Coal seam mining control method and device, electronic equipment and medium

Abstract

The invention provides a coal seam mining control method and device, electronic equipment and a medium, and the method comprises the steps: obtaining real-time measurement data from a coal seam mining monitoring device, the real-time measurement data comprising coal seam measurement data and product measurement data in a coal seam gasification process; determining the reaction stage of the current coal bed gasification according to the real-time measurement data; and adjusting injection parameters of the coal seam mining injection device by comparing the real-time measurement data with preset measurement data corresponding to the reaction stage so as to optimize the injection parameters. And finally, a control instruction for indicating the adjusted injection parameters is sent to a coal seam mining injection device, so that the current coal seam gasification process reaches a preset gasification process, and the gas recovery efficiency of the deep coal seam is improved.

Description

Technical Field

[0001] This application relates to the field of geological exploration and development, and in particular to a control method, apparatus, electronic equipment and medium for coal seam mining. Background Technology

[0002] Compared to shallow coal seams, deep coal seams have more complex reservoir conditions and are affected by more frequent and multi-stage tectonic movements. Consequently, the coal bodies in deep coal seams are more prone to fracturing, deformation, and changes in coal quality, leading to reduced gas content and permeability, which in turn affects the extraction of combustible gases from the coal seams.

[0003] Currently, the equipment parameters used for mining combustible gases in deep coal seams are generally determined by employees, which further reduces the gas recovery rate of deep coal seams. Summary of the Invention

[0004] This application provides a control method, apparatus, electronic device, and medium for coal seam mining to improve the gas recovery rate of deep coal seams.

[0005] In a first aspect, embodiments of this application provide a control method for coal seam mining, the method comprising: acquiring real-time measurement data from a coal seam mining monitoring device, the real-time measurement data including coal seam measurement data and product measurement data during the coal seam gasification process; determining the current reaction stage of coal seam gasification based on the real-time measurement data; adjusting the injection parameters of a coal seam mining injection device by comparing the real-time measurement data with preset measurement data corresponding to the reaction stage; and sending a control command to the coal seam mining injection device, the control command indicating the adjusted injection parameters.

[0006] In some embodiments of the first aspect, the injection parameters of the coal seam mining injection device are adjusted by comparing real-time measurement data with preset measurement data corresponding to the reaction stage, including: acquiring preset measurement data corresponding to the reaction stage; if the real-time measurement data is inconsistent with the preset measurement data corresponding to the reaction stage, adjusting the injection parameters of the coal seam mining injection device according to the pre-stored coal seam mining simulation results, the real-time measurement data, and the preset measurement data corresponding to the reaction stage; the coal seam mining simulation results are used to indicate the adjustment strategies corresponding to different types of measurement data.

[0007] In some embodiments of the first aspect, the injection parameters of the coal seam mining injection device are adjusted based on pre-stored coal seam mining simulation results, real-time measurement data, and preset measurement data corresponding to the reaction stage. This includes: determining the type of injection parameter to be adjusted from the coal seam mining simulation results based on the inconsistent data types of the measurement data; and determining the value of increasing or decreasing the injection parameter to be adjusted by comparing the magnitude relationship between the real-time measurement data and the preset measurement data corresponding to the reaction stage.

[0008] In some embodiments of the first aspect, the method further includes: constructing a coal seam mining prediction model, which is used to simulate the gasification process of the coal seam to be mined under different injection parameters; inputting different injection parameters into the coal seam mining prediction model; obtaining prediction data output by the coal seam mining prediction model under different injection parameters; generating coal seam mining simulation results based on the prediction data; and storing the coal seam mining simulation results in a preset storage space.

[0009] In some embodiments of the first aspect, the coal seam mining prediction model includes a geological model, a reaction model, a heat transfer model, and a fluid transport model; the geological model is used to simulate the changes in the force field during the gasification process of the coal seam to be mined based on injection parameters; the reaction model is used to simulate the changes in the multiphase concentration field during the gasification process of the coal seam to be mined based on injection parameters; the heat transfer model is used to simulate the changes in the temperature field during the gasification process of the coal seam to be mined based on injection parameters; and the fluid transport model is used to simulate the changes in the flow field during the gasification process of the coal seam to be mined based on injection parameters.

[0010] Some embodiments of the first aspect involve constructing a coal seam mining prediction model, including: constructing a geological model based on the continuity equation, the equilibrium equation, and the geometric equation of the isotropic elastoplastic coal seam skeleton, which are based on the mechanical properties of the coal seam and the stress-strain conditions of the coal seam skeleton; constructing a reaction model based on the Arrhenius equation; constructing a heat transfer model based on the energy conservation formula, which is used to characterize the relationship between the temperature of the fluid and the heat conduction of the coal seam to be mined; and constructing a fluid transport model based on the Darcy's law algorithm.

