Pipeline geological environment safety assessment method based on photogrammetry technology combined with numerical simulation

Abstract

The present invention discloses a pipeline geological environment safety assessment method that combines photogrammetry technology with numerical simulation, which involves geological monitoring technology and solves the technical problem that the existing pipeline geological disaster assessment method has high operating costs and is difficult to promote and popularize. Image data P in the study area are collected at different time points, and the increase and decrease status of the terrain elevation of the study area in all image data P is analyzed by terrain elevation differential analysis to determine the unstable area Dus in the study area; the unstable area Dus is combined with pipeline parameter data to carry out finite element analysis of slope-pipeline coupling to evaluate the safety of the pipeline under the current slope displacement state. The present invention can effectively determine whether the pipeline geological environment is in a safe state, and has the outstanding advantages of being flexible, fast, and low-cost, and is easy to promote; it can also further achieve rapid assessment and early warning.

Description

Technical Field

[0001] The present invention relates to geological monitoring technology, and more particularly to a pipeline geological environment safety assessment method combining photogrammetry technology with numerical simulation. Background Art

[0002] Pipeline transportation is the most economical and rational method of transporting oil and natural gas. However, because both oil and natural gas are toxic substances, characterized by flammability and explosiveness, high energy and pressure, toxicity and harmfulness, and complex environments, they place high demands on safety. Due to the spatial disparity between oil and gas supply and demand, oil and gas pipeline routes often involve extremely long-distance transportation. Line design also requires specific safety requirements, such as distance from populated areas and necessary shielding, to meet safety standards. These factors combine to make identifying pipeline geological hazards and conducting pipeline safety assessments within large, unmanned areas a critical component of oil and gas pipeline safety and a major challenge in pipeline transportation disaster mitigation and prevention.

[0003] The research methods for identification and assessment of pipeline geological hazards mainly focus on three categories: on-site investigation, monitoring and early warning, and remote sensing technology.

[0004] The on-site survey method involves collecting data on the pipeline's terrain, geomorphology, stratigraphic structure, lithology, hydrological and meteorological conditions, and residential areas to comprehensively assess the risk and impact of geological hazards on pipelines. However, this method is time-consuming and labor-intensive, and difficult to carry out in areas with steep terrain. Therefore, it is not suitable for large-scale pipeline geological hazard identification.

[0005] Monitoring and early warning methods primarily rely on long-term monitoring of changes in parameters related to deformation and damage, such as rainfall, surface and deep displacement, inclination, crack width, and soil moisture content, to identify pipeline geological hazards and provide timely warnings. However, determining specific thresholds for monitoring and early warning using scientific algorithms based on various data remains a challenge. Furthermore, various prediction models exhibit distinct regional characteristics, limiting their general applicability.

[0006] Remote sensing technologies, primarily based on InSAR and LiDAR, can, to a certain extent, identify pipeline geological hazards early over large areas. However, these technologies are expensive to operate, and their widespread adoption remains limited. Summary of the Invention

[0007] The technical problem to be solved by the present invention is to address the shortcomings of the existing technology and provide a pipeline geological environment safety assessment method that combines photogrammetry technology with numerical simulation. It can effectively determine whether the pipeline geological environment is in a safe state, and has the outstanding advantages of being flexible, fast, and low-cost, and is easy to promote.

[0008] The present invention combines photogrammetry with a numerical simulation-based pipeline geological environment safety assessment method. Image data P is collected within the study area at different time points. Terrain elevation differential analysis is used to analyze the increase and decrease in terrain elevation within the study area in all of the image data P to identify unstable regions Dus within the study area. Finite element analysis of slope-pipeline coupling is then performed on these unstable regions Dus, combined with pipeline parameter data, to assess the safety of the pipeline under the current slope displacement state.

[0009] For further improvement, the terrain elevation differential analysis method specifically includes the following steps:

[0010] The first step is to convert the image data P into a digital orthophoto map DOM;

[0011] The second step is to extract the terrain point cloud TP from the digital orthophoto map DOM through point cloud filtering, and construct the digital terrain model DTM of the study area based on the terrain point cloud TP;

[0012] The third step is to obtain the difference result DTMs between the two digital terrain models DTMs with a time interval T, extract the terrain elevation increase and decrease data Δh based on the difference result DTMs, and determine the unstable area Dus by combining the terrain elevation increase and decrease data Δh with the actual landform change information.

