Oil and gas pipeline defect composite magnetic flux leakage signal quantitative inversion method

Abstract

The invention discloses an oil and gas pipeline defect composite magnetic flux leakage signal quantitative inversion method, which comprises the following steps: data collection: collecting basic information of a pipeline and a site; formulating a simulation scheme, and establishing a pipeline defect magnetic flux leakage model; according to different magnetic flux leakage signal features, laws of each defect feature and different components of the magnetic flux leakage signal are subjected to statistical analysis, and weight coefficients of the defect features and the different components of the magnetic flux leakage signal are constructed to form a defect magnetic flux leakage signal composite inversion model; magnetic flux leakage signals under actual working conditions are collected; and inverting the defect size and depth of the pipeline under the actual working condition according to the acquired magnetic flux leakage signal. Corresponding defect detection models can be established for different pipelines according to actual site conditions, the efficiency is high, the practical application value is achieved, a new detection thought is provided for the operation state of the oil and gas pipeline, and the method has great significance in guaranteeing safe and normal operation of the oil and gas pipeline.

Description

Technical Field

[0001] The invention relates to the field of oil and gas pipeline detection, and specifically embodies a quantitative inversion method for composite magnetic leakage signals of oil and gas pipeline defects. Technical Background

[0002] In the field of long-distance transportation and gathering of oil and gas pipelines, various corrosion pits will inevitably occur during the service of oil and gas pipelines due to various factors, thus affecting the safety of production and operation. When detecting whether there are defects in oil and gas pipelines after a period of service, pipeline magnetic leakage internal detection is widely used as an internal detection method and the most common detection method. However, the current quantitative inversion of defects in oil and gas pipelines mostly calculates defect features through single magnetic leakage signal features, and the accuracy of the obtained defect features needs to be improved. Summary of the invention

[0004] In view of the above problems, the present invention provides a quantitative inversion method for composite leakage magnetic signals of oil and gas pipeline defects. By acquiring basic information of the oil and gas pipeline and the leakage magnetic detector, and establishing a leakage magnetic model of the oil and gas pipeline defects, the leakage magnetic signals of the oil and gas pipeline at different defect radii and depths are simulated. According to the characteristics of different leakage magnetic signals, the laws of various defect characteristics and different components of the leakage magnetic signals are statistically analyzed, and the weight coefficients of the defect characteristics and different components of the leakage magnetic signals are constructed to form a composite inversion model of the defect leakage magnetic signals. According to the composite inversion model, the actual defect characteristics can be inverted according to the actual leakage magnetic signals.

[0005] The method can invert the characteristics of defects based on the magnetic flux leakage signals collected from pipelines of different working conditions and materials. It should be noted that, unless otherwise specified, all technical and scientific terms used in this application have the same meanings as those commonly understood by ordinary technicians in the technical field to which this application belongs.

