Dynamic early warning method for high-sulfur natural gas leakage influence range

Abstract

The invention discloses a dynamic early warning method for a high-sulfur-content natural gas leakage influence range in the field of leakage gas monitoring. The method comprises the following steps: arranging an intermediate infrared laser remote measurement system in a high-sulfur-content natural gas field to monitor the concentration of hydrogen sulfide gas in the gas field in real time; judging whether the gas field is leaked or not according to the concentration of the hydrogen sulfide gas, if so, executing the next step, otherwise, repeating the judgment; calculating leakage flow and leakage hole radius; and substituting the leakage hole radius and the leakage flow into the optimized time sequence Gaussian smoke cloud model to obtain the concentration values of the hydrogen sulfide gas at different moments and different spatial positions, namely the influence ranges of the leakage gas at different moments. According to the method, the size of the leakage hole can be calculated, the dynamic correction process of the three-dimensional leakage range of the Gaussian model is completed, various conditions of mixed gas leakage factors are considered at the same time, and the dynamic calculation process of the influence range of the leakage gas is achieved.

Description

Technical Field

[0001] The present invention belongs to the field of gas leakage monitoring, and in particular relates to a dynamic early warning method for the impact range of high-sulfur natural gas leakage. Background Art

[0002] Due to interference such as pipeline corrosion and external forces, natural gas transmission pipelines may be damaged, causing leaks of high-sulfur natural gas. High-sulfur natural gas contains a high content of hydrogen sulfide, which is highly toxic. Therefore, leaks from high-sulfur natural gas gathering and transmission pipelines pose a threat to nearby personnel and the environment. To reduce the risk of accidents and disasters caused by high-sulfur natural gas leaks and to quickly estimate the impact range of leaked gas, it is necessary to develop a dynamic early warning method for the impact range of high-sulfur natural gas to provide information for emergency decision-making after a high-sulfur natural gas leak occurs.

[0003] A Chinese invention patent, published on June 28, 2019, with publication number CN106021817B, discloses a method for rapidly simulating leaks in high-sulfur natural gas gathering and transmission equipment in marine gas fields. Using a Gaussian model as a baseline, the patent calculates the leakage flow rate based on the area of the leak hole, enabling rapid and quantitative calculation of the impact range of the leaked gas. While the Gaussian model generally performs relatively well for pure gas leaks, high-sulfur natural gas, as a typical mixed gas, not only exhibits variations in the average molar mass of the leaked gas but also interacts with other gases. These combined factors cause the impact range of the leaked gas to vary. Furthermore, hydrogen sulfide in high-sulfur natural gas is a highly toxic gas. After a leak occurs, the concentration of hydrogen sulfide near the leak source remains high, making it impossible to directly measure the leak hole size. Therefore, a dynamic early warning method suitable for leaks in high-sulfur natural gas gathering and transmission pipelines is needed to support the rapid calculation of the impact range of a high-sulfur natural gas leak. Summary of the Invention

[0004] The purpose of the present invention is to provide a dynamic early warning method for the impact range of high-sulfur natural gas leakage, which can calculate the radius of the leakage hole and dynamically calculate the three-dimensional impact range of the leaked gas based on the leakage hole radius.

[0005] The technical solution adopted by the present invention is a dynamic early warning method for the impact range of high-sulfur natural gas leakage, comprising the following steps: Step 1: deploying a medium-infrared laser telemetry system in a high-sulfur natural gas field to monitor the concentration of hydrogen sulfide in the field in real time; Step 2: Determine whether the gas field is leaking based on the hydrogen sulfide gas concentration. If leakage occurs, proceed to step 3. If no leakage occurs, repeat step 2. Step 3, calculate the leakage flow rate and the leakage hole radius; Step 4: Substitute the leakage hole radius and leakage flow into the optimized time-series Gaussian smoke cloud model to obtain the concentration values of hydrogen sulfide gas at different times and different spatial positions, which is the influence range of the leakage gas at different times.

