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

Abstract

The invention provides a shale oil gathering and transportation pipeline leakage risk analysis and safety prevention and control method which comprises the following steps: establishing an FTA model to analyze a pipeline leakage accident of a shale oil gathering and transportation pipeline, and defining pipeline erosion as a key risk factor causing the pipeline leakage accident; performing quantitative risk analysis on pipeline leakage by using a Bayesian network, and calculating the probability of pipeline leakage; establishing a pipeline erosion model in Fluent software, and simulating reasons of pipeline leakage risks; establishing a pipeline leakage diffusion model of the shale oil gathering and transportation pipeline in FLACS software; performing grid division on the pipeline leakage diffusion model; setting pipeline leakage output gas components and component proportions in the pipeline leakage diffusion model; setting a pipeline leakage aperture and leakage pressure in the pipeline leakage diffusion model; setting factory environment parameters; analyzing a shale oil and gas leakage diffusion rule by using FLACS software; and formulating pipeline leakage risk safety prevention and control measures based on quantitative analysis of influence 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 particularly to a method for analyzing the leakage risk of a shale oil gathering and transportation pipeline and safety prevention and control. Background Art

[0002] China has rich shale oil reserves, most of which are medium- to low-maturity continental shale oil. For the exploitation of such shale oil, the in-situ conversion technology is the key. This technology injects heat into the reservoir to promote the transformation of unsaturated organic matter in the rock mass into saturated hydrocarbons, and extracts oil and gas through production wells. The oil and gas produced by the in-situ conversion technology are characterized by high temperature and high sulfur. The temperature of the produced substances is above 300°C, which is transported through pipelines to a cooling and separation system, and undergoes multi-stage cooling and desulfurization treatment to finally refine the finished oil.

[0003] In the in-situ conversion process, the pipeline plays a key role in transporting semi-finished and finished products. Corrosion, external force damage, and human operation errors can all cause pipeline leakage. Since the shale oil gathering process is usually in a high-temperature operation state, and the contents transported by the pipeline are usually volatile and corrosive gases or liquids, once a pipeline leakage accident occurs, it will not only cause equipment damage and affect normal production operations, but also cause environmental pollution due to the diffusion of pipeline contents and affect human health. Therefore, an analysis method and a prevention and control method for pipeline leakage risks should be given to carry out early prevention and post-accident treatment, strengthen safety protection measures and safety management, prevent potential accidents from occurring, and ensure the safe transportation and effective separation of shale oil. Summary of the Invention

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

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

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

[0007] S2, use a Bayesian network to conduct a quantitative risk analysis of pipeline leakage and calculate the probability of pipeline leakage;

[0008] S3, establish a pipeline erosion model in Fluent software to simulate the reasons for the occurrence of pipeline leakage risks, including the following steps:

[0009] S301, perform grid division on the pipeline erosion model;

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

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

[0012] S304, set the fluid particle size function and velocity exponent function in the pipeline;

[0013] S305, perform pressure-velocity coupling using a pressure-based solver and the Simple algorithm, initialize and solve; view the pipeline erosion rate through Fluent software, and generate an erosion rate contour map and a particle motion trajectory map.

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

[0015] Four angles are selected for the pipeline elbow angle simulation from 90° to 150°; four temperatures are selected for the fluid temperature simulation from 50° to 300°; six velocities are selected for the fluid velocity simulation from 5 m / s to 30 m / s; five mass flows are selected for the sand particle mass simulation from 0.0002 kg / s to 0.001 kg / s; five diameters are selected for the sand particle diameter simulation from 0.1 mm to 0.9 mm; seven sections are divided at the 90° elbow to simulate the pressure and velocity distributions in the pipeline, the sand particle motion trajectory, and the wall erosion area distribution.

[0016] Further, in step S301, the following settings are made for mesh generation: the computational domain along the pipeline axis is divided into three blocks and progressive meshes are used; the cross-sectional fluid computational domain is divided into five blocks, a boundary layer and four layers of meshes are set near the pipe wall, the first layer height and growth factor are set to capture the near-wall flow, the pipeline meshes are evenly distributed, five meshes are divided radially and the wall thickness remains unchanged; the entire region is discretized into hexahedral elements, and independent meshes are obtained through repeated calculations.

[0017] Further, when establishing the FTA model, take the pipeline leakage accident as the top event and analyze it 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, internal pipeline corrosion, and pipeline stress corrosion; the pipeline defects include inherent defects and operation defects.

[0018] Further, in step S2, using the Bayesian network for quantitative risk analysis of pipeline leakage includes the following steps:

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

[0020] S202, Directly assign the prior probabilities of the basic events in the FTA model to the corresponding root nodes in the BN as the prior probabilities of the root nodes;

[0021] S203, Express the intermediate events in the FTA model as a node in the BN, with the node flag and state values being the same as the output events of the logic gates in the FTA model;

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

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

[0024] S206, Set that the node relationships in the BN are all represented by directed arrows, with the arrows starting from the control events and pointing to the affected events;

[0025] S207, Obtain the occurrence probabilities of the direct cause events in the FTA model through the expert scoring method and referring to data, and use this probability as the prior probability of the parent nodes in the Bayesian network. Thus, calculate the probabilities of each intermediate event and pipeline leakage through the Bayesian network.