[0006] The main steps are as follows: Step 1: Data collection, collect basic information of the pipeline and on-site information, including but not limited to: pipe diameter, wall thickness, pipeline material, etc. Step 2: Develop a simulation plan based on on-site working conditions and establish an oil and gas pipeline defect magnetic leakage model. Step 3: According to the leakage magnetic flux model of oil and gas pipeline defects, simulate the axial and radial leakage magnetic flux signals of pipelines at different defect radii and depths, and statistically analyze the laws of various defect characteristics and different components of leakage magnetic flux signals according to different leakage magnetic flux signal characteristics, and construct the weight coefficients of defect characteristics and different components of leakage magnetic flux signals to form a composite inversion model of defect leakage magnetic flux signals. Among them, axial refers to the direction along the length of the pipeline, and radial refers to the direction along the radius of the pipeline. Defect radius and axial magnetic leakage signal inversion calculation model: r1=a1ΔT a1 +b1 (1) Where: r1 is the axial inversion defect radius, mm; ΔT a1 is the amplitude of the axial magnetic induction intensity, mT; a1, b1 are unknown coefficients, and the unknown coefficients of different pipelines are determined by fitting the simulated data of the leakage magnetic signal. Defect radius and radial magnetic flux leakage signal inversion calculation model: r2=c1ΔT r1 +d1 (2) Where: r2 is the radial inversion defect radius, mm; ΔT r1 is the peak-to-valley value of radial magnetic induction intensity, mT; c1, d1 are unknown coefficients, and the unknown coefficients of different pipelines are determined by fitting the simulated data of leakage magnetic signal. Construct a composite inversion model, defect radius: r=mr1+nr2 (3) Where: r is the defect radius; m and n are weight coefficients. The weight coefficients of different pipelines are determined by fitting the simulated data of magnetic flux leakage signals. Axial defect depth and magnetic flux leakage signal inversion calculation model: Where: h1 is the axial inversion defect depth, mm; ΔT a2 is the amplitude of the axial magnetic induction intensity, mT; a2, b2 are unknown coefficients, and the unknown coefficients of different pipelines are determined by fitting the simulated data of the leakage magnetic signal. Radial defect depth and magnetic flux leakage signal inversion calculation model: Where: h2 is the radial inversion defect depth, mm; ΔT r2 is the peak-to-valley value of radial magnetic induction intensity, mT; c2, d2 are unknown coefficients, and the unknown coefficients of different pipelines are determined by fitting the simulated data of leakage magnetic signal. Construct a composite inversion model, defect depth: h=sh1+th2 (6) Where: h is the defect radius; s, t are weight coefficients. The weight coefficients of different pipelines are determined by fitting the simulated data of magnetic flux leakage signals. Step 4: Place the magnetic flux leakage internal detector into the actual oil and gas pipeline to be tested and make corresponding preparations. After the preparations are completed, the pipeline begins to be pressurized to push the magnetic flux leakage internal detector forward, and the axial and radial magnetic flux leakage signals of the oil and gas pipeline are collected during the movement. Step 5: Analyze the axial and radial magnetic leakage signals collected by the magnetic leakage internal detector, and calculate the actual oil and gas pipeline defect size and depth based on the composite inversion calculation model of the defect radius, depth and magnetic leakage signal. BRIEF DESCRIPTION OF THE DRAWINGS

[0007] Figure 1 This is an example diagram of the axial magnetic leakage signal of an oil and gas pipeline defect at different defect radii. Figure 2 This is an example diagram of radial magnetic leakage signal of an oil and gas pipeline defect at different defect radii. Figure 3 This is an example diagram of radial magnetic leakage signal of an oil and gas pipeline defect at different defect depths. Figure 4 The above example diagrams are only example data of the present invention, and the specific sample data volume is large, so they are not listed one by one. DETAILED DESCRIPTION