[0013] Furthermore, the digital terrain model (DTM) of the study area is constructed, which specifically includes the following steps:

[0014] The first step is to calculate the VDVI value of the digital orthophoto map DOM;

[0015] The second step is to determine the VDVI value for filtering the vegetation in the study area by using the histogram entropy domain value method;

[0016] The third step is to filter the vegetation point cloud of the digital orthophoto map DOM according to the VDVI value used to filter the vegetation in the study area to extract the terrain point cloud TP;

[0017] Step 4: Generate a digital terrain model DTM based on the terrain point cloud TP.

[0018] Furthermore, the VDVI value is calculated by the following formula:

[0019]

[0020] Where, ρ green is the color value of green in the digital orthophoto DOM; red is the color value of red in the digital orthophoto DOM; blueis the color value of blue in the digital orthophoto DOM.

[0021] The unstable area Dus is determined by combining the terrain elevation increase and decrease data Δh with the actual landform change information, specifically:

[0022] The changed area in the image data P is determined based on the terrain elevation increase / decrease data Δh, and the image data P corresponding to two digital terrain models DTMs at a time interval T is compared to determine the cause of the change in the terrain elevation increase / decrease data Δh in the changed area. The area where the terrain elevation increase / decrease data Δh changes due to geological factors is marked as an unstable area Dus.

[0023] Furthermore, the area with an increasing elevation trend in the unstable area Dus is identified through the elevation information in the digital terrain model DTM, and is recorded as the slope S; the slope displacement data SD of the slope S is obtained according to the differential result DTMs, and the area corresponding to the slope displacement data SD greater than zero is marked as an unstable slope Sus.

[0024] The finite element analysis of the slope-pipeline coupling specifically includes:

[0025] The first step is to establish a terrain structure model 3D-Dus based on the data information of the unstable area Dus, slope S, and unstable slope Sus, and simultaneously establish a pipeline structure model 3D-P based on the pipeline parameter data; and then establish a finite element model FEsp containing the pipeline by combining the terrain structure model 3D-Dus and the pipeline structure model 3D-P;

[0026] The second step is to use the finite element model FEsp to establish a process model Ps-us of the unstable slope Sus from a stable state to an unstable state, identify the critical time node t of the slope S instability in the process model Ps-us, and extract the slope displacement data SDt and pipeline stress data PSt at the critical time node t;

[0027] The third step is to evaluate the safety of the pipeline under the current slope displacement state based on the relationship between the pipeline allowable stress σ and the pipeline stress data PSt in the study area;

[0028] If the pipeline stress data PSt is less than or equal to the pipeline allowable stress σ, the pipeline geological environment in the study area is safe; otherwise, the pipeline geological environment in the study area is unsafe.

[0029] Furthermore, the finite element model FEsp is used to establish a process model Ps-us of the unstable slope Sus from a stable state to an unstable state, specifically including:

[0030] The finite element model FEsp is used to perform geostress balance analysis on the slope S to obtain a slope model of geostress balance of the slope S under the action of natural gravity; then the strength reduction method is used to obtain a process model Ps-us of the unstable slope Sus from a stable state to an unstable state.

[0031] Furthermore, the slope displacement data SDt corresponding to when the slope S reaches the limit equilibrium state at the key time node t is determined as the threshold SDpg of the slope displacement data SD in the subsequent monitoring process of the study area;

[0032] If, in the later monitoring of the study area, the slope displacement data SD detected in real time is less than or equal to the threshold SDpg, the geological environment of the pipeline in the slope S in the study area is safe.

[0033] Furthermore, the method for identifying the key time node t is:

[0034] If the real-time monitored slope displacement data SD is within the error range of the slope displacement data SDt at the critical time node t, or the slope displacement data SDt shows a significant increase, or the slope S reaches a predetermined sliding amplitude, or the slope S reaches a limit equilibrium state, then the time point at this time is judged to be the current critical time node t.

