Intelligent operation and maintenance system for oil and gas field pipeline leakage detection

Abstract

The invention discloses an intelligent operation and maintenance system for oil and gas field pipeline leakage detection, which comprises a quantum enhanced distributed optical fiber sensing unit, a leakage positioning unit and a self-healing unit, and is characterized in that quantum enhanced optical fibers implanted with nanoscale gratings are arranged along the outer wall of a pipeline, and a compressed laser light source is utilized to trigger vibration and sound wave signals; the superconducting quantum edge node performs quantum Fourier transform preprocessing on the signal, and realizes sub-meter accurate positioning by combining a space-time convolutional neural network model with pipeline physical parameters; and finally, the system drives the directional microwave device to activate the intelligent coating at the leakage point, the shape memory polymer microcapsule pre-buried in the pipeline coating is triggered to be broken and expanded, a self-adaptive sealing layer is formed, and full-closed-loop automatic response from quantum-level sensing to molecular-level repairing is completed. Detection and repair are completed autonomously, manual intervention is not needed, zero commuting time occupation is achieved, and the corresponding repair speed can be increased to the second level from the traditional day / hour level.

Description

Technical Field

[0001] The present invention relates to the technical field of oil and gas field management systems, in particular to the technical field of oil and gas field pipeline leakage detection, and specifically to an intelligent operation and maintenance system for oil and gas field pipeline leakage detection. Background Art

[0002] Leakage monitoring technology for oil and gas field pipelines is the key to ensuring energy transportation safety, reducing environmental pollution and economic losses. The current mainstream monitoring methods can be divided into two categories: indirect monitoring based on physical parameters and direct monitoring based on sensors. The technical means cover traditional algorithms and new intelligent systems, forming a multi-dimensional and multi-level monitoring system.

[0003] Traditional leakage monitoring technology mainly relies on the real-time change analysis of pipeline operating parameters. The pressure gradient method and flow balance method are the most widely used basic methods. The pressure gradient method identifies leaks by monitoring the changes in the pressure difference between the two ends of the pipeline. The principle is that the leakage point will cause a sudden drop in pressure and form a specific waveform. Combined with the propagation speed of the negative pressure wave, the leakage position can be located. The positioning accuracy is usually within 1%-2% of the total length of the pipeline. The flow balance law judges leaks by comparing the difference between the inlet and outlet flow rates. It is suitable for steady-state conditions, but it is not sensitive enough to small leaks (<1% flow). In addition, the acoustic wave detection technology uses the acoustic emission signal generated by the leak, which is transmitted through the pipe wall to the sensor array, and combines the time difference positioning algorithm (such as cross-correlation analysis) to realize the identification of the leak point. The accuracy can reach tens of meters, but it is easily affected by environmental noise.

[0004] Gas sensing technology and infrared thermal imaging are direct detection methods. The former monitors abnormal gas concentrations around pipelines in real time by arranging gas sensors such as methane and hydrogen sulfide, and is suitable for surface or shallow buried pipelines; the latter uses infrared cameras to capture local temperature changes caused by leaks, and is especially suitable for low-temperature or high-temperature medium leakage scenarios. For long-distance pipelines, infrasound monitoring technology captures low-frequency pressure waves (0.01-1Hz) for long-distance detection, with an effective coverage range of hundreds of kilometers, but slow response to small leaks. The limitations of traditional technology are that it relies on a single parameter, has weak anti-interference capabilities, and requires manual experience to assist decision-making. In recent years, multi-sensor fusion technology has significantly reduced the false alarm rate by integrating multi-source data such as pressure, flow, and sound waves, and combining Kalman filtering or wavelet transform algorithms to improve detection reliability.

[0005] In the prior art, detection or monitoring is the main method. After the detection system finds a leak in the oil and gas pipeline, it issues an alarm, then arranges manual inspections to verify, and finally plugs the leak through manual repair. This method has a low plugging efficiency for oil and gas pipelines, mainly because the length of the oil and gas pipelines is too long. For this reason, the present invention proposes another operation and maintenance system for oil and gas field pipelines, which is used to realize leak detection and self-repair of oil and gas field pipelines, reduce the probability of manual intervention, and improve the accuracy of detection and the efficiency of plugging. Summary of the invention

[0006] In order to solve the real-time detection and plugging problems of oil and gas field pipelines in the prior art, the present application provides an intelligent operation and maintenance system for oil and gas field pipeline leakage detection, which can realize autonomous detection and plugging. Compared with traditional manual inspections and sensor leak detection, and then manual repair and plugging, it has the advantages of high detection accuracy, accurate positioning, and timely plugging.