[0006] The present invention is also characterized in that: In step 1, the mid-infrared laser telemetry system includes a mid-infrared laser device and several corner mirrors. The mid-infrared laser device includes a laser transmitter, a laser receiver and an optical processor. Specifically, the laser transmitter sequentially transmits a mid-infrared laser to the several corner mirrors. The mid-infrared laser enters the laser receiver after being reflected by the corner mirrors, and then the optical processor calculates the concentration of hydrogen sulfide gas in the gas field.

[0007] Step 2 specifically includes: setting a safety threshold for hydrogen sulfide gas, comparing the hydrogen sulfide gas concentration with the safety threshold, if the hydrogen sulfide gas concentration is greater than or equal to the safety threshold, the gas field equipment has leaked, and step 3 is performed; otherwise, step 2 is repeated.

[0008] Step 3 is as follows: Step 3.1: Use the pressure sensor on the gas field gathering pipeline to read the gas pressure of each section of the gathering pipeline P and flow rate V ; Step 3.2: Calculate the maximum gas pressure difference between two adjacent sections of the gathering and transportation pipeline according to formula (1), and determine the pipeline section with the maximum pressure difference as the leakage section. Then calculate the real-time leakage flow of the leakage section pipeline according to formula (2). (1) in, Pi For the i Pressure of the section gathering pipeline, Pa; b is the maximum pressure difference between gathering and transportation pipelines, Pa; (2) in, Q is the leakage flow; r is the radius of the gathering and transportation pipeline; ρ is the average density of high-sulfur natural gas leakage; V 1 and V 2 is the flow velocity of the front and rear sections of the leaking gathering and transportation pipeline; Step 3.3, calculate the leakage flow Q Substitute into formula (3) to calculate the radius of the leakage hole, (3) in, P 1 and P 2 is the pressure of the upstream and downstream sections of the leaking gathering and transportation pipeline; M is the relative molecular mass of the leaked gas; Ris the leakage gas constant; T is the leakage gas temperature, K; λ is the gas adiabatic coefficient, d is the leakage hole radius.

[0009] The optimization method of the time series Gaussian smoke cloud model in step 4 is: Step 4.1, set the hydrogen sulfide warning concentration; Step 4.2: Using the hydrogen sulfide warning concentration as input, optimize the double-layer GRNN network model to obtain the leakage distance coupling model; In step 4.3, the output of the leakage distance coupling model is used to optimize the time series Gaussian smoke cloud model.

[0010] The hydrogen sulfide warning concentration in step 4.1 is set according to the "Petrochemical Combustible and Toxic Gas Detection Alarm Design Standard" and the "Guidelines for Protection against Occupational Hazards of Hydrogen Sulfide". The hydrogen sulfide warning concentration in leaked high-sulfur natural gas is set to three levels: 20, 100 and 500 ppm.

[0011] The training method of the leakage distance coupling model is as follows: Step 4.2.1. Conduct numerical simulation experiments in a simulated gas field environment by varying the leak hole radius, ambient temperature, and ambient wind speed. Record the pressure in the gas field pipeline and the corresponding leakage duration to each hydrogen sulfide warning concentration under different leak hole radius, ambient temperature, and ambient wind speed conditions. Obtain simulation and experimental data on leakage in a high-sulfur natural gas gathering and transmission pipeline under different experimental variable conditions. Use the leak hole radius, gas field pipeline pressure, hydrogen sulfide and methane concentrations in high-sulfur natural gas, ambient wind speed, ambient temperature, hydrogen sulfide warning concentration, and leakage duration as inputs, and the actual maximum diffusion distance of the leaked gas as output to construct a time-series leakage dataset for high-sulfur natural gas. Step 4.2.2: Establish a two-layer GRNN network model, input the high-sulfur natural gas time series leakage dataset into the first-layer GRNN network of the two-layer GRNN network model, and after training, obtain the maximum distance of the leakage gas output by the first-layer GRNN network; use the actual maximum diffusion distance of the leakage gas in the time series leakage dataset minus the maximum distance output by the first layer to obtain the first-layer training error, and then input the original time series leakage dataset and the first-layer training error into the second-layer GRNN network. The output of the second-layer GRNN network is the maximum distance of the high-sulfur natural gas leakage finally coupled by the model.

