Real-time monitoring method for liquid level based on distributed optical fiber acoustic wave sensing technology

Abstract

The present application relates to a kind of dynamic liquid level real-time monitoring method based on distributed optical fiber acoustic sensing technology, including armored cable being laid in well, high spatial resolution optical fiber acoustic sensing modem located at wellhead;Armored cable is fixed on the outer wall of oil pipe by optical cable clamp;Armored cable is connected with optical fiber acoustic sensing modem, ground acoustic sensing modem keeps open state and detects optical cable state in real time continuously, obtains the sound vibration signal along the track of oil pipe or wellbore, and is saved in ground storage device, the sound vibration signal recorded by playback acoustic sensing modem is obtained, and dynamic liquid level is identified and monitored by intelligent algorithm.The present application is based on the dynamic liquid level real-time monitoring method of distributed optical fiber acoustic sensing technology, and optical fiber acoustic sensing modem collects vibration / sound signal along line in real time, and real-time display downhole dynamic liquid level depth position.

Description

Technical Field

[0001] This invention relates to the field of oil fields, and more specifically, to a method for real-time monitoring of dynamic fluid levels based on distributed fiber optic acoustic sensing technology. Background Technology

[0002] In the production and development of oilfields, dynamic fluid level data is a crucial foundation for oilfield management, directly reflecting the fluid supply capacity of oil wells. Real-time monitoring of dynamic fluid level data allows for analysis of well operation and downhole supply and drainage status, enabling the optimization of operating parameters. This is of great significance for reducing energy consumption, improving recovery rates, minimizing well accidents, and extending well lifespan.

[0003] Currently, the main method for measuring the dynamic fluid level depth in oil wells is the ultrasonic reflection method. This method uses an echo meter based on the principle of sound wave reflection. However, due to the complex state of the annulus, the reflected waves may be affected by factors such as dead oil, heavy oil, foamy oil, wax deposition, tubing diameter changes, well trajectory, and mechanical vibration noise, resulting in inaccurate measurement results. Furthermore, this method can only be used for periodic or irregular production shutdowns and cannot continuously measure the fluid level depth in oil wells, thus failing to monitor the state of oil wells in real time throughout the entire oil production process. Summary of the Invention

[0004] To address the shortcomings of the existing technology, this invention provides a method for real-time monitoring of dynamic liquid levels based on distributed fiber optic acoustic wave sensing technology. This method is simple in structure, easy to operate, and capable of real-time monitoring of vibration / sound signals along the length of an optical fiber.

[0005] The technical solution adopted in this invention is:

[0006] A method for real-time monitoring of dynamic fluid level based on distributed fiber optic acoustic sensing technology includes an armored optical cable deployed inside the well and a high spatial resolution fiber optic acoustic sensing modulator / demodulator located at the wellhead; the armored optical cable is fixed to the outer wall of the tubing by optical cable clamps; the armored optical cable is connected to the fiber optic acoustic sensing modulator / demodulator, and includes the following steps:

[0007] (1) Before entering the well, use an acoustic wave sensor modulator on the ground to test the optical fibers in the armored optical cable to ensure that they meet the quality requirements and work normally.

[0008] (2) When entering the well, the armored optical cable is tied to the oil pipe and lowered into the well. During the lowering process, the ground acoustic wave sensor modulator is turned on at key time points to detect and monitor the status of the optical cable.

[0009] (3) After entering the well, the ground acoustic wave sensor modulator and demodulator is kept on to continuously detect the status of the optical cable in real time, obtain the sound vibration signal distributed along the trajectory of the oil pipe or wellbore, and save it in the ground storage device or display it in real time on the ground monitoring screen.

[0010] (4) By playing back the sound vibration signal recorded by the acoustic wave sensor modulator and demodulator, the dynamic liquid surface is identified and monitored by intelligent algorithms;

[0011] (5) After the construction is completed, leave the well site.

