low-frequency and high-frequency limits of the selected frequency band, respectively, and s(f) is the Fourier transform result at frequency f.

[0045] The present invention also discloses a method for interpreting oil well production profiles based on distributed optical fiber acoustic wave monitoring, comprising the following steps:

[0046] S1. Setting an FBE-flow interpretation chart in the FBE-flow chart module to show the relationship between FBE data related to formation fluid flow and flow rate as flow rate changes under different water cut ratios;

[0047] S2. Using a data preprocessing module, the sound data related to the flow of formation fluid entering the wellbore collected during the production process is converted into FBE data to obtain FBE data for each production layer;

[0048] S3. The oil well production profile interpretation module uses the sound data processed by the data preprocessing module and the FBE-flow interpretation chart in the FBE-flow chart module to determine the fluid flow rate and water content data of each production layer using a built-in algorithm;

[0049] S3.1. Based on the FBE data of each production layer calculated by the data preprocessing module, assume the water cut of each section and interpolate the corresponding flow rate in the FBE-flow chart. Specifically, the water cut of each layer section is arbitrarily assumed based on the wellhead water cut. Based on the assumed water cut of each layer section, the FBE data of each section calculated by the data preprocessing module is used to query the corresponding flow rate value in the FBE-flow chart corresponding to the assumed water cut of each layer section, or the flow rate values ​​of two adjacent FBE-flow interpretation charts corresponding to the water cut are used to linearly interpolate the flow rate value corresponding to the assumed water cut in the middle position, thereby obtaining the flow rate of each layer section under the assumed water cut;

[0050] The wellhead flow rate Q' under the assumed water cut is obtained by decreasing the flow rate layer by layer to obtain the inflow flow rate q for each layer. i ;

[0051] S3.2, use the built-in algorithm to calculate the water content of each layer and the inflow flow rate q of each layer i Verification includes the following steps:

[0052] S3.2.1. Calculate the error ΔQ = QQ′ between the actual wellhead flow rate and the wellhead flow rate under the current assumed water cut. In each layer, assume the water cut f′ w and the actual moisture content f w The error between them is x i , the change in flow rate when the water content increases or decreases by 1% under the corresponding FBE data is Δq i ;

[0053] Δq iThe calculation method is as follows: select the flow rate under the corresponding FBE data (i.e., the calculated FBE data) at the minimum and maximum water cuts in the FBE-flow chart, perform linear interpolation, and calculate the change in flow rate under unit water cut change; that is, gradually reduce the water cut selection range during correction, and ensure that the assumed water cut is within the selected range during subsequent selections, and try to keep the assumed value at the midpoint of the selected range;

[0054] S3.2.2. Establish the hypothetical flow error equation and water content error equation, which are Equation (2) and Equation (3) respectively:

[0055]

[0056] Where n is the number of production intervals, f w0 is the wellhead water content, f wi The water content assumed for each interval;

[0057] S3.2.3. Combine equations (2) and (3) and solve them to obtain the error x for each segment. i , further calculate the corrected moisture content f′ of each layer wi =f wi +x i , then query the FBE-flow chart according to the corrected water cut to obtain the sum of the flow rates of each layer, and compare it with the actual flow rate at the wellhead to recalculate the flow error ΔQ;

[0058] If ΔQ / Q<ε, the accuracy is met and the iteration is stopped and the corrected moisture content f′ of each layer is output. wi , or when the water content selection range is the water content interval Δf% corresponding to the establishment of the FBE-flow interpretation chart, stop the iteration, otherwise update Δq i , and return to step 2-1) to continue to correct the moisture content, the precision ε is pre-set and can be selected arbitrarily;

[0059] Δq i The updating method is as follows: by narrowing the selection range between the minimum and maximum water cuts of the FBE-flow chart, a more refined linear interpolation of the flow rate is performed under the corresponding FBE data to calculate the change in flow rate under unit water cut change; after narrowing the value range, a more refined linear interpolation operation can be performed;

[0060] S3.2.4. Based on the calculated FBE data for each section and the determined corrected moisture content f′ wi , find the corresponding flow in the FBE-flow chart;

[0061] If there is no FBE-flow chart with the corresponding water content, the flow corresponding to the adjacent water content is used to interpolate and calculate the flow at this water content. That is, the flow value corresponding to the FBE data is found in the FBE-flow charts of the two adjacent water content ratios and then interpolated. For example, if the water content is 83%, the 80% and 85% water content charts are selected, the corresponding values ​​are searched respectively, and then the flow corresponding to the water content of 83% is interpolated and calculated. The inflow flow q of each layer is calculated by decreasing the flow layer by layer. i ;

[0062] S3.2.5. Output the inflow flow rate q of each layer i and the corrected moisture content f′ wi .

[0063] Preferably, the method for establishing the FBE-flow interpretation chart of the present invention is as follows: by conducting an oil well simulated fluid flow experiment at different flow rates and different water cuts in a distributed optical fiber flow monitoring experimental device, the experiment is intervalled at every N% water cut, N being a preset value, the flow rate at this water cut and the FBE data extracted from the DAS signal are matched, and a curve corresponding to the FBE data and the flow rate when the water cut is determined is fitted, and based on a large amount of experimental data, an FBE-flow interpretation chart is established, that is, one FBE-flow interpretation chart corresponds to one water cut.

[0064] Preferably, in step S3.2.3, when the water content selection range is the water content interval Δf% corresponding to the establishment of the FBE-flow interpretation chart, When the water cut interval is less than Δf%, the FBE-flow interpretation chart is used to re-update Δq i .