[0026] Furthermore, transform the Bayesian network in step S2 into a dynamic Bayesian network, specifically including the following steps:

[0027] S208, Determine the influence magnitudes of the basic events in the FTA model according to the Bayesian network analysis, and determine the basic events whose probabilities increase with time, and use their nodes as dynamic parent nodes;

[0028] S209, Set the number of calculation time periods of the dynamic Bayesian network, set the transfer speed according to the change rate of the probabilities of the dynamic parent nodes, set the transfer probabilities of the dynamic parent nodes according to expert experience, perform dynamic Bayesian network calculation, obtain the trend of each node changing with time, transform the Bayesian network into a dynamic Bayesian network, and obtain the trend of key events changing with time;

[0029] S210, Set the number of calculation time periods of the Bayesian network as a common multiple of the probability transfer speeds of the dynamic parent nodes.

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

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

[0032] S5. Conduct mesh generation for the pipeline leakage and diffusion model;

[0033] S6. Set the gas components and their proportions of the pipeline leakage output gas in the pipeline leakage and diffusion model;

[0034] S7. Set the pipeline leakage aperture and leakage pressure in the pipeline leakage and diffusion model; Set the plant area environmental parameters, including environmental temperature, environmental pressure, environmental wind speed, environmental wind direction, atmospheric stability, and ground roughness;

[0035] S8. Use the CASD preprocessing module, Run Manager operation and solution module, and Flowvis postprocessing module of the FLACS software to analyze the leakage and diffusion law of shale oil and gas;

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

[0037] Furthermore, verify and calculate the gas distribution concentration of shale oil and gas pipeline leakage and diffusion through the Gaussian plume model, and obtain the dangerous concentration range of shale oil and gas pipeline leakage and diffusion; The expression of the Gaussian plume model is as follows:

[0038]

[0039] In the formula,

[0040] C(x,y,z) is the expression of the Gaussian plume model; q is the mass leakage rate, mg / s; π is the pi; u is the wind speed, m / s; σ y is the lateral diffusion coefficient; σ z is the vertical diffusion coefficient; x is the downwind distance, m; y is the lateral distance, m; z is the ground concentration distribution; e is the base of the natural logarithm; exp is the exponential function, representing the power of e; H is the effective height of the pollution source, m.

[0041] Furthermore, set the mesh generation area of the pipeline leakage and diffusion model, and divide the mesh generation area into a core area, a boundary area, and a core encryption area;

[0042] Conduct primary encryption on the meshes in the core area and set the mesh size; The boundary area extends at the mesh boundary of the core area to obtain a complete divided mesh area; Subdivide the meshes in the core encryption area according to the size of the leakage aperture, and then perform Smooth smoothing on the meshes at the boundary of the core encryption area.

[0043] Furthermore, the grid of the pipeline leakage diffusion model is divided for grid quality detection and porosity verification, and the method is as follows:

[0044] View the grid quality detection at Grid information in the Grid menu. The X, Y, and Z values in the Max percentage diff column should not exceed 30;

[0045] View the porosity verification through the Flowvis module. 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 value between 0 and 1 indicates partial blockage.

[0046] Furthermore, select the pipeline leakage aperture through the following steps:

[0047] S701, divide the pipeline model in the pipeline leakage diffusion model into three types according to the ratio of the pipeline leakage hole diameter to the pipeline diameter When, it is a small-hole pipeline model; When, it is a large-hole pipeline model; When, it is a pipeline fracture model; When, it is a pipeline fracture model;

[0048] 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 rate:

[0049] Compare "P a / P" with "(2 / (k + 1))^(k / (k + 1))" to judge the gas flow state in the pipeline:

[0050] If "P a / P" ≤ "(2 / (k + 1))^(k / (k + 1))", it belongs to laminar flow, and calculate the gas leakage rate through the following:

[0051]

[0052] If "P a / P" > "(2 / (k + 1))^(k / (k + 1))", it belongs to turbulent flow, and calculate the gas leakage rate through the following:

[0053]

[0054] In the above formulas,

[0055] P a is the critical pressure, Pa; P is the pressure in the container, Pa; q m is the mass flow rate, kg / s; C dC 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 specific heat ratio of the gas / isentropic exponent; R g is the universal gas constant, J / (mol·K); T is the gas temperature, K.

[0056] Furthermore, MATLAB is used to calculate the leakage rate of the leakage aperture,

[0057] and the function file written is as follows:

[0058] function[Q c =ex3_10(C d ,A,P,k,M,R,T)

[0059] Qc=C d *A*P*(k*M / R / T*(2 / (k + 1))^((k + 1) / (k - 1)))^0.5;

[0060] end

[0061] The code for calculating the leakage rate is as follows:

[0062] C = 0.9; A = [0.0016, 0.0036, 0.0064, 0.0144]; P = 1e6; k = 1.315;

[0063] M = 19.804e-3; R = 8.314; T = 273.15 + 300;

[0064] Q c = ex3_10(C d ,A,P,k,M,R,T).

