A shale oil gathering and transportation pipeline leakage risk analysis and safety prevention and control method

Abstract

The present invention provides a shale oil gathering and transportation pipeline leakage risk analysis and safety control method, comprising the following steps: establishing an FTA model to analyze pipeline leakage accidents of the shale oil gathering and transportation pipeline, defining pipeline erosion as a key risk factor causing pipeline leakage accidents; using a Bayesian network to perform quantitative risk analysis on pipeline leakage and calculate the probability of pipeline leakage; establishing a pipeline erosion model in Fluent software to simulate the causes of pipeline leakage risks; establishing a pipeline leakage diffusion model of the shale oil gathering and transportation pipeline in FLACS software; gridding the pipeline leakage diffusion model; setting pipeline leakage output gas components and component ratios in the pipeline leakage diffusion model; setting the pipeline leakage aperture and leakage pressure in the pipeline leakage diffusion model; setting plant environmental parameters; using FLACS software to analyze the shale oil and gas leakage diffusion law; and formulating pipeline leakage risk safety control measures based on the quantitative analysis of influencing factors before and after pipeline leakage.

Description

Technical Field

[0001] The present invention relates to the technical field of in-situ conversion of shale oil, and in particular to a shale oil gathering and transportation pipeline leakage risk analysis and safety prevention and control method. Background Art

[0002] The oil and gas produced using in-situ conversion technology are characterized by high temperature and high sulfur. The temperature of the produced material is as high as over 300°C. It is transported via pipelines to a cooling and separation system, and undergoes multi-stage cooling and desulfurization treatments before finally refining into finished oil.

[0003] In the in-situ conversion process, pipelines play a key role in transporting semi-finished and finished products. However, corrosion, external damage, and human error can all lead to pipeline leaks. Since shale oil production typically involves high-temperature operations, and the contents transported through pipelines are often volatile and corrosive gases or liquids, a pipeline leak can not only damage equipment and disrupt normal production operations, but also cause environmental pollution and human health risks due to the spread of pipeline contents. Therefore, a pipeline leak risk analysis and prevention method should be developed to facilitate both preventive and post-accident handling, strengthen safety precautions and management, prevent potential accidents, and ensure the safe transportation and effective separation of shale oil. Summary of the Invention

[0004] In order to solve the problems existing in the above-mentioned prior art, the present invention provides a shale oil gathering and transportation pipeline leakage risk analysis and safety control method, which specifically includes the following technical solutions.

[0005] A shale oil gathering and transportation pipeline leakage risk analysis and safety prevention and control method includes the following steps:

[0006] S1, establish an FTA model to analyze pipeline leakage accidents in shale oil gathering and transportation pipelines, and define pipeline erosion as the key risk factor causing pipeline leakage accidents;

[0007] S2, using Bayesian networks to perform quantitative risk analysis on pipeline leakage and calculate the probability of pipeline leakage;

[0008] S3: Establish a pipeline erosion model in Fluent software to simulate the causes of pipeline leakage risks, including the following steps:

[0009] S301, meshing the pipeline erosion model;

[0010] S302, setting the simulation parameters of fluid erosion in the pipeline, including the pipeline elbow angle, fluid temperature, fluid flow rate, pipeline wall surface, sand mass, and sand diameter;

[0011] S303, setting the physical parameters and boundary conditions of the pipeline erosion model: setting the pipeline erosion model to a turbulence model, setting the flow of the fluid in the pipeline to gas-solid two-phase flow, setting the inlet of the pipeline erosion model to a velocity inlet, and setting the outlet of the pipeline erosion model to a pressure outlet;

[0012] S304, setting a particle size function and a velocity index function of the fluid in the pipeline;

[0013] In step S305, pressure-velocity coupling is initialized and solved using the pressure-based solver and the Simple algorithm. The pipeline erosion rate is viewed using Fluent software, and an erosion rate cloud map and a particle motion trajectory map are generated.

[0014] Furthermore, in order to truly restore the fluid state in the pipeline, the following settings are made for step S302:

[0015] For pipe elbow angle simulation, four angles are selected from 90° to 150°; for fluid temperature simulation, four temperatures are selected from 50° to 300°; for fluid flow rate simulation, six speeds are selected from 5m / s to 30m / s; for sand mass simulation, five mass flow rates are selected from 0.0002kg / s to 0.001kg / s; for sand diameter simulation, five diameters are selected from 0.1mm to 0.9mm; 7 sections are divided at the 90° elbow to simulate the pressure and velocity distribution in the pipeline, the sand movement trajectory, and the wall erosion area distribution.

[0016] Furthermore, in step S301, the grid division is set as follows: the calculation domain along the pipeline axis is divided into three blocks and progressive grids are used; the cross-sectional fluid calculation domain is divided into five blocks, a boundary layer and four-layer grids are set near the pipe wall, the first layer height and growth factor are set to capture the near-wall flow, the pipeline grid is evenly distributed, the radial direction is divided into five grids and the wall thickness remains unchanged; the hexahedral units in the entire area are discretized, and independent grids are obtained through repeated calculations.

[0017] Furthermore, when establishing the FTA model, the pipeline leakage accident is taken as the top event, and analysis is conducted from three aspects: external factors, corrosion factors and pipeline defects; the external factors include human factors and natural factors; the corrosion factors include external corrosion, pipeline internal corrosion, and pipeline stress corrosion; the pipeline defects include inherent defects and operational defects.