[0012] The initial parameters of the two-layer GRNN network model include the initial number of network training rounds of 100, the smoothing parameter σ min is 0.001, and the smoothing parameter σ max is 1.0.

[0013] The optimization method of the time series Gaussian smoke cloud model is: Formula (5) is the output of the leakage distance coupling model. Substituting formula (5) into formula (4), the parameters in the formula are: x n and y n After modification, the optimized time series Gaussian smoke cloud model shown in formula (6) is obtained. (4), (5), (6), in, t It is the time it takes for the leaking gas plume to travel from the leak source to the calculation point; u— is the average wind speed at the leakage height; C t （x n ,y n ） After optimization, the horizontal leakage hole space position (x,y) The concentration of leaked gas at the location; σx 、 σy 、 σz are the diffusion coefficients in the horizontal and vertical directions, the horizontal transverse axis direction and the vertical direction, namely the diffusion coefficients in the downwind direction, the crosswind direction and the vertical wind direction; g(a) For the coupled model t At this moment, the warning concentration is a Output when C -1 (a) is the inverse function of the original Gaussian smoke cloud model, that is, when the warning concentration is a Output when H is the distance between the leak port and the ground.

[0014] The beneficial effects of the present invention are: 1. This invention uses a mid-infrared laser to monitor trace gas concentration leaks in a large gas field, uses a pipeline pressure sensor to determine the leak source location, and calculates the leak hole radius based on parameters such as pressure difference and pipeline diameter. This solves the problem of high-sulfur natural gas pipeline leaks being unable to be directly measured, and realizes the process of determining pipeline leakage status and calculating leakage flow.

[0015] 2. This invention uses small-scale experiments and large-scale simulations to obtain high-sulfur natural gas pipeline leakage data. It then uses an improved two-layer GRNN for model training. The resulting model is then used to modify a time-series Gaussian cloud model at the same height as the leak source, dynamically correcting the Gaussian model's three-dimensional leakage range. This approach, coupled with neural networks, considers various factors affecting mixed gas leakage and dynamically calculates the impact range of the leaked gas. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 It is a schematic flow diagram of the present invention; Figure 2 A schematic diagram of the experimental platform structure of Example 2 of the present invention; Figure 3 Schematic diagram of the two-dimensional output of the leakage port at the horizontal height according to Example 2 of the present invention; Figure 4 Schematic diagram of slice output at different heights of the leakage port in Example 2 of the invention; Figure 5 This is a slice diagram of the Gaussian puff output at three hydrogen sulfide warning concentrations in Example 2 of the present invention, where the colored area is the original time-series Gaussian puff model output; Figure 6 Schematic diagram of gas leakage when the hydrogen sulfide concentration is 2% and the leakage time is 5 seconds in Example 3 of the present invention; Figure 7 Schematic diagram of gas leakage when the hydrogen sulfide concentration is 2% and the leakage time is 40 seconds in Example 4 of the present invention; Figure 8 Schematic diagram of gas leakage when the hydrogen sulfide concentration is 2% and the leakage time is 100s in Example 5 of the present invention; Figure 9 Schematic diagram of gas leakage when the hydrogen sulfide concentration is 5% and the leakage time is 40 seconds in Example 6 of the present invention; Figure 10 Schematic diagram of gas leakage when the hydrogen sulfide concentration is 10% and the leakage time is 40 seconds in Example 7 of the present invention; Figure 11 This is a schematic diagram of gas leakage when the hydrogen sulfide concentration is 20% and the leakage time is 40s in Example 8 of the present invention. DETAILED DESCRIPTION

[0017] The present invention will be described in detail below with reference to the accompanying drawings and specific embodiments.