[0008] The present invention is further described below with reference to the accompanying drawings and examples. It should be noted that, unless otherwise specified, all technical and scientific terms used in this application have the same meanings as those commonly understood by those skilled in the art to which this application belongs. Step 1: Collect basic information of the field test pipeline. The pipe diameter is 323.8mm, the outer material of the pipeline is L360QS, and the wall thickness is 12mm; the inner material is Incoloy825, the wall thickness is 3mm, the prefabrication defect radius is 4mm, and the prefabrication defect depth is 2.4mm. Step 2: Based on the basic information of the pipeline, use ABAQUS to establish an oil and gas pipeline defect leakage magnetic detection model. Step 3: According to the oil and gas pipeline defect magnetic leakage model, simulate the pipeline axial and radial magnetic leakage signals at different defect radius and depth. According to the characteristics of different magnetic leakage signals, statistically analyze the laws of various defect characteristics and different components of magnetic leakage signals, and construct the weight coefficients of defect characteristics and different components of magnetic leakage signals to form a composite inversion model of defect magnetic leakage signals: Axial defect radius and magnetic flux leakage signal inversion calculation model: r1=1.879ΔT a1 +1.330 (7) Where: r1 is the axial inversion defect radius, mm; ΔT a1 is the amplitude of the axial magnetic induction intensity, mT. Radial defect radius and magnetic flux leakage signal inversion calculation model: r2=1.114ΔT r1 +1.534 (8) Where: r2 is the radial inversion defect radius, mm; ΔT r1 is the peak-to-peak value of radial magnetic induction intensity, mT. Composite inversion model of defect radius: r=0.892r1+0.108r2 (9) Axial defect depth and magnetic flux leakage signal inversion calculation model: h1=2.235ΔT a2 0.817(10) Where: h1 is the axial inversion defect depth, mm; ΔT a2 is the amplitude of the axial magnetic induction intensity, mT. Radial defect depth and magnetic flux leakage signal inversion calculation model: h2=1.523ΔT r2 0.824 (11) Where: h2 is the radial inversion defect depth, mm; ΔT r2 is the radial magnetic induction intensity value amplitude, mT. Defect depth composite inversion model: h=0.295h1+0.705h2 (12) Step 4: In a specific embodiment, the axial leakage magnetic flux intensity amplitude of a defect collected by the leakage magnetic internal detector is 1.372mT, and the radial leakage magnetic flux intensity peak-to-peak value is 2.110mT. The axial leakage magnetic flux intensity amplitude of a defect collected by the leakage magnetic internal detector is 1.052mT, and the radial leakage magnetic flux intensity peak-to-peak value is 1.692mT. Step 5: Based on the composite inversion calculation model of defect radius, depth and magnetic leakage signal, in a specific embodiment, the defect radius inversion value is r=3.91 mm; the defect depth inversion value is h=2.34 mm. The radius of the prefabrication defect of the pipeline is 4mm, the inversion value of the defect radius is r=3.91mm, and the relative error is 2.25%. The prefabrication defect depth is 2.4mm; the inversion value of the defect depth is h=2.34mm, and the relative error is 2.50%. By changing the pipeline parameter settings, the inversion model of the defect radius and depth of pipelines of different materials and the leakage magnetic signal can be obtained. According to the inversion model, the defect radius and depth under different working conditions can be obtained. The above description is only a preferred embodiment of the present invention and does not constitute any form of limitation to the present invention. Although the present invention has been disclosed as a preferred embodiment as above, it is not intended to limit the present invention. Any technician familiar with the profession can make some changes or modifications to equivalent embodiments of equivalent changes using the technical contents disclosed above without departing from the scope of the technical solution of the present invention. However, any simple modification, equivalent change and modification made to the above embodiments based on the technical essence of the present invention without departing from the content of the technical solution of the present invention still falls within the scope of the technical solution of the present invention. Technical Effects

[0009] The defect detection method of the oil and gas pipeline of the present invention can invert the defect size and depth of the oil and gas pipeline under actual working conditions according to the magnetic leakage signal. In specific implementation, a corresponding defect detection model can be established for different pipelines according to the actual situation on site, which is highly efficient and has practical application value.