[0018] Furthermore, in step S2, using the Bayesian network to perform quantitative risk analysis on pipeline leakage includes the following steps:

[0019] S201, expressing the basic events in the FTA model as root nodes in the BN;

[0020] S202, directly assigning the prior probability of the basic event in the FTA model to the corresponding root node in the BN as the prior probability of the root node;

[0021] S203, expressing the intermediate event in the FTA model as a node in the BN, where the node flag and state values ​​are consistent with the output event of the logic gate in the FTA model;

[0022] S204, connecting the nodes in the BN according to the relationship between the logic gates and basic events expressed in the FTA model, where the directions of the directed edges connecting the nodes correspond to the input-output relationships of the logic gates in the FTA model;

[0023] S205, expressing the logical relationship of the logic gates in the FTA model as the conditional probability of the corresponding nodes in the BN;

[0024] S206, setting the node relationships in the BN to be represented by directed arrows, with the arrows starting from the control event and pointing to the affected event;

[0025] S207, the probability of occurrence of the direct cause event in the FTA model is obtained by expert scoring and reference to data, and this probability is used as the prior probability of the parent node in the Bayesian network, thereby calculating the probability of each intermediate event and pipeline leakage through the Bayesian network.

[0026] Furthermore, the Bayesian network in step S2 is converted into a dynamic Bayesian network, which specifically includes the following steps:

[0027] S208, determining the impact of basic events in the FTA model based on Bayesian network analysis, and determining basic events whose probabilities increase over time, and using their nodes as dynamic parent nodes;

[0028] S209, setting the number of calculation time periods for the dynamic Bayesian network, setting the transfer speed according to the speed of change of the dynamic parent node probability, setting the transfer probability of the dynamic parent node according to expert experience, performing dynamic Bayesian network calculations, obtaining the time-varying trend of each node, converting the Bayesian network into a dynamic Bayesian network, and obtaining the time-varying trend of key events;

[0029] S210 , setting the number of calculation time periods of the Bayesian network to a common multiple of the dynamic parent node probability transfer speed.

[0030] Furthermore, the method also includes diffusion analysis of the pipeline contents after the pipeline leaks, comprising the following steps:

[0031] S4, establishing a pipeline leakage diffusion model for the shale oil gathering and transportation pipeline in the FLACS software, and setting the leakage model at the shale oil gathering and transportation pipeline as a continuous leakage source model;

[0032] S5, performing grid division on the pipeline leakage diffusion model;

[0033] S6, setting the pipeline leakage output gas components and component ratios in the pipeline leakage diffusion model;

[0034] S7, setting the pipeline leakage aperture and leakage pressure in the pipeline leakage diffusion model; setting the plant environment parameters, including ambient temperature, ambient pressure, ambient wind speed, ambient wind direction, atmospheric stability, and ground roughness;

[0035] S8, using the CASD pre-processing module, Run Manager run solution module, and Flowvis post-processing module of the FLACS software to analyze the shale oil and gas leakage diffusion law;

[0036] S9. Based on the quantitative or qualitative analysis of the influencing factors before and after the pipeline leakage, formulate safety prevention and control measures for pipeline leakage risks.

[0037] Furthermore, the gas distribution concentration of shale oil and gas pipeline leakage and diffusion was verified and calculated using the Gaussian plume model, and the dangerous concentration range of shale oil and gas pipeline leakage and diffusion was obtained; the Gaussian plume model expression is as follows:

[0038] ,

[0039] ,

[0040] Where,

[0041] is the Gaussian plume model expression; q is the mass leakage rate, mg / s; is pi; u is wind speed, m / s; is the lateral diffusion coefficient; is the vertical diffusion coefficient; x is the downwind distance, m; y is the lateral distance, m; z is the concentration distribution on the ground; e is the base of the natural logarithm; is an exponential function, which means e The power of; H is the effective height of the pollution source, m.

[0042] Furthermore, the grid division area of ​​the pipeline leakage diffusion model is set, and the grid division area is divided into a core area, a boundary area, and a core encryption area;

[0043] The grid of the core area is initially encrypted and the grid size is set; the boundary area is extended at the grid boundary of the core area to obtain a complete divided grid area; the grid of the core encrypted area is subdivided according to the size of the leakage aperture, and then the grid at the boundary of the core encrypted area is smoothed using Smooth processing.

[0044] Furthermore, the mesh quality and porosity verification of the pipeline leakage diffusion model are carried out as follows:

[0045] Check the grid quality in the Grid information section of the Grid menu. The X, Y, and Z values ​​in the Max percentage diff column should not exceed 30.

[0046] Use the Flowvis module to check the porosity verification. Click on the geometric structure grid of the simulation area of ​​the pipeline leakage diffusion model. A porosity of 0 indicates solid blockage, 1 indicates no obstruction, and a porosity between 0 and 1 indicates partial blockage.

[0047] Furthermore, the pipeline leakage aperture is selected through the following steps:

[0048] S701, based on the ratio of the pipeline leakage hole diameter to the pipeline diameter The size of the pipeline model is divided into three types: When , it is a small hole pipe model; 0.2< When <0.6, it is a large-pore pipe model; When , it is the pipeline fracture model;

[0049] S702: Calculate the leakage rates of the three different leakage apertures in step S701 through the following steps, and select the pipeline leakage aperture according to the leakage rates:

[0050] Will" ” is compared with “(2 / (k+1))^(k / (k+1))” to determine the gas flow state in the pipeline:

[0051] like" ”≤“(2 / (k+1))^(k / (k+1))”, belongs to sonic flow, and the gas leakage rate is calculated as follows:

[0052] ,

[0053] like" ">"(2 / (k+1))^(k / (k+1))", belongs to subsonic flow, the gas leakage rate is calculated as follows:

[0054] ,

[0055] In the above formula,

[0056] is the critical pressure, Pa; p is the pressure inside the container, Pa; is the mass flow rate, kg / s; is the flow coefficient; A is the leakage hole area, m 2 ; M is the molar mass of the gas, kg / mol; k is the gas heat capacity ratio / isentropic index; is the universal gas constant, J / (mol⋅K); T is the gas temperature, K.