[0007] In order to achieve the above purpose, the technical solution adopted in this application is:

[0008] An intelligent operation and maintenance system for oil and gas field pipeline leakage detection, including a quantum enhanced distributed optical fiber sensing unit, including an ultra-weak grating optical fiber spirally arranged along the outer wall of the pipeline, and an implanted nanoscale optical fiber grating is built every meter; a quantum light source module for emitting compressed state laser into the grating optical fiber, wherein the wavelength stability of the compressed state laser is ≤±0.01nm; and a superconducting quantum edge computing node deployed along the pipeline, with a built-in superconducting quantum bit array, for performing quantum Fourier transform preprocessing on the optical fiber sensing signal; a leakage positioning unit, including a spatiotemporal convolutional neural network model for receiving signals processed by the superconducting quantum edge computing node, fusing the pipeline pressure F and historical flow data Q, and outputting a probability distribution of the leakage point, and a microwave excitation device for directionally emitting 2.45GHz microwaves to the pipeline coating area corresponding to the leakage point; a self-healing unit, including pre-buried shape memory polymer SMP microcapsules, which are ruptured under the triggering of microwaves emitted by the microwave excitation device to release SMP to form a sealing layer to block the leakage point.

[0009] Preferably, the process of the superconducting quantum edge computing node performing quantum Fourier transform preprocessing on the optical fiber sensing signal comprises the following steps:

[0010] Step 1: Fiber Bragg grating collects time domain signals including vibration or temperature;

[0011] Step 2: Convert the analog signal collected in step 1 into a digital signal through an analog-to-digital converter ADC, and perform sampling and normalization processing;

[0012] Step 3: Encode the digital signal obtained in step 2 into the quantum state |ψ> to complete quantum encoding; where the quantum state |n> is the calculation ground state;

[0013] Step 4: Use quantum Fourier transform QFT to convert the quantum state |ψ> that completes the quantum encoding into a frequency domain state By frequency domain Feature extraction is performed, and the extracted frequency domain features are used for the subsequent leakage location unit to determine the leakage point.

[0014] Further preferably, the quantum Fourier transform QFT in step 4 acts on the quantum state |ψ> and converts the quantum state |ψ> into a frequency domain state Defined as:

[0015]

[0016] Among them, |n> is the quantum state, which represents the nth calculation basis state, corresponding to the nth sampling point of the discrete time domain signal in signal processing; |k> represents the output quantum state, which represents the kth basis state in the frequency domain, corresponding to the kth frequency component in the discrete frequency domain; N represents the total number of sampling points of the signal; represents the normalization factor; the exponential term e 2 πink / N Represents the core phase rotation factor of the Fourier transform.

[0017] Still further preferably, the process of the leakage locating unit outputting the probability distribution of leakage points comprises the following steps:

[0018] Step a: Concatenate the frequency domain state and the time domain signal in the feature dimension to form a joint input tensor X joint :

[0019] X joint =Concat(X freq ,X time )∈R T*N(D+2)

[0020] Among them, X freq ∈R T*N*D is the frequency domain feature matrix after QFT preprocessing, T represents the time window length, N represents the number of locations / sensor nodes after pipeline discretization, and N represents the frequency domain feature dimension;

[0021] Step b: Map high-level features to the leakage probability distribution matrix P through the fully connected layer leak :

[0022]

[0023] Among them, σ represents the Sigmoid function, which outputs the leakage probability P of each position n ∈[0,1], leakage probability distribution matrix P leak ∈R N , indicating the possibility of leakage at various locations of the pipeline; Represents the high-level feature tensor output by the last layer of spatial convolution; the Flatten operation is to convert the three-dimensional tensor Flattened into a one-dimensional vector; the Linear layer maps the flattened features to the same dimension as the number of pipeline positions N, that is, the output R N .

[0024] Beneficial effects:

[0025] 1. The present invention uses autonomous detection and repair, without the need for human intervention, to achieve zero commuting time, and the corresponding repair speed can be improved from the traditional day / hour level to the second level; the existing manual inspection cycle is as long as several days, for example, the response delay of the automation system (such as SCADA) is about 10-30 minutes. The quantum edge node of the present invention processes signals in real time, combined with the self-healing coating (microwave-triggered SMP seal), to achieve a leakage alarm of less than 10 seconds and a self-healing response of no more than 60 seconds, and the efficiency is significantly improved.

