A system for non-destructive testing and result analysis of well pipe porosity

Abstract

This invention relates to the field of well casing inspection technology, specifically a well casing porosity nondestructive testing and result analysis system, comprising: a first construction module for acquiring the design parameters of the target well casing and constructing a standard well casing 3D model based on the design parameters; a second construction module for acquiring the original physical inspection data of the entire well casing wall and constructing an actual well casing 3D model reflecting the actual physical state of the well casing based on the original physical inspection data; a setting module for establishing comparison rule information between the actual well casing 3D model and the standard well casing 3D model, wherein the comparison rule information includes the actual data loop and the standard data loop, as well as the association chain between the actual data loop and the standard data loop; and a porosity identification module for comparing the well casing 3D model with the standard well casing 3D model based on the comparison rules, identifying and segmenting the porous and non-porous regions on the well casing surface; thereby improving the efficiency of porosity calculation.

Description

Technical Field

[0001] This invention relates to the field of well pipe testing technology, specifically a well pipe porosity non-destructive testing and result analysis system. Background Technology

[0002] In oil and gas extraction, well casing serves as the core channel for oil and gas transportation, and its structural integrity directly impacts extraction safety and production efficiency. Well casings are exposed to high-pressure, corrosive environments for extended periods, making their surfaces prone to pitting, cracks, and other porosity defects. These defects can reduce the well casing's pressure-bearing capacity and even lead to leaks. Therefore, accurate detection of the porosity of the well casing surface is crucial for assessing its remaining lifespan and operational safety risks.

[0003] Current methods for calculating well casing porosity primarily rely on a combination of 3D scanning technology and manual interpretation. In practice, global registration followed by point-by-point comparison is typically used, requiring calculation for every single facet of the entire model. When the well casing model contains multiple facets, the computational load for point-by-point comparison is enormous, resulting in a lengthy porosity region identification process that fails to meet the demands of rapid on-site inspection and thus reduces the efficiency of well casing porosity calculation.

[0004] To address these issues, we propose a non-destructive testing and result analysis system for well casing porosity. Summary of the Invention

[0005] The purpose of this invention is to provide a system for non-destructive testing and result analysis of well pipe porosity, so as to solve the problems mentioned in the background art.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a system for non-destructive testing and result analysis of well casing porosity, comprising: The first construction module is used to obtain the design parameters of the target well casing and build a standard well casing 3D model based on the design parameters. The second construction module is used to acquire the original physical inspection data of the entire wall of the well pipe, and to construct a three-dimensional model of the actual well pipe that reflects the actual physical state of the well pipe based on the original physical inspection data; The configuration module is used to establish comparison rule information between the actual well casing 3D model and the standard well casing 3D model. The comparison rule information includes the actual data loop and the standard data loop, as well as the association chain between the actual data loop and the standard data loop. The porosity identification module is used to compare the 3D model of the well casing with the standard 3D model of the well casing based on comparison rules, and to identify and segment the porosity and non-porosity areas on the surface of the well casing. The calculation module is used to calculate the area ratio of the pore region in the total detection area, and output the actual effective porosity of the target well pipe in combination with the pipe wall thickness parameter.

[0007] Preferably, the step of obtaining the design parameters of the target well casing and constructing a standard well casing 3D model based on the design parameters includes: Obtain the design parameters of the target well casing, including geometric dimensions, structural features, and material properties. Based on the geometric dimensions and structural features, the geometric profile of the target well casing is constructed. Based on the material property parameters, corresponding physical and visual properties are assigned to the geometric contour to generate a standard well casing 3D model.

[0008] Preferably, the step of obtaining the original physical inspection data of the entire well casing wall and constructing a three-dimensional model of the actual well casing reflecting its actual physical state based on the original physical inspection data includes: Point cloud data representing the outer surface profile of the target well casing, point cloud data representing the inner surface profile of the well casing, and detection data representing the wall thickness distribution and internal defects of the well casing are acquired as raw physical detection data. A three-dimensional mesh model of the inner and outer walls of the target well casing is constructed based on the original physical inspection data; Based on the detection data mapped to the corresponding spatial location of the 3D mesh model, an actual 3D model of the well casing containing wall thickness distribution information and internal defect information is generated.