[0065] Compared with the prior art, the present invention has the following beneficial effects:

[0066] 1. Provide a flow rate and water content chart and interpretation method for each downhole production well section based on distributed fiber optic acoustic wave monitoring. Since the water cut and flow rate corresponding to the measured FBE data are uncertain, by establishing an FBE-flow interpretation chart that shows the change of formation fluid with flow rate under different water cuts, when the number of production layers, wellhead water cut and wellhead flow rate are known, by assuming the water cut of each production layer, the flow rate corresponding to the assumed water cut is calculated based on the measured FBE data under the corresponding FBE-flow interpretation chart, and then the wellhead water cut and flow rate under the assumed water cut conditions are obtained. By controlling the error between the calculated wellhead flow rate and the actual wellhead flow rate detected, the flow rate and water content parameters of each production well section are determined, thereby realizing downhole production profile monitoring and interpretation.

[0067] 2. The production profile monitoring method provided by the present invention can obtain the flow rate and water content parameters of each production well section in real time.

[0068] 3. The production profile monitoring method provided by the present invention reduces the skill requirements for on-site operators, simplifies the operation process, and is easy to implement on-site.

[0069] 4. The production profile monitoring method provided by the present invention can effectively reduce the cost of oil well monitoring and production profile analysis. BRIEF DESCRIPTION OF THE DRAWINGS

[0070] Figure 1 This is a flow chart of a specific embodiment of the oil well production profile interpretation method based on distributed optical fiber acoustic wave sensing of the present invention;

[0071] Figure 2 Schematic diagram of the structure of an oil well production profile interpretation system based on distributed optical fiber acoustic wave monitoring in an embodiment of the present invention;

[0072] Figure 3 Schematic diagram of the structure of a distributed optical fiber flow monitoring experimental device in an embodiment of the present invention;

[0073] In the figure, 1DAS production profile monitor, 2optical cable, 3wellhead, 4production layer section I, 5production layer section II, 6production layer section III, 7casing, 8tubing, 9artificial bottom hole, 10optical fiber counterweight;

[0074] 100 simulated oil pipes, 101 production layer simulated holes, 200 optical fibers inside the pipe, 300 optical fibers outside the pipe, 400 liquid supply modules, 500 DAS monitors, and 600 waste liquid barrels;

[0075] 401 water storage tank, 402 oil storage tank, 403 first pump body, 404 second pump body, 405 valve group, 406 first flow meter, 407 second flow meter. DETAILED DESCRIPTION

[0076] The present invention will be described in detail below with reference to the embodiments and accompanying drawings, but is not limited thereto. In the present invention, "each section", "each section", "layer section", "production layer section" and "production well section" have the same meaning.

[0077] like Figure 2 As shown, an oil well production profile interpretation system based on distributed fiber optic acoustic monitoring (DAS) includes a casing 7, an oil pipe 8, an optical cable 2, and a surface-mounted DAS production profile monitor 1. The oil pipe 8 is located within the casing 7, and the optical cable 2 is located within the oil pipe 8 or on the outer wall of the oil pipe 8 or the outer wall of the casing 7. An optical fiber counterweight 10 is provided below the optical cable 2. This ensures that the optical fiber remains vertical and stable after being lowered. Otherwise, the spatial position of the downhole optical cable will be inaccurately calibrated, resulting in errors in the final result. The optical cable 2 is an armored optical cable.

[0078] The DAS production profile monitor 1 is connected to the optical cable 2 , and the DAS production profile monitor 1 includes a DAS oil well production profile interpretation module.

[0079] The DAS oil well production profile interpretation module is used to process the oil well DAS data acquired in real time by the optical cable to obtain the real-time flow rate and water content of each production layer section of the oil well.

[0080] Specifically, obtaining oil well DAS data under a certain working system includes:

[0081] 1) After arriving at the well site, confirm that the well being tested meets the logging conditions and use an optical time domain reflectometer on the ground to test the optical fiber in the armored cable to ensure that it is continuous without breakpoints and that the quality meets normal operating requirements.

[0082] 2) During testing, lower the instrument at a speed no faster than 3000 m / h. The lowering speed should be reduced when approaching abnormal points such as the downhole reducer, bottom ball (reverse circulation valve), bellmouth, cross, and tail pipe. During the lowering process, constantly monitor the tension indicator, depth indicator, and wellhead conditions. Stop the machine immediately if any obstruction is encountered.

[0083] 3) During measurement, the distributed acoustic sensor on the ground remains on to continuously detect the status of the optical cable in real time, obtaining the sound vibration signal distributed along the oil pipe 8 or the wellbore trajectory. At the same time, the data is stored in the ground storage device and monitored in real time on the ground monitoring screen to observe whether there are any abnormal conditions. If any abnormal conditions are found, they should be handled immediately.

[0084] 4) During the measurement process, check the quality of the logging data. If it does not meet the on-site quality control requirements, perform additional measurements.

[0085] The DAS oil well production profile interpretation module includes an FBE-flow chart module, a data preprocessing module and an oil well production profile interpretation module.

[0086] The FBE-flow chart module is used to set an FBE-flow interpretation chart showing the relationship between FBE data related to formation fluid flow and flow rate as the flow rate changes under different water content ratios.

[0087] The data preprocessing module is used to convert the sound data related to the flow of formation fluid entering the wellbore collected during the production process into FBE data to obtain FBE data of each production layer.