Claims

1. A quantitative inversion method for composite magnetic leakage signals of oil and gas pipeline defects, characterized in that: The following steps are involved: S1. Data collection: collect basic information of pipelines and on-site information, including but not limited to: pipe diameter, wall thickness, pipeline material, etc.; S2. Develop a simulation plan based on the on-site working conditions and establish a magnetic flux leakage model for oil and gas pipeline defects; S3. According to the leakage magnetic flux model of oil and gas pipeline defects, the axial and radial leakage magnetic flux signals of pipelines at different defect radius and depth are simulated. According to the characteristics of different leakage magnetic flux signals, the laws of various defect characteristics and different components of leakage magnetic flux signals are statistically analyzed, and the weight coefficients of defect characteristics and different components of leakage magnetic flux signals are constructed to form a composite inversion model of defect leakage magnetic flux signals. Defect radius and axial magnetic leakage signal inversion calculation model: r1=a1ΔT a1 +b1 (1) Where: r1 is the axial inversion defect radius, mm; ΔT a1 is the amplitude of the axial magnetic induction intensity, mT; a1, b1 are unknown coefficients, and the unknown coefficients of different pipelines are determined by fitting the simulated data of the leakage magnetic signal; Defect radius and radial magnetic flux leakage signal inversion calculation model: r2=c1ΔT r1 +d1 (2) Where: r2 is the radial inversion defect radius, mm; ΔT r1 is the peak-to-valley value of radial magnetic induction intensity, mT; c1, d1 are unknown coefficients, which are determined by fitting the simulated data of magnetic flux leakage signal; Construct a composite inversion model, defect radius: r=mr1+nr2 (3) Where: r is the defect radius; m, n are weight coefficients, and the weight coefficients of different pipelines are determined by fitting the simulated data of magnetic flux leakage signals; Axial defect depth and magnetic flux leakage signal inversion calculation model: Where: h1 is the axial inversion defect depth, mm; ΔT a2 is the amplitude of the axial magnetic induction intensity, mT; a2, b2 are unknown coefficients, and the unknown coefficients of different pipelines are determined by fitting the simulated data of the leakage magnetic signal; Radial defect depth and magnetic flux leakage signal inversion calculation model: Where: h2 is the radial inversion defect depth, mm; ΔT r2 is the peak-to-valley value of radial magnetic induction intensity, mT; c2, d2 are unknown coefficients, which are determined by fitting the simulated data of magnetic flux leakage signal; Construct a composite inversion model, defect depth: h=sh1+th2 (6) Where: h is the defect radius; s, t are weight coefficients. The weight coefficients of different pipelines are determined by fitting the simulated data of magnetic flux leakage signals. S4. Place the magnetic flux leakage internal detector into the actual oil and gas pipeline to be tested, and make corresponding preparations. After the preparations are completed, pressurize the pipeline to push the magnetic flux leakage internal detector forward, and collect axial and radial magnetic flux leakage signals of the oil and gas pipeline during the movement; S5. Analyze the axial and radial magnetic leakage signals collected by the magnetic leakage internal detector, and calculate the actual oil and gas pipeline defect size and depth based on the composite inversion calculation model of the defect radius, depth and magnetic leakage signal.

2. The quantitative inversion method of composite magnetic leakage signal of oil and gas pipeline defects according to claim 1 is characterized in that: The oil and gas pipeline defect magnetic leakage model established in step S2.

3. The quantitative inversion method of composite magnetic leakage signal of oil and gas pipeline defects according to claim 1 is characterized in that: The composite inversion model of defect leakage magnetic signal formed in step S3, the inversion calculation model of axial defect radius and leakage magnetic signal: Defect radius and axial magnetic leakage signal inversion calculation model: r1=a1ΔT a1 +b1 (1) Where: r1 is the axial inversion defect radius, mm; ΔT a1 is the amplitude of the axial magnetic induction intensity, mT; a1, b1 are unknown coefficients, and the unknown coefficients of different pipelines are determined by fitting the simulated data of the leakage magnetic signal; Defect radius and radial magnetic flux leakage signal inversion calculation model: r2=c1ΔT r1 +d1 (2) Where: r2 is the radial inversion defect radius, mm; ΔT r1 is the peak-to-valley value of radial magnetic induction intensity, mT; c1, d1 are unknown coefficients, which are determined by fitting the simulated data of magnetic flux leakage signal; Construct a composite inversion model, defect radius: r=mr1+nr2 (3) Where: r is the defect radius; m, n are weight coefficients, and the weight coefficients of different pipelines are determined by fitting the simulated data of magnetic flux leakage signals; Axial defect depth and magnetic flux leakage signal inversion calculation model: Where: h1 is the axial inversion defect depth, mm; ΔT a2 is the amplitude of the axial magnetic induction intensity, mT; a2, b2 are unknown coefficients, and the unknown coefficients of different pipelines are determined by fitting the simulated data of the leakage magnetic signal; Radial defect depth and magnetic flux leakage signal inversion calculation model: Where: h2 is the radial inversion defect depth, mm; ΔT r2 is the peak-to-valley value of radial magnetic induction intensity, mT; c2, d2 are unknown coefficients, which are determined by fitting the simulated data of magnetic flux leakage signal; Construct a composite inversion model, defect depth: h=sh1+th2 (6) Where: h is the defect radius; s, t are weight coefficients. The weight coefficients of different pipelines are determined by fitting the simulated data of magnetic flux leakage signals.

Images