Buried oil and gas pipeline landslide disaster coupling quantitative risk assessment method

Abstract

The present application relates to oil and gas pipeline safety assessment technical field, specifically relates to a kind of buried oil and gas pipeline landslide disaster coupling quantitative risk assessment method, three dimensions of the coupling evaluation index system covering landslide disaster development, disaster prevention and control efficiency and pipeline structure vulnerability are constructed, standardization quantization grading assignment rule is established to each evaluation index, and the weight is determined using the analytic hierarchy process of consistency test, landslide development index H1, control failure index H2 and pipeline vulnerability index V are respectively solved by normalization weighted summation algorithm, then comprehensive risk index is calculated by substituting into multiplication coupling model P=H1×H2×V, according to the preset threshold interval corresponding determination low, lower, medium, higher, high risk five levels of risk grade.The present application breaks through the limitation of traditional single dimension evaluation, realizes the nonlinear collaborative quantitative evaluation of landslide disaster, control failure and pipeline damage three elements, and the evaluation result is objective and reproducible, which can be directly used for pipeline landslide risk classification control and operation decision.

Description

Technical Field

[0001] This invention relates to the field of oil and gas pipeline safety assessment technology, specifically to a quantitative risk assessment method coupled with landslide disasters for buried oil and gas pipelines. Background Technology

[0002] Buried oil and gas pipelines are core infrastructure for the cross-regional allocation of oil and gas resources and the transmission of energy in my country. They are laid underground in complex geological environments and are susceptible to various geological disasters such as landslides, collapses, and debris flows. Among these, landslides are characterized by their high frequency of occurrence, wide distribution, rapid development, and high destructive intensity, making them the primary geological disaster threatening the long-term safe and stable operation of buried oil and gas pipelines.

[0003] The mountainous and hilly terrain of Yunnan, Guizhou, and Guangxi in southwestern my country is characterized by significant elevation differences, complex geological structures, and poor soil and rock stability. Coupled with a concentrated rainy season and frequent short-duration heavy rainfall, the region is prone to landslides. Long-term pipeline operation and maintenance data, along with geological hazard monitoring records, indicate that landslides frequently compress, drag, and bend buried oil and gas pipelines, easily leading to pipeline deformation, weld cracking, pipeline fracture, and oil and gas leaks. These incidents not only cause interruptions in oil and gas transportation and huge economic losses but also trigger secondary disasters such as fires, explosions, and soil and water pollution, severely hindering the safe, stable, and efficient operation of the regional oil and gas transportation network.

[0004] Current mainstream landslide risk assessment technologies in the industry have significant technical shortcomings. Existing assessment methods mostly focus on analyzing the stability, development trend, and single occurrence probability of the landslide itself, neglecting the interaction mechanism and coupling influence between landslides and buried oil and gas pipelines, and lacking a targeted integrated assessment system for "landslide-pipeline". At the same time, existing technologies cannot achieve synergistic coupling analysis of the three core elements of landslide occurrence probability, landslide prevention and control engineering effectiveness, and pipeline structure failure probability. They can only conduct qualitative or semi-quantitative assessments of single elements, resulting in assessment results that are highly one-sided, have low accuracy, are highly subjective, and have poor repeatability.

[0005] Existing assessment methods fail to accurately reflect the true damage risk level of buried oil and gas pipelines under landslide disasters, making it difficult to directly support practical engineering work such as pipeline risk classification and management, differentiated operation and maintenance inspections, precise landslide disaster control, and optimized allocation of prevention and control resources. Therefore, the industry urgently needs a comprehensive, quantitative, high-precision, and engineering-applicable method for assessing the landslide risk of buried oil and gas pipelines. Summary of the Invention

[0006] The purpose of this invention is to provide a coupled quantitative risk assessment method for landslide disasters of buried oil and gas pipelines, construct a three-dimensional assessment index system of landslide development, prevention and control effectiveness, and pipeline vulnerability, calculate the comprehensive risk index through the multiplicative coupling model P=H1×H2×V, and achieve quantitative judgment of five levels of risk based on preset thresholds.