[0088] The oil well production profile interpretation module is used to use the sound data processed by the data preprocessing module and the FBE-flow interpretation plate in the FBE-flow plate module to determine the fluid flow and water content data of each production layer using a built-in algorithm.

[0089] The specific method is as follows:

[0090] Based on the FBE data for each production layer calculated by the data preprocessing module, an assumption is made regarding the water cut of each segment, and the flow rate corresponding to each segment is interpolated and calculated on the FBE-flow chart. The detailed steps are as follows: Based on the wellhead water cut, an arbitrary water cut is assumed for each layer segment. Based on this assumed water cut, the FBE data for each segment calculated by the data preprocessing module is used to query the corresponding flow rate value on the FBE-flow chart corresponding to each assumed water cut. Alternatively, the flow rate value corresponding to the assumed water cut at the intermediate position is linearly interpolated using the flow rate values ​​from two adjacent FBE-flow interpretation charts corresponding to the water cut, thereby obtaining the flow rate for each layer segment at the assumed water cut. In the present invention, any water cut assumption for each production segment can be made, but it is best to assume an increasing, decreasing, or equal assumption based on the wellhead water cut. An empirical formula can also be used for this assumption. For example, the FBE-flow chart in this embodiment covers moisture content from 0 to 100%, with intervals of 5% moisture content, totaling 21 charts. Each chart shows the correspondence between FBE data and flow rate under that moisture content. Two charts are fitted for each of the 21 charts: one inside the oil pipe 8 and one outside the oil pipe 8. The chart is selected based on the fiber's insertion position. If no chart corresponds to a hypothetical moisture content, two charts with adjacent hypothetical moisture content are used. The same FBE data is used to query a flow rate in each chart, and these two flow rates are interpolated to calculate the flow rate at the current hypothetical moisture content.

[0091] The wellhead flow rate Q' is obtained under the assumed water cut, and the flow rate of each layer is reduced layer by layer to obtain the inflow flow rate q i The FBE data of each layer segment can be obtained by calculation, but this data corresponds to the total flow of the layer segment, that is, the sum of the inflow flow of the layer segment and the flow of deeper layers. The production profile requires the inflow flow of each layer segment, so after obtaining the flow value, it is necessary to subtract it from the deep flow value to obtain the inflow flow of the layer segment.

[0092] The built-in algorithm is used to calculate the water content of each layer and the inflow rate q of each layer. i Verification includes the following steps:

[0093] 2-1) Calculate the error ΔQ = QQ′ between the actual wellhead flow rate and the wellhead flow rate under the current assumed water cut. In each layer, assume the water cut f′ w and the actual moisture content f w The error between them is x i , the change in flow rate when the water content increases or decreases by 1% under the FBE data in the corresponding FBE-flow chart is Δq i .

[0094] Δq iThe calculation method is as follows: select the flow rate with the minimum water cut and the maximum water cut under the corresponding FBE data in the FBE-flow chart, perform linear interpolation, and calculate the change in flow rate under unit water cut change.

[0095] 2-2) Establish the assumed flow error equation and water content error equation, which are equations (2) and (3) respectively:

[0096]

[0097] Where n is the number of production intervals, f w0 is the wellhead water content, f wi is the assumed water content for each layer.

[0098] 2-3) Combine equations (2) and (3) and solve to obtain the error x of each segment. i , further calculate the corrected moisture content f′ of each layer wi =f wi +x i , then query the FBE-flow chart according to the corrected water cut to obtain the sum of the flow rates of each layer, and compare it with the actual flow rate at the wellhead to recalculate the flow error ΔQ.

[0099] If ΔQ / Q<ε, the accuracy is met and the iteration is stopped and the corrected moisture content f′ of each layer is output. wi , or when the water content selection range is the water content interval Δf% corresponding to the establishment of the FBE-flow interpretation chart, stop the iteration, otherwise update Δq i , and return to step 2-1) to continue correcting the moisture content. The precision ε is preset and can be selected arbitrarily.

[0100] Δq i The updating method is as follows: by narrowing the selection range between the minimum and maximum water cuts of the FBE-flow chart, a more refined linear interpolation of the flow is performed under the corresponding FBE data to calculate the change in flow under unit water cut change; that is, the water cut selection range is gradually reduced during correction, and in subsequent selections, the assumed water cut is ensured to be within the selected range, and the assumed value is kept at the midpoint of the selection range as much as possible.

[0101] 2-4) Based on the FBE data calculated for each segment and the corrected moisture content f′ wi , find the corresponding flow in the FBE-Flow Chart.

[0102] If there is no FBE-flow chart for the corresponding water content, the flow corresponding to the adjacent water content is used to interpolate and calculate the flow at this water content, and the flow rate of each layer is calculated by decreasing the flow rate layer by layer. i .

[0103] 2-5) Output the inflow flow rate q of each layer segment i and the corrected moisture content f′ wi .

[0104] The method for establishing an FBE-flow interpretation chart is as follows: by conducting oil well simulated fluid flow experiments at different flow rates and different water cuts in a distributed fiber optic flow monitoring experimental device, the water cut needs to be fixed and then the experiments are conducted at different flow rates. The experiments are intervals of every N% water cut, where N is a preset value. The flow rate at this water cut is matched with the FBE data extracted from the DAS signal, and a curve corresponding to the FBE data and flow rate when the water cut is determined is fitted. Based on a large amount of experimental data, an FBE-flow interpretation chart is established, that is, each water cut corresponds to one FBE-flow interpretation chart.