[0009] Preferably, the step of establishing comparison rules between the actual well casing 3D model and the standard well casing 3D model includes: Obtain the surface information of the actual well casing 3D model, and construct the actual data loop based on the surface information; Obtain surface information of a standard well casing 3D model and construct a standard data loop based on the surface information; Establish association chains between the actual data ring and the standard data ring, and use the association chains between the actual data ring and the standard data ring, as well as between the actual data ring and the standard data ring, as comparison rule information.

[0010] Preferably, the step of obtaining the surface information of the actual well casing 3D model and constructing the actual data loop based on the surface information includes: Obtain raw physical inspection data of the entire wall of the well casing. The raw physical inspection data includes surface information of multiple layers, and each layer of surface information corresponds to a point of inspection layer. Each location is configured with an actual data point, and a first communication connection is established between multiple actual data points to form an actual data ring. Configure a selection point for each actual data point, and establish a second communication connection between the actual data point and the corresponding selection point; A third communication connection is established for multiple selection points to form a selection box; multiple stationary points are set in the selection box, each stationary point is used to stop the selection point, any selection point stops at any stationary point, and at least one selection point stops at any stationary point; The rules for establishing a standard data ring are the same as those for establishing an actual data ring. A standard data ring includes multiple standard data points and a selection box corresponding to each standard data point.

[0011] Preferably, the step of establishing the association chain between the actual data ring and the standard data ring includes: Establish a synchronous movement association between each standard data point and the corresponding actual data point, and the movement trajectory of the standard data point is the same as the movement trajectory of the actual data point; Establish a mapping relationship between the selected points of the actual data points and the selected points of the standard data points, so that the selected points on the actual side and the selected points on the standard side move synchronously to the corresponding points of the next layer.

[0012] Preferably, the step of comparing the 3D model of the well casing with a standard 3D model of the well casing based on comparison rules to identify and segment the porous and non-porous regions on the surface of the well casing includes: The standard data loop, composed of control standard data points, moves on the surface of a standard well casing 3D model. Based on the correlation chain, the actual data loop composed of actual data points moves synchronously on the surface of the actual well casing 3D model; When the actual data point moves to the current level, the selected point corresponding to the actual data point moves to the next level and collects the surface information corresponding to the next level. By selecting points to merge and separate at the same detection level and using a pre-analysis mechanism on the standard data point side, multiple actual data points can achieve full coverage of the next level of detection and perform comparative analysis of surface information in advance. Determine whether the surface information on the actual well casing 3D model is consistent with the surface information on the standard well casing 3D model; For surface information where the judgment result is inconsistent, control the position of the actual data point away from the current level; For surface information that is consistent with the judgment result, control the actual data point to move to the location of the consistent surface information, and mark the consistent surface information. Based on the movement paths of multiple actual data points, the entire surface of the actual well casing 3D model is covered. The contours and volumes corresponding to the marked surface information are taken as non-porous regions, and the contours and volumes corresponding to the unmarked surface information are taken as porous regions.

[0013] Preferably, the step of achieving full coverage of the next level of detection layer by multiple actual data points and comparative analysis of surface information through the merging and separation mechanism of selected points at the same detection level and the pre-analysis mechanism on the standard data point side includes: Multiple selected points at the same detection level are automatically merged or separated based on the distribution of surface information at the next level. Based on the location of the surface information of the next level, multiple actual data points are moved to the location of their respective selected points, thereby achieving full coverage of the next level of detection by multiple actual data points. When the standard data point moves to a point in the current level, the selected point corresponding to the standard data point moves to a point in the next level at the same time. When selecting points to mark the locations of the next level, the surface information of the next level is compared and analyzed with the location data of the actual data points in the current level.

[0014] Compared with the prior art, the beneficial effects of the present invention are: Based on pre-established multi-level synchronous movement comparison rules, during the synchronous movement of the actual data loop and the standard data loop, a pre-movement mechanism for selected points ensures that the corresponding selected points have moved to the next level and collected surface information before the actual data points reach their current positions. This pre-probing method enables parallel processing of pore region identification, shortening the acquisition time for pore regions. Simultaneously, a merging and separating mechanism for selected points automatically adjusts the layout based on the distribution of surface information at the next level, avoiding repeated detection of invalid points and improving the efficiency of pore region identification. Attached Figure Description

[0015] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 This is a system structure block diagram of the present invention. Detailed Implementation