[0057] Furthermore, the leakage rate of the leakage aperture is calculated using MATLAB.

[0058] The function files written are as follows:

[0059] function [ Q c ] = ex3_10( C d ,A,P,k,M,R,T )

[0060] Qc=C d *A*P*(k*M / R / T*(2 / (k+1))^((k+1) / (k-1)))^0.5;

[0061] end

[0062] The code to calculate the leak rate is as follows:

[0063] C=0.9; A=[0.0016, 0.0036, 0.0064, 0.0144]; P=1e6; k=1.315;

[0064] M=19.804e-3; R=8.314; T=273.15+300;

[0065] Q c =ex3_10( C d ,A,P,k,M,R,T ).

[0066] Based on the above technical solution, the present invention has the following beneficial effects.

[0067] 1. Establish a pipeline leakage FTA model, which can accurately and comprehensively find the direct cause events and intermediate events that cause pipeline leakage, establish the connection between each event, and thus find and determine the risk factors that cause pipeline leakage.

[0068] 2. Quantitative risk analysis of pipeline leakage is performed through Bayesian networks, and the Bayesian network is converted into a dynamic Bayesian network, which can further accurately calculate the probability of pipeline leakage, making it easier for managers and operators to take corresponding safety prevention and control measures.

[0069] 3. Based on fluid mechanics theory and key risk factors that cause pipeline leakage, a pipeline erosion model for oil and gas-carrying solid particles in the pipeline is established. This model can analyze the sensitivity of various pipeline erosion factors to pipeline wear, thereby formulating corresponding safety prevention and control measures before pipeline leakage, thereby providing guidance in pipeline design and actual safe operation of the project.

[0070] 4. Establish a pipeline leakage diffusion model for shale oil gathering and transportation pipelines, and set the leakage model at the shale oil gathering and transportation pipeline as a continuous leakage source model to more realistically simulate pipeline leakage at the production wellhead. In the pipeline leakage diffusion model, appropriate or representative pipeline leakage apertures, leakage pressures, and ambient wind field conditions are selected. Simulations are performed using the control variable method to characterize the impact of leakage diffusion. This allows for accurate prediction and assessment of the impact and severity of leakage accidents, providing a scientific basis for plant safety design, operation management, and emergency response, enabling the development of effective emergency response measures and safety protection strategies.

[0071] 5. The Gaussian plume model is used to calculate the gas distribution concentration of shale oil and gas pipeline leakage and diffusion, and the dangerous concentration range of shale oil and gas pipeline leakage and diffusion is obtained. The results are compared and confirmed with the FLACS analysis results to ensure the accuracy of the pipeline leakage and diffusion model prediction, which provides a basis for the subsequent safety protection measures. BRIEF DESCRIPTION OF THE DRAWINGS

[0072] Figure 1 : Schematic diagram of the pipeline leakage FTA model established in the exemplary embodiment;

[0073] Figure 2 : Figure 1 A magnified view of point A;

[0074] Figure 3 : Figure 1 Enlarged view of point B;

[0075] Figure 4 : Schematic diagram of the pipeline erosion model established in the exemplary embodiment;

[0076] Figure 5 : Schematic diagram of a pipeline leakage diffusion model established in an exemplary embodiment;

[0077] Figure 6 : Schematic diagram of the risk analysis and safety control method flow in the exemplary embodiment;

[0078] Figure 7 : Schematic representation of the leakage diffusion conditions of the production wellhead pipeline under different leakage apertures, leakage rates, leakage directions and wind field conditions in the exemplary embodiment. DETAILED DESCRIPTION

[0079] It should be noted that:

[0080] 1. Certain terms are used in the specification and claims to refer to specific components. Those skilled in the art should understand that technicians may use different terms to refer to the same component. Therefore, this specification and claims do not use differences in terms as a means of distinguishing components. Instead, the distinction is based on differences in the functions of the components.

[0081] 2. Unless otherwise defined, technical or scientific terms used in the present disclosure should have the same meaning as commonly understood by persons having ordinary skills in the field to which the present disclosure belongs.

[0082] As attached Figure 1 -Attached Figure 7 As shown, this embodiment describes a shale oil gathering and transportation pipeline leakage risk analysis and safety control method, including the following steps:

[0083] S1. Establish a pipeline leakage FTA model to analyze leakage accidents in shale oil gathering and transportation pipelines and obtain the key risk factors that cause pipeline leakage accidents.

[0084] When establishing the FTA model, in order to comprehensively cover the inducing factors that lead to pipeline leakage accidents, this embodiment uses pipeline leakage accidents as the top event and conducts a top-down analysis from three aspects: external factors, corrosion factors, and pipeline defects. This is to find the direct cause events and intermediate events that cause pipeline leakage, and to establish the relationship between each event, thereby finding and determining the risk factors that cause pipeline leakage.

[0085] in,

[0086] The causes of pipeline leakage accidents caused by external factors are set as: human factors and natural factors;

[0087] The causes of pipeline leakage accidents caused by corrosion factors are: external corrosion, internal corrosion of pipelines, and stress corrosion of pipelines;

[0088] The causes of pipeline leakage accidents caused by pipeline defects are: defects in the pipeline itself, operational defects;

[0089] Operational errors, natural disasters, corrosion perforation, structural defects and other events are set as the causes of pipeline leakage accidents.

[0090] Based on the above content, the following Figure 1-3The pipeline leakage FTA model shown in the figure identifies internal pipeline corrosion as the key risk factor for pipeline leakage accidents. The primary factor affecting internal pipeline corrosion is pipeline erosion, which is caused by factors including, but not limited to, pipe elbow angles, flow media, pipe wall surface, and particles. Flow media factors include fluid temperature and flow velocity, while particle factors include sand quality and diameter.