[0035] Beneficial effects

[0036] The advantages of the present invention are:

[0037] 1. By performing finite element analysis on the previously collected image data P, the safety of the pipeline's geological environment is effectively determined. Compared with existing methods for identifying large-scale pipeline geological hazards based on remote sensing technology, the data acquisition and processing process of this invention offers the advantages of flexibility, speed, and low cost, making it easy to promote.

[0038] 2. By determining a threshold value SDpg for the slope displacement index as one of the evaluation data, it can be further used as the monitoring threshold in subsequent cruise monitoring, solving the problem that it is difficult to establish a specific threshold standard in existing technologies, and can further achieve rapid assessment and early warning. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 Schematic diagram of the evaluation method of the present invention;

[0040] Figure 2 This is a schematic diagram of the layout of ground control points in the study area of ​​the present invention;

[0041] Figure 3 This is an example table of measured base station parameters of the present invention;

[0042] Figure 4 A schematic diagram of the flight path generated by the parameter settings of the UAV flight control software of the present invention;

[0043] Figure 5a Schematic diagram of a digital orthophoto map DOM1 corresponding to the image data P1 of the study area of ​​the present invention;

[0044] Figure 5b Schematic diagram of the digital orthophoto map DOM2 corresponding to the image data P2 of the study area of ​​the present invention;

[0045] Figure 6 This is a schematic diagram of non-terrain feature point cloud filtering according to the present invention;

[0046] Figure 7a This is a schematic diagram of the differential results of the digital terrain model of the study area of ​​the present invention;

[0047] Figure 7b This is a schematic diagram of identifying elevation change areas according to the present invention;

[0048] Figure 7c Schematic diagram of the unstable region Dus of the present invention;

[0049] Figure 8 Schematic diagram of the unstable area Du, slope S, and unstable slope Sus of the present invention;

[0050] Figure 9 A statistical table of the areas of each region identified in the present invention;

[0051] Figure 10 This is the X60 pipe material parameter table of the present invention;

[0052] Figure 11 Schematic diagram of a finite element model FEsp containing a pipeline established in the finite element software of the present invention;

[0053] Figure 12 The physical and mechanical parameter table of the slope S of the present invention;

[0054] Figure 13 Schematic diagram of the finite element model FEsp after meshing of the present invention;

[0055] Figure 14a Schematic diagram of slope displacement in the current monitoring state of the present invention;

[0056] Figure 14b Schematic diagram of slope displacement in the limit equilibrium state of the present invention;

[0057] Figure 14c Schematic diagram of pipeline stress in the current monitoring state of the present invention;

[0058] Figure 14dSchematic diagram of pipeline stress in the limit equilibrium state of the present invention. DETAILED DESCRIPTION

[0059] The present invention will be further described below in conjunction with the embodiments, but this does not constitute any limitation to the present invention. Any limited number of modifications made by anyone within the scope of the claims of the present invention are still within the scope of the claims of the present invention.

[0060] This pipeline geological environment safety assessment method combines photogrammetry with numerical simulation. Image data P is collected within the study area at different time points. Terrain elevation differential analysis is used to analyze the changes in terrain elevation within the study area, identifying unstable regions Dus within the study area. Finite element analysis of slope-pipeline coupling is then performed on the unstable regions Dus, combined with pipeline parameter data, to assess pipeline safety under the current slope displacement conditions.

[0061] This method effectively determines whether the pipeline's geological environment is safe by performing finite element analysis on pre-collected image data P. Compared to existing methods for identifying large-scale pipeline geological hazards based on remote sensing technology, the data collection and processing process of this method offers significant advantages in flexibility, speed, and cost-effectiveness, making it easy to scale.

[0062] See Figure 1 The evaluation method of this embodiment specifically includes:

[0063] Step 1: Collect image data P of the study area using UVA technology.

[0064] The study area is defined based on the distribution of oil and gas pipelines. For example, the study area in this example is 0.456 km 2 .

[0065] like Figure 2 As shown in the figure, a ground control point is placed at each of the four corners and the center of the study area. A survey base station is set up at each ground control point and a Zhonghui i50 RTK device is installed. Figure 3 As shown, set the parameters of each measurement base station, including base station longitude, latitude, elevation, base station mode, etc.