[0012] When the ground-based acoustic wave sensor modulator / demodulator detects and monitors the optical cable's status, it compares the OTDR attenuation curves of the optical fiber cable with those of normal optical fiber cables stored in the OTDR attenuation curve database. If the OTDR attenuation curve of a normal optical fiber cable is smooth and the attenuation rate is within a reasonable range, the optical fiber cable is considered normal. If reflective discontinuities (i.e., strong reflection signals at abnormal points, usually caused by fiber breaks or fiber scratches) or non-reflective rapid attenuation discontinuities (usually due to poor fiber quality and severe attenuation of the optical signal within the fiber) occur, the optical fiber cable is considered abnormal, and a backup optical fiber cable is activated. The ground-based acoustic wave sensor modulator / demodulator then re-detects and monitors the optical cable's status, comparing the OTDR attenuation curves of the optical fiber cable with those of normal optical fiber cables stored in the OTDR attenuation curve database. If the attenuation rate is within a reasonable range, the backup fiber optic cable is considered normal. If the same reflective discontinuity or non-reflective rapid attenuation discontinuity occurs, the backup fiber optic cable is preliminarily considered abnormal. After the armored fiber optic cable is lowered 50 to 100 meters into the well along with the tubing, the surface acoustic wave sensor modulator is restarted to detect and monitor the status of both the fiber optic cable and the backup fiber optic cable. If the OTDR attenuation curves of the fiber optic cable and the backup fiber optic cable are compared with the OTDR attenuation curves of normal fiber optic cables stored in the database, and the attenuation rate is within a reasonable range, both the fiber optic cable and the backup fiber optic cable are considered normal. If either the fiber optic cable or the backup fiber optic cable is normal, the normal fiber optic cable is used to continue lowering. If both the fiber optic cable and the backup fiber optic cable are abnormal, the armored fiber optic cable is pulled up, replaced on the surface, and then re-lowered into the well.

[0013] Identify and monitor dynamic liquid levels using intelligent algorithms;

[0014] The dynamic fluid level is located above the production layer and close to the surface (above the top boundary of the perforation layer and the oil pump, and generally within the upper 3 / 4 depth of the entire well). The dynamic fluid level fluctuates regularly as production progresses. When production increases, the dynamic fluid level decreases, and when production decreases, the dynamic fluid level tends to rise. The location of a large-amplitude sound vibration that meets the above characteristics can be identified as the dynamic fluid level.

[0015] The steps for intelligent algorithms to identify and monitor dynamic liquid levels are as follows:

[0016] Input 1 is the phase vector input into the 1DCNN module of a one-dimensional convolutional neural network. After passing through a total of 12 layers of convolutional layers (Conv1D), activation layers (Activation), and pooling layers (Pooling), it is input into a fully connected layer (FC) as the output of the CNN module. The activation layer uses the rectified linear function (ReLU), and the pooling layer uses max pooling.

[0017] Input 2 is an intensity vector input into the MLP module. After being activated by two FC layers and one tanh function layer, it is connected to an FC layer as the output of the MLP module.

[0018] The outputs of the CNN and MLP modules are combined and then fed into two consecutive FC+ReLU layers for compressed activation. Finally, the output is classified through a softmax layer.

[0019] Based on abnormal dynamic fluid level data, predict impending well accidents. Reduce energy consumption and improve recovery rate.

[0020] For flowing oil or gas wells, when the dynamic fluid level depth plus the annular pressure is insufficient to ensure the well flows, it is necessary to supplement the reservoir with energy. The annular pressure can be measured from a surface pressure gauge.

[0021] Monitoring and predicting the dynamic fluid level depth is crucial for the normal production of flowing oil and gas wells. Real-time identification, monitoring, and prediction of the dynamic fluid level's location not only provides valuable guidance for determining current flowability but also allows for prediction of future dynamic fluid level conditions based on historical and recent patterns of change, successfully forecasting potential accidents such as flow stoppages.

[0022] For ESP wells, the ESP will not work when the dynamic fluid level is lower than the ESP inlet. To avoid ESP failure, this technology can be used to monitor the rise and fall of the dynamic fluid level in real time, so that measures can be taken in advance to ensure that the ESP can work normally or in the best condition.

[0023] For pumped oil wells, when the submersion depth (the difference in depth between the dynamic fluid level and the pumped oil well's suction inlet) is less than a certain value, the pumped oil well may not be able to draw enough fluid, thus affecting its working efficiency. In extreme cases, when the dynamic fluid level is lower than the pumped oil well's suction inlet, the pumped oil well cannot pump fluid or operate. Therefore, in order to reduce energy consumption and ensure the normal progress of the oil production plan, it is necessary to monitor the dynamic fluid level in real time, thereby ensuring that the pumped oil well operates in good condition and avoiding malfunctions.