[0018] Example 1 A dynamic early warning method for the impact range of high-sulfur natural gas leakage, such as Figure 1 Said method comprises the following steps: Step 1: deploying and building a mid-infrared laser telemetry system in a high-sulfur natural gas field, and using the mid-infrared laser telemetry system to detect the concentration of hydrogen sulfide gas in the gas field in real time; The mid-infrared laser telemetry system includes a mid-infrared laser device and an angle reflector. The mid-infrared laser device and the angle reflector are arranged at the gas field site. The mid-infrared laser device includes a laser transmitter, a laser receiver, an optical processor and a rotation control pan-tilt device. The laser beam emitted by the laser transmitter is reflected by the angle reflector and then enters its own laser receiver. The optical processor then calculates the concentration of hydrogen sulfide gas in the gas field and transmits the signal collected by the optical processor to the local industrial computer through optical fiber. The rotation control pan-tilt device is used to change the emission direction of the laser transmitter and increase the detection range.

[0019] Step 2: Determine whether the gas field is leaking based on the hydrogen sulfide gas concentration. If leakage occurs, proceed to step 3. If no leakage occurs, repeat step 2. Specifically, a safety threshold of hydrogen sulfide gas is set, and the concentration of hydrogen sulfide gas is compared with the safety threshold. If the concentration of hydrogen sulfide gas is greater than or equal to the safety threshold, the gas field equipment has leaked, and step 3 is performed. Otherwise, step 2 is repeated.

[0020] Step 3, calculating the leakage flow rate and the leakage hole radius; Step 4: Input the leakage hole radius and leakage flow into the optimized Gaussian smoke cloud model to obtain the concentration values of hydrogen sulfide gas at different times and different spatial positions, which are the influence ranges of the leakage gas at different times.

[0021] Example 2 A dynamic early warning method for the impact range of a high-sulfur natural gas leakage comprises the following steps: Step 1: deploying and building a mid-infrared laser telemetry system in a high-sulfur natural gas field, and using the mid-infrared laser telemetry system to detect the concentration of hydrogen sulfide gas in the gas field in real time; The mid-infrared laser telemetry system includes a mid-infrared laser device and a corner reflector. Specifically, a mid-infrared laser device and three corner reflectors are arranged at the gas field site. The mid-infrared laser device includes a laser transmitter, a laser receiver, an optical processor and a rotation control pan-tilt device. The laser transmitter is set according to the cycle and is controlled by a stepper motor to emit a mid-infrared laser to the three corner reflectors in turn. After being reflected by the corner reflector, the mid-infrared laser re-enters its own laser receiver. After the optical processor monitors the hydrogen sulfide gas concentration in the gas field, the monitoring signal is transmitted to the gas field ring network through optical fiber communication; the receiving end converts the optical fiber signal into an optical fiber converter, converts the optical fiber signal into an RS485 signal, and stores historical data in the industrial control computer.

[0022] Step 2: Determine whether the gas field is leaking based on the hydrogen sulfide gas concentration. If leakage occurs, proceed to step 3. If no leakage occurs, repeat step 2. In this embodiment, the mid-infrared laser telemetry system uses a mid-infrared telemetry laser device. The telemetry device controls the emission direction of the mid-infrared laser transmitter to achieve the effect of monitoring a large range. The mid-infrared telemetry laser device inspects the three optical paths to be measured in the gas field at a fixed time frequency, obtains the hydrogen sulfide gas concentration in the gas field, and compares it with the safety threshold. β In comparison, if the concentration of hydrogen sulfide gas is greater than or equal to β , the gas field equipment has leaked, and proceed to step 3; if the hydrogen sulfide concentration is less than β , then the gas field equipment has not leaked, and step 2 is repeated. In this embodiment, the safety threshold of the mid-infrared laser device for hydrogen sulfide gas is set β It is 20ppmm.