[0017] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0018] For examples, please refer to Figure 1 This invention provides a technical solution for a well pipe porosity nondestructive testing and result analysis system: a well pipe porosity nondestructive testing and result analysis system, comprising the following steps: The first construction module is used to obtain the design parameters of the target well casing and build a standard well casing 3D model based on the design parameters. The steps for obtaining the design parameters of the target well casing and constructing a standard well casing 3D model based on the design parameters include: obtaining the design parameters of the target well casing, wherein the design parameters include geometric dimension parameters, structural feature parameters, and material property parameters; constructing the geometric contour of the target well casing based on the geometric dimension parameters and structural feature parameters; and assigning corresponding physical and visual properties to the geometric contour based on the material property parameters to generate a standard well casing 3D model. Specifically, the design parameters of the target well casing are obtained. These parameters form the basis for building a standard model and are mainly derived from CAD design drawings or product specifications. Geometric dimensional parameters: These are basic data describing the size of the well casing, such as outer diameter, inner diameter, wall thickness, and total length. Structural characteristic parameters: These are data describing the specific shape of the well casing, such as the taper of the casing, end joint type (e.g., thread type, sealing surface structure), and whether there are any special structures (e.g., centralizer location). Material property parameters: These are data describing the physical properties of the well casing, such as the steel grade, to facilitate subsequent physical simulations or to assign the model the correct density, color, and other attributes. After obtaining the above parameters, 3D modeling is performed... The modeling software is used for model construction. First, geometric contour construction is performed: based on the geometric dimensions and structural feature parameters, a two-dimensional cross-sectional view of the well pipe is drawn in the software, and a three-dimensional solid is generated through operations such as rotation and stretching to form the basic shape of the well pipe. Attribute information is assigned: based on the geometric model, according to the material property parameters, corresponding visual attributes such as material, color, and texture, as well as physical attributes such as density and elastic modulus, are assigned to the model, thereby constructing a standard well pipe three-dimensional model containing complete design and manufacturing information. The standard well pipe three-dimensional model includes at least the geometric dimensions of the well pipe, the pipe wall thickness, and the distribution pattern and initial porosity data of the preset pores.

[0019] The second construction module is used to acquire the original physical inspection data of the entire wall of the well pipe, and to construct a three-dimensional model of the actual well pipe that reflects the actual physical state of the well pipe based on the original physical inspection data; The steps for acquiring raw physical inspection data of the entire well casing wall and constructing a three-dimensional model of the actual well casing reflecting its actual physical state based on the raw physical inspection data include: acquiring point cloud data representing the outer surface contour of the target well casing, point cloud data representing the inner surface contour of the well casing, and inspection data representing the wall thickness distribution and internal defects of the well casing as raw physical inspection data; constructing a three-dimensional mesh model of the inner and outer walls of the target well casing based on the raw physical inspection data; and generating a three-dimensional model of the actual well casing containing wall thickness distribution information and internal defect information by mapping the inspection data to the corresponding spatial location of the three-dimensional mesh model. Specifically, using 3D scanning equipment or physical flaw detection equipment, a full-coverage data acquisition is performed on the entire wall surface of the target well casing to obtain raw physical inspection data containing the geometric morphology of the inner and outer walls and internal defects. This raw physical inspection data includes at least point cloud data characterizing the outer surface contour of the well casing, point cloud data characterizing the inner surface contour, and ultrasonic or radiographic inspection data characterizing the wall thickness distribution and internal defects. Depending on the inspection requirements, laser scanners or structured light 3D scanners are selected to acquire the surface geometric data of the inner and outer walls of the well casing; ultrasonic flaw detectors or industrial CT equipment are used to acquire the wall thickness distribution and internal defect data of the well casing. A 360° full-coverage scan of the well casing is performed. For the outer wall, high-density point cloud data is acquired through laser scanning to record every detail of the well casing's outer surface. For the inner wall, the inner surface contour and wall thickness variations are obtained using endoscopic scanning equipment or an ultrasonic thickness gauge array. For internal defects, the location and size information of defects such as cracks, inclusions, and pores are obtained through ultrasonic or X-ray penetration. The final raw data includes: outer wall point cloud data (recording geometric coordinates), inner wall point cloud data (if available), wall thickness distribution data (which can generate a wall thickness cloud map), and a list of internal defects (location + size + type). A combination of laser 3D scanning and ultrasonic flaw detection technology is used to obtain the raw physical inspection data of the entire well casing wall. Specifically, laser scanning is used to collect surface point cloud data of the inner and outer walls of the well casing, which can completely record the geometric shape and surface corrosion, deformation, and other characteristics of the well casing; ultrasonic flaw detection is used to obtain wall thickness distribution data and information on internal defects such as cracks and pores across the entire well casing wall. All acquired data are labeled with spatial locations for easy subsequent fusion processing. Based on point cloud data, a 3D mesh model of the inner and outer surfaces of the well casing is generated through triangulation. Internal defect information detected by ultrasound or CT (such as crack location and porosity distribution) is embedded into the corresponding positions of the 3D mesh model in the form of voxels or annotations. The original data is registered from multiple perspectives, and the point clouds obtained from scanning at different angles are stitched together to form a complete well casing point cloud model. Finally, the surface point cloud data and ultrasonic detection data are spatially aligned and fused to establish the correspondence between geometric information and physical property information. The final result is a real 3D model of the well casing that accurately reflects its current physical state. This model not only includes the geometric shape of the well casing (including defects such as corrosion pits and deformation) but also includes visualization information of internal wall thickness variations and hidden defects. During model generation, the wall thickness distribution data obtained by ultrasonic detection is rendered on the model surface using color mapping to form a wall thickness cloud map. Internal defect data is embedded into the model using 3D annotations or semi-transparent voxels. The final constructed 3D model of the actual well casing can comprehensively and intuitively reflect the current geometric deformation, wall thickness reduction, and internal defects of the well casing.