[0007] To achieve the above-mentioned technical objectives and effects, the present invention is implemented through the following technical solution: A coupled quantitative risk assessment method for landslide hazards along buried oil and gas pipelines includes the following steps: S1: Construct a three-dimensional coupled risk assessment index system, which consists of three evaluation dimensions: indicators for evaluating the development of landslide disasters, indicators for evaluating the effectiveness of disaster prevention and control, and indicators for evaluating the vulnerability of pipeline structures. S2: For all evaluation indicators in the three-dimensional coupled risk assessment index system, establish standardized quantitative grading and value assignment rules to complete the conversion of each indicator from qualitative or quantitative characteristics to standardized scores; S3: Using a multi-criteria decision analysis method, a hierarchical analysis model is constructed to calculate and obtain the normalized weight vector of each evaluation index relative to the superior evaluation target. The weight vector passes the consistency test. S4: Based on the quantitative scores of each indicator obtained in step S2 and the weight vectors of each indicator obtained in step S3, the landslide development index, prevention and control failure index and pipeline vulnerability index are solved independently by using a preset weighted summation algorithm. S5: Substituting the landslide development index, prevention and control failure index, and pipeline vulnerability index into the coupled calculation model, a comprehensive risk index is obtained to characterize the overall risk level of pipelines under landslide disasters. The coupled calculation model is as follows:

[0008] In the formula, P is the comprehensive risk index. This refers to the landslide development index. V is the failure index for prevention and control, and V is the pipeline vulnerability index. S6: Compare the comprehensive risk index with the preset multi-level risk threshold range, determine and output the pipeline landslide disaster risk level of the current assessment object.

[0009] Furthermore, the indicators for evaluating landslide disaster development described in step S1 shall include at least one indicator item reflecting each of the following categories: landslide topographic features, landslide material composition features, landslide deformation and failure features, and landslide external inducing environmental features.

[0010] Furthermore, the indicators for evaluating the effectiveness of disaster prevention and control described in step S1 shall include at least one indicator item reflecting the status of landslide interception and drainage measures, anti-slide reinforcement measures, and soil and rock property improvement measures.

[0011] Furthermore, the indicators for evaluating the vulnerability of the pipeline structure described in step S1 include at least one indicator item for each of the following categories: the spatial burial location of the pipeline, the burial depth of the pipeline body, and the spatial geometric tangency relationship between the pipeline and the landslide body.

[0012] Furthermore, the standard for consistency testing in step S3 is a consistency ratio CR < 0.1.

[0013] Furthermore, the weighted summation algorithm in step S4 is as follows: each index is obtained by multiplying the product of the quantitative score of each indicator under the corresponding dimension and its weight, and then multiplying it by a preset normalization factor. The value range of each index is uniformly mapped to the interval [0, 1] after normalization.

[0014] Furthermore, the normalization factor is 1 / 10, and the landslide development index... Prevention and control failure index The specific formula for calculating the pipeline vulnerability index V is as follows:

[0015]

[0016] In the formula, , , The normalized weights correspond to the sub-indicators under each evaluation dimension of landslide disaster development, disaster prevention and control effectiveness, and pipeline structure vulnerability. , , Each of these corresponds to a quantitative score for one of the sub-indicators.

[0017] Furthermore, the multi-level risk threshold range mentioned in step S6 is specifically divided into five levels, and the corresponding threshold determination criteria are as follows: Low risk; Low risk; Medium risk; It is considered a high-risk situation. It is considered high-risk.

[0018] On the other hand, the present invention proposes the application of the above-mentioned method in guiding the layout of pipeline operation and maintenance inspections, determining the priority of disaster prevention and control, or making engineering management decisions.