[0023] Step 3, calculate the leakage flow and the leakage hole radius, such as Figure 3 As shown: Step 3.1: Use the pressure sensor on the gathering pipeline to read the gas pressure of each section of the gathering pipeline. P and flow rate V ; Step 3.2: Calculate the pressure difference of the gas between two adjacent sections of the gathering and transportation pipeline, and determine the pipeline section with the largest pressure difference as the leakage section. The calculation formula is formula (1). Then, calculate the real-time leakage flow of the leakage section pipeline according to formula (2). (1) in, Pi For the i The pressure of the section gathering pipeline, in Pa; b is the maximum pressure difference between gathering and transportation pipelines, in Pa; (2) in, Q is the leakage flow rate, in mg / s; r is the radius of the gathering and transportation pipeline, in meters; ρ is the average density of high-sulfur natural gas leakage, in kg / m; V 1 and V 2 is the flow velocity of the upstream and downstream sections of the leaking gathering and transportation pipeline, in m / s; Step 3.3, calculate the leakage flow Q Substitute into formula (3) to calculate the radius of the leakage hole, (3) in, P 1 and P 2 is the pressure of the upstream and downstream sections of the leaking gathering and transportation pipeline, in Pa;M is the relative molecular mass of the leaked gas; R is the leakage gas constant; T is the leakage gas temperature, K; λ is the gas adiabatic coefficient, d is the leakage hole radius.

[0024] Step 4: Input the leak hole radius and leakage flow into the optimized Gaussian smoke cloud model, and output the concentration values of hydrogen sulfide gas at different times and different spatial positions, which are the impact ranges of the leaked gas at different times; Step 4.1: Set the hydrogen sulfide warning concentration According to the relevant standards and regulations of the "Petrochemical Combustible and Toxic Gas Detection and Alarm Design Standard" and the "Guidelines for Occupational Hazard Protection of Hydrogen Sulfide", the warning concentration of hydrogen sulfide in leaked high-sulfur natural gas is set at 20, 100, and 500 ppm. Four warning levels are divided according to the hydrogen sulfide concentration: <20ppm, 20-100ppm, 100-500ppm, and ≥500ppm; among them, the concentration <20ppm is the safe area, the concentration 20-100ppm is the level 3 danger area, the concentration 100-500ppm is the level 2 danger area, and the concentration >500ppm is the level 1 danger area. The lower the danger level number, the higher the risk factor. Step 4.2: Using the hydrogen sulfide warning concentration as input, optimize the double-layer GRNN network model to obtain the leakage distance coupling model; In order to simulate the real gas field environment, a Figure 2 The test bench shown in the figure is used to conduct gas field simulation and numerical simulation experiments. The specific experimental steps are as follows: For different leak hole radii, a hydrogen sulfide gas leakage scenario is simulated in a high-sulfur natural gas gathering and transmission pipeline under a specific leak duration, and the actual maximum diffusion distance of the leaked gas is recorded. Simultaneously, the pipeline pressure at the time of the leak, the concentrations of methane and hydrogen sulfide in the high-sulfur natural gas, and parameters such as ambient wind speed and temperature are recorded. Furthermore, the leakage duration corresponding to each hydrogen sulfide warning concentration is calculated. The simulation experiments are repeated by varying environmental variables such as ambient wind speed and temperature to obtain simulation and experimental data under different experimental variable combinations. Using the leak hole radius, pipeline pressure, methane and hydrogen sulfide concentrations in the high-sulfur natural gas, ambient wind speed, ambient temperature, hydrogen sulfide warning concentration, and leak duration as input data, and the actual maximum diffusion distance of the leaked gas as output data, a time-series high-sulfur natural gas leakage dataset is established.

[0025] A two-layer GRNN network model was constructed, using a high-sulfur natural gas time series leakage dataset as input. The initial network parameters were set and optimized. After the optimization was completed, a gas leakage distance coupling model for high-sulfur natural gas gathering and transmission pipelines was obtained. Specifically, the initial number of network training rounds is set to 100, the smoothing parameter σmin is 0.001, and the smoothing parameter σmax is 1.0. The high-sulfur natural gas time series leakage dataset is input into the first-layer GRNN network of the two-layer GRNN network model. After model training, the maximum distance of the leakage gas output by the first-layer GRNN network is obtained; the actual maximum distance of the leakage gas in the time series leakage dataset is subtracted from the maximum distance output by the first layer to obtain the first-layer training error. The original time series leakage dataset and the first-layer training error are then input into the second-layer GRNN network together. The output of the second-layer GRNN network is the maximum distance of the high-sulfur natural gas leakage finally coupled by the model.

