Active oil-gas-water flow monitoring device based on optical fiber sound wave sensing and interpretation method

Abstract

The invention provides an active oil-gas-water flow monitoring device based on optical fiber sound wave sensing and an interpretation method.The device comprises a horizontal wellbore part, an injection system part, an active signal monitoring part and a DAS data acquisition part, and the horizontal wellbore part simulates that underground fluid flows into a wellbore in the radial direction and flows in the wellbore; the injection system part is connected to the horizontal shaft part and injects oil-gas-water three-phase fluid into the horizontal shaft part, the active signal monitoring part enhances optical fiber DAS signals, and the DAS data acquisition part simulates an on-site optical cable well entering mode and performs DAS data acquisition. The problems that optical fiber DAS signals are difficult to monitor and collect under the low liquid amount, optical fiber DAS signal frequency band screening is difficult, and production characteristics such as flow water content are difficult to explain are solved, the liquid production parameter interpretation precision is improved, establishment of a field production system is guided, and field multi-layer (section) oil well development understanding is promoted.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of oil and gas exploitation, in particular to a passive oil and gas water flow monitoring device based on optical fiber acoustic sensing and an interpretation method. BACKGROUND

[0002] Real-time monitoring and accurate interpretation of the liquid production profile of an oil well are of great significance to the judgment of the production status of the oil well, especially multi-layer and multi-section horizontal wells, and the adjustment of the field development plan. At present, the commonly used production profile testing methods in domestic and foreign oilfields mainly include production dynamic logging, engineering logging and production layer evaluation method logging. Production dynamic logging mainly includes flow meters, fluid density meters, thermometers and pressure gauges, etc. Engineering logging includes magnetic positioning logging instruments, radioactive tracers and wellbore fluid scanning imaging logging instruments, etc. Production layer evaluation method logging includes boron neutron lifetime, C / O ratio logging, and other conventional logging method combinations, etc. However, under the current well conditions and mechanical pumping production in oilfields, it is difficult for traditional electronic flow monitoring instruments to achieve liquid production profile monitoring. For horizontal wells, traditional electronic instruments are difficult to be tripped in and out, and it is difficult for them to enter the horizontal section of the oil layer. For heavy oil thermal recovery wells, traditional instruments cannot withstand high temperatures for a long time, and are prone to sticking and resistance during tripping. The response of the instrument is weak, and the testing accuracy is low. In addition, the traditional electronic instrument logging belongs to point testing, and after testing at one position, the instrument needs to be tripped to test other positions. Different positions cannot be tested synchronously, so it is impossible to achieve real-time monitoring of the entire wellbore section and the entire cycle.

[0003] Distributed optical fiber sensing technology is a downhole monitoring technology developed in recent years, which has the advantages of strong anti-electromagnetic interference ability, corrosion resistance, high temperature resistance, high spatial resolution and good real-time performance. Its working principle is that changes in temperature, pressure and stress and strain around the optical fiber will affect the laser signal transmitted by the optical fiber, causing changes in the intensity, phase, amplitude and light intensity of the laser signal. By demodulating these parameter changes, the temperature, pressure and fluid flow around the optical fiber can be measured. In the early 1990s, distributed optical fiber monitoring technology began to be used for downhole production monitoring. Subsequently, Schlumberger, Halliburton, Silixa and other companies have developed downhole distributed optical fiber monitoring technology and applied it in the field of oilfields. Among them, the rapid development of distributed acoustic sensing (DAS) technology provides a new important means for multi-layer (section) oil well liquid production profile interpretation, and is the new direction of development of oil and gas well production dynamic monitoring technology.

[0004] At present, optical fiber DAS technology has been partially applied in oilfields, and some understanding has been achieved on site, but it is mostly for production dynamic monitoring of high liquid volume wells. For low liquid volume and high water cut oil wells, how to realize the monitoring, collection and interpretation analysis of optical fiber DAS weak vibration signals and flow and water cut still faces great challenges. In addition, the current DAS signal processing still lacks reasonable frequency band selection method and mature theoretical interpretation model.

[0005] In the Chinese patent application with application number: CN202110788474.7, a wellbore flow monitoring system and a flow and water cut interpretation method are involved. The distributed optical fiber temperature monitoring (DTS), DAS monitoring and single-point thermal excitation functions are integrated into one, realizing the simultaneous monitoring of downhole temperature and acoustic wave multi-parameters, and meeting the requirements of real-time monitoring of downhole fluid state in high temperature, high pressure and corrosive environment. A flow and water cut interpretation method is constructed, especially for oil, water and gas three-phase fluid in oil wells, the temperature information and acoustic wave information after fluid pulse heating are fused and interpreted, the flow and water cut situation is interpreted from multiple angles, the purpose of mutual verification and reducing multiple solutions is achieved, the obtained fluid flow and water cut and gas cut are more accurate, providing more accurate data support for actual production, which helps to save production cost and reduce production risk.

[0006] In the Chinese patent application with application number: CN202110531730.4, a downhole fluid monitoring system and method based on distributed optical fiber hydrophone are involved. The sound-sensitive and heat-sensitive sensing armored optical cable is bound outside the oil and gas pipe of the vertical well, deviated well or horizontal well by metal clips, a downhole sensing unit of a liquid production profile or water absorption profile measurement and long-term dynamic monitoring system for oil and gas production wells or water injection wells is constructed, and the DAS and DTS modems near the wellhead are added to jointly form a downhole liquid production profile or water absorption profile measurement and fluid distribution dynamic monitoring system, which can long-term monitor the liquid production or water absorption profile of oil and gas production wells or water injection wells.

[0007] In the Chinese patent application with application number: CN201910640346.0, a production profile monitoring method based on DAS and DTS monitoring is involved. The sound signals reflected by the single-mode sound-sensitive optical fiber and the temperature signals reflected by the multi-mode temperature-sensitive optical fiber are processed by the DTS / DAS injection-production well production profile interpretation module, and finally the real-time flow and water cut of each production layer of the injection-production well are obtained. The production profile monitoring method in the invention can complete "one-time well operation to realize full well production profile test"; can realize real-time, long-term or temporary monitoring of the production profile of injection-production wells; can obtain the flow and water cut parameters of each production well in real time; can judge the production contribution of each well section in real time; can evaluate the production effect of downhole operation measures and production parameter adjustment of injection-production wells in real time.