[0066] like Figure 4 As shown in Figure 1, a UAV flight path is generated based on the above parameters. The flight is then divided into two flights at different times to collect image data P of the study area at different time points. Specifically, the time interval T can be set to about six months. This avoids the problem of wasting resources when the collection interval is too short, and also avoids the problem of not being able to detect geological hazards in the study area in a timely manner when the collection interval is too long.

[0067] Step 2: Convert the image data P into a digital orthophoto map DOM.

[0068] Specifically, image data P is imported into professional aerial image processing software, such as Pix4D. This software performs preprocessing on image data P. The image data P is processed according to the following process: raw data acquisition → project creation and data import → rapid processing and inspection → image control point puncturing → fully automatic aerial triangulation → DSM generation → DOM generation → output of the results. This ultimately completes the data conversion.

[0069] The digital orthophoto map DOM was imported into ArcGIS 10.5 software for UAV measurement results mapping. The spatial resolution of the final original digital orthophoto map DOM was about 3.7 cm. Figure 5a It is the digital orthophoto map DOM1 corresponding to the image data P1 collected at the first time point. Figure 5b It is the digital orthophoto map DOM2 corresponding to the image data P2 collected at the second time point.

[0070] Step 3: Extract the terrain point cloud TP from the digital orthophoto map DOM through point cloud filtering, and construct the digital terrain model DTM of the study area based on the terrain point cloud TP.

[0071] Specifically, the digital terrain model (DTM) of the study area is constructed, including:

[0072] The first step is to import each digital orthophoto DOM of the study area into a geographic information system analysis software, such as ArcGIS, and then calculate the VDVI value of the digital orthophoto DOM.

[0073] Among them, the VDVI value is calculated by the following formula,

[0074]

[0075] Where, ρ green is the green color value in the digital orthophoto DOM; ρ red is the color value of red in the digital orthophoto DOM; ρ blue It is the color value of blue in the digital orthophoto DOM.

[0076] The second step is to determine the VDVI value for filtering vegetation in the study area by using the histogram entropy threshold method. For example, the appropriate VDVI value for filtering vegetation in this embodiment is 0.076.

[0077] The third step is to filter the vegetation point cloud of the digital orthophoto map DOM according to the VDVI value used to filter the vegetation in the study area to extract the terrain point cloud TP. That is, the part with a VDVI value greater than 0.076 is imported into the point cloud data processing software, such as Meptek I-Site Studio software. The vegetation point cloud filtering is completed through the software. Figure 6 As shown in Figure 2, after the vegetation is filtered out, other non-topographic point clouds, such as cars, buildings, and people, are manually filtered out in the point cloud data processing software. Finally, the topographic point cloud TP of the study area is obtained.

[0078] The fourth step is to generate a digital terrain model (DTM) based on the terrain point cloud TP. This involves importing the terrain point cloud TP into geographic information system analysis software to generate a high-precision digital terrain model (DTM) of the study area. The DTMs corresponding to the image data P collected at the two time points are designated as DTM1 and DTM2, respectively.

[0079] Step 4: Refer to Figure 7a-7c , obtaining the difference results (DTMs) between two digital terrain models (DTMs) at time interval T. Specifically, DTM1 and DTM2 are imported into geomorphic change detection software, such as GCD 7.0 (Geomorphic Change Detection 7.0). The software analyzes the two DTMs to obtain the difference results (DTMs).

[0080] The terrain elevation change data Δh is extracted from the difference result DTMs. The unstable area Dus is determined by combining the terrain elevation change data Δh with the actual landform change information.

[0081] Among them, the unstable area Dus is determined by combining the terrain elevation increase and decrease data Δh with the actual landform change information, specifically:

[0082] The changed area in the image data P is determined based on the terrain elevation increase / decrease data Δh, and the image data P corresponding to the two digital terrain models DTM with the largest time interval are compared to determine the cause of the change in the terrain elevation increase / decrease data Δh in the changed area. The area where the terrain elevation increase / decrease data Δh changes due to geological factors is marked as an unstable area Dus.

[0083] Geological factors include soil erosion, ground subsidence, slope movement, etc. Determining the unstable area Dus based on geological factors can effectively exclude areas in the study area that are caused by human activities and recorded geological disasters. Figure 7b Among them, A and B are the reasons why the terrain elevation increase and decrease data △h decreases due to crop harvesting; Figure 7bIn the equation, C is the reason why the terrain elevation increase or decrease data △h decreases due to geological disasters within the interval between two acquisitions; Figure 7b In the equation, D is the reason why the terrain elevation increase or decrease data △h increases due to vegetation growth.