[0024] To improve the depth accuracy of monitoring data, well depth correction is required for the fiber optic cable insertion depth when interpreting dynamic fluid level monitoring data. The correction principle is illustrated below:

[0025] At a fixed location on the ground, the optical cable is tapped with a special tool. The location of the increased amplitude on the DAS waterfall chart is observed in real time. From the DAS time waterfall chart, the distance L1 from the location of the calibration point to the DAS demodulator can be accurately read. Then, the distance L2 from the calibration point to the wellhead is measured along the optical cable. The total length of the optical fiber is L... 光纤总长 Under certain conditions, the length of the optical cable entering the well, L3 = L, can be calculated. 光纤总长 -L1-L2, the fiber optic insertion length L3 plus the overlay spacing KB gives the depth of the well corresponding to the maximum insertion depth of the optical cable. Therefore:

[0026] MD 光缆末端 =L3+KB=L 光纤总长 -L1-L2+KB

[0027] Similarly, if the distance from a point on the optical fiber (such as a dynamic liquid surface) to the DAS demodulator is X (i.e., the position reading on the DAS waterfall chart is X), then the corresponding well depth can be calculated by the following formula:

[0028] MD X =MD 光缆末端 -(L 光纤总长 -X)=MD 光缆末端 -L 光纤总长 +X

[0029] Thus, according to the above formula, the well depth corresponding to the change in the dynamic fluid level coordinate X can be calculated.

[0030] The advantages of this invention over the prior art are:

[0031] This invention relates to a method for real-time monitoring of dynamic fluid levels based on distributed fiber optic acoustic sensing technology. The downhole dynamic fluid level will experience slight fluctuations, generating vibration / sound signals. The fiber optic acoustic sensing modulator collects the vibration / sound signals along the fiber optic cable in real time and displays the depth and position of the downhole dynamic fluid level in real time. Attached Figure Description

[0032] Figure 1 This is a schematic diagram of the equipment composition structure for real-time monitoring of dynamic liquid levels based on distributed fiber optic acoustic wave sensing technology, as per the present invention.

[0033] Figure 2 This is a diagram of the distributed acoustic wave transmission signal for liquid level monitoring.

[0034] Figure 3 This is an OTDR attenuation curve of a normal optical fiber cable;

[0035] Figure 4 This is an OTDR attenuation curve of an abnormal optical fiber cable;

[0036] Figure 5This is a schematic diagram illustrating the principle of well depth correction based on the fiber optic cable insertion depth.

[0037] Figure 6 This is a logic diagram of a pattern recognition method based on mixed input of intensity and phase two-dimensional signals;

[0038] Figure 7 This is a monitoring chart of the dynamic liquid level at 622 meters;

[0039] Figure 8 This is a monitoring chart of the dynamic liquid level at 807 meters.

[0040] Explanation of symbols for key components in the attached diagram:

[0041] In the picture:

[0042] 1. Armored optical cable; 2. Fiber optic acoustic wave sensor modulator / demodulator.

[0043] 3. Fiber optic cable clamps 4. Oil pipes

[0044] 5. Casing 6. Oil pump. Detailed Implementation

[0045] The present invention will now be described in detail with reference to the accompanying drawings and embodiments:

[0046] Appendix Figure 1-8 It is known that a method for real-time monitoring of dynamic fluid level based on distributed fiber optic acoustic sensing technology includes an armored optical cable deployed inside the well and a high spatial resolution fiber optic acoustic sensing modulator / demodulator located at the wellhead; the armored optical cable is fixed to the outer wall of the tubing by optical cable clamps; the armored optical cable is connected to the fiber optic acoustic sensing modulator / demodulator, and includes the following steps:

[0047] (1) Before entering the well, use an acoustic wave sensor modulator on the ground to test the optical fibers in the armored optical cable to ensure that they meet the quality requirements and work normally.

[0048] (2) When entering the well, the armored optical cable is tied to the oil pipe and lowered into the well. During the lowering process, the ground acoustic wave sensor modulator is turned on at key time points to detect and monitor the status of the optical cable.