[0026] 2. The detection sensitivity has been greatly improved. Conventional technologies generally rely on pressure waves, sound waves or conventional optical fiber sensors, and the minimum detectable leakage is ≥10L / min. However, the present invention uses quantum compressed state light source (signal-to-noise ratio increased by 10 times) and ultra-weak grating array (spatial resolution 0.1m) to achieve 0.1L / min-level micro-leak detection, which can capture early tiny cracks or corrosion perforations in pipelines. It can detect leaks 90% earlier, preventing small leaks from developing into catastrophic accidents.

[0027] 3. The positioning accuracy of the detection is higher than that of existing detection technologies. The positioning error based on single-ended signal analysis is usually greater than 50 meters (such as distributed optical fiber sensing Φ-OTDR technology), which requires manual secondary investigation. The present invention combines quantum edge computing (quantum Fourier transform acceleration) and spatiotemporal convolutional neural network (ST-CNN) physical model to achieve sub-meter positioning accuracy of less than 0.5 meters.

[0028] 4. The single optical fiber of the present invention covers the material cost of the entire pipeline, and the self-healing coating reduces the need for repair by 80%. Compared with the traditional technology that relies on dense sensor distribution and high-frequency manual inspections, the comprehensive operation and maintenance cost is significantly reduced.

[0029] 5. The present invention can adapt to more severe installation environments. The present invention uses titanium alloy sheathed optical fiber (pressure resistance 60MPa), quantum light source constant temperature control (±0.1℃), SMP coating (-40℃~150℃ stable), and adapts to all terrains and climates. Compared with traditional technologies, sensors are prone to failure in extreme environments, such as deep sea high pressure environment and desert high temperature environment, which are prone to detection failure. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For those skilled in the art, other drawings can be obtained based on these drawings without paying any creative labor.

[0031] Figure 1 It is a system principle block diagram of the present invention.

[0032] In the figure: 1-grating optical fiber; 1a-fiber grating; 2-quantum light source module; 3-superconducting quantum edge computing node; 3a-superconducting quantum bit array; 4-space-time convolutional neural network model; 5-microwave excitation device; 6-microcapsule. DETAILED DESCRIPTION

[0033] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments. The components of the embodiments of the present application described and shown in the drawings here can be arranged and designed in various different configurations.

[0034] Therefore, the following detailed description of the embodiments of the present application provided in the accompanying drawings is not intended to limit the scope of the present application for which protection is sought, but merely represents selected embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in the field without creative work are within the scope of protection of the present application.

[0035] It should be noted that similar reference numerals and letters denote similar items in the following drawings, and therefore, once an item is defined in one drawing, further definition and explanation thereof is not required in subsequent drawings.

[0036] In the description of this application, it should be noted that if the terms "center", "up", "down", "left", "right", "vertical", "horizontal", "inside", "outside", etc. appear, the orientation or position relationship indicated is based on the orientation or position relationship shown in the drawings, or the orientation or position relationship in which the product of the application is usually placed when in use. It is only for the convenience of describing this application and simplifying the description, and does not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operate in a specific orientation, and therefore cannot be understood as a limitation on this application. In addition, if the terms "first", "second", etc. appear in the description of this application, they are only used to distinguish the description and cannot be understood as indicating or implying relative importance.

[0037] In addition, if the terms "horizontal" or "vertical" appear in the description of this application, it does not mean that the components are required to be absolutely horizontal or suspended, but can be slightly tilted. For example, "horizontal" only means that its direction is more horizontal than "vertical", and does not mean that the structure must be completely horizontal, but can be slightly tilted.

[0038] In the description of this application, it should also be noted that, unless otherwise clearly specified and limited, the terms "set", "install", "connect", and "connect" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal connection of two components. For ordinary technicians in this field, the specific meanings of the above terms in this application can be understood according to specific circumstances.