[0091] S2: Based on the pipeline leakage FTA model, a Bayesian network is used to perform a quantitative risk analysis of pipeline leakage and calculate the probability of pipeline leakage. For ease of description, this step will refer to the pipeline leakage FTA model as the FTA model, and the Bayesian network as the BN. The basic events in the FTA model are the most fundamental causes of pipeline leakage accidents, such as corrosion perforation and valve leakage.

[0092] The specific steps include:

[0093] S201, all basic events in the FTA model are represented as root nodes in the BN. If a root node appears multiple times, only one root node is required in the BN.

[0094] S202, directly assigning the prior probability of each basic event in the FTA model to the corresponding root node in the BN as the prior probability of the root node;

[0095] S203, express all intermediate events in the FTA model as a node in the BN, and the node flag and state value are consistent with the output event of the logic gate in the FTA model;

[0096] S204, connecting the nodes in the BN according to the relationship between the logic gates and basic events expressed in the FTA model, where the directions of the directed edges connecting the nodes correspond to the input-output relationships of the logic gates in the FTA model;

[0097] S205: Express the logical relationship of the logic gates in the FTA model as a conditional probability table of the corresponding nodes in the BN.

[0098] S206 , setting the node relationships in the BN to be represented by directed arrows, with the arrows starting from the control event and pointing to the affected event.

[0099] The probability of the direct cause event is determined through expert scoring and data review. This probability is used as the prior probability of the parent node in the Bayesian network. From this, the probability of each intermediate event and pipeline leak is calculated using the Bayesian network. The fuzzy triangular number algorithm is used to mathematically transform the expert scoring results.

[0100] S3: To further accurately calculate the probability of pipeline leakage, the Bayesian network in step S2 can be converted into a dynamic Bayesian network. The key events in this step are: basic events whose probability increases significantly over time and basic events with greater impact.

[0101] The specific steps include:

[0102] S301, determining the impact of basic events based on Bayesian network analysis, and determining basic events whose probabilities increase over time, and using their nodes as dynamic parent nodes;

[0103] S302: Setting the number of calculation time periods for the dynamic Bayesian network, setting the transfer speed based on the speed of change of the dynamic parent node probability, setting the transfer probability of the dynamic parent node based on expert experience, performing dynamic Bayesian network calculations, obtaining the time-varying trend of each node, converting the Bayesian network into a dynamic Bayesian network, and obtaining the time-varying trend of key events;

[0104] S303, setting the number of calculation time periods of the Bayesian network to a common multiple of the dynamic parent node probability transfer speed. The dynamic parent node probability transfer speed is expressed in time periods and is set to four change speeds:

[0105] For nodes with a fast probability growth rate, set the probability to change once every 1 time period;

[0106] For nodes with fast growth, the probability transfer rate changes once every 2 nodes;

[0107] For nodes with slow growth, the transfer probability is set to change every 3 nodes;

[0108] For nodes with slow growth rate, the node transfer probability is set to change once every 5 nodes.

[0109] S4, based on the fluid mechanics theory and the key risk factors that cause pipeline leakage determined in step S1, use Fluent software to establish a pipeline erosion model for oil and gas carrying solid particles in the pipeline, and conduct sensitivity analysis of each pipeline erosion factor on pipeline wear. The established model is shown in the attached Figure 2 As shown, corresponding safety prevention and control measures before pipeline leakage can be formulated to provide guidance in pipeline design and actual safe operation of the project.

[0110] The specific steps include:

[0111] S401. In order to realistically simulate the erosion and wear that pipelines experience during oil and gas transportation, this embodiment is based on the actual operating conditions of the shale oil in-situ conversion oil and gas gathering and transportation system. Parameters such as pressure distribution, velocity distribution, sand particle movement trajectory, and wall erosion and wear distribution in the bend flow field are set to perform numerical simulation of pipeline erosion.

[0112] For example: set the pipeline as a curved pipe, including a front straight pipe section, a curved pipe section and a rear straight pipe section. The length of the front straight pipe and the rear straight pipe are both 1000mm, and the pipe diameter is 120mm; the inner diameter and outer diameter of the curved pipe are 156mm and 168mm respectively, and the bend-to-diameter ratio is 1.5; the content of the pipeline is a gas-solid two-phase fluid with a flow rate of 30m / s; the particle size of the sand is 300μm, and the mass flow rate of the sand is 0.0006kg / s.

[0113] S402: Use the ICEM CFD mesh generator to mesh the pipeline erosion model. The computational domain in this step refers to the entire spatial region used to define fluid flow and erosion analysis in numerical simulation. When meshing, the following settings can be preferably made:

[0114] The computational domain is divided into three blocks along the pipeline axis and uses progressive meshes, with the mesh being densest at the elbow.

[0115] The cross-sectional fluid calculation domain is divided into five blocks. A boundary layer and four-layer grid are set near the pipe wall. The first layer height and growth factor are set. For example, the first layer height is 0.05mm and the growth factor is 1.2 to capture the near-wall flow. The pipe grid is evenly distributed, divided into five grids in the radial direction, and the wall thickness remains unchanged.

[0116] The entire area is discretized into hexahedral elements, and independent grids are obtained through repeated calculations. The final number of grid elements is 2.7×10 5 .