[0008] The above prior art is quite different from the present application, and cannot solve the technical problems we want to solve, therefore we have invented a new optical fiber DAS signal frequency band intelligent screening and downhole each production layer flow rate and water cut interpretation method. SUMMARY

[0009] The purpose of the present application is to provide an optical fiber acoustic sensing active oil, gas and water flow monitoring device and interpretation method for improving the interpretation accuracy of flow rate and water cut and other production parameters of field production wells, especially multi-layer straight and inclined wells and multi-section long horizontal wells.

[0010] The purpose of the present application can be achieved by the following technical measures: an optical fiber acoustic sensing active oil, gas and water flow monitoring device, which comprises a horizontal wellbore part, an injection system part, an active signal monitoring part and a DAS data acquisition part, the horizontal wellbore part simulates the radial flow of downhole fluid into the wellbore and the flow in the wellbore, the injection system part is connected to the horizontal wellbore part and injects oil, gas and water three-phase fluid into the horizontal wellbore part, the active signal monitoring part is located in the horizontal wellbore part and enhances the optical fiber DAS signal, and the DAS data acquisition part simulates the field optical cable into the well mode and performs DAS data acquisition.

[0011] The purpose of the present application can also be achieved by the following technical measures:

[0012] The horizontal wellbore part comprises a casing, a tubing, a first injection hole, a second injection hole, a third injection hole, a first packer, a second packer, a third packer, a glass tube and a tail hose, the tubing is located in the casing, the first injection hole, the second injection hole and the third injection hole are located on the casing, oil, gas and water fluid can be injected from any one, two or three injection holes according to laboratory experiment requirements, and the injection can be single-phase, two-phase or three-phase fluid, the first packer, the second packer and the third packer are used to seal the fluid in the corresponding three injection holes, respectively, the tail hose is connected between the tubing and the glass tube, oil, gas and water three-phase fluid flows in the tubing and finally flows out of the horizontal wellbore part through the glass tube and the tail hose.

[0013] The injection system comprises an injection system part comprising an oil tank, a water tank, a gas tank, a tail liquid tank, an oil injection pump, a water injection pump, a gas injection pump, an oil control one-way valve, a water control one-way valve, a gas control one-way valve, a ground connection pipeline and a ground manifold, the oil injection pump is located between the oil tank and the oil control one-way valve, the water injection pump is located between the water tank and the water control one-way valve, the gas injection pump is located between the gas tank and the gas control one-way valve, the ground connection pipeline is connected to the oil control one-way valve, the water control one-way valve and the gas control one-way valve respectively, the ground manifold is located between the ground connection pipeline and the horizontal wellbore part, the oil, gas and water in the oil tank, the water tank and the gas tank are fully mixed in the ground connection pipeline and then injected into the horizontal wellbore part through the ground manifold, and the tail liquid tank is connected to the tail end hose and receives the three-phase fluid flowing out of the tail end hose, the oil and water in the tail liquid tank are separated after standing and then re-injected into the oil tank and the water tank.

[0014] The active signal monitoring part comprises an active signal enhancement device, when the horizontal wellbore part is in oil-water two-phase flow, the active signal enhancement device adopts a throttling device to throttle the fluid through a small hole, and a vortex plug can be generated in the fluid flow.

[0015] When the horizontal wellbore part is in oil-gas, gas-water or oil-gas-water flow, the active signal enhancement device adopts an electric heating device to locally and concentratedly heat the fluid in the active signal enhancement area of the horizontal wellbore part, and a heat plug can be generated in the process of fluid flow, so as to increase the vibration intensity of the sound wave of the fluid flow and further enhance the visibility of the DAS signal.

[0016] The DAS data acquisition part comprises a test optical cable and a ground demodulator, the test optical cable is bundled on the outer wall of the oil pipe to simulate the mode of the field optical cable into the well, the DAS ground demodulator is connected to the test optical cable, the test optical cable collects the optical fiber DAS signal under different pressures and temperatures, different oil-gas-water flow and proportion, and transmits the signal to the DAS ground demodulator.

[0017] The purpose of the application can also be achieved by the following technical measures: an active oil-gas-water flow monitoring and interpretation method of optical fiber sound wave sensing, which adopts an active oil-gas-water flow monitoring device of optical fiber sound wave sensing, comprising:

[0018] Step 1, carry out optical fiber monitoring experiment of oil-gas-water three-phase flow, and collect experimental data;

[0019] Step 2, pre-process the original sound wave data of DAS;

[0020] Step 3, analyze the response of DAS signal under different frequency bands and intelligently screen the frequency bands;

[0021] Step 4, establish the flow water cut interpretation chart based on FBE acoustic wave frequency band energy;

[0022] Step 5, apply the chart to the field well, evaluate the production fluid profile interpretation effect;

[0023] Step 6, integrate the field well data into the interpretation chart, enrich the chart content.

[0024] The object of the application can also be achieved by the following technical measures:

[0025] In step 1, a large number of oil, gas and water three-phase flow optical fiber monitoring experiments are carried out by using the active oil, gas and water flow monitoring device of the optical fiber acoustic wave sensor, and a large number of optical fiber DAS signals under different pressures and temperatures, different oil, gas and water flow and proportion are collected.

[0026] In step 1, after the fluid flows stably in the wellbore, the optical fiber DAS signal monitored in the test area of the fluid stable flow in the pipeline under different experimental conditions is collected by using the DAS ground demodulator; in the oil-water two-phase flow monitoring experiment, the water cut is increased by 5% as the step size, the water cut range is 0-100%, and the flow range is 10-120m 3 / d, which meets the optical fiber DAS monitoring under low liquid volume.

[0027] In step 2, the preprocessing includes special outlier data cleaning and data normalization processing.