[0026] Step 4.3: Use the leakage distance coupling model output to optimize the time series Gaussian smoke cloud model: Formula (4) is the concentration calculation formula of the parallel leakage hole plane of the time series Gaussian smoke cloud model. The present invention calculates its parameters x n and y n Modify the parameters by using formula (5) x n and y n Correction, formula (5) is the output result of the leakage distance coupling model. The original Gaussian smoke cloud model is segmented and optimized through the above four warning levels, so that the gas concentration in each segment is divided more finely. Figure 3 and 5 As shown; Then, Equation (5) is substituted into Equation (4) to obtain the optimized time series Gaussian smoke cloud model. Its three-dimensional output is shown in Equation (6). The three-dimensional output diagram is shown in Figure 4 As shown, (4), (5), (6), in, t The time it takes for the leaking gas puff to travel from the leak source to the calculation point, in seconds; u— is the average wind speed at the leakage height, in m / s; C t （x n ,y n ) is the optimized horizontal leakage hole spatial position (x,y) The concentration of leaked gas at the location, in kg / m 3 ; σx 、 σy 、 σz are the diffusion coefficients in the horizontal and vertical directions, the horizontal transverse axis direction, and the vertical direction, namely, the diffusion coefficients in the downwind, crosswind, and vertical wind directions. The values are taken from Table 1, and the unit is m; g(a) For the leakage distance coupling model at time t, the warning concentration is a The output when , the unit is m; C -1 (a) is the inverse function of the original Gaussian smoke cloud model, that is, when the warning concentration is a The output when , the unit is m, H is the distance between the leak port and the ground, the unit is m; In formula (6) of Table 1 σ x , σ y , σ z Query table for value

[0027] Step 4.4: Input the leak hole radius and leakage flow rate from step 3 into the optimized time-series Gaussian smoke cloud model, and output the concentration values of hydrogen sulfide gas at different times and spatial locations, which are the impact ranges of the leaked gas at different times; Corresponding emergency measures are proposed based on the maximum leakage distances of the three hydrogen sulfide warning concentrations.

[0028] Example 3 On the basis of Example 2, the leakage of hydrogen sulfide gas in the gas field was simulated. When the concentration of hydrogen sulfide at the leakage source was 2%, the present invention calculated that the radius of the leakage hole was 25 mm. When the leakage time was 5 s, the three-dimensional dynamic diffusion range of the leakage gas was as follows: Figure 6 shown.

[0029] Example 4 Based on Example 2, the leakage of hydrogen sulfide gas in the gas field was simulated. When the hydrogen sulfide concentration of the leakage source was 2%, the radius of the leakage hole was 25 mm, and the leakage time was 40 s, the three-dimensional dynamic diffusion range of the leakage gas was as follows: Figure 7 shown.

[0030] Example 5 Based on Example 2, the leakage of hydrogen sulfide gas in the gas field was simulated. When the hydrogen sulfide concentration of the leakage source was 2%, the radius of the leakage hole was 25 mm, and the leakage time was 100 s, the three-dimensional dynamic diffusion range of the leakage gas was as follows: Figure 8 shown.

[0031] Example 6 Based on Example 2, the leakage of hydrogen sulfide gas in the gas field was simulated. When the hydrogen sulfide concentration of the leakage source was 5%, the radius of the leakage hole was 25 mm, and the leakage time was 40 s, the three-dimensional dynamic diffusion range of the leakage gas was as follows: Figure 9 shown.

[0032] Example 7 Based on Example 2, the leakage of hydrogen sulfide gas in the gas field was simulated. When the hydrogen sulfide concentration of the leakage source was 10%, the radius of the leakage hole was 25 mm, and the leakage time was 40 s, the three-dimensional dynamic diffusion range of the leakage gas was as follows: Figure 10 shown.