[0039] Embodiment 1:

[0040] Combination Figure 1An intelligent operation and maintenance system for oil and gas field pipeline leakage detection is shown, including a quantum enhanced distributed optical fiber sensing unit, including an ultra-weak grating optical fiber 1 spirally arranged along the outer wall of the pipeline, and an implanted nanoscale optical fiber grating 1a is built every meter; a quantum light source module 2 for emitting compressed state laser into the grating optical fiber 1, wherein the wavelength stability of the compressed state laser is ≤±0.01nm; and a superconducting quantum edge computing node 3 deployed along the pipeline, with a built-in superconducting quantum bit array 3a, for performing quantum Fourier transform preprocessing on the optical fiber sensing signal; a leakage positioning unit, including a spatiotemporal convolutional neural network model 4 for receiving the signal processed by the superconducting quantum edge computing node 3, and then fusing the pipeline pressure F and the historical flow data Q to output the probability distribution of the leakage point, and a microwave excitation device 5 for directionally emitting 2.45GHz microwaves to the pipeline coating area corresponding to the leakage point; a self-healing unit, including a pre-buried shape memory polymer SMP microcapsule 6, which is triggered by microwaves emitted by the microwave excitation device 5 to rupture and release SMP to form a sealing layer to block the leakage point. It is worth noting that, in this embodiment, the ultra-weak grating fiber 1 and the nanoscale fiber grating 1a are not the same object, but there is a hierarchical inclusion relationship, as follows:

[0041] Ultra-weak grating fiber refers to an optical fiber with an integrated grating structure, which can be divided into two categories: ordinary optical fiber and special structure optical fiber; such as the carrier of fiber grating: that is, FBG is written on ordinary optical fiber. It can also be a special structure optical fiber: such as long period grating fiber (LPG), tilted grating fiber (TFG), or the grating function is directly realized through optical fiber design (such as microstructured optical fiber). The fiber grating in this embodiment is a periodic refractive index modulation structure formed in the optical fiber core by ultraviolet laser etching or other technologies, which can reflect light of a specific wavelength (Bragg wavelength) and transmit other wavelengths, and is used for single-point or multi-point sensing.

[0042] In this embodiment, the process of the superconducting quantum edge computing node 3 performing quantum Fourier transform preprocessing on the optical fiber sensor signal includes the following steps:

[0043] Step 1: The fiber Bragg grating 1a collects time domain signals including vibration or temperature;

[0044] Step 2: Convert the analog signal collected in step 1 into a digital signal through an analog-to-digital converter ADC, and perform sampling and normalization processing;

[0045] Step 3: Encode the digital signal obtained in step 2 into the quantum state |ψ> to complete quantum encoding; where the quantum state |n> is the calculation ground state;

[0046] Step 4: Use quantum Fourier transform QFT to convert the quantum state |ψ> that completes the quantum encoding into a frequency domain state By frequency domain Feature extraction is performed, and the extracted frequency domain features are used for the subsequent leakage location unit to determine the leakage point.

[0047] In this embodiment, the quantum Fourier transform QFT in step 4 acts on the quantum state |ψ> and converts the quantum state |ψ> into a frequency domain state Defined as:

[0048]

[0049] Among them, |n> is the quantum state, which represents the nth calculation basis state, corresponding to the nth sampling point of the discrete time domain signal in signal processing; |k> represents the output quantum state, which represents the kth basis state in the frequency domain, corresponding to the kth frequency component in the discrete frequency domain; N represents the total number of sampling points of the signal; represents the normalization factor; the exponential term e 2 πink / N Represents the core phase rotation factor of the Fourier transform.

[0050] In this embodiment, the process of the leakage location unit outputting the probability distribution of leakage points includes the following steps:

[0051] Step a: Concatenate the frequency domain state and the time domain signal in the feature dimension to form a joint input tensor X joint :

[0052] X joint =Concat(X freq ,X time )∈R T*N(D+2)

[0053] Among them, X freq ∈R T*N*D is the frequency domain feature matrix after QFT preprocessing, T represents the time window length, N represents the number of locations / sensor nodes after pipeline discretization, and N represents the frequency domain feature dimension;

[0054] Step b: Map high-level features to the leakage probability distribution matrix P through the fully connected layer leak :

[0055]

[0056] Among them, σ represents the Sigmoid function, which outputs the leakage probability P of each position n ∈[0,1], leakage probability distribution matrix P leak ∈R N , indicating the possibility of leakage at various locations of the pipeline; Represents the high-level feature tensor output by the last layer of spatial convolution; the Flatten operation is to convert the three-dimensional tensor Flattened into a one-dimensional vector; the Linear layer maps the flattened features to the same dimension as the number of pipeline positions N, that is, the output R N .

[0057] In order to more clearly explain the working principle and process of the present invention in the process of leak detection of oil and gas field pipelines, the present invention will be described in detail from three parts: hardware composition and preparation before installation, staged installation process and debugging after installation.