[0084] The elevation information in the digital terrain model DTM is used to identify the area with an increasing elevation trend in the unstable area Dus, and it is recorded as the slope S. The slope displacement data SD of the slope S is obtained based on the differential result DTMs, and the area corresponding to the slope displacement data SD greater than zero is marked as the unstable slope Sus. Figure 8 shown.

[0085] Step 5: Based on the data for the unstable area Dus, slope S, and unstable slope Sus, a 3D-Dus terrain structure model is created. Simultaneously, a 3D-P pipeline structure model is created based on the pipeline parameter data. The 3D-Dus and 3D-P pipeline structure models are combined to create a finite element model containing the pipeline, FEsp.

[0086] Regarding the construction of the terrain structure model 3D-Dus, specifically:

[0087] Use geographic information system analysis software to extract the following from the digital terrain model DTM: Figure 9 The scattered coordinates and elevation data for the unstable slope Sus are imported into 3D modeling software, such as Rhino. This software generates a 3D-Dus terrain structure model for the unstable region Dus. The model components of the 3D-Dus terrain structure model include a 3D-Sus boundary model for the unstable slope Sus and a 3D-S terrain structure model for the side slope S.

[0088] Regarding the construction of the pipeline structure model 3D-P, specifically:

[0089] From Figure 10 The pipeline parameter data is extracted from the pipeline design data of the study area shown in the figure, and the pipeline structure model 3D-P is established based on the data.

[0090] Among them, the terrain structure model 3D-Dus and the pipeline structure model 3D-P are both in ".sat" format.

[0091] Import the terrain structure model 3D-Dus and the pipeline structure model 3D-P into the finite element software, such as Abaqus, and establish the finite element model FEsp of the slope S including the pipeline through Boolean operation. Figure 11 The finite element model FEsp is shown, and the arrows in the figure indicate the position of the pipeline.

[0092] Step 6: Use the finite element model FEsp to establish a process model Ps-us for the unstable slope Sus as it transitions from a stable state to an unstable state. Specifically, perform a geostress equilibrium analysis on the slope S using the finite element model FEsp to obtain a slope model that represents the geostress equilibrium of the slope S under the action of natural gravity. Then, use the strength reduction method to obtain a process model Ps-us for the unstable slope Sus as it transitions from a stable state to an unstable state.

[0093] When establishing the process model Ps-us, the material parameters required for the finite element model FEsp simulation analysis in the finite element software must be determined first. Figure 10 The pipeline parameters shown and Figure 12 The soil parameters shown in the figure are obtained by referring to the engineering geology manual to determine the relevant parameters of rock and soil properties based on the lithology of the study area (composed of sandstone, siltstone, mudstone, and shale).

[0094] In the finite element software, the pipeline parameters and soil parameters are set in the finite element model FEsp for simulation analysis. First, the boundary conditions are set as fixed in the three directions of xyz at the bottom, fixed in the vertical direction of the side, and free boundary on the top surface, and the finite element model FEsp is divided into the following Figure 13 The tetrahedron shown in the figure is meshed. Then the process model Ps-us is constructed in the finite element software through the following three analysis steps.

[0095] The first step is to execute the "geo" command in the finite element software to complete the ground stress balance and obtain the slope model of ground stress balance.

[0096] The second step is to execute the "addpipe" command in the finite element software to add the pipeline model to the balanced formation.

[0097] The third step is to execute the "reduce" command in the finite element software to reduce the strength, gradually reducing the strength of the unstable slope region to simulate the process of slope instability. This is done by reducing the cohesion and internal friction angle of the slope model based on the equilibrium of in-situ stresses using the strength reduction method, thereby obtaining a model Ps-us for the process of an unstable slope Sus transitioning from a stable state to an unstable state.

[0098] Identify the critical time node t of slope S instability in the process model Ps-us, and extract the slope displacement data SDt and pipeline stress data PSt of the critical time node t. Figure 14a-14b As shown in Figure 1, the slope displacement data SDt and pipeline stress data PSt under different conditions.