[0019] The beneficial effects of this invention are: This invention constructs an evaluation index system covering three evaluation dimensions: landslide disaster development, disaster prevention and control effectiveness, and pipeline structural vulnerability, and adopts a multiplicative coupling model. Nonlinear synergistic integration of normalized indices across three dimensions aligns the assessment logic with the chain-like catastrophic physical mechanism of landslide-damaged pipelines, resolving the systematic distortion of assessment results caused by single-dimensional assessments or linear superposition in existing technologies. Landslide-induced failure of buried pipelines is the result of the nonlinear interaction of external disaster-causing loads, artificial control barriers, and the pipeline's own disaster-bearing capacity. This invention abstracts this physical process into three independent, quantifiable indices and characterizes their interaction relationship in a multiplicative coupling form. The three indices, normalized to the [0,1] interval, independently describe the risk gradient from absolute safety to complete failure in their respective dimensions. The multiplicative operation amplifies the overall risk of any high-risk state in any dimension through a multiplicative mechanism, rather than being averaged or submerged by the low-risk values ​​of the other two dimensions. Simultaneously, if the risk in any dimension approaches zero, the overall risk is directly reduced by the multiplicative zeroing effect. It accurately reproduces the cascading vulnerability characteristic of pipeline landslide disasters, where "failure of a single link can lead to the collapse of the entire line." This makes the comprehensive risk index output by this invention consistent with the nonlinear nature of the physical disaster-causing process in terms of mathematical properties. The assessment results can truly distinguish the qualitative boundary between "medium risk" and "higher risk," avoiding the systematic bias of linear superposition models that incorrectly classify high-risk conditions as medium-risk.

[0020] This invention establishes a unified hierarchical and quantitative assignment rule for all evaluation indicators, and uses a consistency ratio (CR) < 0.1 as the validity criterion for weight calculation in the analytic hierarchy process (AHP). This achieves fully mathematical processing from indicator input to weight allocation, eliminating the subjectivity and non-reproducibility introduced by traditional methods relying on qualitative experience. This invention maps qualitative descriptive indicators such as slope morphology, soil and rock condition, and current deformation degree, as well as quantitative measurement indicators such as slope and rainfall, to standardized risk scores ranging from 1 to 10. This numerical anchoring method solidifies the unique correspondence between indicator state and risk equivalent, eliminating the possibility of different assessors making different score judgments for the same state. Based on this, the AHP transforms expert knowledge into mathematical weights through pairwise comparison judgment matrices, while the mandatory CR < 0.1 test verifies the validity of the judgment matrix from a logical consistency perspective, eliminating inherent contradictions such as A being superior to B, B being superior to C, and C being superior to A. The valid weight parameters, after verification, are logically strictly valid in their transmission order, ensuring the scientific nature of the weight allocation. The dual constraints of standardized assignment and consistency testing ensure that the entire evaluation process of this invention is based on definite mathematical rules. Different operators will inevitably obtain the same evaluation conclusions under the same input data conditions. The repeatability and verifiability of the evaluation results are significantly better than traditional qualitative or semi-quantitative methods that rely on personal experience.

[0021] This invention uses a normalization factor to scale the weighted summation result, unifying the value ranges of the landslide development index, prevention and control failure index, and pipeline vulnerability index to the [0,1] interval. Based on this continuous risk spectrum, a five-level threshold standard is set to classify the comprehensive risk index P, making the assessment results both mathematically accurate and engineering intuitive. The theoretical upper limit of the weighted summation term is subject to the mathematical constraint that the maximum score of each indicator is 10 and the sum of the weights in the same dimension is 1, and its value range strictly does not exceed [0,10]. After multiplying by the normalization factor 1 / 10, the value range of the resulting index is precisely limited to [0,1]. An index value of 0 is given the meaning of absolute safety with no identifiable risk in that dimension, a value of 1 is given the meaning of complete failure that the dimension has reached the highest risk limit under the evaluation standard, and the intermediate value is the continuous risk gradient. The five-level threshold segmentation set on this continuous risk spectrum with an absolute reference system can directly map the value of a single comprehensive index P to a clear risk level and corresponding differentiated control measures. This eliminates the need for engineers to perform secondary relative interpretation or experience-based judgment on the assessment results, providing a direct and usable quantitative decision-making basis for the accurate classification and control of pipeline landslide risks and the allocation of operation and maintenance resources.

[0022] Of course, any product implementing this invention does not necessarily need to achieve all of the advantages described above at the same time. Attached Figure Description

[0023] 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.

[0024] Figure 1 A schematic diagram of the process for coupled quantitative risk assessment of landslide disasters along oil and gas pipelines; Figure 2 This is a schematic diagram of a landslide occurrence probability assessment system; Figure 3 This is a schematic diagram of the landslide prevention and control indicator system; Figure 4 This is a schematic diagram of a pipeline failure probability evaluation system. Detailed Implementation

[0025] 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.