[0058] Part 1: Hardware composition and preparation before installation

[0059] The core hardware list required by the present invention is shown in Table 1 below

[0060]

[0061]

[0062] Table 1 Core hardware list

[0063] After preparing the core hardware that needs to be installed in the system, the installation environment needs to be surveyed before the formal installation. Since oil and gas field pipelines usually run through the ocean and the continent, installation in the ocean requires professional equipment and responsible processes. In order to facilitate the description and understanding of the technical content of the present invention, this embodiment takes land installation as an example for illustration. Since there may be unpredictable situations in the preset installation path of the pipeline, especially in desert areas; therefore, before installation, it is necessary to use drone LiDAR to scan the pipeline direction, identify geological disaster risk areas (such as landslides, frost heaves), plan and clarify the fiber optic laying path, so as to ensure that the pipeline installation path is feasible and avoid unnecessary losses and cost increases caused by midway stoppages due to weather during construction. After ensuring that the installation requirements are met in both the construction period and the path, it is necessary to pre-package the optical fiber: compound the ultra-weak grating optical fiber with the armored protective layer (including hydrogen permeation barrier coating) to improve the mechanical strength. At the same time, the pipeline pressure fluctuation (0-20MPa) is simulated in the laboratory, the laser wavelength stability (1550nm±0.01nm) is optimized, and the quantum light source is calibrated.

[0064] Part 2: Staged Installation

[0065] First, the quantum optical fiber sensor network is installed. The synchronous winding method is used to spirally wind the optical fiber on the outer wall of the pipeline (spacing <5cm), and the outer layer is covered with SMP microcapsule coating (thickness 2mm). During the installation process, it is preferred to use an automatic laying robot to ensure constant optical fiber tension (50N±5N). Redundant optical fiber rings are added at welds and elbows to avoid stress concentration and breakage. If the installation path includes an overhead section, it is necessary to fill an aerogel insulation layer between the optical fiber and the pipeline to prevent temperature drift caused by sunlight exposure. After the installation of the optical fiber sensor network is completed, a quantum light source station needs to be set up every 50km, including: compressed state laser (power consumption <100W), acousto-optic modulator (AOM) and quantum noise suppression module; during the installation process, it is particularly important to note that the site should be built in the pipeline valve room or booster station, using a double-layer electromagnetic shielding cabin (shielding effectiveness ≥80dB), and maintaining the temperature stability of the laser through a thermoelectric cooler (TEC) (fluctuation <0.05℃). Finally, the installation of the superconducting quantum edge node is completed. A superconducting quantum edge node is deployed every 10km along the optical fiber, including: superconducting quantum processor (including 50+ quantum bits), dilution refrigerator, and microwave control circuit. During installation, it is preferred to encapsulate the quantum chip in a multi-layer adiabatic radiation shield, pre-cool it to 4K with liquid helium, connect the refrigerator to maintain low temperature, and deploy a vibration-resistant foundation (vibration isolation frequency <1Hz) to prevent mechanical disturbances from affecting the coherence of the quantum state. The operation of the entire operation and maintenance system is inseparable from stable electricity. The system is powered by a wind-solar complementary power supply system (wind power + photovoltaic + supercapacitor) to ensure continuous energy supply in extreme environments (power consumption is about 5kW / node). Generally, the areas where oil and gas pipelines are laid are dominated by strong winds. The use of wind power + photovoltaic functions has an innate environmental advantage. Combined with supercapacitors and energy storage equipment to back up the system's energy, it can not only ensure the stability of power supply, but also maintain the continuity of power supply.

[0066] After completing the above installation, the self-healing system is installed. Integrating the self-healing system into the detection system is one of the key technologies of the present invention to shorten the repair response time cycle compared to traditional detection technology. Due to the integration of the self-healing system, it can replace the existing manual secondary positioning inspection. Therefore, it is an essential leap in response speed, and can solve leakage problems hundreds of kilometers away in seconds. Specifically, directional microwave transmitters are installed in high-leakage risk areas of the pipeline (such as elbows and welding points): operating frequency: 2.45GHz (matching the resonant frequency of SMP capsules), installation spacing: one group every 500m, coverage angle 120°, explosion-proof design: in compliance with IECEx certification, housing IP68 protection level. Use a high-pressure spray robot to evenly cover the surface of the pipeline with the SMP microcapsule coating: coating thickness: 2mm±0.2mm, capsule density ≥10 5 Pieces / cm 3Activation test: The capsule rupture response threshold (power density ≤ 10W / m2) was verified by microwave frequency sweep (2.4-2.5GHz).

