Pipeline leakage prediction method and system

Abstract

The present invention discloses a pipeline leakage prediction method and system, belonging to the technical field of pipeline leakage monitoring. The present invention predicts leakage for buried pipelines that have not yet leaked. By establishing a corresponding relationship between the depth of the corrosion pit and the axial strain of the pipeline outer wall, and with the monitoring cooperation of an optical fiber measurement system, the present invention can effectively predict the leakage location and the time when a leak will occur in the buried pipeline that has not yet leaked, thereby preventing problems before they occur, eliminating the need to wait until the pipeline leaks before taking measures, greatly reducing the risk of explosions and the like caused by pipeline leakage, and facilitating its application in pipeline transportation in the fields of oil and natural gas.

Description

Technical Field

[0001] The present invention belongs to the technical field of pipeline leakage monitoring, and in particular relates to a pipeline leakage prediction method and system. Background Art

[0002] Pipeline transportation is the primary mode of transport in the oil and gas industry. As pipelines age, problems such as corrosion, wear, and aging gradually intensify, ultimately leading to pipeline leaks and posing a serious threat to energy transportation safety. Therefore, real-time monitoring of the health of buried pipelines is crucial to promptly detect and accurately locate leaks, enabling maintenance or replacement, thereby minimizing economic losses and environmental pollution.

[0003] Domestic and international scholars have conducted a series of studies on pipeline leakage monitoring, and leakage monitoring technology has developed rapidly, mainly including chemical composition analysis, acoustic analysis, optical measurement, distributed fiber optic sensors, and smart ball methods. However, all current monitoring methods are aimed at predicting the leak location or leakage volume after the pipeline leak occurs, and cannot predict the pipeline leak location and leakage time in advance. Summary of the Invention

[0004] The purpose of the present invention is to provide a pipeline leakage prediction method and system to solve the problems raised in the above background technology.

[0005] To achieve the above object, the present invention provides the following technical solution: a pipeline leakage prediction method, comprising the following steps:

[0006] S1. Measure and determine the inner diameter d, outer diameter D, wall thickness t, and internal pressure p of the target buried pipeline;

[0007] S2. Based on the inner diameter d, outer diameter D, and wall thickness t of the target buried pipeline, a finite element numerical simulation model is established, and a corrosion pit with a length L, a width b, and a depth t×α% is dug on the inner wall of the target buried pipeline;

[0008] S3. Apply internal pressure p as a load to the inner wall of the pipeline containing the corrosion pit;

[0009] S4. The axial and hoop strain distribution of the outer wall of the pipeline containing the corrosion pit is obtained by finite element calculation;

[0010] S5. Based on the axial and hoop strain distribution of the pipeline outer wall, a fiber optic measurement system is deployed to ensure that the corrosion depth of the pipeline containing corrosion pits can be detected when it reaches α% of the wall thickness;

[0011] S6. Using the optical fiber measurement system, measure the depth of the corrosion pit on the inner wall of the pipeline compared to α% of the pipeline wall thickness. If the measured corrosion pit exceeds α% of the pipeline wall thickness, determine that the strain on the outer wall of the pipeline will change. Calculate the strain on the outer wall of the pipeline based on the Brillouin scattering principle, and locate the specific location where the strain change occurs based on the optical time domain reflectometry principle. If the measured corrosion pit does not exceed α% of the pipeline wall thickness, determine that the strain on the outer wall of the pipeline has not changed.

[0012] S7. Based on the pipeline dimensions of inner diameter d, outer diameter D, and wall thickness t, the corrosion pit length L, width b, and depth t×α%, and applying internal pressure p, multiple finite element models with different corrosion pit depths are established. The axial strain ε of the pipeline outer wall corresponding to the multiple corrosion pit depths is calculated, and the functional relationship between the axial strain of the pipeline outer wall and the corrosion pit depth is obtained by fitting.

[0013] S8. Using the optical fiber measurement system, monitor the change in the axial strain of the outer wall of the pipeline in real time, and calculate the depth of the corrosion pit based on the functional relationship between the axial strain of the outer wall of the pipeline and the depth of the corrosion pit;

[0014] S9. Calculate the corrosion pit growth rate based on the corrosion pit depth d1 at time t1 and the corrosion pit depth d2 at time t2, and predict the pipeline leakage time based on the calculated corrosion pit growth rate.

[0015] As a preferred embodiment, in step S9, the specific formula for calculating the corrosion pit growth rate is:

[0016]

[0017] The specific formula for predicting pipeline leakage time is:

[0018]

[0019] A pipeline leakage prediction system, comprising an optical fiber measurement system, wherein the optical fiber measurement system comprises a pulse laser, a wavelength division multiplexer, signal acquisition, signal processing, and an optical fiber cable;

[0020] The pulse laser is used to generate a pulsed light beam;

[0021] The wavelength division multiplexer is used to combine optical signals of different wavelengths into a single optical fiber, or to separate optical signals of different wavelengths from a single optical fiber;

[0022] Signal acquisition, used to receive the changed optical signal and convert it into an electrical signal;

[0023] Signal processing, used to process electrical signals and output strain data;

[0024] Fiber optic cables are used to transmit optical signals to the pipe under test and are subject to strain.