[0020] The configuration module is used to establish comparison rule information between the actual well casing 3D model and the standard well casing 3D model. The comparison rule information includes the actual data loop and the standard data loop, as well as the association chain between the actual data loop and the standard data loop. The steps for establishing comparison rules between the actual well casing 3D model and the standard well casing 3D model include: obtaining the surface information of the actual well casing 3D model and constructing an actual data loop based on the surface information; obtaining the surface information of the standard well casing 3D model and constructing a standard data loop based on the surface information; establishing the association chain between the actual data loop and the standard data loop, and using the actual data loop and the standard data loop, as well as the association chain between the actual data loop and the standard data loop, as comparison rule information. The steps for acquiring surface information of an actual well casing 3D model and constructing an actual data loop based on the surface information include: acquiring raw physical inspection data of the entire well casing wall, the raw physical inspection data including multiple layers of surface information, each layer of surface information corresponding to a point on an inspection layer; configuring an actual data point for each point, establishing a first communication connection between multiple actual data points to form an actual data loop; configuring a selection point for each actual data point, establishing a second communication connection between the actual data point and the corresponding selection point; establishing a third communication connection between multiple selection points to form a selection box; setting multiple stationary points in the selection box, each stationary point being used to stop at a selection point, any selection point stopping at any stationary point, and at least one selection point stopping at any stationary point; wherein, the rules for establishing a standard data loop are the same as the rules for establishing an actual data loop, and the standard data loop includes multiple standard data points and a selection box corresponding to each standard data point. The steps for establishing the association chain between the actual data ring and the standard data ring include: establishing a synchronous movement association between each standard data point and the corresponding actual data point, wherein the movement trajectory of the standard data point is the same as the movement trajectory of the actual data point; and establishing a mapping relationship between the selected points of the actual data point and the selected points of the standard data point, so that the selected points on the actual side and the selected points on the standard side move synchronously to the corresponding points of the next layer. Specifically, the actual data loop includes multiple actual data points, with each surface information corresponding to a point. Each point is configured with an actual data point, and these data points are interconnected. A selection point is set for each actual data point, and the actual data point and the selection point are also interconnected. Multiple selection points form a selection frame, with multiple stationary points set within the selection frame. Each stationary point is used to stop at a selection point, and a selection point can stop at any stationary point. Any stationary point can hold one or more selection points. The selection points are used to pre-select the next stop point for the actual data point. When an actual data point moves to its current stationary point, the corresponding selection point simultaneously moves to the next layer's point and collects the corresponding surface information. It is then determined whether the surface information on the actual well casing's 3D model is consistent with the surface information on the standard well casing's 3D model. Inconsistent surface information is discarded, and the actual data point is moved to the point containing consistent surface information. The consistent surface information is marked. The contour and volume corresponding to the unmarked surface information are then considered as the pore area. The actual data points move according to the movement of the standard data points, and communication between the two is maintained. The number of synchronously moving selection points located at the same level can be automatically merged and separated. Merging means that selection points corresponding to different actual data points can be located at the same point. Separation means that selection points at the same point can be separated as needed. Multiple actual data points move to the corresponding selection point location based on the location of the surface information of the next layer. This allows the actual well casing 3D model to be covered by the movement paths of multiple actual data points, thereby quickly identifying areas consistent with the standard well casing 3D model as non-porosity areas and areas that are inconsistent as porosity areas. The standard data loop includes multiple standard data points and a selection box corresponding to each standard data point. When the standard data point moves to the corresponding selection point, the selection point also moves to the surface information of the next layer at the same time. Therefore, when the selection point marks the location, the surface information of the next layer is compared with the data at the location of the actual data point in advance, and analysis is performed in advance, saving the time of analysis after the actual data point moves to the location. This improves the comparison efficiency of the 3D model and thus improves the calculation efficiency of well casing porosity.