[0049] During the well entry process, at integer depths such as 500m, 1000m, 2000m, and 3000m (depending on the tightness of the construction time and the precision of construction risk control, 3-5 detection and monitoring depth points are generally selected during the entry process; the specific number of detection and monitoring checks is to balance the early detection of fiber optic anomalies with the reduction of the number of shutdowns), the fiber optic signal entry operation is paused and tested.

[0050] The fiber optic cable is most vulnerable to damage during the well entry phase, and any damage will prevent subsequent monitoring and construction. Therefore, the following protective measures should be taken during the installation of armored fiber optic cables: a. Before installing the armored fiber optic cable, the well conditions (including the wellbore trajectory, instrument strings, etc.) should be thoroughly understood, and its suitability for installation should be assessed; b. Once it is determined that the armored fiber optic cable can be installed, it should be installed as smoothly and at a uniform speed as possible; c. At well drilling points, points of abrupt changes in the well trajectory, or where downhole tools obstruct the path, the installation speed should be further slowed down, and surface observation and inspection should be intensified.

[0051] (3) After entering the well, the ground acoustic wave sensor modulator and demodulator is kept on to continuously detect the status of the optical cable in real time, obtain the sound vibration signal distributed along the trajectory of the oil pipe or wellbore, and save it in the ground storage device or display it in real time on the ground monitoring screen.

[0052] (4) By playing back the sound vibration signal recorded by the acoustic wave sensor modulator and demodulator, the dynamic liquid surface is identified and monitored by intelligent algorithms;

[0053] (5) After the construction is completed, leave the well site.

[0054] When the ground-based acoustic wave sensor modulator / demodulator detects and monitors the optical cable's status, it compares the OTDR attenuation curves of the optical fiber cable with those of normal optical fiber cables stored in the OTDR attenuation curve database. If the OTDR attenuation curve of a normal optical fiber cable is smooth and the attenuation rate is within a reasonable range, the optical fiber cable is considered normal. If reflective discontinuities (i.e., strong reflection signals at abnormal points, usually caused by fiber breaks or fiber scratches) or non-reflective rapid attenuation discontinuities (usually due to poor fiber quality and severe attenuation of the optical signal within the fiber) occur, the optical fiber cable is considered abnormal, and a backup optical fiber cable is activated. The ground-based acoustic wave sensor modulator / demodulator then re-detects and monitors the optical cable's status, comparing the OTDR attenuation curves of the optical fiber cable with those of normal optical fiber cables stored in the OTDR attenuation curve database. If the attenuation rate is within a reasonable range, the backup fiber optic cable is considered normal. If the same reflective discontinuity or non-reflective rapid attenuation discontinuity occurs, the backup fiber optic cable is preliminarily considered abnormal. After the armored fiber optic cable is lowered 50 to 100 meters into the well along with the tubing, the surface acoustic wave sensor modulator is restarted to detect and monitor the status of both the fiber optic cable and the backup fiber optic cable. If the OTDR attenuation curves of the fiber optic cable and the backup fiber optic cable are compared with the OTDR attenuation curves of normal fiber optic cables stored in the database, and the attenuation rate is within a reasonable range, both the fiber optic cable and the backup fiber optic cable are considered normal. If either the fiber optic cable or the backup fiber optic cable is normal, the normal fiber optic cable is used to continue lowering. If both the fiber optic cable and the backup fiber optic cable are abnormal, the armored fiber optic cable is pulled up, replaced on the surface, and then re-lowered into the well.

[0055] like Figure 2 As shown, the normal curve is smooth and relatively flat.

[0056] like Figure 3 This is a schematic diagram of an OTDR attenuation curve exhibiting abnormal phenomena and failing the test results. There are two types of abnormal phenomena in the diagram: one is reflective discontinuity (i.e., there is a strong reflected signal at the abnormal point, usually caused by a broken fiber or fiber scratches, resulting in a reflection peak), and the other is non-reflective rapid attenuation discontinuity (usually caused by poor fiber quality, resulting in severe attenuation of the optical signal in the fiber).

[0057] Identify and monitor dynamic liquid levels using intelligent algorithms;

[0058] The dynamic fluid level is located above the production layer and close to the surface (above the top boundary of the perforation layer and the oil pump, and generally within the upper 3 / 4 depth of the entire well). The dynamic fluid level fluctuates regularly as production progresses. When production increases, the dynamic fluid level decreases, and when production decreases, the dynamic fluid level tends to rise. The location of a large-amplitude sound vibration that meets the above characteristics can be identified as the dynamic fluid level.