[0117] S403, set the physical parameters and boundary conditions of the pipeline erosion model, the specific contents are as follows:

[0118] S403-1, select the Realize k-ε turbulence model in the Fluent software and set the turbulence intensity, for example, 4%;

[0119] In S403-2, the flow of the fluid in the pipeline is simplified to gas-solid two-phase flow, where the gas phase is methane and the solid phase is sand particles in the formation. Since the volume fraction of the solid phase during gas production is usually less than 5%, the gas phase is regarded as the continuous phase and the solid phase as the discrete phase;

[0120] S403-3, to truly restore the fluid state in the pipeline,

[0121] Pipe elbow angle simulation: Select four angles from 90° to 150° for slicing study;

[0122] Fluid temperature simulation Four temperatures were selected from 50° to 300° for study;

[0123] Fluid flow velocity simulation: Six speeds are selected from 5m / s to 30m / s for study;

[0124] Sand mass simulation was studied by selecting five mass flow rates from 0.0002 kg / s to 0.001 kg / s;

[0125] Five sand particle diameters ranging from 0.1 mm to 0.9 mm were selected for study.

[0126] Set the sand density and mass flow rate, for example, set the sand density to 1500kg / m³ and the mass flow rate to 0.5kg / s;

[0127] Seven sections were divided at the 90° elbow to simulate the pressure and velocity distribution in the pipeline, the trajectory of sand particles, and the distribution of wall erosion areas.

[0128] S403-4, set a velocity inlet at the inlet, and set the solid particle flow rate and fluid velocity, for example, both are set to 10m / s; set a pressure outlet at the outlet, and set the outlet pressure, for example, the pressure is set to 140MPa;

[0129] S403-5, set the specimen wall condition to rebound in the DPM option, define the impact angle function in a piecewise linear manner, see the table below for details; set the particle size function and velocity exponential function, for example, set the particle size function to a constant of 1.8×10⁻ 9 , the velocity exponential function is set to a constant of 2.6; the pressure-velocity coupling is solved using the SIMPLEC algorithm to calculate the pressure distribution in the manifold flow field, the particle trajectory and velocity distribution, and the erosion wear rate distribution of the manifold inner wall.

[0130] ,

[0131] In step S404, pressure-velocity coupling is performed using the pressure-based solver and the Simple algorithm. The initialization condition is set to Hybrid Initialization, and the total number of iterations is set to 1000. Initialization and solution are performed. Convergence is monitored using the residual monitoring graph. Convergence is determined when the residual values ​​of each physical variable meet the preset convergence criteria. The simulation results are then processed using the Fluent built-in post-processor. The specimen erosion rate is examined and an erosion rate cloud map and particle motion trajectory map are generated.

[0132] S5. Establish a pipeline leakage diffusion model for shale oil gathering and transportation pipelines in FLACS software. Set the leakage model at the shale oil gathering and transportation pipelines as a continuous leakage source model. Select a point in the area where the production wellhead pipeline and the cooling system are connected as the leakage point to conduct pipeline leakage diffusion analysis. The schematic diagram is shown in the attached figure. Figure 3 shown.

[0133] The reasons for making the above settings are:

[0134] ① Leakage diffusion models are categorized based on the stability of the diffusion results, which depends on the duration of the leakage source, into continuous leakage sources and transient leakage sources. Shale oil in-situ conversion oil and gas gathering and transportation systems use nickel-based alloy steel pipelines for production wellheads, which are highly safe and explosion-resistant, with few transient leaks. Therefore, pipeline leakage in this system is generally suitable for the continuous leakage source model.

[0135] ② The safety or risk level of the production wellhead pipeline is higher. Therefore, a point near the connection between the production wellhead pipeline and the cooling system is selected as the leakage point for leakage diffusion analysis.

[0136] The pipeline leakage diffusion model established in this step includes the buildings and open areas within the oil and gas production wells. Since this model is designed to simulate the diffusion of pipeline contents after a leak, the distances between buildings, particularly the distances between buildings and production wellheads, as well as the shape and area of ​​the open areas, can be set based on actual scenarios. This step will not further describe this modeling process.

[0137] S6: The accuracy and efficiency of the simulation results are closely related to the precision of the model meshing. Therefore, it is necessary to set up meshing for the pipeline leakage diffusion model established in step S5. Specifically, the following steps are included:

[0138] S601: Set a grid division area for the pipeline leakage diffusion model, and divide the grid division area into a core area, a boundary area, and a core encryption area.

[0139] S602: Perform primary mesh encryption on the core area and set the mesh size. Use the Stretch command in the Grid menu to extend the mesh boundary of the core area to obtain a complete mesh area. Subdivide the mesh of the core encrypted area according to the size of the leakage aperture, and then use Smooth processing on the mesh at the boundary of the core encrypted area.

[0140] After mesh subdivision, the mesh subdivision rules of the core encrypted area of ​​the FLACS software should be met: the area of ​​the subdivided mesh unit should not be greater than twice the area of ​​the leakage hole, and the leakage point should not be on the grid line.

[0141] S603: Perform mesh quality inspection and porosity verification on the mesh generated by the pipeline leakage diffusion model. The method is as follows:

[0142] Check the grid quality in the Grid information section of the Grid menu. The X, Y, and Z values ​​in the Max percentage diff column should not exceed 30.

[0143] Use the Flowvis module to check the porosity verification. Click on the geometric structure grid of the simulation area of ​​the pipeline leakage diffusion model. A porosity of 0 indicates solid blockage, 1 indicates no obstruction, and a porosity between 0 and 1 indicates partial blockage.