[0021] The porosity identification module is used to compare the 3D model of the well casing with the standard 3D model of the well casing based on comparison rules, and to identify and segment the porosity and non-porosity areas on the surface of the well casing. The steps for comparing a 3D well casing model with a standard 3D well casing model based on comparison rules to identify and segment the porous and non-porous regions on the well casing surface include: controlling the movement of a standard data loop composed of standard data points on the surface of the standard 3D well casing model; driving the synchronous movement of an actual data loop composed of actual data points on the surface of the actual 3D well casing model according to the correlation chain; when an actual data point moves to a point at the current level, controlling the selected point corresponding to the actual data point to simultaneously move to the point at the next level, and collecting the surface information corresponding to the point at the next level; through the merging and separation mechanism of selected points at the same detection level and the pre-analysis mechanism on the standard data point side, realizing the lower-level detection of multiple actual data points. The system performs full coverage of each level of detection and conducts pre-comparison analysis of surface information; it determines whether the surface information on the actual well casing 3D model is consistent with the surface information on the standard well casing 3D model; for inconsistent surface information, it controls the actual data points to leave the current level; for consistent surface information, it controls the actual data points to move to the location of the consistent surface information and marks the consistent surface information; based on the movement paths of multiple actual data points, it covers the entire surface of the actual well casing 3D model, treating the contours and volumes corresponding to the marked surface information as non-porous areas, and the contours and volumes corresponding to the unmarked surface information as porous areas. The steps for achieving full coverage of the next-level detection layer by multiple actual data points and comparative analysis of surface information, through a merging and separation mechanism of selected points within the same detection layer and a pre-analysis mechanism on the standard data point side, include: Multiple selected points within the same detection layer are automatically merged or separated based on the distribution of surface information at the next level; merging refers to multiple selected points corresponding to different actual data points staying at the same location; separation refers to multiple selected points at the same location moving independently to different locations based on the different locations of their corresponding surface information at the next level; based on the location of the surface information at the next level, multiple actual data points move to the locations of their respective selected points, achieving full coverage of the next-level detection layer by multiple actual data points; when a standard data point moves to a location at the current level, the selected points corresponding to the standard data point simultaneously move to locations at the next level; when a selected point marks a location at the next level, the surface information at the next level is compared and analyzed with the data at the current level of the actual data point. Specifically, multiple stationary points are set in multiple selection boxes, and these stationary points are interconnected. Each stationary point corresponds to a point on the surface information. A one-to-one correspondence is established between each stationary point and each point. When the standard data loop moves the actual data loop, the actual data points on the actual data loop move on the actual well casing 3D model, simultaneously moving the corresponding selection points. The selection points on the actual data loop move along with the selection points on the standard data loop, with the two selection points located at the same position. This "same position" means that the position on the actual well casing 3D model is the same as its position on the standard well casing 3D model. The two selection points are connected through an association chain, and the selection points correspond to the same point information. This maps the points on the actual well casing 3D model to the same points on the standard well casing 3D model, ensuring that the movement of the standard data loop synchronously moves the actual data loop. Furthermore, the movement trajectory of the actual data loop after movement can be marked. Unmarked points are subsequently extracted for their corresponding contour information to determine the corresponding pore areas. When defining non-porous regions, as the actual data point moves to the corresponding location, while marking that location, the surface information of the corresponding location at the next level is collected through the selected point corresponding to the actual data point (here, "level" refers to dividing the well casing 3D model into regions, for example, a cylindrical well casing is divided into regions from top to bottom, each region corresponds to a level, each level corresponds to multiple locations, and these multiple locations refer to locations located on the same concentric circle, with each concentric circle corresponding to a region, each concentric circle being a level, and in each level, only one vertical unit location is collected at a time in the vertical direction, but multiple horizontal unit locations can be collected simultaneously, so multiple horizontal unit locations form a concentric circle, which is also considered a level). The surface information on the actual well casing 3D model is compared with the surface information on the standard well casing 3D model, allowing for comparison in advance without waiting for the actual data point to move to that location, thus improving the efficiency of comparing the actual well casing 3D model with the standard well casing 3D model.When the surface information encountered in the next level of the actual well casing 3D model differs from that in the standard well casing 3D model, the selected point for collecting the surface information at that location is automatically moved to another stationary point on the same level. Simultaneously, the actual data point corresponding to that selected point is moved to the point on the previous level corresponding to that stationary point. Then, as the actual data point continues to move to the next level and collect the corresponding surface information, any redundant selected points on the stationary point are returned to an empty stationary point. Finally, the actual data point is moved from its overlapping position with other actual data points back to the point corresponding to the empty stationary point, thus determining each marked stationary point. The surface information corresponding to each point is consistent with the surface information of the standard well casing 3D model. Unmarked points are moved, and when they need to be marked again, they are separated from other stationary points. The stationary point of the selected point is changed continuously, thus filtering out inconsistent surface information. This allows for a more intuitive identification of locations inconsistent with the standard well casing 3D model. Based on pre-established multi-level synchronous movement comparison rules, during the synchronous movement of the actual data loop and the standard data loop, the pre-movement mechanism of the selected points ensures that the corresponding selected points have moved to the next level and collected surface information before the actual data points reach their current location. Parallel processing of pore region identification is achieved through pre-detection, shortening the acquisition time for pore regions. Simultaneously, through the merging and separating mechanism of selected points, the layout of the selected points is automatically adjusted according to the distribution of the next level of surface information, avoiding repeated detection of invalid points and improving the efficiency of pore region identification.