[0067] After the system is installed, it is necessary to debug the system and run it continuously for at least 72 hours to monitor the laser wavelength drift, which is required to be less than 0.01nm. Then a simulated leakage test is performed, that is, a small leakage of 0.1L / min is created on the test section pipeline, and the following indicators are detected and recorded:

[0068] Detection delay: <10 seconds; Positioning error: <0.5m; Self-healing response: SMP material completes sealing within 60 seconds (leakage volume drops by 99%); High-temperature desert: Continuously operate for 48 hours at 50°C to monitor the optical fiber temperature drift compensation performance.

[0069] In order to more intuitively demonstrate the differences between the present invention and the traditional technology in terms of detection, positioning, response time and cost, the present invention has statistically analyzed the relevant indicators as shown in Table 2 below:

[0070]

[0071] Table 2 Comparison of indicators between the present invention and conventional technology in the field of oil and gas pipeline leakage detection

[0072] Through the above comparison, this technology not only surpasses traditional solutions in all aspects of performance indicators, but also achieves disruptive breakthroughs in economic benefits, environmental compliance, scenario adaptability, etc., providing core technical support for the intelligent transformation of the oil and gas industry.

[0073] The implementation of the oil and gas pipeline leakage monitoring function based on quantum enhanced optical fiber sensing and self-healing materials in this embodiment is briefly described as follows:

[0074] First, quantum-enhanced optical fibers embedded with nanoscale gratings are laid along the outer wall of the pipeline, and compressed laser light sources are used to greatly improve the sensing signal-to-noise ratio, capturing vibration and acoustic wave signals caused by tiny leaks (0.1L / min level) in real time. Subsequently, superconducting quantum edge nodes perform quantum Fourier transform preprocessing on the signals, and combine the spatiotemporal convolutional neural network model to fuse the physical parameters of the pipeline to achieve sub-meter (<0.5m) precise positioning. Finally, the system drives the directional microwave device to activate the smart coating at the leak point, triggering the rupture and expansion of shape memory polymer microcapsules embedded in the pipeline coating, forming an adaptive sealing layer within 60 seconds, completing a fully closed-loop automated response from "quantum-level perception" to "molecular-level repair."

[0075] The technical effects of the technical solution adopted in this embodiment compared with the traditional detection technology are briefly described as follows:

[0076] 1. Since the present invention uses autonomous detection and repair, no human intervention is required, zero commuting time is occupied, and the corresponding repair speed can be improved from the traditional day / hour level to the second level; the existing manual inspection cycle is as long as several days. For example, the response delay of the automation system (such as SCADA) is about 10-30 minutes. The quantum edge node of the present invention processes the signal in real time, combined with the self-healing coating (microwave triggered SMP seal), to achieve a leakage alarm of less than 10 seconds and a self-healing response of no more than 60 seconds, and the efficiency is significantly improved.

[0077] 2. The detection sensitivity has been greatly improved. Conventional technologies generally rely on pressure waves, sound waves or conventional optical fiber sensors, and the minimum detectable leakage is ≥10L / min. However, the present invention uses quantum compressed state light source (signal-to-noise ratio increased by 10 times) and ultra-weak grating array (spatial resolution 0.1m) to achieve 0.1L / min-level micro-leak detection, which can capture early tiny cracks or corrosion perforations in pipelines. It can detect leaks 90% earlier, preventing small leaks from developing into catastrophic accidents.

[0078] 3. The positioning accuracy of the detection is higher than that of existing detection technologies. The positioning error based on single-ended signal analysis is usually greater than 50 meters (such as distributed optical fiber sensing Φ-OTDR technology), which requires manual secondary investigation. The present invention combines quantum edge computing (quantum Fourier transform acceleration) and spatiotemporal convolutional neural network (ST-CNN) physical model to achieve sub-meter positioning accuracy of less than 0.5 meters.

[0079] 4. The single optical fiber of the present invention covers the material cost of the entire pipeline, and the self-healing coating reduces the need for repair by 80%. Compared with the traditional technology that relies on dense sensor distribution and high-frequency manual inspections, the comprehensive operation and maintenance cost is significantly reduced.