[0028] In step 2, at any position point, the DAS original acoustic wave data is a row of vectors, which represents the phase change of the optical fiber laser signal at this position point with different time; the outlier data cleaning method adopts the method of observing outliers by box plot and supplementing outliers by adjacent average value; the box plot has five reference lines, which are maximum, minimum, upper quartile, lower quartile and median; the upper limit of the box plot is the maximum value in the non-outlier range, and the lower limit is the minimum value in the non-outlier range; when the DAS data is outside the upper limit and the lower limit, it is determined that it is extremely abnormal, and the average value of the two adjacent numbers can be used to supplement the interpolation after deleting; the quartile distance in the box plot is the difference between the upper quartile and the lower quartile, and the expressions of the upper limit and the lower limit are:

[0029] Upper limit = upper quartile + 1.5*quartile distance (1) lower limit = lower quartile - 1.5*quartile distance (2)

[0030] In step 2, the data normalization processing can preferably be maximum-minimum normalization, energy normalization and Z-Score normalization, so as to eliminate the influence of magnitude and dimension, and the specific normalization mode is selected according to the effect of DAS data outlier processing; the maximum-minimum normalization is very sensitive to the existence of outliers, and the energy normalization and Z-Score normalization are less sensitive to outliers.

[0031] In step 3, the sampling frequency of the DAS ground demodulator used is F s , according to the Nyquist theorem, the maximum frequency F max of the DAS signal that can be collected is F s / 2; first, the frequency range [0, F max ] is divided into frequency bands, assuming that each frequency band has an incremental step of F max / n, then the entire frequency range is divided into n segments, which are [0, F max / n), [F max / n, 2*F max / n), [2*F max / n, 3*F max / n), …, [(n-1)*F max / n, F max ]; the amplitude value corresponding to each frequency is obtained by using one-dimensional Fourier transform, the average amplitude value of each frequency band is calculated, the greater the amplitude value, the stronger the response of the DAS signal in this frequency band, indicating that the DAS signal in this frequency band can better reflect the fluid flow characteristics; the above method is a rough division of the DAS signal frequency band, after determining the frequency band with the maximum average amplitude value, the frequency band is further finely divided; an optimization algorithm is used to find the optimal solution of the objective function, i.e., to determine a continuous frequency band with the maximum average amplitude value, the objective function is shown in formula (3):

[0032]

[0033] In the formula, [F1, F i ] represents a continuous frequency band, amplitude i represents the amplitude value corresponding to the i-th frequency, Sum represents the summation function, and Avg represents the average amplitude value to be solved.

[0034] In step 3, a binary search and prefix sum algorithm is used for intelligent optimization, assuming a fixed value A, in the entire frequency band amplitude sequence a1, a2, a3, …, a i , …, a j , …, the optimization of a certain segment of amplitude (a i + … +a j ) / (j-i+1)≥A, then the fixed value A must be between the maximum value and the minimum value of the sequence; define b i =a i -A, then the final transformation is to optimize (b i + … +b j )≥0, i.e., the difference between the prefix sums (sum j -sum i-1 )≥0, the prefix sum sum jIt refers to the sum of all data in the interval from the first number to the current number; the optimal frequency band is determined by binary search, also known to as dichotomous search, which belongs to high-efficiency search method; for a frequency band sequence interval [a left , a right ], the midpoint number mid of the interval is used for verification, that is, the fixed value A here is the midpoint number mid, if the difference of the prefix sum of the interval is greater than or equal to 0, the left boundary is changed to mid, that is, the sequence interval becomes [mid, a right ]; otherwise, the right boundary is changed to mid-1, that is, the sequence interval becomes [a left , mid-1]; the optimal frequency band with the maximum average amplitude value is finally output by continuously calculating, and the intelligent filtering of the fiber DAS signal is realized.

[0035] In step 4, after intelligent frequency selection in step 3, different flow and proportion under single-phase, two-phase and three-phase flow interpretation chart based on FBE sound wave frequency band energy is established.

[0036] In step 4, based on the processing of a large amount of experimental data in steps 1 to 3, it is found that there is a certain relationship between the flow and the sound wave energy FBE between the specific frequency band (f1-f2) of the DAS signal, and the calculation principle of FBE is to obtain the one-dimensional Fourier amplitude value of the DAS signal in the specific frequency band, so as to reflect the size of the sound wave energy; through a large number of indoor experiments, the relationship formula of the flow Q and the three times of the square of FBE is obtained, as shown in formula (4):

[0037]

[0038] In the formula, a and b are calibration coefficients.

[0039] The optical signal frequency band intelligent screening and flow water cut interpretation method provided by the application uses active signal enhancement technology, combines fluid properties, noise logging theory and data processing technology, establishes an optical signal frequency band intelligent screening method and a flow water cut interpretation method under low liquid volume. Compared with the prior art, the application has the following advantages:

[0040] 1. An active signal oil, gas and water three-phase flow optical fiber monitoring simulation device system is provided, which can be selected according to different experimental objects, and realizes monitoring and collection of low-liquid weak optical fiber signals.

[0041] 2. The maximum average amplitude value is used as the basis, combined with dichotomous search and prefix sum algorithm to realize optical signal frequency band intelligent screening, and the signal frequency band that can best reflect the flow characteristics of the fluid is selected.

[0042] 3. Single-phase, two-phase and three-phase flow interpretation charts based on DAS signals are formed, in which the water cut of oil-water two-phase is increased by 5%, the water cut range covered is 0-100%, and the flow and water cut of different production layers in oil wells, especially in multi-layer straight and inclined wells and multi-section long horizontal wells, are interpreted, which is of great significance for judging the downhole production condition, water plugging in water producing layers and intelligent management and control of fine injection and production.

[0043] 4. The flow and water cut interpretation chart can be updated in real time, the DAS data measured from the field well are integrated into the chart, the chart content is enriched, the chart type is improved, and the chart is better applied to the field production.