[0099] The criteria for determining the critical time node t are: if the real-time monitored slope displacement data SD and the slope displacement data SDt at the critical time node t are within the error range, or if the slope displacement data SDt shows a significant increase, or if the slope S reaches a predetermined sliding amplitude, or if the slope S reaches a limit equilibrium state, then the current time node t is determined to be the current critical time node t. The error range can be a floating range of ±0.5 cm.

[0100] Step 7: Evaluate the safety of the pipeline under the current slope displacement state based on the relationship between the designed allowable stress σ of the pipeline in the study area and the pipeline stress data PSt.

[0101] If the pipeline stress data PSt is less than or equal to the pipeline allowable stress σ, the pipeline geological environment in the study area is safe; otherwise, the pipeline geological environment in the study area is unsafe.

[0102] For example, at a critical time node t, the slope displacement data SDt = 7.72 cm, which is close to the real-time monitored slope displacement data SD = 7.2 cm, that is, SDt ≈ SD. Therefore, the simulation results can be considered equivalent to the current actual situation and can be used for safety assessment. Figure 10 The allowable stress of X60 pipe shown is σ=k*σ s =249MPa. Among them, the material yield stress of X60 pipe is σ s The design coefficient k in this embodiment is 0.6. Through finite element analysis, the maximum pipeline stress data PSt is 45.88 MPa, which is much smaller than 249 MPa. Therefore, the geological environment of the pipeline is assessed to be safe.

[0103] In this embodiment, the slope displacement data SDt corresponding to when the slope S reaches the limit equilibrium state at the key time node t is determined as the threshold SDpg of the slope displacement data SD in the subsequent monitoring process of the study area.

[0104] If the slope displacement data SD detected in real time during the later monitoring of the study area is less than or equal to the threshold SDpg, the geological environment of the pipeline in the slope S in the study area is safe.

[0105] For example, the slope displacement data SDt obtained when the landslide reaches the limit equilibrium state through numerical simulation rehearsal is set to 167.9 cm. This data is then used as the threshold SDpg for the slope displacement data SD of slope S during subsequent patrol monitoring. In other words, during subsequent monitoring and assessment, as long as the slope displacement data SD ≤ the threshold SDpg (i.e., SD ≤ 167.9 cm), the geological environment safety of the pipeline in slope S can be quickly assessed. Otherwise, further monitoring and investigation is required.

[0106] By setting the threshold SDpg, it can be further used as a monitoring threshold in later cruise monitoring, solving the problem that it is difficult to establish specific threshold standards in existing technologies, and can further achieve rapid assessment and early warning.

[0107] The above is only a preferred embodiment of the present invention. It should be pointed out that for those skilled in the art, several modifications and improvements can be made without departing from the structure of the present invention. These modifications and improvements will not affect the effect of the implementation of the present invention and the practicality of the patent.