[0026] Example 1

[0027] This embodiment describes a coupled quantitative risk assessment method for landslide disasters affecting buried oil and gas pipelines. It aims to address the technical problems of existing technologies, such as a single assessment dimension, failure to achieve multi-factor synergistic coupling analysis, low accuracy of assessment results, and poor engineering guidance. Its core inventive concept lies in the first-ever construction of a three-dimensional coupled risk assessment model encompassing "landslide disaster development," "disaster prevention and control effectiveness," and "pipeline structural vulnerability." Through a specific multiplicative coupled mathematical model, the quantitative indices of the three dimensions are organically integrated, thereby yielding an assessment result that accurately reflects the comprehensive damage risk level of the pipeline under landslide disasters.

[0028] Specifically, the method for coupled quantitative risk assessment of landslide hazards along buried oil and gas pipelines includes the following steps: S1: Construct a three-dimensional coupled risk assessment index system.

[0029] A three-pronged assessment framework was established, consisting of three evaluation dimensions: indicators for evaluating landslide disaster development, indicators for evaluating disaster prevention and control effectiveness, and indicators for evaluating pipeline structural vulnerability. This framework comprehensively covers the entire risk chain, from the disaster itself to human intervention and pipeline withstand capacity.

[0030] S2: Establish standardized quantitative grading and value assignment rules.

[0031] For all evaluation indicators in the aforementioned three-dimensional coupled risk assessment indicator system, a unified standardized quantitative grading and scoring rule is established to convert each indicator from qualitative description or quantitative measurement value to a standardized score. In a preferred embodiment, a unified quantitative scoring rule of 1 to 10 points is adopted. The score is positively correlated with the degree of risk or failure probability reflected by the corresponding indicator; that is, the higher the score, the greater the risk under that indicator.

[0032] For the indicators used to evaluate landslide disaster development, they must include at least one indicator reflecting each of the following categories: landslide topographic features, landslide material composition, landslide deformation and failure characteristics, and external triggering environmental characteristics. In this embodiment, this dimension includes nine sub-evaluation indicators: slope, slope morphology, soil and rock type, historical deformation, current deformation, landslide thickness, soil and rock condition, seismic intensity, and 24-hour maximum rainfall. The standardized quantitative classification and value assignment rules for each indicator are shown in the following tables.

[0033] Table 1. Classification and Value Assignment of Soil and Rock Mass Conditions to Landslide Occurrence Probability Indicators

[0034] Table 2. Classification and Value Assignment of Topographic Slope to Landslide Occurrence Probability Indicators

[0035] Table 3. Classification and Value Assignment of Landslide Occurrence Probability Index Based on Soil and Rock Deformation and Failure Characteristics

[0036] Table 4. Classification and Value Assignment of Landslide Occurrence Probability Index by Soil and Rock Mass Type

[0037] Table 5. Classification and Value Table of Probability Indicators for Landslide Occurrence in Landslide Conditions

[0038] Table 6. Classification and Value Assignment of External Triggering Factors to Landslide Occurrence Probability Indicators

[0039] For indicators evaluating the effectiveness of disaster prevention and control, they must include at least one indicator item reflecting the status of landslide interception and drainage measures, anti-slide reinforcement measures, and soil and rock property improvement measures. In this embodiment, this dimension includes three sub-evaluation indicators: interception and drainage measures, anti-slide reinforcement measures, and soil and rock property improvement measures. Their specific classification and assignment rules are shown in Table 7 below.

[0040] Table 7 Classification and Value Table of Landslide Prevention Indicators

[0041] For the indicators evaluating the vulnerability of pipeline structures, at least one indicator item should be included for each of the following categories: the spatial burial location of the pipeline, the burial depth of the pipeline body, and the spatial geometric tangency relationship between the pipeline and the landslide body. In this embodiment, this dimension includes three sub-evaluation indicators: pipeline burial depth, pipeline location, and pipeline-landslide tangency relationship. The specific classification and assignment rules are shown in Table 8 below.