[0065] Based on the above technical solutions, the present invention has the following beneficial effects.

[0066] 1. Establish a pipeline leakage FTA model, which can accurately and comprehensively find the direct cause events and intermediate events causing pipeline leakage, establish the connection between each event, and thus search for and determine the risk factors leading to pipeline leakage.

[0067] 2. Through quantitative risk analysis of pipeline leakage by Bayesian network and converting the Bayesian network into a dynamic Bayesian network, the probability of pipeline leakage can be further accurately calculated, which is convenient for managers and operators to make corresponding safety prevention and control measures.

[0068] 3. Based on the fluid mechanics theory and the key risk factors causing pipeline leakage, a pipeline erosion model for oil and gas carrying solid particles in the pipeline is established, which can analyze the sensitivity of various pipeline erosion factors to pipeline wear. Accordingly, corresponding safety prevention and control measures before pipeline leakage can be formulated to provide guidance for pipeline design and actual safe operation in engineering.

[0069] 4. A pipeline leakage diffusion model for shale oil gathering and transportation pipelines is established, and the leakage model at the shale oil gathering and transportation pipeline is set as a continuous leakage source model, which can more realistically simulate the pipeline leakage at the production wellhead. Appropriate or representative pipeline leakage aperture, leakage pressure, and environmental wind field conditions are selected in the pipeline leakage diffusion model, and simulations are carried out by the method of controlling variables to characterize the influence of leakage diffusion, so as to accurately predict and evaluate the influence range and harm degree of leakage accidents, provide a scientific basis for the safety design, operation management, and emergency response of the plant area, and thus formulate effective emergency response measures and safety protection strategies.

[0070] 5. The Gaussian plume model is used to calculate the gas distribution concentration of shale oil and gas pipeline leakage diffusion, and the dangerous concentration range of shale oil and gas pipeline leakage diffusion is obtained. By comparing and confirming with the FLACS analysis results, the accuracy of the pipeline leakage diffusion model prediction can be ensured, providing a basis for subsequent proposed safety protection measures. Description of the Drawings

[0071] Figure 1 : Schematic diagram of the pipeline leakage FTA model established in the exemplary embodiment;

[0072] Figure 2 : Figure 1 Enlarged view of location A of

[0073] Figure 3 : Figure 1 Enlarged view of location B of

[0074] Figure 4 : Schematic diagram of the pipeline erosion model established in the exemplary embodiment;

[0075] Figure 5 : Schematic diagram of the pipeline leakage diffusion model established in the exemplary embodiment;

[0076] Figure 6 : Schematic diagram of the risk analysis and safety prevention and control method process in the exemplary embodiment;

[0077] Figure 7 : Schematic diagram showing the pipeline leakage diffusion conditions at the production wellhead under different leakage apertures, leakage rates, leakage directions, and wind field conditions in the exemplary embodiment. Detailed Description of the Invention

[0078] It should be noted that:

[0079] 1. In the specification and claims, certain terms are used to refer to specific components. Those skilled in the art should understand that technicians may use different nouns to refer to the same component. Therefore, the specification and claims do not distinguish components by the difference in nouns, but by the difference in the functions of the components as the criterion for distinction.

[0080] 2. Unless otherwise defined, the technical terms or scientific terms used in this disclosure shall have the ordinary meanings understood by those of ordinary skill in the art to which this disclosure pertains.

[0081] As shown in the Figure 1 - appended Figure 7 drawing, this embodiment describes a method for analyzing the leakage risk and safety prevention and control of shale oil gathering and transportation pipelines, including the following steps:

[0082] S1. Establish a FTA model for pipeline leakage to analyze the leakage accidents of shale oil gathering and transportation pipelines, and obtain the key risk factors causing pipeline leakage accidents.

[0083] When establishing the FTA model, in order to comprehensively cover the inducing factors leading to pipeline leakage accidents, this embodiment takes the pipeline leakage accident as the top event and conducts a hierarchical analysis from top to bottom in three aspects: external factors, corrosion factors, and pipeline defects to find the direct cause events and intermediate events causing pipeline leakage, and establish the connections between each event, so as to search for and determine the risk factors causing pipeline leakage.

[0084] Among them,

[0085] Set the inducing factors for pipeline leakage accidents caused by external factors as: human factors, natural factors;

[0086] Set the inducing factors for pipeline leakage accidents caused by corrosion factors as: external corrosion, internal pipeline corrosion, pipeline stress corrosion;

[0087] Set the inducing factors for pipeline leakage accidents caused by pipeline defects as: inherent defects, operation defects;

[0088] Set events such as operation errors, natural disasters, corrosion perforation, and structural defects as the cause events leading to pipeline leakage accidents.

[0089] According to the above content, establish as shown in the appended Figures 1-3The pipeline leakage FTA model shown in the figure can be used to determine that the key risk factor causing pipeline leakage accidents is internal corrosion of the pipeline. The main influencing factor of internal corrosion of the pipeline is pipeline erosion, and the causes of pipeline erosion include but are not limited to: pipeline elbow angle, flow medium, pipeline wall, and particles. Among them, flow medium factors include fluid temperature, fluid flow rate, etc., and particle factors include sand quality, sand diameter, etc.