[0011] In some embodiments of the first aspect, the injection parameters include the injection pressure, injection temperature, injection volume, and injection rate of supercritical water and oxygen, and the prediction data output by the coal seam mining prediction model includes the product prediction data and coal seam prediction data of the coal seam to be mined at each reaction stage.

[0012] Secondly, embodiments of this application provide a control device for coal seam mining, comprising:

[0013] The acquisition module is used to acquire real-time measurement data from the coal seam mining monitoring device. The real-time measurement data includes coal seam measurement data and product measurement data during the coal seam gasification process.

[0014] The processing module is used to determine the current reaction stage of coalbed gasification based on real-time measurement data;

[0015] The processing module is also used to adjust the injection parameters of the coal seam mining injection device by comparing real-time measurement data with preset measurement data corresponding to the reaction stage;

[0016] The sending module is used to send control commands to the coal seam mining injection device, and the control commands indicate the adjusted injection parameters.

[0017] Thirdly, embodiments of this application provide an electronic device, including:

[0018] Processor, memory, communication interface;

[0019] Memory is used to store the processor's executable instructions;

[0020] The processor is configured to execute the method of the first aspect by executing executable instructions.

[0021] Fourthly, embodiments of this application provide a readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the method of the first aspect.

[0022] Fifthly, embodiments of this application provide a chip system applied to an electronic device. The chip system includes one or more processors, which are used to invoke computer instructions to enable the electronic device to perform the method of the first aspect.

[0023] This application provides a control method, apparatus, electronic device, and medium for coal seam mining. After acquiring real-time measurement data from a coal seam mining monitoring device, the current reaction stage of coal seam gasification can be determined based on the real-time measurement data. Next, by comparing the real-time measurement data with preset measurement data corresponding to the reaction stage, the injection parameters of the coal seam mining injection device can be adjusted to optimize the injection parameters. Finally, a control command instructing the adjusted injection parameters is sent to the coal seam mining injection device to ensure that the current coal seam gasification process reaches the preset gasification process, thereby improving the gas recovery rate of deep coal seams. Attached Figure Description

[0024] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0025] Figure 1 A schematic diagram of an application scenario for the control method for coal seam mining provided in this application embodiment;

[0026] Figure 2 A schematic flowchart of a coal seam mining control method provided in an embodiment of this application;

[0027] Figure 3 A schematic diagram illustrating another application scenario of the control method for coal seam mining provided in the embodiments of this application;

[0028] Figure 4A schematic diagram illustrating another application scenario of the coal seam mining control method provided in an embodiment of this application;

[0029] Figure 5 A schematic diagram illustrating another application scenario of the coal seam mining control method provided in the embodiments of this application;

[0030] Figure 6 A schematic diagram of the control device for coal seam mining provided in the embodiments of this application;

[0031] Figure 7 A schematic diagram of the structure of the electronic device provided in this application. Detailed Implementation

[0032] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments made by those skilled in the art under the guidance of these embodiments are within the scope of protection of this application.

[0033] The terms “first,” “second,” “third,” “fourth,” etc. (if present) in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a particular order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms “comprising” and “having,” and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0034] Compared to shallow coal seams, deep coal seams have more complex reservoir conditions and are affected by more frequent and multi-stage tectonic movements. Consequently, the coal bodies in deep coal seams are more prone to fracturing, deformation, and changes in coal quality, leading to reduced gas content and permeability, which in turn affects the extraction of combustible gases from the coal seams.

[0035] Currently, when using underground coal gasification technology to extract combustible gases from deep coal seams, the ignition face can easily cause the roof and lower plate of the deep coal seam to collapse during the process of advancing into the deep coal seam, resulting in gas leakage and dispersion, thus reducing the gas recovery rate of the deep coal seam.

[0036] In addition, the equipment parameters used for extracting combustible gases are generally determined by employees, which further reduces the gas recovery rate of deep coal seams.

[0037] In view of this, this application provides a control method, apparatus, electronic equipment and medium for coal seam mining to improve the gas recovery rate of deep coal seams.

[0038] Please see Figure 1 , Figure 1 This diagram illustrates an application scenario of the coal seam mining control method according to an embodiment of this application. The application scenario includes an injection well 21, a production well 22, a mining injection device 20, a mining monitoring device 30, and electronic equipment 10. The injection well 21 and production well 22 penetrate the formation surface to the deep coal seam, with the injection well 21 connected to a horizontal well 23. During well completion, a cavity region is drilled below the production well 22. This cavity region includes the area where the horizontal well 23 connects to the production well 22, as well as a pocket region. The pocket region is used to prevent objects such as sand from clogging the wellhead of the production well 22. The injection well 21 is used to inject various fluids required for underground coal gasification technology into the deep coal seam. These fluids include oxygen and high-temperature water, where high-temperature water refers to water with a temperature higher than a preset temperature. The injection well 21 includes an oxygen injection pipe 212 and a high-temperature water injection pipe 211. The oxygen injection pipe 212 is used to inject oxygen, and the high-temperature water injection pipe 211 is used to inject high-temperature water. The production well 22 includes a gas pipe 221. After oxygen and high-temperature water enter the deep coal seam, they react with the coal in the gasification chamber to produce combustible gas, which flows out from the combustible gas outlet of the gas pipeline 221 of the production well 22.