[0144] Steps S601-S603 are described as follows:

[0145] A. The core area includes major analytical equipment and buildings, such as wellhead pipelines, valves, and crude oil storage tanks;

[0146] B. The core encrypted area refers to the further subdivision of 3 to 5 grids near the pipeline leakage point based on the initial division to improve the accuracy of the leakage diffusion results near the leakage point;

[0147] C. Set the grid area size of the pipeline leakage diffusion model to 100m in length, 80m in width, and 25m in height, expressed in coordinate axes as: X, 0-100m; Y, 0-80m; Z, 0-25m;

[0148] D. Take the lower left corner (0, 0, 0) of the pipeline leakage diffusion model as the coordinate origin, and the leakage point coordinates as (13.125, 28.625, 4.625). In the Grid menu of the CASD module, divide the diffusion model grid as follows:

[0149] ① Perform primary refinement of the grid in the core area (X, 8-28m; Y, 20-40m; Z, 0-14m) with a grid size of 0.5m;

[0150] ② The mesh of the core reinforcement area (X, 12.5-13.5m; Y, 28-29m; Z, 4-5m) is subdivided according to the leakage aperture size of 120mm, and the mesh size is set to 0.25m. Then, the mesh at the boundary of the core reinforcement area is smoothed.

[0151] ③ Use the Stretch command to extend the boundary area to obtain a complete mesh area;

[0152] E. The number of grid divisions is 203770, the volume of the simulated grid area is 2000000 m³, and the blocked area is 19288.510 m³, indicating that the grid division is reasonable and feasible.

[0153] S7: Set the pipeline leakage output gas components in the pipeline leakage diffusion model based on the actual components of the output gas from the production wells, and set the component ratios of the output gas. For example, set the output gas components to methane, hydrogen sulfide, hydrogen, and carbon dioxide, with a volume ratio of 65.9% methane, 15.4% hydrogen sulfide, 10.1% hydrogen, and 8.6% carbon dioxide.

[0154] S8. Set the pipeline leakage aperture and leakage pressure in the pipeline leakage diffusion model. Also, set the plant environmental parameters based on the actual environment of the production well site, including but not limited to ambient temperature, ambient pressure, ambient wind conditions, atmospheric stability, and ground roughness. For example, set the ambient temperature to 20°C, the ambient pressure to 101.325 kPa, the atmospheric stability to F, and the ground roughness to 0.25 m.

[0155] Select appropriate or representative pipeline leakage apertures, leakage pressures, and environmental wind field conditions, perform simulations using the control variable method, characterize the impact of leakage diffusion, accurately predict and assess the impact range and degree of harm of leakage accidents, and provide a scientific basis for plant safety design, operation management, and emergency response, so as to formulate effective emergency response measures and safety protection strategies. Specific steps or methods include:

[0156] S801, Pipeline Leakage Aperture Selection

[0157] According to the ratio of the diameter of the pipeline leakage hole to the pipeline diameter The size of the pipeline model is divided into three types: When , it is a small hole pipe model; 0.2< When <0.6, it is a large-pore pipe model; When , it is the pipeline fracture model.

[0158] Based on the actual dimensions of the equipment, its accessories, and valves, and in accordance with AQ / T3046-2013, select leakage apertures representing small, medium, and large leakage conditions, such as 5mm, 25mm, and 100mm. Combined with the plant environmental parameters, calculate the leakage rates for different leakage apertures using the following steps:

[0159] Will" ” is compared with “(2 / (k+1))^(k / (k+1))” to determine the gas flow state in the pipeline:

[0160] like" ”≤“(2 / (k+1))^(k / (k+1))”, belongs to sonic flow, and the gas leakage rate is calculated as follows:

[0161] ,

[0162] like" ">"(2 / (k+1))^(k / (k+1))", belongs to subsonic flow, the gas leakage rate is calculated as follows:

[0163] ,

[0164] In the above formula,

[0165] is the critical pressure, Pa; p is the pressure inside the container, Pa; is the mass flow rate, kg / s; is the flow coefficient; A is the leakage hole area, m 2 ; M is the molar mass of the gas, kg / mol; k is the gas heat capacity ratio / isentropic index; is the universal gas constant, J / (mol⋅K); T is the gas temperature, K.

[0166] To improve efficiency, MATLAB is used to calculate the leakage rate of the leakage aperture.

[0167] The function files written are as follows:

[0168] function [ Q c ] = ex3_10( C d ,A,P,k,M,R,T )

[0169] Qc=C d *A*P*(k*M / R / T*(2 / (k+1))^((k+1) / (k-1)))^0.5;

[0170] end

[0171] The code to calculate the leak rate is as follows:

[0172] C=0.9; A=[0.0016, 0.0036, 0.0064, 0.0144]; P=1e6; k=1.315;

[0173] M=19.804e-3; R=8.314; T=273.15+300;

[0174] Q c =ex3_10( C d ,A,P,k,M,R,T ).

[0175] The calculation results are as follows:

[0176] Q c =1.97 4.43 7.87 17.7 kg / s

[0177] Therefore, the size of the leakage aperture is selected from three apertures ranging from 5 mm to 100 mm, and preferably 5 mm, 25 mm, and 100 mm.

[0178] S802, selection of environmental wind field conditions

[0179] Wind field conditions are usually expressed by wind direction and wind speed. For example, we can select wind direction of south wind and wind speeds of 0.1 m / s, 2 m / s, 5 m / s, and 10 m / s, i.e., wind field conditions of level 0 calm, level 2 light breeze, level 3 breeze, and level 5 strong wind; and wind field conditions of different wind directions such as wind speed of 5 m / s and westerly and northerly winds, to study the influence of different wind field conditions on shale oil and gas leakage and diffusion.

[0180] In this embodiment, the preferred wind speed simulation selects four wind speeds from 0.1 m / s to 10 m / s for research, namely 0.1 m / s, 2 m / s, 5 m / s, and 10 m / s.

[0181] Attachment Figure 6 A table showing the leakage diffusion conditions of production wellhead pipelines under different leakage apertures, leakage rates, leakage directions, and wind field conditions is shown.