[0090] S2, based on the pipeline leakage FTA model, use the Bayesian network to perform quantitative risk analysis on pipeline leakage and calculate the probability of pipeline leakage. For ease of description, the pipeline leakage FTA model is referred to as the FTA model in this step; the Bayesian network is referred to as BN; the basic event in the FTA model refers to the most fundamental cause of the pipeline leakage accident, such as corrosion perforation, valve leakage, etc.

[0091] The specific steps include:

[0092] S201, all basic events in the FTA model are expressed as root nodes in the BN. If the root node appears multiple times, it only needs to be expressed as one root node in the BN;

[0093] 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;

[0094] S203, expressing 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;

[0095] S204, connecting the nodes in the BN according to the relationship between the logic gates and the basic events expressed in the FTA model, and the direction of the directed edge connecting the nodes corresponds to the input-output relationship of the logic gates in the FTA model;

[0096] S205, expressing the logical relationship of the logic gates in the FTA model as a conditional probability table of the corresponding nodes in the BN.

[0097] 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.

[0098] The probability of occurrence of direct cause events is obtained through expert scoring and reference, 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. Among them, the fuzzy triangular number algorithm is used for mathematical transformation of the expert scoring language results.

[0099] S3. To calculate the probability of pipeline leakage more accurately, the Bayesian network in step S2 can be transformed into a dynamic Bayesian network. The key events in this step refer to the basic events with significantly increasing probabilities over time and the basic events with greater impacts.

[0100] Specifically, it includes the following steps:

[0101] S301. Determine the influence size of the basic events according to the Bayesian network analysis, and determine the basic events with probabilities increasing over time. Take their nodes as dynamic parent nodes.

[0102] S302. Set the number of calculation time periods of the dynamic Bayesian network. Set the transfer speed according to the change rate of the probabilities of the dynamic parent nodes and set the transfer probabilities of the dynamic parent nodes according to expert experience. Conduct the dynamic Bayesian network calculation to obtain the changing trends of each node over time, transform the Bayesian network into a dynamic Bayesian network, and obtain the changing trends of the key events over time.

[0103] S303. Set the number of calculation time periods of the Bayesian network as the common multiple of the probability transfer speeds of the dynamic parent nodes. The probability transfer speed of the dynamic parent nodes is expressed in terms of the number of time periods and is set to four changing speeds:

[0104] For the nodes with a very fast probability growth rate, set the probability to change once every 1 time period.

[0105] For the nodes with a fast growth rate, the probability transfer speed is to change once every 2 nodes.

[0106] For the nodes with a slow growth rate, set the transfer probability to change once every 3 nodes.

[0107] For the nodes with a very slow growth rate, set the transfer probability to change once every 5 nodes.

[0108] S4. Based on the fluid mechanics theory and the key risk factors for pipeline leakage determined in step S1, use Fluent software to establish a pipeline erosion model for the erosion of oil and gas carrying solid particles in the pipeline, and conduct a sensitivity analysis of each pipeline erosion factor on pipeline wear. The established model is as shown in the appendix Figure 4 Thus, corresponding safety prevention and control measures before pipeline leakage can be formulated to provide guidance for pipeline design and actual safe operation in engineering.

[0109] Specifically, it includes the following steps:

[0110] S401. In order to truly simulate the erosion and wear suffered by the pipeline during the transportation of oil and gas, in this embodiment, based on the actual working conditions of the in-situ conversion oil and gas gathering and transportation system of shale oil, parameters such as the pressure distribution, velocity distribution, sand particle movement trajectory, and wall erosion and wear distribution in the elbow flow field are set to conduct numerical simulation of pipeline erosion.

[0111] For example: Set the pipeline as a bent pipe, including a front straight pipe section, a bent pipe section, and a rear straight pipe section. The lengths of the front straight pipe and the rear straight pipe are both 1000 mm, and the pipe diameter is 120 mm; the inner diameter and outer diameter of the bent pipe are 156 mm and 168 mm respectively, and the bend diameter ratio is 1.5; the content in the pipeline is a gas-solid two-phase fluid, and the flow velocity is 30 m / s; the sand particle size is 300 μm, and the sand particle mass flow rate is 0.0006 kg / s.

[0112] 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:

[0113] The computational domain along the pipeline axis is divided into three blocks and progressive meshes are used. The meshes at the elbow are the densest;

[0114] The cross-sectional fluid computational domain is divided into five blocks. A boundary layer and four layers of meshes are set near the pipe wall, and the first layer height and growth factor are set. For example, the first layer height is 0.05 mm and the growth factor is 1.2 to capture the near-wall flow. The pipeline meshes are evenly distributed, with five meshes in the radial direction and the wall thickness remaining unchanged;

[0115] The entire region is discretized into hexahedral elements. After repeated calculations, an independent mesh is obtained, and the final number of mesh elements is 2.7×105.