[0044] The present application solves the problems of difficult monitoring and collection of optical fiber DAS signals under low liquid volume, difficult filtering of optical fiber DAS signal frequency bands and difficult interpretation of production characteristics such as flow and water cut, improves the test system and interpretation method for the interpretation accuracy of flow and water cut and other production parameters of field production wells, especially multi-layer straight and inclined wells and multi-section long horizontal wells, guides the establishment of field production system and promotes the understanding of multi-layer (section) oil well development. BRIEF DESCRIPTION OF DRAWINGS

[0045] Figure 1 A flow chart of a specific embodiment of the distributed optical fiber acoustic signal frequency band intelligent screening and flow and water cut monitoring system interpretation method of the present application;

[0046] Figure 2 A structure schematic diagram of the active signal oil, gas and water three-phase flow optical fiber monitoring simulation device;

[0047] Figure 3 An intelligent optimization process schematic diagram of the optical fiber signal frequency band of the present application;

[0048] Figure 4 A flow and water cut interpretation chart of the present application;

[0049] Figure 5 A schematic diagram of the liquid production of each production layer in the straight and inclined well in embodiment 2 of the present application;

[0050] Figure 6 A schematic diagram of the oil production and water production of each production layer in the horizontal well in embodiment 3 of the present application;

[0051] Figure 7 A water plugging measure effect diagram implemented according to the interpretation result in embodiment 3 of the present application;

[0052] Figure 1A set of pipes; 2 oil pipe; 3-1 first injection hole; 3-2 second injection hole; 3-3 third injection hole; 4-1 first packer; 4-2 second packer; 4-3 third packer; 5 glass tube; 6 tail hose; 7-1 oil tank; 7-2 water tank; 7-3 gas tank; 7-4 tail liquid tank; 8-1 variable frequency screw pump (oil injection pump); 8-2 variable frequency screw pump (water injection pump); 8-3 air booster pump (gas injection pump); 9-1 oil control check valve; 9-2 water control check valve; 9-3 gas control check valve; 10 ground connection pipeline; 11 ground manifold; 12 active signal enhancement area; 13 active signal enhancement device; 14 pipeline fluid stable flow test area; 15 test optical cable; 16 DAS ground demodulator;

[0053] Figure 4 (a) oil and gas two-phase; (b) water and gas two-phase; (c) oil, gas and water three-phase; (d) oil and water two-phase, water content 20%; (e) oil and water two-phase, water content 50%; (f) oil and water two-phase, water content 80%. DETAILED DESCRIPTION

[0054] It should be noted that the following detailed description is exemplary in nature and is intended to provide further description of the application. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.

[0055] It should be noted that the terms used herein are for the purpose of describing specific embodiments and are not intended to limit exemplary embodiments according to the present application. As used herein, the singular form is intended to include the plural form unless the context clearly indicates otherwise, and it should also be understood that when the term "comprising" and / or "including" is used in the specification, it means that the features, steps, operations and / or combinations thereof are present.

[0056] As shown in Figure 1 , Figure 1 is a flow chart of the distributed optical fiber acoustic wave signal frequency band intelligent screening and flow water cut monitoring interpretation method of the present application. The distributed optical fiber acoustic wave signal frequency band intelligent screening and flow water cut monitoring interpretation method comprises:

[0057] Step 1, build an active signal oil, gas and water three-phase flow optical fiber monitoring simulation device system, which can monitor the weak signal of the optical fiber DAS under different pressures and temperatures;

[0058] Step 2, carry out a large number of oil, gas and water three-phase flow optical fiber monitoring experiments in the simulation device system built in step 1, and collect a large number of DAS monitoring experimental data under different pressures and temperatures, different oil, gas and water flow and ratio;

[0059] Step 3, preprocessing the DAS raw acoustic wave data collected in Step 2, including particularly prominent outlier data cleaning and data normalization processing;

[0060] Step 4, analyzing the response of the preprocessed DAS signal in Step 3 under different frequency bands, and using intelligent algorithms to optimize and select the frequency bands.

[0061] Step 5, after intelligent frequency selection in Step 4, establishing single-phase, two-phase and three-phase flow interpretation charts under different flow rates and proportions based on FBE (Frequency Band Energy) acoustic wave frequency band energy;

[0062] Step 6, applying the flow interpretation chart established in Step 5 to the field production well to evaluate the feasibility and effectiveness of the chart in interpreting flow rate and water cut and other production parameters of the field well.

[0063] Step 7, integrating the DAS monitoring data measured from the field production well into the flow rate and water cut interpretation chart established in Step 5 to enrich the chart content and improve the chart type, so that the interpretation chart can be better applied to the field production.

[0064] In Step 2, after the fluid flows stably in the wellbore, the 16DAS ground demodulator is used to collect the DAS data monitored in the 14-pipeline fluid stable flow test area under different experimental conditions. In the oil-water two-phase flow monitoring experiment, the water cut is increased by 5% as the step size, the water cut range is 0-100%, and the flow rate range is 10-120m 3 / d, meeting the optical fiber DAS monitoring under low liquid volume.

[0065] In Step 3, at any position point, the DAS raw acoustic wave data is a row of vectors, representing the phase change of the fiber laser signal at this position point over time. The outlier data cleaning method uses the box plot to observe outliers and the method of supplementing outliers by adjacent average value interpolation. The box plot has five reference lines, which are the maximum value, the minimum value, the upper quartile, the lower quartile and the median. The upper limit of the box plot is the maximum value in the non-outlier range, and the lower limit is the minimum value in the non-outlier range. When the DAS data is outside the upper and lower limits, it is determined to be extremely abnormal, and the average value of the two adjacent numbers can be used to supplement the interpolation after deletion. The interquartile range in the box plot is the difference between the upper quartile and the lower quartile, and the expressions of the upper limit and the lower limit are:

[0066] Upper limit = upper quartile + 1.5*interquartile range (1)

[0067] Lower limit = lower quartile - 1.5*interquartile range (2)

[0068] The data normalization processing can preferably be maximum-minimum normalization, energy normalization and Z-Score normalization, etc., and the purpose is to eliminate the influence of magnitude and dimension, simplify calculation, improve model accuracy and accelerate model calculation speed.

[0069] In step 4, the sampling frequency of the DAS demodulator used in the step 1 simulation device system is F s , according to the Nyquist theorem, the maximum frequency Fma x of the DAS signal that can be collected in the system is F s / 2. First, the frequency range [0, Fma x ] is divided into frequency bands, assuming that each frequency band has an incremental step of Fma x / n, then the entire frequency range is divided into n segments, which are [0, Fma x / n), [Fma x / n, 2*Fma x / n), [2*Fma x / n, 3*Fma x / n), …, [(n-1)*Fma x / n, Fma x ]. The amplitude value corresponding to each frequency is obtained by using one-dimensional Fourier transform, the average amplitude value of each frequency band is calculated, and the greater the amplitude value, the more intense the response of the DAS signal in the frequency band, indicating that the DAS signal in the frequency band can better reflect the fluid flow characteristics. The above method is a rough division of the DAS signal frequency band, and after determining the frequency band with the maximum average amplitude value, the frequency band is further finely divided. An optimization algorithm is used to find the optimal solution of the objective function, i.e., to determine a continuous frequency band with the maximum average amplitude value, and the objective function is shown in formula (3).