[0105] In step 2-3), when the water content selection range is the corresponding water content interval Δf% when establishing the FBE-flow interpretation chart, When the water cut interval is less than Δf%, the FBE-flow interpretation chart is used to re-update Δq i .

[0106] like Figure 3 As shown, the distributed optical fiber flow monitoring experimental device includes a simulated oil pipe 100, an in-pipe optical fiber 200 arranged in the simulated oil pipe 100, an out-pipe optical fiber 300 arranged outside the simulated oil pipe, a liquid supply module 400 and a DAS monitor 500.

[0107] The DAS monitor 500 is connected to an in-pipe optical fiber 200 and an out-pipe optical fiber 300. The in-pipe optical fiber 200 and the out-pipe optical fiber 300 are interconnected. Specifically, the optical fibers are installed close to the inner and outer walls of the pipeline to be tested, namely the simulated oil pipeline 100. The fibers pass through the pipeline from the inside and then return to the outside to simultaneously measure the acoustic signals from the inner and outer walls of the pipeline, thereby fitting two FBE flow interpretation charts for the outside and inside of the oil pipeline. This is because the two sets of data monitored by the in-pipe optical fiber 200 and the out-pipe optical fiber 300 need to be compared, and variables can be controlled by simultaneous implementation. One side of the optical fiber is connected to the DAS monitor 500, while the other side is processed by a tail-end processing device. This tail-end processing is required to prevent a stable and clear signal from being obtained. A persistent and strong signal at the tail-end will disturb the overall signal. The tail-end processing device and processing method are conventional technology and will not be described in detail here.

[0108] The simulated oil pipe 100 is provided with multiple production layer simulation holes 101 on its sidewall, each equipped with a screen. The simulated oil pipe 100 is constructed by splicing three 1-meter-long screens of equal size onto the tail ends of three 7 / 8-inch oil pipes. The injection ports, or production layer simulation holes 101, are spaced 4 meters apart, with the three injection ports located between the three screens. The screens are connected by equal-sized oil pipes and are covered with five 1 / 2-inch casing pipes. The annular spaces at both ends of the screens are sealed with packers to ensure that fluid injection occurs only radially from the injection port into the tubing, preventing axial flow between the multiple injection ports.

[0109] The liquid supply module 400 is connected to the production layer simulation hole 101 and is used to inject simulated oil well fluids of varying flow rates and water contents into the simulated oil pipe. The simulated oil well fluids are formation fluids. The FBE flow interpretation charts obtained in the experiment correspond to single-layer conditions. Multi-layer injection and injection port replacement in the experiment are intended to reveal the impact of adjacent layers on a single layer in a multi-layered situation, thereby generating more accurate interpretation charts for single-layer conditions.

[0110] The liquid supply module 400 includes a water tank 401 , an oil tank 402 , a first pump body 403 , a second pump body 404 and a valve group 405 .

[0111] The water tank 401 is connected to the inlet of the valve block 405 via a first pump body 403. A first flowmeter 406 is provided between the first pump body 403 and the valve block 405. The oil tank 402 is connected to the inlet of the valve block 405 via a second pump body 404. A second flowmeter 407 is provided between the second pump body 404 and the valve block 405. The outlets of the valve block 405 are respectively connected to the production layer simulation holes 101. The flow rate of the liquid is adjusted by controlling the first pump body 403 and the second pump body 404, achieving oil-water mixing within the valve block 405. During the actual experiment, after the water content is adjusted, the different flow rates are continuously monitored while the water content remains unchanged.

[0112] In this embodiment, Figure 3 As shown, three production layer simulation holes 101 are provided, and the oil well simulation fluid is mixed in the valve group 405 and then enters the pipeline to be tested through three screen pipes at different positions.

[0113] The first pump body 403 and the second pump body 404 are both vertical centrifugal pumps with a maximum flow rate of 360m 3 d-1, controlled by a variable frequency speed regulator, meets the flow regulation requirements in the experiment; the first flow meter 406 and the second flow meter 407 are both electromagnetic flow meters with a measurement accuracy of 0.24m 3 d-1, measuring range is 0-480m 3 d-1, to meet the maximum flow requirement of the experiment.

[0114] The distributed fiber-optic flow monitoring experimental setup also includes a waste liquid bucket 600, connected to the outlet of the simulated oil pipe 100. The waste liquid bucket 600 is equipped with an oil outlet and a water outlet, connected to the oil tank 402 and water tank 401, respectively. After sedimentation, the waste liquid separates into oil and water within the waste liquid bucket 600. The oil and water can then be recycled back to the water tank 401 and oil tank 402 for reuse, reducing experimental costs. The water tank 401, oil tank 402, and waste liquid bucket 600 are constructed from 1000L transparent plastic containers, enabling real-time monitoring of the fluids within.

[0115] The detailed steps of converting the sound data related to the flow of formation fluid into the wellbore collected during the production process into FBE data by the data pre-processing module are as follows:

[0116] 1-1) The collected raw DAS signal is filtered to remove noise. This is accomplished by applying a bandpass filter to select the specific frequency range required for analysis. Different analysis requirements, such as sand production, wellbore leak detection, fracture parameter interpretation, and production profile interpretation, require different frequency ranges. The primary frequency bands containing the information differ for each requirement, but some overlap exists. Therefore, frequency band selection is highly dependent on experience and theoretical knowledge, and different researchers may select different frequency bands for the same problem.