[0182] S803, Pipeline Leakage Pressure Selection

[0183] The operating pressure has a certain influence on the shape, height, diffusion distance and concentration of the gas cloud during diffusion. According to the leakage diffusion conditions of shale oil and gas pipelines, leakage pressure simulation is selected. Three pressures are selected from 0.1MPa to 2MPa for research, with 0.2MPA, 1MPA and 2MPA being the preferred ones.

[0184] S9 uses the Leakage and Explosion Analysis module of FLACS software to analyze the leakage and diffusion patterns of shale oil and gas. This analysis module includes the CASD preprocessing module, the Run Manager run-time solution module, and the Flowvis post-processing module. Because the diffusion process of leakage from production wellhead pipelines is extremely complex, potentially involving pressure changes, energy exchange, and chemical reactions between gases, the following simplifications are made to the difficult-to-determine conditions and models in the production wellhead pipeline leakage and diffusion model to facilitate calculation and analysis:

[0185] ①The ambient pressure is constant at 101325Pa;

[0186] ②The pressure and leakage hole in the pipeline do not change, that is, the leakage rate remains constant;

[0187] ③ When leaking and spreading, shale oil and gas do not undergo energy or heat changes;

[0188] ④ Ignore the chemical reaction between leaked shale oil and gas and air.

[0189] In step S10, to ensure the accuracy of the pipeline leakage and diffusion model prediction, the Gaussian plume model is used to calculate the gas distribution concentration of the shale oil and gas pipeline leakage and diffusion, and the dangerous concentration range of the shale oil and gas pipeline leakage and diffusion is obtained. The concentration range is compared and confirmed with the FLACS analysis results obtained in step S9, which provides a basis for the subsequent safety protection measures.

[0190] The Gaussian plume model was chosen because it is a mathematical model used to simulate and predict the diffusion of pollutants in the atmosphere. It assumes that the pollution source is continuous and steady-state, that is, the gas is evenly mixed and the emission rate is constant, and is suitable for continuous leakage.

[0191] The Gaussian plume model expression recorded in this embodiment is as follows:

[0192] ,

[0193] ,

[0194] Where,

[0195] is the Gaussian plume model expression; q is the mass leakage rate, mg / s; is pi; u is wind speed, m / s; is the lateral diffusion coefficient; is the vertical diffusion coefficient; x is the downwind distance, m; y is the lateral distance, m; z is the concentration distribution on the ground; e is the base of the natural logarithm; is an exponential function, which means e The power of; H is the effective height of the pollution source, m.

[0196] S11, based on the simulation of steps S4-S10, quantitatively analyze the influencing factors before and after the leakage, and propose safety prevention and control measures for leakage risks.

Claims

1. A shale oil gathering and transportation pipeline leakage risk analysis and safety prevention and control method, characterized by: The following steps are involved: S1, establish an FTA model to analyze pipeline leakage accidents in shale oil gathering and transportation pipelines, and define pipeline erosion as the key risk factor causing pipeline leakage accidents; S2, using Bayesian networks to perform quantitative risk analysis on pipeline leakage and calculate the probability of pipeline leakage, including the following steps: S201, expressing the basic events in the FTA model as root nodes in the BN; S202, directly assigning the prior probability of the basic event in the FTA model to the corresponding root node in the BN as the prior probability of the root node; S203, expressing the intermediate event in the FTA model as a node in the BN, where the node flag and state values ​​are consistent with the output event of the logic gate in the FTA model; S204, connecting the nodes in the BN according to the relationship between the logic gates and basic events expressed in the FTA model, where the directions of the directed edges connecting the nodes correspond to the input-output relationships of the logic gates in the FTA model; S205, expressing the logical relationship of the logic gates in the FTA model as the conditional probability of the corresponding nodes in the BN; S206, setting the node relationships in the BN to be represented by directed arrows, with the arrows starting from the control event and pointing to the affected event; S207, using the expert scoring method and data review to obtain the probability of occurrence of the direct cause event in the FTA model, and using this probability as the prior probability of the parent node in the Bayesian network, thereby calculating the probability of each intermediate event and pipeline leakage through the Bayesian network; S208, determining the impact of basic events in the FTA model based on Bayesian network analysis, and determining basic events whose probabilities increase over time, and using their nodes as dynamic parent nodes; S209, setting the number of calculation time periods for the dynamic Bayesian network, setting the transfer speed according to the speed of change of the dynamic parent node probability, setting the transfer probability of the dynamic parent node according to expert experience, performing dynamic Bayesian network calculations, obtaining the time-varying trend of each node, converting the Bayesian network into a dynamic Bayesian network, and obtaining the time-varying trend of key events; S210, setting the number of calculation time periods of the Bayesian network to a common multiple of the dynamic parent node probability transfer speed; S3, establish a pipeline erosion model in Fluent software, including the following steps: S301, meshing the pipeline erosion model; S302, setting the simulation parameters of fluid erosion in the pipeline, including the pipeline elbow angle, fluid temperature, fluid flow rate, sand mass, and sand diameter; S303, setting the physical parameters and boundary conditions of the pipeline erosion model: setting the pipeline erosion model to a turbulence model, setting the flow of the fluid in the pipeline to gas-solid two-phase flow, setting the inlet of the pipeline erosion model to a velocity inlet, and setting the outlet of the pipeline erosion model to a pressure outlet; S304, setting a particle size function and a velocity index function of the fluid in the pipeline; In step S305, pressure-velocity coupling is initialized and solved using the pressure-based solver and the Simple algorithm. The pipeline erosion rate is viewed using Fluent software, and an erosion rate cloud map and a particle motion trajectory map are generated.