[0116] S403. Set the physical parameters and boundary conditions of the pipeline erosion model. The specific content is as follows:

[0117] S403-1. Select the Realize k-ε turbulence model in the Fluent software and set the turbulence intensity, for example, 4%;

[0118] S403-2. The fluid flow in the pipeline is simplified to a gas-solid two-phase flow, where the gas phase is methane and the solid phase is sand grains in the formation. Since the volume fraction of the solid phase is usually less than 5% during the gas production process, the gas phase is regarded as the continuous phase and the solid phase is regarded as the discrete phase;

[0119] S403-3. To truly restore the fluid state in the pipeline,

[0120] Four angles are selected from 90° to 150° for slice research in the simulation of the pipeline elbow angle;

[0121] Four temperatures are selected from 50° to 300° for research in the fluid temperature simulation;

[0122] Six velocities are selected from 5 m / s to 30 m / s for research in the fluid flow velocity simulation;

[0123] The sand particle mass simulation selects 5 mass flow rates for research from 0.0002 kg / s to 0.001 kg / s;

[0124] The sand particle diameter simulation selects 5 diameters for research from 0.1 mm to 0.9 mm.

[0125] Set the sand particle density and mass flow rate. For example, set the sand particle density to 1500 kg / m 3 , and the mass flow rate to 0.5 kg / s;

[0126] Divide 7 cross-sections at the 90° elbow, and thus simulate the pressure and velocity distributions inside the pipeline, the sand particle movement trajectories, and the wall erosion area distribution;

[0127] S403-4, set a velocity inlet at the inlet, and set the solid particle flow velocity and the fluid velocity. For example, set both to 10 m / s; set a pressure outlet at the outlet, and set the outlet pressure. For example, set the pressure to 140 MPa;

[0128] S403-5, set the wall condition of the specimen to rebound in the DPM option, define the impact angle function in a piecewise linear manner, see the following table for details; set the particle size function and the velocity exponent function. For example, set the particle size function to a constant of 1.8×10 -9 , and set the velocity exponent function to a constant of 2.6; use the SIMPLEC solution algorithm for pressure-velocity coupling to calculate the pressure distribution in the pipe manifold flow field, the particle trajectories and velocity distributions, and the erosion wear rate distribution on the inner wall of the pipe manifold.

[0129]

[0130] S404, use a pressure-based solver and the Simple algorithm for pressure-velocity coupling, set the initialization condition to Hybrid Initialization, set the total number of iterations Number ofIterations to 1000, initialize and solve. Observe the calculation convergence situation through the residual monitor diagram. When the residual values of each physical variable reach the preset convergence standard, it is determined that the calculation converges. Then use the built-in post-processor in Fluent to process the simulation results, view the erosion rate of the specimen, and generate an erosion rate contour map and a particle movement trajectory map.

[0131] S5, establish a pipeline leakage diffusion model of the shale oil gathering and transportation pipeline in the FLACS software, set the leakage model at the shale oil gathering and transportation pipeline to a continuous leakage source model, select a certain point in the area of the connection between the production wellhead pipeline and the cooling system as the leakage point to conduct pipeline leakage diffusion analysis, and the schematic diagram is as shown in the appendix Figure 5 as shown.

[0132] The reason for making the above settings is;

[0133] ① The leakage diffusion model is classified according to the stability of the diffusion result and depends on the leakage time of the leakage source. It is divided into continuous leakage sources and instantaneous leakage sources. The production wellhead pipeline of the in-situ conversion oil and gas gathering and transportation system for shale oil uses nickel-based alloy steel pipelines, which have high safety and anti-explosion performance and few instantaneous leakage situations. Therefore, the pipeline leakage of this system generally applies to the continuous leakage source model;

[0134] ② The safety or risk level at the production wellhead pipeline is relatively high. Therefore, a certain point near the connection between the production wellhead pipeline and the cooling system is selected as the leakage point for leakage diffusion analysis.

[0135] The pipeline leakage diffusion model established in this step includes buildings and open spaces in the factory area where the oil and gas production wells are located. Since the establishment of this model is to simulate the diffusion state of the pipeline contents after pipeline leakage, the distances between the buildings in this model, especially the distance between the building and the production wellhead, as well as the shape and area of the open space, can all be set with reference to the actual scenario. The modeling process is not elaborated in this step.

[0136] S6. The accuracy and operation efficiency of the simulation results are closely related to the precision of the model grid division. Therefore, it is necessary to set the grid division for the pipeline leakage diffusion model established in step S5, which specifically includes the following steps:

[0137] S601. Set the grid division area of the pipeline leakage diffusion model and divide the grid division area into a core area, a boundary area, and a core encryption area.

[0138] S602. Primarily encrypt the grids in the core area and set the grid size; for the boundary area, use the Stretch command in the Grid menu to extend at the grid boundary of the core area to obtain a complete divided grid area; subdivide the grids in the core encryption area according to the size of the leakage aperture, and then perform Smooth smoothing on the grids at the boundary of the core encryption area.

[0139] After grid subdivision, it should meet the grid subdivision rules for the core encryption area of the FLACS software: the area of the subdivided grid cells is not greater than 2 times the area of the leakage hole, and the leakage point is not on the grid line.