[0042] Table 8. Pipeline Failure Probability Classification and Assignment Table

[0043] It should be understood that the detailed indicators and corresponding grading and assignment standards given in Tables 1 to 8 above are all preferred solutions summarized by this invention in long-term engineering practice. In practical applications, those skilled in the art can add, delete, or adjust the grading thresholds of these indicators according to the specific geological characteristics of the assessment area and pipeline conditions. As long as they conform to the three-dimensional coupled assessment framework and subsequent quantitative analysis logic of this invention, they all fall within the protection scope of this invention.

[0044] S3: Calculate and verify the weights using a multi-criteria decision analysis method.

[0045] A multi-criteria decision analysis method is employed to construct a hierarchical analysis model. This model calculates and obtains the normalized weight vectors of each evaluation index relative to the higher-level evaluation target, ensuring that the weight vectors pass a consistency check. In a preferred embodiment, the analytic hierarchy process (AHP) is used as the multi-criteria decision analysis method. Specifically, a three-level analysis model—target layer, criterion layer, and index layer—is constructed. A 1-9 scale is used to construct the judgment matrix for each level, and weights are calculated. To ensure the scientific and reasonable allocation of weights and eliminate subjective judgment bias, a consistency check is performed on the calculation results. The preferred check criterion is a consistency ratio (CR) < 0.1. Weight vectors that meet this criterion are deemed valid and retained; those that do not meet the criterion require reconstructing the judgment matrix and iterative calculation until the check is passed.

[0046] Using the above method, in an assessment of typical landslide pipelines in the southwestern mountainous region, the effective weight parameters of each indicator obtained after calculation and verification are shown in Tables 9 to 11 below.

[0047] Table 9 Weight values ​​of landslide occurrence probability index

[0048] Table 10 Weight Values ​​of Landslide Prevention Effectiveness Indicators

[0049] Table 11 Weight Values ​​of Pipeline Failure Probability Index

[0050] S4: Calculate the quantitative index for each single dimension. Based on the quantitative scores of each indicator obtained in step S2. The effective normalized weights of each indicator obtained in step S3 The landslide development index is solved independently using a pre-defined weighted summation algorithm. Prevention and control failure index Pipeline vulnerability index The weighted summation algorithm specifically involves quantifying the scores of each index based on the corresponding indicators within the same dimension. Its weight The sum of the products is then multiplied by a preset normalization factor. In a preferred embodiment, the normalization factor is... Its function is to uniformly map and restrict the value range of each index to a certain range. Within the interval, to facilitate subsequent coupled operations and unified comparisons. The specific calculation formula is as follows:

[0051]

[0052]

[0053] In the formula, , , The normalized weights correspond to the sub-indicators under each evaluation dimension of landslide disaster development, disaster prevention and control effectiveness, and pipeline structure vulnerability. , , Each of the subdivided indicators has a specific quantitative score determined according to the standardized quantitative grading and assignment rules described in step S2.

[0054] S5: Three-dimensional coupled calculation of the comprehensive risk index. The landslide development index obtained in step S4 is then used... Prevention and control failure index Pipeline vulnerability index Substituting the core coupled calculation model of this invention, a comprehensive risk index is obtained to characterize the overall risk level of pipelines under landslide disasters. The coupled calculation model is a mathematical model of the multiplication of three exponents:

[0055] The physical significance of this multiplicative model lies in the fact that it is not a simple summation of three risk indicators, but rather reflects the synergistic coupling and amplification effect among them. An increase in risk in any dimension, i.e., an exponential value approaching 1, will multiply the risk levels in other dimensions; conversely, effective control of risk in any dimension, i.e., an exponential value approaching 0, will significantly reduce the overall comprehensive risk level. This accurately reflects the objective mechanics and evolutionary mechanism of pipeline failure caused by landslide disasters, which is the core difference between this invention and existing simple linear superposition assessment methods.

[0056] S6: Risk level determination and output.

[0057] Finally, the calculated comprehensive risk index P is compared with the preset multi-level risk threshold range to determine and output the pipeline landslide disaster risk level of the current assessment object.

[0058] In a preferred embodiment, based on long-term engineering experience and data analysis, the risk level is divided into five levels, and the corresponding threshold judgment criteria are shown in Table 12.

[0059] Table 12 Classification of Pipeline Landslide Disaster Risk Levels

[0060] This classification standard is clear and intuitive, requiring no complex secondary calculations. Engineers can directly use the final risk level assessment to guide pipeline operation and maintenance inspection layout, disaster prevention priority determination, or engineering management decisions, making it highly practical.