[0022] The calculation module is used to calculate the area ratio of the pore region in the total detection area, and output the actual effective porosity of the target well pipe in combination with the pipe wall thickness parameter. The steps for calculating the area ratio of the pore region in the total detected area and outputting the actual effective porosity of the target well pipe, combined with the pipe wall thickness parameter, include: performing boundary extraction and area integration on the pore region to obtain the total area of ​​the pore region; obtaining the total detected area of ​​all surfaces of the actual well pipe 3D model; dividing the total area of ​​the pore region by the total detected area to obtain the area ratio; using the area ratio as the planar distribution coefficient of the pores; using the pipe wall thickness parameter as the depth influence coefficient of the pores; and weightedly fusing the planar distribution coefficient and the depth influence coefficient to generate the actual effective porosity.

[0023] Specifically, for example, a section of an in-service oil and gas well pipe, 1 meter long, with an outer diameter of 114.3 mm and a designed wall thickness of 6.35 mm, was analyzed using a 3D laser scanner and an ultrasonic thickness gauge. The actual 3D model of the well pipe had a total surface area of ​​0.45 m² and an average wall thickness of 5.82 mm (due to corrosion thinning). Through a multi-level synchronous moving comparison method, three pore areas were identified on the surface of the actual 3D model of the well pipe. P-01 The middle part of the outer wall of the tube Oval-shaped corrosion pits 25mm for the major axis and 18mm for the minor axis P-02 The outer wall of the tube near the joint Irregular strip cracks 32mm long, 3-5mm wide P-03 inner wall of tube Circular pitting 12mm in diameter Automatically identify the edge contour points of each pore region and generate closed boundary curves. Area integration: Calculate the area integral for each region enclosed by the closed boundary. The result is: P-01 58 boundary points were extracted and fitted into an elliptic curve. The formula for the area of ​​an ellipse is π×a×b. π × 12.5 mm × 9 mm = 353.43 mm² P-02 46 boundary points were extracted and fitted into an irregular polygon. Polygonal Partition Integration Method 112.00mm² P-03 Extract 24 boundary points and fit them into a circular curve. Formula for the area of ​​a circle: π × r² π × 6mm × 6mm = 113.10mm² total - - 578.53mm² The total area of ​​the pore region is 578.53 mm²; unit conversion: 578.53 mm² = 0.00057853 m². The total surface area data is directly read from the actual well casing 3D model. The total detected area is 0.45 m². Dividing the total pore region area by the total detected area gives the area percentage: Area percentage = Total pore region area / Total detected area × 100%. The calculation process is: Area percentage = 0.00057853 m². 2 / 0.45m 2 ×100%=0.1286%, which means that approximately 1.3 / 1000 of the well casing surface is covered by porosity defects. Using this area percentage as the planar distribution coefficient of the porosity, we set: Planar distribution coefficient = Area percentage = 0.1286%. The logic for setting the depth influence coefficient is as follows: In this example, the wall thickness parameter (5.82 mm) reflects the current remaining wall thickness of the well casing. To convert the thickness parameter into a dimensionless depth influence coefficient, a reference wall thickness needs to be introduced for normalization. The reference wall thickness is set as: the design wall thickness of the standard well casing = 6.35 mm. The depth influence coefficient is calculated as follows: Depth influence coefficient = (Reference wall thickness − Actual wall thickness) / Reference wall thickness. The depth influence coefficient = (6.35 mm − 5.82 mm) / 6.35 mm = 0.0835, which is 0.0835 (i.e., 8.35%). The wall thickness is reduced by 8.35%, meaning that the pores not only exist on the surface but also extend into the depth direction, having a greater impact on the structural strength of the well casing. The planar distribution coefficient and the depth influence coefficient are weighted and integrated. Based on engineering experience, the weight of the planar distribution coefficient is set as α = 0.4, and the weight of the depth influence coefficient is set as β = 0.6, reflecting the greater