2. A shale oil gathering and transportation pipeline leakage risk analysis and safety control method according to claim 1, characterized in that: The following settings are made for step S302: For pipe elbow angle simulation, select four angles from 90° to 150°; for fluid temperature simulation, select four temperatures from 50° to 300°; for fluid flow rate simulation, select six speeds from 5m / s to 30m / s; for sand mass simulation, select five mass flow rates from 0.0002kg / s to 0.001kg / s; for sand diameter simulation, select five diameters from 0.1mm to 0.9mm; divide the cross section at the bend to simulate the pressure and velocity distribution in the pipeline, the sand movement trajectory, and the erosion area distribution on the pipeline wall.

3. The shale oil gathering and transportation pipeline leakage risk analysis and safety control method according to claim 1, characterized in that: In step S301, the grid division is set as follows: The computational domain along the pipeline axis is divided into three blocks and uses progressive grids; the cross-sectional fluid computational domain is divided into five blocks, with a boundary layer and four-layer grids set near the pipe wall. The first layer height and growth factor are set to capture near-wall flow. The pipeline grids are evenly distributed, divided into five grids in the radial direction, and the wall thickness remains unchanged; the hexahedral elements in the entire area are discretized to obtain independent grids.

4. The method for analyzing and preventing leakage risks in shale oil gathering and transportation pipelines according to claim 1, characterized in that: When establishing the FTA model, the pipeline leakage accident is taken as the top event and analyzed from three aspects: external factors, corrosion factors and pipeline defects; The external factors include human factors and natural factors; the corrosion factors include external corrosion, pipeline internal corrosion, and pipeline stress corrosion; the pipeline defects include inherent defects and operational defects.

5. The shale oil gathering and transportation pipeline leakage risk analysis and safety control method according to claim 1 is characterized by: The method also includes a diffusion analysis of the pipeline contents after the pipeline leaks, The following steps are involved: S4, establishing a pipeline leakage diffusion model for the shale oil gathering and transportation pipeline in the FLACS software, and setting the leakage model at the shale oil gathering and transportation pipeline as a continuous leakage source model; S5, performing grid division on the pipeline leakage diffusion model; S6, setting the pipeline leakage output gas components and component ratios in the pipeline leakage diffusion model; S7, setting the pipeline leakage aperture and leakage pressure in the pipeline leakage diffusion model; setting the plant environment parameters, including ambient temperature, ambient pressure, ambient wind speed, ambient wind direction, atmospheric stability, and ground roughness; S8, using the CASD pre-processing module, Run Manager run solution module, and Flowvis post-processing module of the FLACS software to analyze the shale oil and gas leakage diffusion law; S9. Based on the quantitative or qualitative analysis of the influencing factors before and after the pipeline leakage, formulate safety prevention and control measures for pipeline leakage risks.

6. A shale oil gathering and transportation pipeline leakage risk analysis and safety control method according to claim 5, characterized in that: The gas distribution concentration of shale oil and gas pipeline leakage and diffusion is verified and calculated by the Gaussian plume model, and the dangerous concentration range of shale oil and gas pipeline leakage and diffusion is obtained; the Gaussian plume model expression is as follows: ， Where, is the Gaussian plume model expression; q is the mass leakage rate, mg / s; is pi; u is wind speed, m / s; is the lateral diffusion coefficient; is the vertical diffusion coefficient; x is the downwind distance, m; y is the lateral distance, m; z is the concentration distribution on the ground; e is the base of the natural logarithm; H is the effective height of the pollution source, m.

7. The method for analyzing and preventing leakage risks in shale oil gathering and transportation pipelines according to claim 5, characterized in that: Set the mesh division area of ​​the pipeline leakage diffusion model and divide the mesh division area into a core area, a boundary area, and a core encryption area; perform primary encryption on the mesh of the core area and set the mesh size; extend the boundary area at the mesh boundary of the core area to obtain a complete mesh division area; subdivide the mesh of the core encryption area according to the size of the leakage aperture, and then use Smooth smoothing on the mesh at the boundary of the core encryption area.

8. The method for analyzing and preventing leakage risks in shale oil gathering and transportation pipelines according to claim 7, characterized in that: The mesh quality and porosity verification of the pipeline leakage diffusion model are performed as follows: Check the grid quality in the Grid information section of the Grid menu. The X, Y, and Z values ​​in the Max percentage diff column should not exceed 30. Use the Flowvis module to check the porosity verification. Click on the geometric structure grid of the simulation area of ​​the pipeline leakage diffusion model. A porosity of 0 indicates solid blockage, 1 indicates no obstruction, and a porosity between 0 and 1 indicates partial blockage.

9. The method for analyzing and preventing leakage risks in shale oil gathering and transportation pipelines according to claim 5, characterized in that: Select the pipe leak diameter by following the steps below: S701, based on the ratio of the pipeline leakage hole diameter to the pipeline diameter The size of the pipeline model is divided into three types: When , it is a small hole pipe model; 0.2< When <0.6, it is a large-pore pipe model; When , it is the pipeline fracture model; S702: Calculate the leakage rates of the three different leakage apertures in step S701 through the following steps, and select the pipeline leakage aperture according to the leakage rates: Will" ” is compared with "(2 / (k+1))^(k / (k+1))" to determine the gas flow state in the pipeline: like" ”≤"(2 / (k+1))^(k / (k+1))", belongs to sonic flow, the gas leakage rate is calculated as follows: , like" ">"(2 / (k+1))^(k / (k+1))", belongs to subsonic flow, and the gas leakage rate is calculated as follows: , In the above formula, is the critical pressure, Pa; p is the pressure inside the container, Pa; is the mass flow rate, kg / s; is the flow coefficient; A is the leakage hole area, m 2 ; M is the molar mass of the gas, kg / mol; k is the gas heat capacity ratio / isentropic index; is the universal gas constant, J / (mol⋅K); T is the gas temperature, K.

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