[0061] Example 2

[0062] To further illustrate the technical solution and effects of this invention, three typical landslide hazard points of buried oil and gas pipelines in Guizhou Province in Southwest my country are used as assessment objects for detailed explanation below. The selected assessment objects are the GZ097 landslide point, NB169+950 landslide point, and MJ053 landslide point at Guiyang Station of Guizhou Oil Transportation Department.

[0063] First, through on-site geological surveys, pipeline condition testing, verification of the integrity of prevention and control facilities, and retrieval of regional meteorological data, a field survey was conducted on the aforementioned 15 subdivided evaluation indicators, and scores were strictly assigned according to the standardized quantitative grading and scoring rules in Tables 1 to 8. The scoring data for each location is shown in Table 13 below.

[0064] Table 13 Quantitative Scoring Data for Each Assessment Point

[0065] Subsequently, based on the scoring data in Table 13, and combined with the normalized weight values ​​of each indicator corresponding to Tables 9 to 11, the normalization calculation formula described in step S4 was substituted to solve for the three hidden danger points. , and Finally, the comprehensive risk index is calculated using the multiplicative coupling model in step S5. The calculation process and results for the GZ097 landslide site are as follows:

[0066]

[0067]

[0068]

[0069] According to the risk level classification standards, The landslide site GZ097 was determined to be at a high-risk level.

[0070] The calculation process and results for the NB169+950 landslide site are as follows:

[0071]

[0072]

[0073]

[0074] According to the risk level classification standards, The landslide site NB169+950 was determined to be at a medium risk level.

[0075] The calculation process and results for the MJ053 landslide site are as follows:

[0076]

[0077]

[0078]

[0079] Based on the risk level classification standard, 0.036 < 0.05, the MJO53 landslide site is classified as low-risk. The final risk assessment results for each of the above sites, along with the differentiated control recommendations based on these results, are summarized in Table 14 below.

[0080] Table 14 Landslide Risk Assessment Results and Control Recommendations for Each Location

[0081] On-site engineering verification results show that the evaluation results of the method of this invention are highly consistent with the actual geological hazard development and pipeline operation risks at the three locations. Specifically, location GZ097 exhibits obvious landslide creep deformation, with severe damage to drainage, anti-slip, and other control facilities, resulting in an extremely high risk of pipeline compression, perfectly matching the output "high risk" level. Location NB169+950 has generally fair geological conditions and mostly intact control facilities, but with minor local hazards, meeting the "medium risk" criteria. Location MJ053 has good geological stability, a complete and effective protection system, and no obvious safety hazards were found, corresponding to a "low risk" level.

[0082] It should be understood that the above application examples are only used as examples of typical pipeline landslide sites in Guizhou Province in Southwest my country to illustrate the present invention, but the application of the present invention is by no means limited to this. The method provided by the present invention has extremely high adaptability and scalability for various buried long-distance oil and gas pipelines, urban gas pipelines, and water pipelines in Yunnan, Guangxi, and other similar complex geological environments such as mountains and hills. Verification by multiple sets of measured data shows that the risk identification accuracy rate using the method of the present invention can reach 92.6%, an improvement of more than 18.3% compared to traditional single-factor assessment methods, demonstrating significant engineering practical value.

[0083] In summary, this invention proposes a coupled quantitative risk assessment method for landslide disasters affecting buried oil and gas pipelines. It constructs a coupled assessment index system covering three dimensions: landslide disaster development, disaster prevention and control effectiveness, and pipeline structural vulnerability. Standardized quantitative grading and assignment rules are established for each evaluation index, and the weights are determined using the analytic hierarchy process (AHP) after consistency verification. The landslide development index H1, prevention and control failure index H2, and pipeline vulnerability index V are calculated using a normalized weighted summation algorithm. These are then substituted into the multiplicative coupled model P = H1 × H2 × V to calculate the comprehensive risk index. Based on the preset threshold range of this index, five risk levels—low, relatively low, medium, relatively high, and high—are determined. This invention overcomes the limitations of traditional single-dimensional assessments, achieving a nonlinear, collaborative, and quantitative assessment of the three elements: landslide-induced disaster, prevention and control failure, and pipeline damage. The assessment results are objective and reproducible, and can be directly used for pipeline landslide risk classification management and operation and maintenance decisions.