impact of depth factors on well casing safety. The actual effective porosity is calculated as α × planar distribution coefficient + β × depth influence coefficient. The calculation process is: Actual effective porosity = 0.4 × 0.1286% + 0.6 × 8.35% = 5.06144%, which is approximately 5.06%. While the surface area appears to be only 0.13% covered by pores, the actual effective porosity reaches 5.06% due to significant wall thinning (8.35%). This indicates that the structural integrity of the well casing has been significantly affected, and repair or replacement is recommended, rather than simply assuming "no major problem" based on surface observation. The entire process, from pore identification to porosity output, is fully automated, eliminating the need for manual boundary delineation. A weighted fusion model incorporates easily overlooked wall thinning factors into the porosity calculation, avoiding the blind spot of "only considering area and not depth," and more accurately reflecting the degree of well casing damage.

[0024] In the description of this specification, references to terms such as "an embodiment," "example," "specific example," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0025] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A system for non-destructive testing and result analysis of well casing porosity, characterized in that, include: The first construction module is used to obtain the design parameters of the target well casing and build a standard well casing 3D model based on the design parameters. The second construction module is used to acquire the original physical inspection data of the entire wall of the well pipe, and to construct a three-dimensional model of the actual well pipe that reflects the actual physical state of the well pipe based on the original physical inspection data; The configuration module is used to establish comparison rule information between the actual well casing 3D model and the standard well casing 3D model. The comparison rule information includes the actual data loop and the standard data loop, as well as the association chain between the actual data loop and the standard data loop. The porosity identification module is used to compare the 3D model of the well casing with the standard 3D model of the well casing based on comparison rules, and to identify and segment the porosity and non-porosity areas on the surface of the well casing. The calculation module is used to calculate the area ratio of the pore region in the total detection area, and output the actual effective porosity of the target well pipe in combination with the pipe wall thickness parameter.

2. The well casing porosity nondestructive testing and result analysis system according to claim 1, characterized in that: The steps of obtaining the design parameters of the target well casing and constructing a standard well casing 3D model based on the design parameters include: Obtain the design parameters of the target well casing, including geometric dimensions, structural features, and material properties. Based on the geometric dimensions and structural features, the geometric profile of the target well casing is constructed. Based on the material property parameters, corresponding physical and visual properties are assigned to the geometric contour to generate a standard well casing 3D model.

3. The well casing porosity nondestructive testing and result analysis system according to claim 1, characterized in that: The steps of obtaining the original physical inspection data of the entire well casing wall and constructing a three-dimensional model of the actual well casing reflecting its actual physical state based on the original physical inspection data include: The point cloud data representing the outer surface profile of the target well casing, the point cloud data representing the inner surface profile of the well casing, and the detection data representing the wall thickness distribution and internal defects of the well casing are acquired as raw physical detection data. A three-dimensional mesh model of the inner and outer walls of the target well casing is constructed based on the original physical inspection data; Based on the detection data mapped to the corresponding spatial location of the 3D mesh model, an actual 3D model of the well casing containing wall thickness distribution information and internal defect information is generated.