[0025] As a preferred embodiment, the number of the optical fiber cables is at least 4, and the multiple optical fiber cables are distributed at equal intervals around the central axis of the pipeline.

[0026] Compared with the prior art, the present invention has the following beneficial effects:

[0027] The present invention predicts leakage for buried pipelines that have not yet leaked. By establishing a corresponding relationship between the depth of the corrosion pit and the axial strain of the pipeline outer wall, and with the monitoring cooperation of the optical fiber measurement system, the leakage location and the time when a leak will occur in the buried pipeline that has not yet leaked can be effectively predicted, thereby preventing problems before they occur. There is no need to wait until the pipeline leaks before taking measures, greatly reducing the risk of explosions and the like caused by pipeline leakage, and is conducive to application in pipeline transportation in the fields of oil and natural gas. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 A schematic diagram of the structure of a pipeline leakage prediction system according to the present invention;

[0029] Figure 2 Provided is a schematic diagram of the axial strain distribution of the outer wall of the pipeline in Example 1 of the present invention;

[0030] Figure 3 Schematic diagram of the functional relationship between axial strain and corrosion pit depth in Example 1 provided by the present invention. DETAILED DESCRIPTION

[0031] The present invention will be further described below with reference to the embodiments.

[0032] The following examples are intended to illustrate the present invention but are not intended to limit the scope of protection of the present invention. The conditions in the examples may be further adjusted according to specific conditions. Simple improvements to the method of the present invention within the scope of the present invention are also within the scope of protection claimed in the present invention.

[0033] Example 1

[0034] This embodiment provides a pipeline leakage prediction method, comprising the following steps:

[0035] S1. Measure and determine the target buried pipeline's inner diameter (d), outer diameter (D), wall thickness (t), and internal pressure (p). Determine the critical depth of the corrosion pit. In this embodiment, α is 50. This means that when the corrosion pit depth reaches 50% of the pipe wall thickness, monitoring of the pipeline for potential leaks begins.

[0036] S2. Establish a finite element model of a pipeline with an inner diameter of 80 mm, an outer diameter of 100 mm, and a wall thickness of 10 mm. The dimensions of the corrosion pit on the inner wall of the pipeline are: 20 mm long, 10 mm wide, and 5 mm deep. Apply an internal pressure load of 1 MPa and calculate the axial strain distribution on the outer wall of the pipeline as follows: Figure 2 shown.

[0037] S3 deploys a fiber optic measurement system based on the axial and circumferential strain distribution on the outer wall of the pipeline.

[0038] S4. Based on the pipeline dimensions of inner diameter d, outer diameter D, wall thickness t, corrosion pit length L, width b, and depth t×α%, internal pressure p is applied, and multiple finite element models with different corrosion pit depths are established. The axial strain ε of the pipeline outer wall corresponding to multiple corrosion pit depths is calculated.

[0039] In this embodiment, five finite element models of pipelines with different corrosion pit depths were established. The pipeline dimensions were 80 mm inner diameter, 100 mm outer diameter, and 10 mm wall thickness. The corrosion pit dimensions were: 20 mm long, 10 mm wide, and 1 mm deep (t×α1%=10 mm×10%=1 mm); 20 mm long, 10 mm wide, and 3 mm deep (t×α1%=10 mm×30%=3 mm); 20 mm long, 10 mm wide, and 5 mm deep (t×α1%=10 mm×50%=5 mm); 20 mm long, 10 mm wide, and 7 mm deep (t×α1%=10 mm×70%=7 mm); and 20 mm long, 10 mm wide, and 9 mm deep (t×α1%=10 mm×90%=9 mm). Applying an internal pressure load of 1 MPa, the axial strains of the outer wall of the pipe are calculated, ε1 = 0.00002, ε2 = 0.0005, ε3 = 0.0015, ε4 = 0.003 and ε5 = 0.006. Through data analysis, the relationship between axial strain and corrosion pit depth can be obtained as follows: Figure 3 shown.

[0040] S5. The incident light pulse is emitted through the optical fiber measurement system. Due to the existence of the corrosion pit, the strain of the outer wall of the pipe corresponding to the corrosion pit becomes abnormal. According to the Brillouin scattering principle, that is, the relationship between strain and frequency shift, the axial strain of 0.0043 can be calculated. Figure 3 Based on the relationship between the depth of the corrosion pit and the depth of the corrosion pit, it can be predicted that the depth of the corrosion pit is 8.51 mm, which is consistent with the actual situation.

[0041] S6. The time difference between the incident light generated by the pulse laser 1 in the optical fiber measurement system and the received scattered light signal is 0.1 microsecond. According to the propagation speed of light 3×108m / s, the position of the corrosion pit is x=15m, which is 15m away from the pulse laser.

[0042] S7. Calculate the corrosion pit growth rate based on the corrosion pit depth d1 at time t1 and the corrosion pit depth d2 at time t2, and predict the pipeline leakage time based on the calculated corrosion pit growth rate.