[0084] The preferred embodiments of the present invention disclosed above are merely illustrative of the invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the invention to the specific implementations described. Clearly, many modifications and variations can be made based on the content of this specification. This specification selects and specifically describes these embodiments to better explain the principles and practical applications of the invention, thereby enabling those skilled in the art to better understand and utilize the invention. The invention is limited only by the claims and their full scope and equivalents.

Claims

1. A coupled quantitative risk assessment method for landslide disasters along buried oil and gas pipelines, characterized in that, Includes the following steps: S1: Construct a three-dimensional coupled risk assessment index system, which consists of three evaluation dimensions: indicators for evaluating the development of landslide disasters, indicators for evaluating the effectiveness of disaster prevention and control, and indicators for evaluating the vulnerability of pipeline structures. S2: For all evaluation indicators in the three-dimensional coupled risk assessment index system, establish standardized quantitative grading and value assignment rules to complete the conversion of each indicator from qualitative or quantitative characteristics to standardized scores; S3: Using a multi-criteria decision analysis method, a hierarchical analysis model is constructed to calculate and obtain the normalized weight vector of each evaluation index relative to the superior evaluation target. The weight vector passes the consistency test. S4: Based on the quantitative scores of each indicator obtained in step S2 and the weight vectors of each indicator obtained in step S3, the landslide development index, prevention and control failure index and pipeline vulnerability index are solved independently by using a preset weighted summation algorithm. S5: Substituting the landslide development index, prevention and control failure index, and pipeline vulnerability index into the coupled calculation model, a comprehensive risk index is obtained to characterize the overall risk level of pipelines under landslide disasters. The coupled calculation model is as follows: In the formula, P is the comprehensive risk index. This refers to the landslide development index. V is the failure index for prevention and control, and V is the pipeline vulnerability index. S6: Compare the comprehensive risk index with the preset multi-level risk threshold range, determine and output the pipeline landslide disaster risk level of the current assessment object.

2. The method as described in claim 1, characterized in that, The indicators for evaluating landslide disaster development described in step S1 include at least one indicator item reflecting each of the following categories: landslide topographic features, landslide material composition features, landslide deformation and failure features, and landslide external inducing environmental features.

3. The method as described in claim 1, characterized in that, The indicators for evaluating the effectiveness of disaster prevention and control described in step S1 shall include at least one indicator item for each of the following categories: the status of landslide interception and drainage measures, the status of anti-slide reinforcement measures, and the status of soil and rock property improvement measures.

4. The method as described in claim 1, characterized in that, The indicators for evaluating the vulnerability of the pipeline structure described in step S1 include at least one indicator item for each of the following categories: the spatial burial location of the pipeline, the burial depth of the pipeline body, and the spatial geometric tangency relationship between the pipeline and the landslide body.

5. The method as described in claim 1, characterized in that, The standard for consistency testing in step S3 is a consistency ratio CR < 0.

1.

6. The method as described in claim 1, characterized in that, The weighted summation algorithm in step S4 is as follows: each index is obtained by multiplying the product of the quantitative score of each indicator under the corresponding dimension and its weight, and then multiplying it by a preset normalization factor. The value range of each index is uniformly mapped to the interval [0, 1] after normalization.

7. The method as described in claim 6, characterized in that, The normalization factor is 1 / 10, and the landslide development index is... Prevention and control failure index The specific formula for calculating the pipeline vulnerability index V is as follows: In the formula, , , The normalized weights correspond to the sub-indicators under each evaluation dimension of landslide disaster development, disaster prevention and control effectiveness, and pipeline structure vulnerability. , , Each of these corresponds to a quantitative score for one of the sub-indicators.

8. The method as described in claim 1, characterized in that, The multi-level risk threshold range mentioned in step S6 is specifically divided into five levels, and the corresponding threshold determination criteria are as follows: Low risk; Low risk; Medium risk; It is considered a high-risk situation. It is considered high-risk.

9. The application of the method as described in any one of claims 1-8 in guiding the layout of pipeline operation and maintenance inspections, determining the priority of disaster prevention and control, or making engineering management decisions.

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