[0080] 5. The present invention can adapt to more severe installation environments. The present invention uses titanium alloy sheathed optical fiber (pressure resistance 60MPa), quantum light source constant temperature control (±0.1℃), SMP coating (-40℃~150℃ stable), and adapts to all terrains and climates. Compared with traditional technologies, sensors are prone to failure in extreme environments, such as deep sea high pressure environment and desert high temperature environment, which are prone to detection failure.

[0081] The above description is only the preferred embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. An intelligent operation and maintenance system for oil and gas field pipeline leakage detection, characterized by: include A quantum enhanced distributed optical fiber sensing unit comprises an ultra-weak grating optical fiber (1) spirally arranged along the outer wall of a pipeline, with an implanted nanoscale optical fiber grating (1a) built every meter; a quantum light source module (2) for emitting compressed state laser light into the grating optical fiber (1), wherein the wavelength stability of the compressed state laser light is ≤±0.01nm; and a superconducting quantum edge computing node (3) deployed along the pipeline and having a built-in superconducting quantum bit array (3a) for performing quantum Fourier transform preprocessing on the optical fiber sensing signal; A leakage locating unit, comprising a spatiotemporal convolutional neural network model (4) for receiving a signal processed by a superconducting quantum edge computing node (3), fusing the pipeline pressure F and historical flow data Q, and outputting a probability distribution of a leakage point, and a microwave excitation device (5) for directionally emitting 2.45 GHz microwaves to a pipeline coating area corresponding to the leakage point; The self-healing unit comprises a pre-buried shape memory polymer SMP microcapsule (6). The microcapsule (6) is broken under the triggering of microwaves emitted by a microwave excitation device (5) to release the SMP to form a sealing layer to block the leakage point.

2. The intelligent operation and maintenance system for oil and gas field pipeline leakage detection according to claim 1 is characterized by: The process of the superconducting quantum edge computing node (3) performing quantum Fourier transform preprocessing on the optical fiber sensing signal comprises the following steps: Step 1: The fiber Bragg grating (1a) collects time domain signals including vibration or temperature; Step 2: Convert the analog signal collected in step 1 into a digital signal through an analog-to-digital converter ADC, and perform sampling and normalization processing; Step 3: Encode the digital signal obtained in step 2 into the quantum state |ψ> to complete quantum encoding; where the quantum state |n> is the calculation ground state; Step 4: Use quantum Fourier transform QFT to convert the quantum state |ψ> that completes the quantum encoding into a frequency domain state By frequency domain Feature extraction is performed, and the extracted frequency domain features are used for the subsequent leakage location unit to determine the leakage point.

3. The intelligent operation and maintenance system for oil and gas field pipeline leakage detection according to claim 2 is characterized by: The quantum Fourier transform QFT in step 4 acts on the quantum state |ψ> and converts the quantum state |ψ> into a frequency domain state. Defined as: Among them, |n> is the quantum state, which represents the nth calculation basis state, corresponding to the nth sampling point of the discrete time domain signal in signal processing; |k> represents the output quantum state, which represents the kth basis state in the frequency domain, corresponding to the kth frequency component in the discrete frequency domain; N represents the total number of sampling points of the signal; represents the normalization factor; the exponential term e 2 πink / N Represents the core phase rotation factor of the Fourier transform.

4. An intelligent operation and maintenance system for oil and gas field pipeline leakage detection according to any one of claims 2-3, characterized in that: The process of the leakage location unit outputting the probability distribution of leakage points comprises the following steps: Step a: Concatenate the frequency domain state and the time domain signal in the feature dimension to form a joint input tensor X joint : X joint =Concat(X freq ,X time )∈R T*N(D+2) Among them, X freq ∈R T*N*D is the frequency domain feature matrix after QFT preprocessing, T represents the time window length, N represents the number of locations / sensor nodes after pipeline discretization, and N represents the frequency domain feature dimension; Step b: Map high-level features to the leakage probability distribution matrix P through the fully connected layer leak : Among them, σ represents the Sigmoid function, which outputs the leakage probability P of each position n ∈[0,1], leakage probability distribution matrix P leak ∈R N , indicating the possibility of leakage at various locations of the pipeline; Represents the high-level feature tensor output by the last layer of spatial convolution; the Flatten operation is to convert the three-dimensional tensor Flattened into a one-dimensional vector; the Linear layer maps the flattened features to the same dimension as the number of pipeline positions N, that is, the output R N .

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