[0033] Example 8 Based on Example 2, the leakage of hydrogen sulfide gas in the gas field was simulated. When the hydrogen sulfide concentration of the leakage source was 20%, the radius of the leakage hole was 25 mm, and the leakage time was 40 s, the three-dimensional diffusion range of the leakage gas was as follows: Figure 11 shown.

[0034] The present invention uses infrared lasers in gas fields to monitor in real time whether a pipeline leaks. When a leak occurs, the radius of the leak hole is calculated based on information such as the pressure difference in the leaking section of the gathering and transportation pipeline and the pipeline diameter, providing basic parameters for a leakage range early warning model. A neural network is then used to optimize the calculation error of the leakage range of high-sulfur natural gas using the original time-series Gaussian smoke cloud model, achieving three-dimensional calculation of the impact range of the leaked gas, thereby dynamically calculating the three-dimensional impact range of the leaked gas.

Claims

1. A dynamic early warning method for the impact range of high-sulfur natural gas leakage, characterized in that: The following steps are involved: Step 1: deploying a medium-infrared laser telemetry system in a high-sulfur natural gas field to monitor the concentration of hydrogen sulfide in the field in real time; Step 2: Determine whether the gas field is leaking based on the hydrogen sulfide gas concentration. If leakage occurs, proceed to step 3. If no leakage occurs, repeat step 2. Step 3, calculate the leakage flow rate and the leakage hole radius; Step 4: Substitute the leakage hole radius and leakage flow into the optimized time-series Gaussian smoke cloud model to obtain the concentration values of hydrogen sulfide gas at different times and different spatial positions, which is the influence range of the leakage gas at different times.

2. The dynamic early warning method for the impact range of high-sulfur natural gas leakage according to claim 1 is characterized in that: The mid-infrared laser telemetry system described in step 1 includes a mid-infrared laser device and several corner mirrors. The mid-infrared laser device includes a laser transmitter, a laser receiver and an optical processor. Specifically, the laser transmitter sequentially transmits a mid-infrared laser to the several corner mirrors. The mid-infrared laser enters the laser receiver after being reflected by the corner mirrors, and then the optical processor calculates the concentration of hydrogen sulfide gas in the gas field.

3. The dynamic early warning method for the impact range of high-sulfur natural gas leakage according to claim 1 is characterized in that: The step 2 specifically includes: setting a safety threshold of hydrogen sulfide gas, comparing the hydrogen sulfide gas concentration with the safety threshold, if the hydrogen sulfide gas concentration is greater than or equal to the safety threshold, the gas field equipment has leaked, and step 3 is performed; otherwise, step 2 is repeated.

4. The dynamic early warning method for the impact range of high-sulfur natural gas leakage according to claim 1 is characterized in that: The step 3 is specifically as follows: Step 3.1: Use the pressure sensor on the gas field gathering pipeline to read the gas pressure of each section of the gathering pipeline P and flow rate V ; Step 3.2: Calculate the maximum gas pressure difference between two adjacent sections of the gathering and transportation pipeline according to formula (1), and determine the pipeline section with the maximum pressure difference as the leakage section. Then calculate the real-time leakage flow of the leakage section pipeline according to formula (2). （1） in, Pi For the i Pressure of the section gathering pipeline, Pa; b is the maximum pressure difference between gathering and transportation pipelines; （2） in, Q is the leakage flow; r is the radius of the gathering and transportation pipeline; ρ is the average density of high-sulfur natural gas leakage; V 1 and V 2 is the flow velocity of the front and rear sections of the leaking gathering and transportation pipeline; Step 3.3, calculate the leakage flow Q Substitute into formula (3) to calculate the radius of the leakage hole, （3） in, P 1 and P 2 is the pressure of the upstream and downstream sections of the leaking gathering and transportation pipeline; M is the relative molecular mass of the leaked gas; R is the leakage gas constant; T is the leakage gas temperature, K; λ is the gas adiabatic coefficient, d is the leakage hole radius.