4. The well casing porosity nondestructive testing and result analysis system according to claim 1, characterized in that: The steps for establishing the comparison rules between the actual well casing 3D model and the standard well casing 3D model include: Obtain the surface information of the actual well casing 3D model, and construct the actual data loop based on the surface information; Obtain surface information of a standard well casing 3D model and construct a standard data loop based on the surface information; Establish association chains between the actual data ring and the standard data ring, and use the association chains between the actual data ring and the standard data ring, as well as between the actual data ring and the standard data ring, as comparison rule information.

5. The well casing porosity nondestructive testing and result analysis system according to claim 4, characterized in that: The steps of obtaining the surface information of the actual well casing 3D model and constructing the actual data loop based on the surface information include: Obtain raw physical inspection data of the entire wall of the well casing. The raw physical inspection data includes surface information of multiple layers, and each layer of surface information corresponds to a point of inspection layer. Each location is configured with an actual data point, and a first communication connection is established between multiple actual data points to form an actual data ring. Configure a selection point for each actual data point, and establish a second communication connection between the actual data point and the corresponding selection point; A third communication connection is established for multiple selection points to form a selection box; multiple stationary points are set in the selection box, each stationary point is used to stop the selection point, any selection point stops at any stationary point, and at least one selection point stops at any stationary point; The rules for establishing a standard data ring are the same as those for establishing an actual data ring. A standard data ring includes multiple standard data points and a selection box corresponding to each standard data point.

6. The well casing porosity nondestructive testing and result analysis system according to claim 5, characterized in that: The steps for establishing the association link between the actual data ring and the standard data ring include: Establish a synchronous movement association between each standard data point and the corresponding actual data point, and the movement trajectory of the standard data point is the same as the movement trajectory of the actual data point; Establish a mapping relationship between the selected points of the actual data points and the selected points of the standard data points, so that the selected points on the actual side and the selected points on the standard side move synchronously to the corresponding points of the next layer.

7. The well casing porosity nondestructive testing and result analysis system according to claim 1, characterized in that: The step of comparing the 3D model of the well casing with a standard 3D model of the well casing based on comparison rules, and identifying and segmenting the porous and non-porous regions on the surface of the well casing, includes: The standard data loop, composed of control standard data points, moves on the surface of a standard well casing 3D model. Based on the correlation chain, the actual data loop composed of actual data points moves synchronously on the surface of the actual well casing 3D model; When the actual data point moves to the current level, the selected point corresponding to the actual data point moves to the next level and collects the surface information corresponding to the next level. By selecting points to merge and separate at the same detection level and using a pre-analysis mechanism on the standard data point side, multiple actual data points can achieve full coverage of the next level of detection and perform comparative analysis of surface information in advance. Determine whether the surface information on the actual well casing 3D model is consistent with the surface information on the standard well casing 3D model; For surface information where the judgment result is inconsistent, control the position of the actual data point away from the current level; For surface information that is consistent with the judgment result, control the actual data point to move to the location of the consistent surface information, and mark the consistent surface information. Based on the movement paths of multiple actual data points, the entire surface of the actual well casing 3D model is covered. The contours and volumes corresponding to the marked surface information are taken as non-porous regions, and the contours and volumes corresponding to the unmarked surface information are taken as porous regions.

8. The well casing porosity nondestructive testing and result analysis system according to claim 1, characterized in that: The steps of achieving full coverage of the next level of detection layer by multiple actual data points and comparative analysis of surface information through the merging and separation mechanism of selected points at the same detection level and the pre-analysis mechanism on the standard data point side include: Multiple selected points at the same detection level are automatically merged or separated based on the distribution of surface information at the next level. Based on the location of the surface information of the next level, multiple actual data points are moved to the location of their respective selected points, thereby achieving full coverage of the next level of detection by multiple actual data points. When the standard data point moves to a point in the current level, the selected point corresponding to the standard data point moves to a point in the next level at the same time. When selecting points to mark the locations of the next level, the surface information of the next level is compared and analyzed with the location data of the actual data points in the current level.

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