[0117] 1-2) Convert the time series data into frequency domain data through fast Fourier transform to determine the signal strength at different frequencies.

[0118] 1-3) Select the appropriate frequency band based on the problem you need to analyze. For example, if analyzing low-frequency acoustic activity, consider selecting a frequency band of 0-10 Hz. Because you only need to analyze the production profile problem, the selected frequency band is fixed and the same frequency band used when creating the FBE-Flow Chart. This FBE-Flow Chart is designed specifically for this problem.

[0119] 1-4) Within the selected frequency band, the sum of the energies of all frequency components calculated as formula (1) is the frequency band energy (FBE):

[0120]

[0121] In formula (1), E(t) represents the frequency band energy of duration t, a and b represent the low-frequency and high-frequency limits of the selected frequency band, respectively, and s(f) is the Fourier transform result at frequency f. FBE data is the characteristic frequency band energy (FBE), also known as frequency band energy. This data contains a large amount of information. Most analyses of DAS-collected data require calculating and then analyzing FBE data. For example, low-frequency FBE data contains information such as fluid flow, while higher-frequency FBE data can reflect information such as bottomhole sand production and lost circulation.

[0122] A method for interpreting oil well production profiles based on distributed fiber optic acoustic monitoring interprets the sound signals reflected from the optical fiber and processes them using the DAS production profile interpretation module to ultimately obtain the real-time flow and water content of each production layer of the oil well. Figure 1 As shown, the following steps are included:

[0123] S1. In the FBE-flow chart module, an FBE-flow interpretation chart is set to show the relationship between FBE data related to formation fluid flow and flow rate as the flow rate changes under different water cut ratios.

[0124] S2. Use the data preprocessing module to convert the sound data related to the flow of formation fluid entering the wellbore collected during the production process into FBE data to obtain the FBE data of each production layer.

[0125] S3. The oil well production profile interpretation module uses the sound data processed by the data preprocessing module and the FBE-flow interpretation chart in the FBE-flow chart module to determine the fluid flow and water content data of each production layer using a built-in algorithm.

[0126] S3.1. Based on the FBE data of each production layer calculated by the data preprocessing module, assume the water cut of each section and interpolate and calculate the corresponding flow rate in the FBE-flow chart. Specifically, assume the water cut of each layer according to the wellhead water cut. Based on the assumed water cut of each layer, use the FBE data of each section calculated by the data preprocessing module to query the corresponding flow value in the FBE-flow chart corresponding to the assumed water cut of each layer, or use the flow values ​​of two adjacent FBE-flow interpretation charts corresponding to the water cut to perform linear interpolation on the flow value corresponding to the assumed water cut in the middle position.

[0127] The wellhead flow rate Q' is obtained under the assumed water cut, and the flow rate of each layer is reduced layer by layer to obtain the inflow flow rate q i ;

[0128] S3.2, use the built-in algorithm to calculate the water content of each layer and the inflow flow rate q of each layer iVerification includes the following steps:

[0129] S3.2.1. Calculate the error ΔQ = QQ′ between the actual wellhead flow rate and the wellhead flow rate under the current assumed water cut. In each layer, assume the water cut f′ w and the actual moisture content f w The error between them is x i , the change in flow rate when the water content increases or decreases by 1% under the corresponding FBE data is Δq i .

[0130] Δq i The calculation method is as follows: select the flow rates with the minimum and maximum water cuts in the FBE-flow chart under the corresponding FBE data, perform linear interpolation, and calculate the change in flow rate under unit water cut change; that is, gradually reduce the water cut selection range during correction, and ensure that the assumed water cut is within the selected range during subsequent selections, and try to keep the assumed value at the midpoint of the selected range.

[0131] S3.2.2. Establish the hypothetical flow error equation and water content error equation, which are Equation (2) and Equation (3) respectively:

[0132]

[0133] Where n is the number of production intervals, f w0 is the wellhead water content, f wi is the assumed water content for each layer.

[0134] S3.2.3. Combine equations (2) and (3) and solve them to obtain the error x for each segment. i , further calculate the corrected moisture content f′ of each layer wi =f wi +x i , then query the FBE-flow chart according to the corrected water cut to obtain the sum of the flow rates of each layer, and compare it with the actual flow rate at the wellhead to recalculate the flow error ΔQ.

[0135] If ΔQ / Q<ε, the accuracy is met and the iteration is stopped and the corrected moisture content f′ of each layer is output. wi , or when the water content selection range is the water content interval Δf% corresponding to the establishment of the FBE-flow interpretation chart, stop the iteration, otherwise update Δq i , and return to step 2-1) to continue correcting the moisture content. The precision ε is preset and can be selected arbitrarily.

[0136] Δq iThe updating method is as follows: by narrowing the selection range between the minimum and maximum water cuts of the FBE-flow chart, a more refined linear interpolation of the flow is performed under the corresponding FBE data to calculate the change in flow per unit water cut change.

[0137] S3.2.4. Based on the calculated FBE data for each section and the determined corrected moisture content f′ wi , find the corresponding flow in the FBE-Flow Chart.

[0138] If there is no FBE-flow chart for the corresponding water content, the flow corresponding to the adjacent water content is used to interpolate and calculate the flow at this water content, and the flow rate of each layer is calculated by decreasing the flow rate layer by layer. i .

[0139] S3.2.5. Output the inflow flow rate q of each layer i and the corrected moisture content f′ wi .