Claims

1. A pipeline geological environment safety assessment method combining photogrammetry with numerical simulation is characterized by: Image data P of the study area are collected at different time points. The terrain elevation difference analysis method is used to analyze the increase and decrease of the terrain elevation of the study area in all image data P to determine the unstable area Dus in the study area. Conducting slope-pipeline coupling finite element analysis on the unstable region Dus combined with pipeline parameter data to assess the safety of the pipeline under the current slope displacement state; The terrain elevation differential analysis method specifically comprises the following steps: The first step is to convert the image data P into a digital orthophoto map DOM; The second step is to extract the terrain point cloud TP from the digital orthophoto map DOM through point cloud filtering, and construct the digital terrain model DTM of the study area based on the terrain point cloud TP; Step 3: Obtain a difference result DTMs between two digital terrain models DTMs at a time interval T, extract terrain elevation change data ∆h based on the difference result DTMs, and determine the unstable area Dus by combining the terrain elevation change data ∆h with actual landform change information; Identifying an area with an increasing elevation trend in the unstable area Dus using the elevation information in the digital terrain model DTM, and marking it as a slope S; obtaining slope displacement data SD of the slope S based on the differential result DTMs, and marking an area corresponding to the slope displacement data SD greater than zero as an unstable slope Sus; The finite element analysis of the slope-pipeline coupling specifically includes: The first step is to establish a terrain structure model 3D-Dus based on the data information of the unstable area Dus, slope S, and unstable slope Sus, and simultaneously establish a pipeline structure model 3D-P based on the pipeline parameter data; and then establish a finite element model FEsp containing the pipeline by combining the terrain structure model 3D-Dus and the pipeline structure model 3D-P; The second step is to use the finite element model FEsp to establish a process model Ps-us of the unstable slope Sus from a stable state to an unstable state, identify the critical time node t of the slope S instability in the process model Ps-us, and extract the slope displacement data SDt and pipeline stress data PSt at the critical time node t; The third step is to evaluate the safety of the pipeline under the current slope displacement state based on the relationship between the pipeline allowable stress σ and the pipeline stress data PSt in the study area; If the pipeline stress data PSt is less than or equal to the pipeline allowable stress σ, the pipeline geological environment in the study area is safe; otherwise, the pipeline geological environment in the study area is unsafe; The slope displacement data SDt corresponding to the time when the slope S reaches the limit equilibrium state at the key time node t is determined as the threshold SDpg of the slope displacement data SD in the later monitoring process of the study area; If, in the later monitoring of the study area, the slope displacement data SD detected in real time is less than or equal to the threshold SDpg, the geological environment of the pipeline in the slope S in the study area is safe; The construction method of the terrain structure model 3D-Dus is: The scattered coordinates and elevation data of the unstable slope Sus are extracted from the digital terrain model DTM using geographic information system analysis software, and the scattered coordinates and elevation data are imported into three-dimensional modeling software. The terrain structure model 3D-Dus of the unstable area Dus is generated using the three-dimensional modeling software. The model components of the terrain structure model 3D-Dus include a boundary model 3D-Sus of the unstable slope Sus and a terrain structure model 3D-S of the slope S.

2. The pipeline geological environment safety assessment method using photogrammetry combined with numerical simulation according to claim 1 is characterized in that: Constructing the digital terrain model DTM of the study area includes the following steps: The first step is to calculate the VDVI value of the digital orthophoto map DOM; The second step is to determine the VDVI value for filtering the vegetation in the study area by using the histogram entropy domain value method; The third step is to filter the vegetation point cloud of the digital orthophoto map DOM according to the VDVI value used to filter the vegetation in the study area to extract the terrain point cloud TP; Step 4: Generate a digital terrain model DTM based on the terrain point cloud TP.

3. The pipeline geological environment safety assessment method combining photogrammetry technology with numerical simulation according to claim 2 is characterized in that: The VDVI value is calculated by the following formula, ； Where, is the color value of green in the digital orthophoto DOM; is the color value of red in the digital orthophoto DOM; is the color value of blue in the digital orthophoto DOM.

4. The pipeline geological environment safety assessment method combining photogrammetry technology with numerical simulation according to claim 1 is characterized in that: The unstable area Dus is determined by combining the terrain elevation increase and decrease data ∆h with the actual landform change information, specifically: A changed area in the image data P is determined based on the terrain elevation change data ∆h, and the image data P corresponding to two digital terrain models DTMs at a time interval T is compared to determine the cause of the change in the terrain elevation change data ∆h in the changed area. The area where the terrain elevation change data ∆h changes due to geological factors is marked as an unstable area Dus.

5. The pipeline geological environment safety assessment method combining photogrammetry technology with numerical simulation according to claim 1 is characterized in that: The finite element model FEsp is used to establish a process model Ps-us of the unstable slope Sus from a stable state to an unstable state, specifically including: The finite element model FEsp is used to perform geostress balance analysis on the slope S to obtain a slope model of geostress balance of the slope S under the action of natural gravity; then the strength reduction method is used to obtain a process model Ps-us of the unstable slope Sus from a stable state to an unstable state.

6. The pipeline geological environment safety assessment method combining photogrammetry technology with numerical simulation according to claim 1 is characterized in that: The identification method of the key time node t is: If the real-time monitored slope displacement data SD is within the error range of the slope displacement data SDt at the critical time node t, or the slope displacement data SDt shows a significant increase, or the slope S reaches a predetermined sliding amplitude, or the slope S reaches a limit equilibrium state, then the time point at this time is judged to be the current critical time node t.

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