[0070]

[0071] In the formula, [F1, F i ] represents a continuous frequency band, amplitude i represents the amplitude value corresponding to the i-th frequency, Sum represents the summation function, and Avg represents the average amplitude value to be solved.

[0072] The present application preferably uses binary search and prefix sum algorithm for intelligent optimization, and the optimization flowchart is shown in Figure 3 . Assuming a fixed value A, in the entire frequency band amplitude sequence a1, a2, a3, …, a i , …, a j ​​, …, optimizing a certain segment of amplitude (a i + … + a j ) / (j-i+1) >= A, then the fixed value A must be between the maximum and minimum values of the sequence. Define b i = a i -A, then finally converted to optimize (b i + … + b j ) >= 0, the difference between the prefix sum j -sum i-1 ) >= 0, the prefix sum sum j refers to the sum of all data in the interval from the first number to the current number. Using binary search to determine the optimal frequency band, binary search is also called halving search, which belongs to high efficiency search method. For a frequency band sequence interval [a left , a right ], the midpoint number mid is used for verification, that is, the fixed value A is the midpoint number mid, if the difference between the prefix sum of the interval >= 0, then change the left boundary to mid, that is, the sequence interval becomes [mid, a right ]; On the contrary, change the right boundary to mid-1, that is, the sequence interval becomes [a left , mid-1]. Constantly loop calculation, finally output the optimal frequency band with the largest average amplitude value, realize the intelligent screening of fiber DAS signal frequency band.

[0073] In step 5, based on the experimental data processing of steps 2 to 4, it is found that there is a certain relationship between the flow and the acoustic energy FBE (Frequency Band Energy) of the specific frequency band (f1-f2) of the DAS signal. The calculation principle of FBE is to calculate the one-dimensional Fourier amplitude value of the DAS signal in the specific frequency band, so as to reflect the size of the acoustic energy. The present application obtains the relationship formula of the flow Q and the cube root of FBE through a large number of indoor experiments, as shown in formula (4), and the flow interpretation chart is shown in Figure 4 , here the oil-water two-phase interpretation chart only shows the cases of 20%, 50% and 80% water content. In the chart, x represents the cube root of FBE, y represents the flow, R2 represents the determination coefficient, and the closer R2 is to 1, the better the linear regression fitting effect in the chart.

[0074]

[0075] In the formula, a and b are calibration coefficients.

[0076] The active oil-gas-water flow monitoring device and interpretation method of the optical fiber acoustic wave sensing in the application provide an active signal oil-gas-water three-phase flow optical fiber DAS monitoring simulation device system which can be selected according to different experimental objects, and realizes monitoring and collection of low liquid volume and weak optical fiber signals. The maximum average amplitude value is taken as the basis, and the optical fiber signal frequency band intelligent screening is realized by combining the dichotomy and the prefix sum algorithm, and the signal frequency band which can best reflect the fluid flow characteristics is selected. It is found from a large amount of experimental data processing of the application that there is a linear relationship between the one-third power of the acoustic wave frequency band energy FBE (Frequency Band Energy) between the wellbore flow and the DAS signal specific frequency band. The application forms a single-phase, two-phase and three-phase flow-FBE interpretation chart based on the DAS signal, the water cut of the oil-water two-phase is increased by 5%, the water cut range covered is 0-100%, and the flow and water cut interpretation of different production layers in the downhole of the oil well, especially the multilayer straight well and the multistage long horizontal well, is realized, which has important significance for the downhole production condition judgment, water plugging of the water layer and intelligent control of fine injection and production. The flow and water cut interpretation chart formed by the optical fiber acoustic wave sensing active oil-gas-water flow monitoring device and interpretation method can be updated in real time, the DAS data measured from the field well are integrated into the chart after processing, the chart content is enriched, the chart type is improved, and the interpretation chart is better applied to the field production.

[0077] The following are several specific embodiments of the application

[0078] Embodiment 1

[0079] In the application of a specific embodiment 1 of the application, the active signal oil-gas-water three-phase flow optical fiber monitoring simulation device has a structure schematic diagram as shown in Figure 2 which mainly includes a horizontal wellbore part, an injection system part, an active signal monitoring part and a DAS data acquisition part. It involves 1 set of pipe, 2 oil pipe, 3-1 first injection hole, 3-2 second injection hole, 3-3 third injection hole, 4-1 first packer, 4-2 second packer, 4-3 third packer, 5 glass tube, 6 tail hose, 7-1 oil tank, 7-2 water tank, 7-3 gas tank, 7-4 tail liquid tank, 8-1 variable frequency screw pump (oil injection pump), 8-2 variable frequency screw pump (water injection pump), 8-3 air booster pump (gas injection pump), 9-1 oil control check valve, 9-2 water control check valve, 9-3 gas control check valve, 10 ground connection pipeline, 11 ground manifold, 12 active signal enhancement area, 13 active signal enhancement device, 14 pipeline internal fluid stable flow test area, 15 test optical cable, 16 DAS ground demodulator.

[0080] The horizontal wellbore part includes 1 casing, 2 tubing, 3-1 first injection hole, 3-2 second injection hole, 3-3 third injection hole, 4-1 first packer, 4-2 second packer, 4-3 third packer, 5 glass tube, 6 tail hose. The horizontal wellbore simulates the radial flow of downhole fluid into the wellbore and the flow in the wellbore. After the fluid is injected into the injection hole through the injection system, the fluid flows in the wellbore, and finally flows through 5 glass tube and 6 tail hose to 7-4 tail liquid tank.

[0081] The injection system part includes 7-1 oil tank, 7-2 water tank, 7-3 gas tank, 7-4 tail liquid tank, 8-1 variable frequency screw pump (oil injection pump), 8-2 variable frequency screw pump (water injection pump), 8-3 air booster pump (gas injection pump), 9-1 oil control check valve, 9-2 water control check valve, 9-3 gas control check valve, 10 ground connection pipeline, 11 ground manifold. After the oil, gas and water fluid is fully mixed in 11 ground manifold, it is injected into the relevant injection hole through 10 ground connection pipeline according to the experimental requirements. After the oil and water in 7-4 tail liquid tank are separated by standing, they are re-injected into 7-1 oil tank and 7-2 water tank for recycling, saving cost.