[0140] S603. Perform grid quality detection and porosity verification on the grids divided for the pipeline leakage diffusion model. The method is as follows:

[0141] View the grid quality detection at Grid information in the Grid menu. The X, Y, and Z values in the Max percentage diff column should not exceed 30;

[0142] Verify the porosity through the Flowvis module. Click on the geometric structure grid of the simulation area of the pipeline leakage diffusion model. A porosity of 0 indicates an entity blockage, 1 indicates no obstruction, and a value between 0 and 1 indicates partial blockage.

[0143] The following is an example of steps S601 - S603:

[0144] A. The core area contains the main analysis equipment and buildings, such as: wellhead pipelines, valves, and crude oil storage tanks;

[0145] B. The core encryption area refers to re - subdividing 3 to 5 grids near the pipeline leakage point on the basis of the preliminary division to improve the accuracy of the leakage diffusion result near the leakage point;

[0146] C. Set the size of the grid division area of the pipeline leakage diffusion model to be 100m in length, 80m in width, and 25m in height. Expressed in terms of the coordinate axis: X, 0 - 100m; Y, 0 - 80m; Z, 0 - 25m;

[0147] D. Taking 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), divide the diffusion model grid in the CASD module Grid menu as follows:

[0148] ① Primarily encrypt the grids in the core area (X, 8 - 28m; Y, 20 - 40m; Z, 0 - 14m), with a grid size of 0.5m;

[0149] ② Sub - divide the grids in the core encryption area (X, 12.5 - 13.5m; Y, 28 - 29m; Z, 4 - 5m) according to the size of the leakage aperture of 120mm, set the grid size to 0.25m, and then perform Smooth smoothing on the grids at the boundary of the core encryption area;

[0150] ③ After extending the boundary area using the Stretch command, obtain the complete divided grid area;

[0151] E. The number of grid divisions is 203770, the volume of the simulated grid area is 2000000m 3 , and the blocked area is 19288.510m 3 , indicating that the grid division is reasonable and feasible.

[0152] S7. According to the actual components of the produced gas from the production well, set the components of the pipeline leakage produced gas in the pipeline leakage diffusion model and set the component ratio of the produced gas. For example, set the produced gas components to methane, hydrogen sulfide, hydrogen, and carbon dioxide, with the volume ratios being 65.9% for methane, 15.4% for hydrogen sulfide, 10.1% for hydrogen, and 8.6% for carbon dioxide.

[0153] S8. Set the pipeline leakage aperture and leakage pressure in the pipeline leakage diffusion model; and set the plant environment parameters according to the actual environment of the plant where the production well is located, including but not limited to environmental temperature, environmental pressure, environmental wind field conditions, atmospheric stability, and ground roughness. For example: set the environmental temperature to 20 °C, the environmental pressure to 101.325 kPa, the atmospheric stability to F, and the ground roughness to 0.25 m.

[0154] Select appropriate or representative pipeline leakage aperture, leakage pressure, and environmental wind field conditions, and conduct simulations through the method of controlling variables to characterize the impact of leakage diffusion, accurately predict and evaluate the impact range and hazard degree of leakage accidents, and provide a scientific basis for the safety design, operation management, and emergency response of the plant, so as to formulate effective emergency response measures and safety protection strategies. Specifically, it includes the following steps or methods:

[0155] S801. Selection of pipeline leakage aperture

[0156] According to the ratio of the pipeline leakage hole diameter to the pipeline diameter The pipeline models in the pipeline leakage diffusion model are divided into three types: When, it is a small-hole pipeline model; When, it is a large-hole pipeline model; When, it is a pipeline fracture model.

[0157] According to the actual sizes of the equipment and its accessories and valves, and based on AQ / T 3046-2013, select leakage apertures representing small, medium, and large leakage conditions, such as 5 mm, 25 mm, and 100 mm, and combine with the plant environment parameters to calculate the leakage rates of different leakage apertures through the following steps:

[0158] Compare "P a / P" with "(2 / (k + 1))^(k / (k + 1))" to judge the gas flow state in the pipeline:

[0159] If "P a / P" ≤ "(2 / (k + 1))^(k / (k + 1))", it belongs to laminar flow, and calculate the gas leakage rate through the following:

[0160]

[0161] If "P a / P" > "(2 / (k + 1))^(k / (k + 1))", it belongs to turbulent flow, and calculate the gas leakage rate through the following:

[0162]

[0163] In the above formulas,

[0164] P a is the critical pressure, Pa; P is the pressure inside the container, Pa; q m is the mass flow rate, kg / s; C d 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 specific heat ratio / isentropic exponent of the gas; R g is the universal gas constant, J / (mol·K); T is the gas temperature, K.

[0165] To improve efficiency, MATLAB is used to calculate the leakage rate of the leakage aperture,

[0166] and the function file written is as follows:

[0167] function[Q c =ex3_10(C d ,A,P,k,M,R,T)

[0168] Qc=C d *A*P*(k*M / R / T*(2 / (k + 1))^((k + 1) / (k - 1)))^0.5;

[0169] end

[0170] The code for calculating the leakage rate is as follows:

[0171] C = 0.9; A = [0.0016, 0.0036, 0.0064, 0.0144]; P = 1e6; k = 1.315;

[0172] M = 19.804e - 3; R = 8.314; T = 273.15 + 300;

[0173] Q c =ex3_10(C d ,A,P,k,M,R,T).