[0140] The method for establishing an FBE-flow interpretation chart is as follows: by conducting oil well simulated fluid flow experiments at different flow rates and different water cuts in a distributed fiber optic flow monitoring experimental device, the experiment is intervalled at every N% water cut, where N is a preset value. The flow rate at this water cut is matched with the FBE data extracted from the DAS signal, and a curve corresponding to the FBE data and flow rate when the water cut is determined is fitted. Based on a large amount of experimental data, an FBE-flow interpretation chart is established, that is, each water cut corresponds to an FBE-flow interpretation chart.

[0141] In step S3.2.3, when the water content selection range is the corresponding water content interval Δf% when establishing the FBE-flow interpretation chart, When the water cut interval is less than Δf%, the FBE-flow interpretation chart is used to re-update Δq i .

[0142] Application Example 1

[0143] like Figure 2 As shown, when the monitoring method of the present invention is applied to long-term real-time monitoring of oil well production profiles, the specific steps are as follows:

[0144] Step 1: Determine the length of the production string according to the process. Ensure that the length of the optical cable 2 exceeds the deepest production layer or can extend to the bottom of the artificial well 9. Connect the optical fiber counterweight 10 to the end of the optical cable 2; fix the portion of the optical cable 2 that is shorter than the oil pipe 8 to the oil pipe 8. The fixing method can be clamped, welded, or prefabricated cable troughs according to the on-site conditions; lower the optical cable 2 into the well along with the production string, that is, inside the casing 7.

[0145] Step 2: Pass the upper end of the optical cable 2 through the wellhead 3 and connect it to the DAS production profile monitor 1 placed on the ground.

[0146] Step 3: Calibrate the spatial position of the downhole optical cable, and obtain the production layer segment I4, production layer segment II5, and production layer segment III6 in this application example.

[0147] Step 4: Start production and start the DAS production profile monitor 1.

[0148] Step 5: Observe the sound data displayed by the display system in the DAS production profile monitor 1, and start recording the sound data after the data stabilizes.

[0149] Step 6: Use the DAS oil well production profile interpretation module built into the computer control and display system of the DAS production profile monitor 1 to interpret the sound data recorded in step 5 in real time to obtain the fluid flow and water content data of the oil well production layer.

[0150] Step 7: Change the working system and repeat steps 5 and 6 to obtain the fluid flow and water content data of the oil well production layer under different working systems.

[0151] Application Example 2

[0152] like Figure 2 As shown, when the system of the present invention is applied to real-time monitoring of oil well production profiles, the specific steps are as follows:

[0153] Step 1: Determine the production string length according to the process, ensuring that the length of the optical cable 2 exceeds the deepest production zone. Attach the fiber optic counterweight 10 to the end of the optical cable 2. Lower the optical cable 2 into the well along with the oil pipe 8. For long-term monitoring, the optical cable 2 is lowered from the outside of the oil pipe 8. For short-term monitoring, the optical cable 2 is typically lowered directly from the inside of the oil pipe 8, as packers and other devices are often placed in the annulus of the casing, making it difficult to lower the cable into the well.

[0154] Step 2: Pass the upper end of the optical cable 2 through the wellhead 3 and connect it to the DAS production profile monitor 1 placed on the ground.

[0155] Step 3: Calibrate the spatial position of the downhole optical cable, and obtain the production layer segment I4, the production layer segment II5, and the production layer segment III6 in this application example.

[0156] Step 4: Start production and start the DAS production profile monitor 1.

[0157] Step 5: Observe the sound data displayed by the display system in the DAS production profile monitor 1, and start recording the sound data after the data stabilizes.

[0158] Step 6: Use the DAS oil well production profile interpretation module built into the computer control and display system of the DAS production profile monitor 1 to interpret the sound data recorded in step 5 in real time to obtain the fluid flow and water content data of the oil well production layer.

[0159] Step 7: Change the working system and repeat steps 5 and 6 to obtain the fluid flow and water content data of the oil well production layer under different working systems.

[0160] Step 8: After the test is completed, the DAS production profile monitor 1 is turned off, and the optical cable 2 is removed from the oil pipe 8 to complete the real-time monitoring of the oil well production profile.

Claims

1. An oil well production profile interpretation system based on distributed fiber optic acoustic wave monitoring, characterized by: It includes a casing, an oil pipe, an optical cable and a DAS production profile monitor arranged on the ground, wherein the oil pipe is located in the casing, and the optical cable is arranged in the oil pipe or on the outer wall of the oil pipe or on the outer wall of the casing; The DAS production profile monitor is connected to the optical cable, and the DAS production profile monitor includes a DAS oil well production profile interpretation module; The DAS oil well production profile interpretation module is used to process the oil well DAS data acquired in real time by the optical cable to obtain the real-time flow rate and water content of each production layer section of the oil well; The DAS oil well production profile interpretation module includes an FBE-flow chart module, a data pre-processing module and an oil well production profile interpretation module; The FBE-flow chart module is used to set an FBE-flow interpretation chart showing the relationship between FBE data related to formation fluid flow and flow rate as the flow rate changes under different water content ratios; The data preprocessing module is used to convert the sound data related to the flow of formation fluid entering the wellbore collected during the production process into FBE data to obtain FBE data of each production layer; The oil well production profile interpretation module is used to utilize the sound data processed by the data preprocessing module and, based on the FBE-flow interpretation plate in the FBE-flow plate module, assume the water cut of each production layer under the condition that the number of production layers, the wellhead water cut and the wellhead flow rate are known. Based on the FBE data of each production layer calculated by the data preprocessing module under the corresponding FBE-flow interpretation plate, the flow rate corresponding to the assumed water cut is calculated, and then the wellhead water cut and flow rate under the assumed water cut conditions are obtained. By controlling the error between the obtained wellhead flow rate and the detected actual wellhead flow rate, the flow rate and water cut parameters of each production well section are determined.