[0082] The active signal monitoring part includes 12 active signal enhancement area and 13 active signal enhancement device. This part is mainly aimed at the problem that the optical fiber DAS signal is difficult to monitor and collect under low liquid volume. If it is oil-water two-phase flow, 13 active signal enhancement device is a throttling device, which throttles the fluid through a small hole, and can generate vortex plug in the fluid flow. If it is oil-gas, water-gas or oil-gas-water flow, 13 active signal enhancement device is an electric heating device, which locally and concentratedly heats the fluid in 12 active signal enhancement area, and can generate heat plug in the process of fluid flow, so as to increase the vibration intensity of sound wave of fluid flow, and then enhance the visibility of DAS signal. At the same time, compared with uniform heating of the whole wellbore, local concentrated heating can rapidly improve the heating efficiency and reduce the heat energy loss, and quickly enhance the signal visibility. 13 active signal enhancement device can be selected according to different experimental objects.

[0083] The DAS data acquisition part includes 14 pipeline fluid stable flow test area, 15 test optical cable, 16 DAS ground demodulator. 15 test optical cable is bundled on the outer wall of the oil pipe to simulate the on-site optical cable into the well mode, and the sampling frequency of 16 DAS ground demodulator is F s .

[0084] Example 2

[0085] A well is a multi-layer production straight inclined well of an oil reservoir, the maximum well deviation angle is 1.5°, the middle buried depth of the oil layer is 2100m, the production layer section includes the 3rd sand group to the 5th sand group of the Shazidui section, the total thickness of the shot sand body is 23.4m, and the oil layer span is 131.4m. The average porosity of the production layer section is 23.6%, and the average permeability is 161mD. The physical properties of each layer section are shown in Table 1.

[0086] Table 1 A well parameter table of each production layer section

[0087]

[0088] The distributed optical fiber DAS logging operation of the A well is successfully carried out. The wellbore sound wave data recording process lasts for 373h. After the well is opened and stably produced, the single well liquid volume is 78.8t / d, and the wellhead water cut is 98.5%. According to the method proposed in the application, the DAS data collected in the stable production stage of the A well are interpreted and analyzed.

[0089] Specifically, in step 101, the collected DAS original sound wave data are preprocessed, the abnormal value is observed by using the box chart method, and the abnormal value is supplemented by using the adjacent average value interpolation method. Meanwhile, the data are normalized by using the maximum-minimum normalization method in Embodiment 2.

[0090] In step 102, the DAS data processed in step 101 are subjected to frequency band intelligent optimization by using the dichotomy search and prefix sum algorithm. After intelligent screening, the specific frequency band range of the optical fiber DAS signal selected in Embodiment 2 is 600-1000Hz, and the FBE sound wave frequency band energy in the specific frequency band is extracted.

[0091] In step 103, the FBE data extracted in step 102 are interpreted and analyzed by using the oil-water interpretation chart based on the FBE sound wave frequency band energy established in the application. The flow rate and water cut interpretation chart similar to the water cut of the A well is selected, and the liquid production of different production layer sections of the A well is finally determined. The result is shown in Table 2. Figure 5 After interpretation and analysis, the production profile of the A well is unevenly distributed in the stable production stage. The optical fiber test liquid production layer section is mainly distributed in the ES2 3-4 layer, the ES2 4-1 layer and the ES2 4-2 layer, and the liquid production of the ES2 4-2 layer accounts for the most.

[0092] In step 104, the liquid production of different production layer sections of the A well obtained by interpretation in step 103 is calculated and added, and compared with the measured liquid production at the wellhead. The calculated liquid production is 69t / d, the measured liquid production at the wellhead is 78.8t / d, the interpretation coincidence rate reaches 87.6%, and the feasibility and effectiveness of the flow rate and water cut interpretation chart proposed in the application are verified.

[0093] Step 105, the DAS monitoring data measured from the A well is integrated into the flow water cut interpretation chart established by the present application, the chart content is enriched, and the chart type is perfected, so that the interpretation chart is better applied to the field production.

[0094] Embodiment 3

[0095] Well B is a steam huff and puff horizontal well in a certain heavy oil reservoir, the oil layer is buried at a depth of about 800 m, the horizontal section length is about 235 m, the average porosity of the drilled oil layer is 32.5%, and the average permeability is 734 mD. The specific reservoir characteristics are shown in Table 2.

[0096] Table 2: Reservoir characteristics and fluid property parameters

[0097]

[0098] Well B successfully carried out distributed optical fiber DAS logging operation, the optical fiber was fixed outside the tubing, and the wellbore acoustic wave data recording process lasted for 387 h. After the well was opened and produced stably, the daily liquid production at the wellhead was 31.7 m 3 / d, and the water cut at the wellhead was 97.3%. According to the method proposed by the present application, the DAS data collected during the stable production stage of Well B was interpreted and analyzed.

[0099] Specifically, step 201, the collected DAS original acoustic wave data is preprocessed, the box plot method is used to observe the abnormal value and the adjacent average value interpolation method is used to supplement the abnormal value. Since the collected DAS data has many abnormal values, the Z-Score method which is less sensitive to abnormal values is preferred in Embodiment 3 to normalize the data.

[0100] Step 202, the DAS data processed in step 201 is subjected to frequency band intelligent optimization by using the dichotomy search and prefix sum algorithm. After intelligent screening, the specific frequency band range of the optical fiber DAS signal selected in Embodiment 3 is 200-600 Hz, and the FBE acoustic wave frequency band energy in this specific frequency band is extracted.

[0101] Step 203, the FBE data extracted in step 202 is interpreted and analyzed by using the oil-water interpretation chart based on FBE acoustic wave frequency band energy established by the present application, the flow water cut interpretation chart similar to the water cut of Well B is selected, and finally the oil production and water production of different production intervals of Well B are determined. The results are shown in Figure 6 After interpretation and analysis, during the stable production stage, the production profile of Well B is unevenly distributed, the oil production profile and the water production profile are relatively consistent. The water production intervals are mainly 1384.8 m-1387.4 m, 1396.4 m-1401.8 m, 1406.3 m-1409.8 m, 1485.1 m-1490.1 m, 1501.0 m-1505.4 m and 1525.3 m-1529.2 m, and the water production proportion of the remaining intervals is small.