[0059] Artificial neural networks have been widely used in pattern recognition in Ф-OTDR systems. Commonly used neural network models include Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), and Long Short-Term Memory Neural Networks (LSTM). Since the intensity of the scattered signal in a Ф-OTDR system does not change linearly with the perturbation signal, while the phase difference of the scattered light at both ends of the perturbation point has a linear relationship with the perturbation signal, existing phase demodulation-based Ф-OTDR pattern recognition typically uses differential phase signals as input to the model network. However, the interference fading phenomenon in coherent detection systems causes a severe deterioration in the signal-to-noise ratio of the intensity signal, leading to anomalies in the demodulated phase at the fading point. If only phase information is used for detection, false alarms will occur. If the signal intensity data is analyzed together, the intensity information at the interference fading point will show obvious minimum points with significant features. Therefore, this invention adopts a pattern recognition method based on a hybrid input of two-dimensional intensity and phase signals. Building upon existing neural network models, it extracts fading noise features from the intensity signal to assist the phase signal in event detection. Considering both algorithm complexity and ease of deployment, this invention uses a 1DCNN model as the base model to construct a hybrid deep neural network (HDNN) with mixed two-dimensional signal input. The HDNN includes a 1DCNN module and a multilayer perceptron (MLP) module, and its network model structure is as follows: Figure 6As shown: Input1 is the phase vector input to the 1DCNN module, which passes through a total of 12 convolutional layers (Conv1D), activation layers, and pooling layers before being fed into a fully connected layer (FC) as the output of the CNN module. The activation layer uses the Rectified Linear Activation (ReLU) function, and the pooling layer uses max pooling. Input2 is the intensity vector input to the MLP module, which passes through 2 FC layers and 1 tanh function activation layer before being connected to an FC layer as the output of the MLP module. The outputs of the CNN module and the MLP module are jointly input into two consecutive FC+ReLU layers for compressed activation, and then passed through a softmax layer for classification output.

[0060] Based on abnormal dynamic fluid level data, predicting impending accidents in oil wells can reduce energy consumption and improve recovery rates.

[0061] For flowing oil or gas wells, when the dynamic fluid level depth plus the annular pressure is insufficient to ensure the well flows, it is necessary to supplement the reservoir with energy. The annular pressure can be measured from a surface pressure gauge.

[0062] Therefore, monitoring and predicting the dynamic fluid level depth is crucial for the normal production of flowing oil and gas wells. This technology can identify, monitor, and predict the location of the dynamic fluid level in real time. This not only provides valuable guidance for determining whether the well can currently flow, but also allows for prediction of the dynamic fluid level at a future point in time based on historical and recent patterns of change, and can successfully predict potential accidents such as well-stopped flow.

[0063] For ESP wells, the ESP will not work when the dynamic fluid level is lower than the ESP inlet. To avoid ESP failure, this technology can be used to monitor the rise and fall of the dynamic fluid level in real time, so that measures can be taken in advance to ensure that the ESP can work normally or in the best condition.

[0064] For pumped oil wells, when the submersion depth (the difference in depth between the dynamic fluid level and the pumped oil well's suction inlet) is less than a certain value, the pumped oil well may not be able to draw enough fluid, thus affecting its working efficiency. In extreme cases, when the dynamic fluid level is lower than the pumped oil well's suction inlet, the pumped oil well cannot pump fluid or operate. Therefore, in order to reduce energy consumption and ensure the normal progress of the oil production plan, it is necessary to monitor the dynamic fluid level in real time, thereby ensuring that the pumped oil well operates in good condition and avoiding malfunctions.

[0065] like Figure 5 To improve the depth accuracy of monitoring data, well depth correction is required for the fiber optic cable insertion depth when interpreting dynamic fluid level monitoring data. The correction principle is as follows:

[0066] At a fixed location on the ground, the optical cable is tapped with a special tool. The location of the increased amplitude on the DAS waterfall chart is observed in real time. From the DAS time waterfall chart, the distance L1 from the location of the calibration point to the DAS demodulator can be accurately read. Then, the distance L2 from the calibration point to the wellhead is measured along the optical cable. The total length of the optical fiber is L... 光纤总长 Under certain conditions, the length of the optical cable entering the well, L3 = L, can be calculated. 光纤总长 -L1-L2, the fiber optic insertion length L3 plus the overlay spacing KB gives the depth of the well corresponding to the maximum insertion depth of the optical cable. Therefore:

[0067] L4 = MD 光缆末端 =L3+KB=L 光纤总长 -L1-L2+KB

[0068] Similarly, if the distance from a point on the optical fiber (such as a dynamic liquid surface) to the DAS demodulator is X (i.e., the position reading on the DAS waterfall chart is X), then the corresponding well depth can be calculated by the following formula:

[0069] MD X =MD 光缆末端 -(L 光纤总长 -X)=MD 光缆末端 -L 光纤总长 +X

[0070] Thus, according to the above formula, the well depth corresponding to the change in the dynamic fluid level coordinate X can be calculated.

[0071] Appendix Figure 6 Medium parameters:

[0072] L1: The optical cable length from the tapping point to the DAS;

[0073] L2: The length of the optical cable from the impact point to the wellhead;

[0074] L3: The length of the optical cable from the wellhead to the end of the well.

[0075] L4: The length from the end of the optical cable to the square filler core along the wellbore direction, i.e., the optical cable end depth measurement MD;

[0076] KB: Oil compensation distance;

[0077] This invention relates to a method for real-time monitoring of dynamic fluid levels based on distributed fiber optic acoustic sensing technology. The downhole dynamic fluid level will experience slight fluctuations, generating vibration / sound signals. The fiber optic acoustic sensing modulator collects the vibration / sound signals along the fiber optic cable in real time and displays the depth and position of the downhole dynamic fluid level in real time.

[0078] Optical fibers are widely used in the oil and gas industry due to their advantages such as small size, light weight, low loss, wide bandwidth, strong anti-interference ability, and ease of construction and maintenance. Fiber optic acoustic wave sensing technology can monitor vibration / sound signals along the length of the optical fiber in real time and can be used for real-time monitoring of dynamic fluid levels in downhole wells.

[0079] The above description is merely a preferred embodiment of the present invention and does not constitute any limitation on the structure of the present invention. Any simple modifications, equivalent changes, and alterations made to the above embodiments based on the technical essence of the present invention shall fall within the scope of the technical solution of the present invention.

Claims

1. A method for real-time monitoring of dynamic fluid level based on distributed fiber optic acoustic sensing technology, comprising an armored optical cable deployed in the well and a high spatial resolution fiber optic acoustic sensing modulator / demodulator located at the wellhead; the armored optical cable is fixed to the outer wall of the tubing by optical cable clamps; the armored optical cable is connected to the fiber optic acoustic sensing modulator / demodulator, characterized in that... Includes the following steps: (1) Before entering the well, use an acoustic wave sensor modulator on the ground to test the optical fibers in the armored optical cable to ensure that they meet the quality requirements and work normally. (2) When entering the well, the armored optical cable is tied to the oil pipe and lowered into the well. During the lowering process, the ground acoustic wave sensor modulator is turned on at key time points to detect and monitor the status of the optical cable. (3) After entering the well, the ground acoustic wave sensor modulator and demodulator is kept on to continuously detect the status of the optical cable in real time, obtain the sound vibration signal distributed along the trajectory of the oil pipe or wellbore, and save it in the ground storage device or display it in real time on the ground monitoring screen. (4) By playing back the sound vibration signal recorded by the acoustic wave sensor modulator and demodulator, the dynamic liquid surface is identified and monitored by intelligent algorithms; (5) Construction completed, evacuated from the well site; The steps for intelligent algorithms to identify and monitor dynamic liquid levels are as follows: Input 1 is the phase vector input into the 1DCNN module of a one-dimensional deep convolutional neural network. After passing through a total of 12 layers of convolutional layers, activation layers and pooling layers, it is input into a fully connected layer as the output of the CNN module. The activation layer uses a linear rectified function and the pooling layer uses max pooling. Input 2 is an intensity vector input into the MLP module. After being activated by two FC layers and one tanh function layer, it is connected to an FC layer as the output of the MLP module. The outputs of the CNN and MLP modules are combined and then fed into two consecutive FC+ReLU layers for compressed activation. Finally, the output is classified through a flexible maximum layer. The steps for correcting the well depth for the fiber optic cable insertion depth are as follows: At a fixed location on the ground, the optical cable is tapped with a special tool. The location of the increased amplitude on the DAS waterfall chart is observed in real time. The distance L1 from the positioning tapping calibration point to the DAS demodulator is accurately read from the DAS time waterfall chart. Then, the distance L2 from the calibration tapping point to the wellhead is measured along the optical cable. The total length L of the optical fiber is... 光纤总长 Under certain conditions, the length of the optical cable entering the well, L3, can be calculated as L. 光纤总长 -L1-L2, the fiber optic insertion length L3 plus the overlay spacing KB gives the depth of the well corresponding to the maximum insertion depth of the optical cable. Therefore: MD 光缆末端 =L3+KB= L 光纤总长 -L1-L2+KB Similarly, if the distance from a point on the optical fiber to the DAS demodulator is X, then its corresponding well depth is calculated by the following formula: MD X = MD 光缆末端 -(L 光纤总长 -X)= MD 光缆末端 -L 光纤总长 +X According to the above formula, the well depth corresponding to the change in the dynamic fluid surface coordinate X can be calculated.