2. The oil well production profile interpretation system based on distributed fiber optic acoustic wave monitoring according to claim 1 is characterized in that: The oil well production profile interpretation module interpolates and calculates the flow rate corresponding to each section in the FBE-flow chart based on the FBE data of each production layer calculated by the data preprocessing module and the water cut of each section. The detailed steps are as follows: arbitrarily assume the water cut of each layer section, and based on the assumed water cut of each layer section, use the FBE data of each section calculated by the data preprocessing module to query the corresponding flow value in the FBE-flow chart corresponding to the assumed water cut of each layer section, or use the flow values ​​of two adjacent water cut corresponding FBE-flow interpretation charts to linearly interpolate the flow value corresponding to the assumed water cut in the middle position, thereby obtaining the flow rate of each layer section under the assumed water cut; The wellhead flow rate under the assumed water cut is thus obtained , the flow rate of each layer is reduced layer by layer to obtain the inflow flow of each layer segment ; Use built-in algorithms to calculate the water content of each layer and the inflow rate of each layer Verification includes the following steps: 2-1) Calculate the error between the actual wellhead flow rate and the wellhead flow rate under the current assumed water cut , in each layer, assuming the water content and actual moisture content The error between , the change in flow rate when the water content increases or decreases by 1% under the FBE data in the corresponding FBE-flow chart is ; The calculation method is as follows: select the flow rate with the minimum water content and the maximum water content under the corresponding FBE data in the FBE-flow chart, perform linear interpolation, and calculate the change in flow rate under unit water content change; 2-2) Establish the assumed flow error equation and water content error equation, which are Equation (2) and Equation (3) respectively: （2） （3） Where n is the number of production intervals, is the wellhead water content, The water content assumed for each interval; 2-3) Combine equations (2) and (3) and solve to obtain the error of each segment , further calculate the corrected moisture content of each layer Then, according to the corrected water cut, query the FBE-flow chart to obtain the sum of the flow rates of each layer, compare it with the actual flow rate at the wellhead, and recalculate the flow error ∆Q; like , then the accuracy is met and the iteration is stopped and the corrected moisture content of each layer is output , or the water content selection range is the corresponding water content interval Δ when establishing the FBE-flow interpretation chart f %, stop iteration, otherwise update , and return to step 2-1) to continue to correct the moisture content, the accuracy Pre-set and select any one; The updating method is as follows: by narrowing the selection range between the minimum and maximum water cuts of the FBE-flow chart, a more refined linear interpolation of the flow is performed under the corresponding FBE data to calculate the change in flow under unit water cut change; when the water cut selection range is the corresponding water cut interval Δ f %, When the water interval is less than Δ f % FBE-Flow Explanation Chart is updated ; 2-4) Based on the calculated FBE data for each section and the corrected moisture content , find the corresponding flow in the FBE-flow chart; If there is no FBE-flow chart for the corresponding water content, the flow corresponding to the adjacent water content is used to interpolate and calculate the flow at this water content, and the flow rate of each layer is calculated by decreasing the flow rate layer by layer. ; 2-5) Output the inflow flow of each layer segment and the corrected moisture content .

3. The oil well production profile interpretation system based on distributed fiber optic acoustic wave monitoring according to claim 1 is characterized in that: The method for establishing the FBE-flow interpretation chart is as follows: by conducting oil well simulated fluid flow experiments at different flow rates and different water cuts in a distributed optical fiber flow monitoring experimental device, the experiment is intervalled at every N% water cut, where N is a preset value, and the flow rate at this water cut is matched with the FBE data extracted from the DAS signal. A curve corresponding to the FBE data and flow rate when the water cut is determined is fitted, and based on a large amount of experimental data, an FBE-flow interpretation chart is established, that is, one FBE-flow interpretation chart corresponds to one water cut.

4. The oil well production profile interpretation system based on distributed fiber optic acoustic wave monitoring according to claim 3 is characterized in that: The distributed optical fiber flow monitoring experimental device includes a simulated oil pipe, an inner optical fiber arranged in the simulated oil pipe, an outer optical fiber arranged outside the simulated oil pipe, a liquid supply module and a DAS monitor, wherein the inner optical fiber and the outer optical fiber are connected to each other; The DAS monitor is connected to the optical fiber inside the pipe or the optical fiber outside the pipe; The side wall of the simulated oil pipe is provided with a plurality of production layer simulation holes; The liquid supply module is connected to the production layer simulation hole and is used to inject oil well simulation fluids with different flow rates and different water contents into the simulation oil pipe.

5. The oil well production profile interpretation system based on distributed fiber optic acoustic wave monitoring according to claim 4 is characterized in that: The liquid supply module includes a water storage tank, an oil storage tank, a first pump body, a second pump body and a valve group; The water storage tank is connected to the inlet of the valve group through the first pump body, the oil storage tank is connected to the inlet of the valve group through the second pump body, and the outlets of the valve group are respectively connected to the production layer simulation holes.

6. The oil well production profile interpretation system based on distributed fiber optic acoustic wave monitoring according to claim 5, characterized in that: The distributed optical fiber flow monitoring experimental device further comprises a waste liquid bucket, which is connected to the outlet of the simulated oil pipe.