[0102] Step 204, the liquid production of different production intervals of B well obtained by interpretation in step 203 is calculated and added, and compared with the measured liquid production at the well head, the liquid production is 35.4m 3 / d, the measured liquid production at the well head is 31.7m 3 / d, the interpretation coincidence rate reaches 88.3%, which verifies the feasibility and effectiveness of the flow rate and water cut interpretation chart proposed in the application.

[0103] Step 205, according to the flow rate interpretation results of each production interval, water plugging measures are implemented on the main water production interval of B well, and the results are shown in Figure 7 , after water plugging, the daily oil production is obviously enhanced, which verifies the feasibility and effectiveness of the flow rate and water cut interpretation chart established in the application in field application.

[0104] Step 206, the DAS monitoring data measured from B well is integrated into the flow rate and water cut interpretation chart established in the application, the chart content is enriched, and the chart type is improved, so that the interpretation chart can be better applied to field production.

[0105] Finally, it should be pointed out that: the above only describes the preferred embodiments of the application, and is not used to limit the application, although the application has been described in detail with reference to the foregoing embodiments, for those skilled in the art, the technical solutions recorded in the foregoing embodiments can still be modified, or some technical features can be replaced. Any modification, equivalent replacement, improvement, etc. within the spirit and principles of the application shall be included in the protection scope of the application.

[0106] In addition to the technical features described in the specification, they are known to those skilled in the art.

Claims

1. An active oil, gas and water flow monitoring device using fiber optic acoustic sensing, characterized in that, The active oil-gas-water flow monitoring device of the optical fiber acoustic wave sensor comprises a horizontal wellbore part, an injection system part, an active signal monitoring part and a DAS data acquisition part, the horizontal wellbore part simulates the radial flow of downhole fluid into the wellbore and the flow in the wellbore, the injection system part is connected to the horizontal wellbore part and injects oil-gas-water three-phase fluid into the horizontal wellbore part, the active signal monitoring part is located in the horizontal wellbore part and enhances the optical fiber DAS signal, and the DAS data acquisition part simulates the field cable into the well mode and carries out DAS data acquisition.

2. The fiber optic acoustic wave sensor based active oil, gas and water flow monitoring device of claim 1, wherein, The horizontal wellbore part comprises a casing, a tubing, a first injection hole, a second injection hole, a third injection hole, a first packer, a second packer, a third packer, a glass tube and a tail hose, the tubing is located in the casing, the first injection hole, the second injection hole and the third injection hole are located on the casing, oil-gas-water fluid can be injected from any one, two or three injection holes according to laboratory experiment requirements, and single-phase, two-phase or three-phase fluid can be injected, the first packer, the second packer and the third packer are respectively used for sealing the fluid in the corresponding three injection holes, and the tail hose is connected between the tubing and the glass tube, oil-gas-water three-phase fluid flows in the tubing and finally flows out of the horizontal wellbore part through the glass tube and the tail hose.

3. The fiber optic acoustic wave sensor based active oil, gas, and water flow monitoring device of claim 1, wherein, The injection system comprises an injection system part comprising an oil tank, a water tank, a gas tank, a tail liquid tank, an oil injection pump, a water injection pump, a gas injection pump, an oil control one-way valve, a water control one-way valve, a gas control one-way valve, a ground connection pipeline and a ground manifold, the oil injection pump is located between the oil tank and the oil control one-way valve, the water injection pump is located between the water tank and the water control one-way valve, the gas injection pump is located between the gas tank and the gas control one-way valve, the ground connection pipeline is respectively connected to the oil control one-way valve, the water control one-way valve and the gas control one-way valve, the ground manifold is located between the ground connection pipeline and the horizontal wellbore part, the oil, gas and water in the oil tank, the water tank and the gas tank are fully mixed in the ground connection pipeline and then injected into the horizontal wellbore part through the ground manifold, and the tail liquid tank is connected to the tail hose and receives the oil-gas-water three-phase fluid flowing out of the tail hose, and the oil and water in the tail liquid tank are separated after standing and then re-injected into the oil tank and the water tank.

4. The fiber optic acoustic wave sensor based active oil, gas, and water flow monitoring device of claim 1, wherein, The active signal monitoring part comprises an active signal enhancement device, when oil-water two-phase flow is in the horizontal wellbore part, the active signal enhancement device adopts a throttling device to throttle the fluid through a small hole, and a vortex plug can be generated in the fluid flow.

5. The fiber optic acoustic wave sensor based active oil, gas, and water flow monitoring apparatus of claim 4, wherein, When oil-gas, gas-water or oil-gas-water flow exists gas, the active signal enhancement device adopts an electric heating device to locally and concentratedly heat the fluid in the active signal enhancement area of the horizontal wellbore part, a heat plug can be generated in the process of fluid flow, so as to increase the vibration intensity of the fluid flow sound wave and further enhance the visibility of the DAS signal.

6. The fiber optic acoustic wave sensor based active oil, gas, and water flow monitoring device of claim 2, wherein, The DAS data acquisition part includes a test optical cable and a ground demodulator, the test optical cable is bundled on the outer wall of the oil pipe to simulate the way of field optical cable into the well, and the DAS ground demodulator is connected to the test optical cable.

7. An active oil, gas, and water flow monitoring interpretation method for fiber optic acoustic wave sensing, characterized by, The active oil-gas-water flow monitoring and interpretation method of the optical fiber acoustic wave sensor adopts the active oil-gas-water flow monitoring device of the optical fiber acoustic wave sensor of claim 1, comprising: Step 1, carry out optical fiber monitoring experiment of oil-gas-water three-phase flow, collect experimental data; Step 2, preprocess the DAS original acoustic wave data; Step 3, analyze the response of DAS signal under different frequency bands and intelligently select the frequency band; Step 4, establish a flow water cut interpretation chart based on FBE acoustic wave frequency band energy; Step 5, apply the chart to the field well to evaluate the interpretation effect of the production fluid profile; Step 6, integrate the field well data into the interpretation chart to enrich the content of the chart.