[0043] Specifically, in this embodiment, the corrosion pit depth d1 = 8.5 mm at time t1, and the corrosion pit depth d2 = 8.6 mm at time t2 10 hours later, the corrosion pit growth rate can be calculated. When the depth of the corrosion pit reaches 10mm, leakage occurs and the leakage time can be predicted 140 hours after t2, the pipeline leaked.

[0044] Example 2

[0045] This embodiment provides a pipeline leakage prediction system, which includes a fiber optic measurement system, and the fiber optic measurement system includes a pulse laser 1, a wavelength division multiplexer 2, a signal acquisition 3, a signal processing 4 and an optical fiber cable 5.

[0046] The pulse laser 1 is used to generate a pulsed light beam; the wavelength division multiplexer 2 is used to merge optical signals of different wavelengths into a single optical fiber, or to separate optical signals of different wavelengths from a single optical fiber; the signal acquisition 3 is used to receive the changed optical signal and convert it into an electrical signal; the signal processing 4 is used to process the electrical signal and output strain data; the optical fiber cable 5 is used to transmit the optical signal to the measured pipeline and is affected by the strain.

[0047] The axial strain distribution of the pipe outer wall obtained in step S2 of Example 1 is as follows: Figure 1 The results show that at least four optical fiber cables 5 need to be laid on the outer wall of the pipeline, namely optical fiber 501, optical fiber 502, optical fiber 503, and optical fiber 504, to monitor possible leaks at any location in the pipeline. While the embodiments of the present invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention. The scope of the invention is defined by the appended claims and their equivalents.

Claims

1. A pipeline leakage prediction method, characterized in that: The following steps are involved: S1. Measure and determine the inner diameter d, outer diameter D, wall thickness t, and internal pressure p of the target buried pipeline; S2. Based on the inner diameter d, outer diameter D, and wall thickness t of the target buried pipeline, a finite element numerical simulation model is established, and a corrosion pit with a length L, a width b, and a depth of t×α% is dug on the inner wall of the target buried pipeline; S3. Apply internal pressure p as a load to the inner wall of the pipeline containing the corrosion pit; S4. The axial and hoop strain distribution of the outer wall of the pipeline containing the corrosion pit is obtained by finite element calculation; S5. Based on the axial and hoop strain distribution of the pipeline outer wall, a fiber optic measurement system is deployed to ensure that the corrosion depth of the pipeline containing corrosion pits can be detected when it reaches α% of the wall thickness; S6. Using the optical fiber measurement system, measure the depth of the corrosion pit on the inner wall of the pipeline compared to α% of the pipeline wall thickness. If the measured corrosion pit exceeds α% of the pipeline wall thickness, determine that the strain on the outer wall of the pipeline will change. Calculate the strain on the outer wall of the pipeline based on the Brillouin scattering principle, and locate the specific location where the strain change occurs based on the optical time domain reflectometry principle. If the measured corrosion pit does not exceed α% of the pipeline wall thickness, determine that the strain on the outer wall of the pipeline has not changed. S7. Based on the pipeline dimensions of inner diameter d, outer diameter D, wall thickness t, corrosion pit length L, width b, and depth t×α%, and applying internal pressure p, multiple finite element models with different corrosion pit depths are established. The axial strain ε of the pipeline outer wall corresponding to the multiple corrosion pit depths is calculated, and the functional relationship between the axial strain of the pipeline outer wall and the corrosion pit depth is obtained by fitting. S8. Using the optical fiber measurement system, monitor the change in the axial strain of the outer wall of the pipeline in real time, and calculate the depth of the corrosion pit based on the functional relationship between the axial strain of the outer wall of the pipeline and the depth of the corrosion pit; S9. Calculate the corrosion pit growth rate based on the corrosion pit depth d1 at time t1 and the corrosion pit depth d2 at time t2, and predict the pipeline leakage time based on the calculated corrosion pit growth rate.

2. A pipeline leakage prediction method according to claim 1, characterized in that: In step S9, the specific formula for calculating the corrosion pit growth rate is: ； The specific formula for predicting pipeline leakage time is: 。 3. A pipeline leakage prediction system, applied to a pipeline leakage prediction method according to any one of claims 1-2, characterized in that: The pipeline leakage prediction system includes an optical fiber measurement system, and the optical fiber measurement system includes a pulse laser, a wavelength division multiplexer, signal acquisition, signal processing and optical fiber cable; The pulse laser is used to generate a pulsed light beam; The wavelength division multiplexer is used to combine optical signals of different wavelengths into a single optical fiber, or to separate optical signals of different wavelengths from a single optical fiber; Signal acquisition, used to receive the changed optical signal and convert it into an electrical signal; Signal processing, used to process electrical signals and output strain data; Fiber optic cables are used to transmit optical signals to the pipe under test and are subject to strain.

4. A pipeline leakage prediction system according to claim 3, characterized in that: The number of the optical fiber cables is at least 4, and the optical fiber cables are distributed at equal intervals around the central axis of the pipeline.

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