[0174] The calculation results are as follows:

[0175] Q c =1.97 4.43 7.87 17.7kg / s

[0176] Therefore, three apertures are selected from the leakage aperture sizes ranging from 5 mm to 100 mm, and are preferably 5 mm, 25 mm, and 100 mm.

[0177] S802, selection of environmental wind field conditions

[0178] Wind field conditions are usually represented by wind direction and wind speed. The wind speed can be selected according to the national standard "Wind Force Scale" issued in June 2012. For example, the wind direction can be selected as south wind, and the wind speeds can be 0.1 m / s, 2 m / s, 5 m / s, 10 m / s, that is, the wind field conditions of calm wind at level 0, gentle breeze at level 2, light breeze at level 3, and fresh breeze at level 5; and the wind field conditions with a wind speed of 5 m / s and different wind directions such as west wind and north wind can be selected to study the influence law of different wind field conditions on the leakage and diffusion of shale oil and gas.

[0179] In this embodiment, it is preferably to select four wind speeds from 0.1 m / s to 10 m / s for research, which are 0.1 m / s, 2 m / s, 5 m / s, and 10 m / s respectively.

[0180] Appendix Figure 6 shows the leakage and diffusion working condition table of the production wellhead pipeline under different leakage apertures, leakage rates, leakage directions, and wind field conditions.

[0181] S803, selection of pipeline leakage pressure

[0182] The operating pressure has a certain influence on the shape, height, diffusion distance, and concentration of the gas cloud during gas cloud diffusion. According to the leakage and diffusion working conditions of the shale oil and gas pipeline, the leakage pressure simulation is selected, and three pressures are selected from 0.1 MPa to 2 MPa for research, preferably 0.2 MPA, 1 MPA, and 2 MPA.

[0183] S9, use the leakage and explosion analysis modules of FLACS software to analyze the leakage and diffusion law of shale oil and gas. The analysis modules include: CASD preprocessing module, Run Manager operation and solution module, and Flowvis post-processing module. Since the process of leakage and diffusion at the production wellhead pipeline is extremely complex, there may be pressure changes, energy exchange, and chemical reactions between gases during leakage and diffusion; for the convenience of calculation and analysis, the following simplifications are made for the conditions and models that are difficult to determine in the leakage and diffusion model of the production wellhead pipeline:

[0184] ① The ambient pressure is kept constant at 101325 Pa;

[0185] ② The pressure inside the pipeline and the leakage hole do not change, that is, the leakage rate remains constant;

[0186] ③ During leakage and diffusion, there are no energy and heat changes in shale oil and gas;

[0187] ④ Ignore the chemical reaction between the leaked shale oil and gas and air.

[0188] S10. To ensure the accuracy of the prediction of the pipeline leakage diffusion model, the Gaussian plume model is used to calculate the gas distribution concentration of the shale oil and gas pipeline leakage diffusion, obtain the dangerous concentration range of the shale oil and gas pipeline leakage diffusion, and compare and confirm it with the FLACS analysis results obtained in step S9, so as to provide a basis for the subsequent proposed safety protection measures.

[0189] The Gaussian plume model is selected because, as a mathematical model for simulating and predicting 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 it is applicable to continuous leakage.

[0190] The expression of the Gaussian plume model recorded in this embodiment is as follows:

[0191]

[0192] In the formula,

[0193] C(x, y, z) is the expression of the Gaussian plume model; q is the mass leakage rate, mg / s; π is the pi; u is the wind speed, m / s; σ y is the lateral diffusion coefficient; σ z 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; exp is the exponential function, indicating the power of e; H is the effective height of the pollution source, m.

[0194] S11. Based on the simulation from steps S4 - S10, quantitatively analyze each influencing factor before and after leakage, and thus 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 the FTA model to analyze pipeline leakage accidents of shale oil gathering and transportation pipelines, and define pipeline erosion as the key risk factor causing pipeline leakage accidents; S2, using Bayesian network to conduct quantitative risk analysis of pipeline leakage and calculate the probability of pipeline leakage; S3, establish the 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 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 a 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; S305, use the pressure-based solver and Simple algorithm to perform pressure-velocity coupling, initialize and solve; use Fluent software to view the pipeline erosion rate, and generate an erosion rate cloud map and a particle motion trajectory map.

2. A shale oil gathering and transportation pipeline leakage risk analysis and safety prevention and control method according to claim 1, characterized in that: The following settings are made for step S302: 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; the section is divided at the bend to simulate the pressure and velocity distribution in the pipeline, the movement trajectory of the sand particles, and the distribution of the erosion area on the pipeline wall.

3. A shale oil gathering and transportation pipeline leakage risk analysis and safety prevention and control method according to claim 1, characterized in that: 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 grids are evenly distributed, the radial direction is divided into five grids and the wall thickness remains unchanged; the full-area hexahedral units are discretized to obtain independent grids.