7. The oil well production profile interpretation system based on distributed fiber optic acoustic wave monitoring according to claim 1, characterized in that: The detailed steps of converting the sound data related to the flow of formation fluid into the wellbore collected during the production process into FBE data by the data pre-processing module are as follows: 1-1) Filter the acquired raw DAS signal to remove noise. This is done by applying a bandpass filter to select the specific frequency range required for analysis. 1-2) Convert the time series data into frequency domain data through fast Fourier transform to determine the signal strength at different frequencies; 1-3) Select the appropriate frequency band based on the problem to be analyzed; 1-4) Within the selected frequency band, the sum of the energies of all frequency components calculated as formula (1) is the frequency band energy FBE: （1） Where E(t) represents the energy of the frequency band with a duration of t, a and b are the low-frequency and high-frequency limits of the selected frequency band, respectively. is the Fourier transform result at frequency f.

8. A method for interpreting oil well production profiles based on distributed fiber optic acoustic wave monitoring, characterized in that: The following steps are involved: S1. Setting an FBE-flow interpretation chart in the FBE-flow chart module to show the relationship between FBE data related to formation fluid flow and flow rate as flow rate changes under different water cut ratios; S2. Using a data preprocessing module, the sound data related to the flow of formation fluid entering the wellbore collected during the production process is converted into FBE data to obtain FBE data for each production layer; S3. The oil well production profile interpretation module uses the sound data processed by the data preprocessing module and the FBE-flow interpretation chart in the FBE-flow chart module to determine the fluid flow rate and water content data of each production layer using a built-in algorithm; S3.

1. Based on the FBE data of each production layer calculated by the data preprocessing module, assume the water cut of each section and interpolate the corresponding flow rate in the FBE-flow chart. Specifically, assume the water cut of each layer section. Based on the assumed water cut of each layer section, use the FBE data of each section calculated by the data preprocessing module to query the corresponding flow rate value in the FBE-flow chart corresponding to the assumed water cut of each layer section, or use the flow rate values ​​of two adjacent FBE-flow interpretation charts corresponding to the water cut to linearly interpolate the flow rate value corresponding to the assumed water cut in the middle position, thereby obtaining the flow rate of each layer section under the assumed water cut; The wellhead flow rate under the assumed water cut is thus obtained , the flow rate of each layer is reduced layer by layer to obtain the inflow flow of each layer segment ; S3.2, use the built-in algorithm to calculate the water content of each layer and the inflow rate of each layer Verification includes the following steps: S3.2.

1. Calculate the error between the actual wellhead flow rate and the wellhead flow rate under the current assumed water cut. , in each layer, assuming the water content and actual moisture content The error between , the change in flow rate when the water content increases or decreases by 1% under the corresponding FBE data is ; The calculation method is as follows: select the flow rate with the minimum water content and the maximum water content under the corresponding FBE data in the FBE-flow chart, perform linear interpolation, and calculate the change in flow rate under unit water content change; S3.2.

2. Establish the assumed flow error equation and water content error equation, which are Equation (2) and Equation (3) respectively: （2） （3） Where n is the number of production intervals, is the wellhead water content, The water content assumed for each interval; S3.2.

3. Combine equations (2) and (3) and solve to obtain the error of each segment , further calculate the corrected moisture content of each layer Then, according to the corrected water cut, query the FBE-flow chart to obtain the sum of the flow rates of each layer, compare it with the actual flow rate at the wellhead, and recalculate the flow error ∆Q; like , then the accuracy is met and the iteration is stopped and the corrected moisture content of each layer is output , or the water content selection range is the corresponding water content interval Δ when establishing the FBE-flow interpretation chart f %, stop iteration, otherwise update , and return to step 2-1) to continue to correct the moisture content, the accuracy Pre-set and select any one; The updating method is as follows: by narrowing the selection range between the minimum and maximum water cuts of the FBE-flow chart, a more refined linear interpolation of the flow rate is performed under the corresponding FBE data to calculate the change in flow rate under unit water cut change; S3.2.

4. Based on the calculated FBE data for each segment and the determined corrected moisture content , find the corresponding flow in the FBE-flow chart; If there is no FBE-flow chart for the corresponding water content, the flow corresponding to the adjacent water content is used to interpolate and calculate the flow at this water content, and the flow rate of each layer is calculated by decreasing the flow rate layer by layer. ; S3.2.

5. Output the inflow flow of each layer and the corrected moisture content .

9. The method for interpreting oil well production profiles based on distributed optical fiber acoustic wave monitoring according to claim 8, characterized in that: The method for establishing the FBE-flow interpretation chart is as follows: by conducting oil well simulated fluid flow experiments at different flow rates and different water cuts in a distributed optical fiber flow monitoring experimental device, the experiment is intervalled at every N% water cut, where N is a preset value, and the flow rate at this water cut is matched with the FBE data extracted from the DAS signal. A curve corresponding to the FBE data and flow rate when the water cut is determined is fitted, and based on a large amount of experimental data, an FBE-flow interpretation chart is established, that is, one FBE-flow interpretation chart corresponds to one water cut.

10. The method for interpreting oil well production profiles based on distributed fiber optic acoustic wave monitoring according to claim 8, characterized in that: In step S3.2.3, when the water content selection range is the corresponding water content interval Δf% when establishing the FBE-flow interpretation chart, When the water cut interval is less than Δf%, the FBE-flow interpretation chart is updated. .

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