2. The method for real-time monitoring of dynamic liquid surface based on distributed fiber optic acoustic sensing technology according to claim 1, characterized in that: When the ground-based acoustic wave sensor modulator and demodulator detects and monitors the condition of optical cables, it compares the OTDR attenuation curves of optical cables with those of normal optical cables stored in the database. If the OTDR attenuation curve of a normal optical cable is smooth and the attenuation rate is within a reasonable range, the optical cable is determined to be normal. If a reflective discontinuity or a non-reflective rapid decay discontinuity occurs; If an abnormality is detected in the fiber optic cable, activate the backup fiber optic cable. The ground-based acoustic wave sensor modulator and demodulator re-detects and monitors the optical cable status, comparing the OTDR attenuation curve of the optical fiber cable with the OTDR attenuation curve of normal optical fiber cables stored in the database; if the attenuation rate is within a reasonable range, the backup optical fiber cable is determined to be normal. If the same reflective discontinuity or non-reflective rapid attenuation discontinuity occurs, it is preliminarily determined that the backup fiber optic cable is abnormal. After the armored optical cable is lowered 50 to 100 meters into the well along with the tubing, the surface acoustic wave sensor modulator is restarted to detect and monitor the status of the optical cable and the backup optical cable. If the OTDR attenuation curves of the optical cable and the backup optical cable are compared with the OTDR attenuation curves of normal optical cables stored in the database, and the attenuation rate is within a reasonable range, both the optical cable and the backup optical cable are considered normal. If either the optical cable or the backup optical cable is normal, the normal optical cable is used to continue lowering. If both the optical cable and the backup optical cable are abnormal, the armored optical cable is pulled up, replaced on the surface, and then lowered back into the well.

3. The method for real-time monitoring of dynamic liquid level based on distributed fiber optic acoustic sensing technology according to claim 1, characterized in that: The dynamic liquid surface is identified and monitored by intelligent algorithms. The dynamic liquid surface is located above the production layer and close to the ground. The dynamic liquid surface fluctuates regularly as mining progresses. When the output increases, the dynamic liquid surface decreases. When the output decreases, the dynamic liquid surface tends to rise. The location of large-amplitude sound vibration that meets the above characteristics is identified as the dynamic liquid surface.

4. The method for real-time monitoring of dynamic liquid level based on distributed fiber optic acoustic sensing technology according to claim 1, characterized in that: Based on abnormal dynamic fluid level data, an accident is predicted to occur in the oil well; For self-flowing oil or gas wells, when the dynamic fluid level depth plus the annular pressure is insufficient to ensure the self-flowing of the oil or gas well, it is necessary to supplement the energy of the oil or gas reservoir. The annular pressure is measured from the surface pressure gauge. For ESP wells, when the dynamic fluid level is lower than the ESP inlet, the ESP will not work. Real-time monitoring of the rise and fall of the dynamic fluid level allows for proactive measures to ensure that the ESP can work normally or operate in optimal condition. For pumping wells, when the submersion is less than the set safety value, the pumping unit cannot draw in enough fluid, which affects the working efficiency of the pumping unit. In extreme cases, when the dynamic fluid level is lower than the pumping unit's downhole suction inlet, the pumping unit will be unable to pump fluid and operate.

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