4. A shale oil gathering and transportation pipeline leakage risk analysis and safety prevention and control method according to claim 1, characterized in that: When establishing the FTA model, the pipeline leakage accident was 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 intrinsic defects and operational defects.

5. A shale oil gathering and transportation pipeline leakage risk analysis and safety prevention and control method according to claim 1, characterized in that: In step S2, the quantitative risk analysis of pipeline leakage using the Bayesian network includes 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, and the node flag and state value 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 the basic events expressed in the FTA model, wherein the direction of the directed edge connecting the nodes corresponds to the input-output relationship 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, the probability of occurrence of direct cause events in the FTA model is obtained by expert scoring method and reference to data, and the 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.

6. A shale oil gathering and transportation pipeline leakage risk analysis and safety prevention and control method according to claim 5, characterized in that: The Bayesian network in step S2 is converted into a dynamic Bayesian network, specifically comprising the following steps: S208, determining the impact of basic events in the FTA model according to Bayesian network analysis, and determining basic events whose probability increases over time, and using their nodes as dynamic parent nodes; S209, setting the number of calculation time periods of the dynamic Bayesian network, setting the transfer speed according to the speed of change of the probability of the dynamic parent node, setting the transfer probability of the dynamic parent node according to expert experience, performing dynamic Bayesian network calculation, 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.

7. A shale oil gathering and transportation pipeline leakage risk analysis and safety prevention and control method according to claim 1, characterized in that: The method also includes a diffusion analysis of the pipeline contents after a pipeline leak, The following steps are involved: S4, establish a pipeline leakage diffusion model of the shale oil gathering and transportation pipeline in the FLACS software, and set the leakage model at the shale oil gathering and transportation pipeline as a continuous leakage source model; S5, meshing 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 running solution module, and Flowvis post-processing module of FLACS software to analyze the leakage and diffusion law of shale oil and gas; 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.

8. A shale oil gathering and transportation pipeline leakage risk analysis and safety prevention and control method according to claim 7, characterized in that: The gas distribution concentration of shale oil and gas pipeline leakage and diffusion is verified and calculated by 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: In the formula, C(x,y,z) is the Gaussian plume model expression; q is the mass leakage rate, mg / s; π is the circumference; u is the wind speed, m / s; σ y is the lateral diffusion coefficient; σ z 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; exp is the exponential function, representing the power of e; H is the effective height of the pollution source, m.

9. A shale oil gathering and transportation pipeline leakage risk analysis and safety prevention and control method according to claim 7, 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 encrypted 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 divided mesh area; subdivide the mesh of the core encrypted area according to the size of the leakage aperture, and then use Smooth smoothing on the mesh at the boundary of the core encrypted area.

10. A shale oil gathering and transportation pipeline leakage risk analysis and safety prevention and control method according to claim 9, characterized in that: The mesh quality test and porosity verification of the pipeline leakage diffusion model are carried out as follows: Check the grid quality in Grid information of the Grid menu. The X, Y, and Z values ​​in the Max percentage diff column should not exceed 30. Check the porosity verification through the Flowvis module. Click 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 between 0 and 1 indicates partial blockage.

11. A shale oil gathering and transportation pipeline leakage risk analysis and safety prevention and control method according to claim 7, 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 in the pipeline leakage diffusion model is divided into three types: When , it is a small hole pipe model; When , it is a large-pore pipe model; When , it is the pipeline fracture model; S702, calculating the leakage rates of the three different leakage apertures in step S701 through the following steps, and selecting the pipeline leakage aperture according to the leakage rates: "P a / P" is compared with "(2 / (k+1))^(k / (k+1))" to determine the gas flow state in the pipeline: If "P a / P”≤"(2 / (k+1))^(k / (k+1))", belongs to factor flow, the gas leakage rate is calculated as follows: If "P a / P”>"(2 / (k+1))^(k / (k+1))", belongs to sub-factor flow, and the gas leakage rate is calculated as follows: In the above formula, P a is the critical pressure, Pa; P is the pressure inside the container, Pa; q m is the mass flow rate, kg / s; C d is the flow coefficient; A is the leakage hole area, m 2 ; M is the gas molar mass, kg / mol; k is the gas heat capacity ratio / isentropic index; R g is the universal gas constant, J / (mol·K); T is the gas temperature, K.

12. A shale oil gathering and transportation pipeline leakage risk analysis and safety prevention and control method according to claim 11, characterized in that: Use MATLAB to calculate the leakage rate of the leak aperture. The function file written is as follows: function[Q c ]=ex3_10(C d ,A,P,k,M,R,T) Qc=C d *A*P*(k*M / R / T*(2 / (k+1))^((k+1) / (k-1)))^0.5; end The code to calculate the leak rate is as follows: C=0.9; A=[0.0016, 0.0036, 0.0064, 0.0144]; P=1e6; k=1.315; M=19.804e-3; R=8.314; T=273.15+300; Q c =ex3_10(C d ,A,P,k,M,R,T)。

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