5. The dynamic early warning method for the impact range of high-sulfur natural gas leakage according to claim 1 is characterized in that: The optimization method of the time series Gaussian smoke cloud model described in step 4 is: Step 4.1, set the hydrogen sulfide warning concentration; Step 4.2: Using the hydrogen sulfide warning concentration as input, optimize the double-layer GRNN network model to obtain the leakage distance coupling model; In step 4.3, the output of the leakage distance coupling model is used to optimize the time series Gaussian smoke cloud model.

6. The dynamic early warning method for the impact range of high-sulfur natural gas leakage according to claim 5 is characterized in that: The hydrogen sulfide warning concentration in step 4.1 is set according to the "Petrochemical Combustible Gas and Toxic Gas Detection Alarm Design Standard" and the "Guidelines for Protection against Occupational Hazards of Hydrogen Sulfide", and the hydrogen sulfide warning concentration in the leaked high-sulfur natural gas is set to three levels of 20, 100 and 500 ppm.

7. The dynamic early warning method for the impact range of high-sulfur natural gas leakage according to claim 5 is characterized in that: The training method of the leakage distance coupling model is as follows: Step 4.2.

1. Conduct numerical simulation experiments in a simulated gas field environment by varying the leak hole radius, ambient temperature, and ambient wind speed. Record the pressure in the gas field pipeline and the corresponding leakage duration to each hydrogen sulfide warning concentration under different leak hole radius, ambient temperature, and ambient wind speed conditions. Obtain simulation and experimental data on leakage in a high-sulfur natural gas gathering and transmission pipeline under different experimental variable conditions. Use the leak hole radius, gas field pipeline pressure, hydrogen sulfide and methane concentrations in high-sulfur natural gas, ambient wind speed, ambient temperature, hydrogen sulfide warning concentration, and leakage duration as inputs, and the actual maximum diffusion distance of the leaked gas as output to construct a time-series leakage dataset for high-sulfur natural gas. Step 4.2.2: Establish a two-layer GRNN network model, input the high-sulfur natural gas time series leakage dataset into the first-layer GRNN network of the two-layer GRNN network model, and after training, obtain the maximum distance of the leakage gas output by the first-layer GRNN network; use the actual maximum diffusion distance of the leakage gas in the time series leakage dataset minus the maximum distance output by the first layer to obtain the first-layer training error, and then input the original time series leakage dataset and the first-layer training error into the second-layer GRNN network. The output of the second-layer GRNN network is the maximum distance of the high-sulfur natural gas leakage finally coupled by the model.

8. The dynamic early warning method for the impact range of high-sulfur natural gas leakage according to claim 7 is characterized in that: The initial parameters of the two-layer GRNN network model include: the number of initial network training rounds is 100, the smoothing parameter σ min is 0.001, and the smoothing parameter σ max is 1.

0.

9. The dynamic early warning method for the impact range of high-sulfur natural gas leakage according to claim 5 is characterized in that: The optimization method of the time series Gaussian smoke cloud model is: Formula (5) is the output of the leakage distance coupling model. Substituting formula (5) into formula (4), the parameters in the formula are: x n and y n After modification, the optimized time series Gaussian smoke cloud model shown in formula (6) is obtained. （4）， （5）， （6）， in, t It is the time it takes for the leaking gas plume to travel from the leak source to the calculation point; u— is the average wind speed at the leakage height; C t （x n ,y n ） After optimization, the horizontal leakage hole space position (x,y) The concentration of leaked gas at the location; σx 、 σy 、 σz are the diffusion coefficients in the horizontal and vertical directions, the horizontal transverse axis direction and the vertical direction, namely the diffusion coefficients in the downwind direction, the crosswind direction and the vertical wind direction; g(a) For the coupled model t At this moment, the warning concentration is a Output when C -1 (a) is the inverse function of the original Gaussian smoke cloud model, that is, when the warning concentration is a Output when H is the distance between the leak port and the ground.

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