8. The fiber optic acoustic wave sensor active oil and gas and water flow monitoring interpretation method of claim 7, wherein, In step 1, a large number of optical fiber DAS signals under different pressures and temperatures, different oil-gas-water flow rates and proportions are collected by using the active oil-gas-water flow monitoring device of the optical fiber acoustic wave sensor to carry out a large number of optical fiber monitoring experiments of oil-gas-water three-phase flow.

9. The fiber optic acoustic wave sensor active oil and gas and water flow monitoring interpretation method of claim 8, wherein, In step 1, after the fluid flows stably in the wellbore, the DAS ground demodulator is used to collect the optical fiber DAS signals monitored in the test area of the stable flow of the fluid in the pipeline under different experimental conditions; in the oil-water two-phase flow monitoring experiment, the water cut is increased by 5% as the step size, the water cut range is 0-100%, the flow range is 10-120 m 3 / d, and the optical fiber DAS monitoring under low liquid volume is met.

10. The fiber optic acoustic wave sensor active oil and gas and water flow monitoring interpretation method of claim 7, wherein, In step 2, preprocessing includes special outlier data cleaning and data normalization processing.

11. The fiber optic acoustic wave sensor active oil and gas and water flow monitoring interpretation method of claim 10, wherein, In step 2, at any position point, the DAS original acoustic wave data is a row of vectors, representing the phase change of the optical fiber laser signal at this position point with different time; the outlier data cleaning method adopts the method of observing outliers by box plot and supplementing outliers by adjacent average value interpolation; the box plot has five reference lines, which are maximum, minimum, upper quartile, lower quartile and median; the upper limit of the box plot is the maximum value in the non-outlier range, and the lower limit is the minimum value in the non-outlier range; when the DAS data is outside the upper limit and the lower limit, it is determined to be extremely abnormal, and the average value of the two adjacent numbers can be used to supplement the interpolation after deletion; the interquartile range of the box plot is the difference between the upper quartile and the lower quartile, and the expressions of the upper limit and the lower limit are: Upper limit = upper quartile + 1.5*interquartile range (1) Lower limit = lower quartile - 1.5*interquartile range (2).

12. The fiber optic acoustic wave sensor active oil and gas and water flow monitoring interpretation method of claim 10, wherein, In step 2, data normalization processing can preferably select maximum-minimum normalization, energy normalization and Z-Score normalization to eliminate the influence of magnitude and dimension, and the specific normalization method is selected according to the effect of DAS data outlier processing; the maximum-minimum normalization is very sensitive to the existence of outliers, and the energy normalization and Z-Score normalization have lower sensitivity to outliers.

13. The fiber optic guided wave sensor active oil and gas and water flow monitoring interpretation method of claim 7, wherein, In step 3, the sampling frequency of the DAS ground demodulator used is F s , according to the Nyquist theorem, the maximum frequency F max of the DAS signal that can be collected is F s / 2; first, the frequency range [0, F max ] is divided into frequency bands, assuming that each frequency band has an incremental step of F max / n, then the entire frequency range is divided into n segments, which are [0, F max / n), [F max / n, 2*F max / n), [2*F max / n, 3*F max / n), …, [(n-1)*F max / n, F max ]; the amplitude value corresponding to each frequency is obtained by using one-dimensional Fourier transform, the average amplitude value of each frequency band is calculated, the greater the amplitude value, the more intense the response of the DAS signal in this frequency band, indicating that the DAS signal in this frequency band can better reflect the flow characteristics of the fluid; The above method is a rough division of the frequency band of DAS signal, and after determining the frequency band with the maximum average amplitude value, the frequency band is further finely divided; the optimal solution of the objective function is found by using the optimization algorithm, that is, a continuous frequency band with the maximum average amplitude value is determined, and the objective function is shown as formula (3): where [F1, F i ] represents a certain continuous frequency band, amplitude i represents the amplitude value corresponding to the i-th frequency, Sum represents the summation function, and Avg represents the average amplitude value.

14. The fiber optic acoustic wave sensor active oil and gas and water flow monitoring interpretation method of claim 13, wherein, In step 3, intelligent optimization is performed using binary search and prefix sum algorithm, assuming a fixed value A, in the entire frequency band amplitude sequence a1, a2, a3, …, a i , …, a j , …, the optimization of a certain amplitude (a i + … + a j ) / (j-i+1) ≥ A, then the fixed value A must be between the maximum and minimum values of the sequence; define b i = a i -A, then finally converted to optimization (b i + … + b j ) ≥ 0, that is, the difference between the prefix sum (sum j -sum i-1 ) ≥ 0, the prefix sum sum j refers to the sum of all data in the interval from the first number to the current number; using binary search to determine the optimal frequency band, binary search is also called halving search, which is a high-efficiency search method; for a frequency band sequence interval [a left , a right ], the midpoint number mid is used for verification, that is, the fixed value A is the midpoint number mid, if the difference between the prefix sum of the interval ≥ 0, then change the left boundary to mid, that is, the sequence interval becomes [mid, a right ]; otherwise, change the right boundary to mid-1, that is, the sequence interval becomes [a left , mid-1]; constantly loop calculation, finally output the optimal frequency band with the maximum average amplitude value, realize the intelligent filtering of optical fiber DAS signal frequency band.

15. The fiber optic acoustic wave sensor active oil and gas and water flow monitoring interpretation method of claim 7, wherein, In step 4, after intelligent frequency selection in step 3, different flow and proportion single-phase, two-phase and three-phase flow interpretation charts based on FBE acoustic wave frequency band energy are established.

16. The fiber optic acoustic wave sensor active oil and gas and water flow monitoring interpretation method of claim 15, wherein, In step 4, based on the experimental data processing of steps 1 to 3, it is found that there is a certain relationship between the flow rate and the acoustic energy FBE between the specific frequency band (f1-f2) of the DAS signal, and the calculation principle of FBE is to calculate the one-dimensional Fourier amplitude value of the DAS signal in the specific frequency band, so as to reflect the size of the acoustic energy; through a large number of indoor experiments, the relationship between the flow rate Q and the three-thirds power of FBE is obtained, as shown in formula (4): In the formula, a and b are calibration coefficients.

Images