[0039] The mining injection device 20 receives control commands from the electronic device 10 and injects various fluids into the injection well 21 according to the control commands. The mining monitoring device 30 collects measurement data of the coal seam and product during the deep coal seam gasification process and sends the measurement data and product measurement data to the electronic device 10. The electronic device 10 implements the coal seam mining control method of this application embodiment based on the measurement data and product measurement data.

[0040] In some embodiments, the electronic device includes a server, tablet computer, desktop computer, laptop computer, handheld computer, notebook computer, and ultra-mobile personal computer (UMPC), etc.

[0041] It should be noted that, Figure 1 This is merely a schematic diagram illustrating one application scenario provided by an embodiment of this application. This embodiment of the application does not necessarily represent an application scenario. Figure 1 The document does not limit the actual form of the various devices included, nor does it specify the form of the devices. Figure 1 The interaction methods between devices are limited, and can be set according to actual needs in the specific application of the solution.

[0042] The technical solution of this application will now be described in detail through specific embodiments. It should be noted that the following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments.

[0043] Figure 2 This is a flowchart illustrating an embodiment of the control method for oil and coal seam mining provided in this application. The executing entity in this embodiment can be an electronic device. The method in this embodiment can be implemented through software, hardware, or a combination of both. Figure 2 As shown, the control method specifically includes the following steps:

[0044] Step S110: Obtain real-time measurement data from the coal seam mining monitoring device.

[0045] like Figure 1 As shown, after high-temperature water is injected into a deep coal seam, it is converted into supercritical water due to the high-pressure environment within the seam. The supercritical water (H2) and oxygen (O2) react with the coal in the deep coal seam to undergo gasification, producing gases such as carbon dioxide (CO2), hydrogen (H2), carbon monoxide (CO), and methane (CH4). Therefore, the mixed fluid in a deep coal seam includes at least one gas selected from supercritical water, oxygen, carbon dioxide, hydrogen, carbon monoxide, and methane.

[0046] Real-time measurement data includes coal seam measurement data and product measurement data during the coal seam gasification process. Coal seam measurement data includes temperature field data and force field data. Temperature field data includes the temperature of each region within the deep coal seam. Force field data includes the magnitude and direction of the force at each point within the deep coal seam. Product measurement data includes flow field data and multiphase concentration field data. Flow field data includes the velocity and direction of the mixed fluid flowing within the deep coal seam. Multiphase concentration field data includes the concentration of each fluid within the deep coal seam.

[0047] Step S120: Determine the current reaction stage of coalbed gasification based on real-time measurement data.

[0048] like Figure 3 As shown, Figure 3 The diagram illustrates the four reaction stages that occur sequentially during coalbed methane gasification: the intense oxygen generation zone, the supercritical water gasification zone, the pyrolysis zone, and the preheating zone. Between the injection well and the production well, these zones are distributed in sequence.

[0049] The intense oxygen generation zone, located near the injection well, is the starting point of the entire gasification reaction. Deep coal seams undergo an oxidation reaction with oxygen, producing carbon dioxide and releasing a large amount of heat, causing the temperature in this area to rapidly rise to over 900°C, for example, 1200°C. Understandably, the in-situ heat generated by the oxidation reaction can effectively and rapidly heat the raw materials, thereby promoting the gasification process. This high-temperature environment provides the necessary energy support for subsequent gasification reactions.

[0050] When supercritical water, carrying a large amount of heat, enters the supercritical water gasification reaction zone from the oxidation-induced heat generation zone, the oxygen concentration gradually decreases, and the temperature drops to between 600℃ and 900℃. Within this temperature range, supercritical water undergoes a vigorous gasification reaction with coal, producing large amounts of hydrogen and carbon dioxide. The supercritical water gasification reaction zone can be understood as the main gas-producing zone, and the produced combustible gas has extremely high energy density and cleanliness.

[0051] As the gasification reaction progresses, supercritical water, oxygen, and hydrogen continue to carry heat into the pyrolysis reaction zone, where the temperature ranges from 400℃ to 600℃. Within this zone, the volatile organic compounds in the coal react with the supercritical water to produce pyrolysis gases such as methane. It is understandable that pyrolysis gases not only have a higher calorific value but are also cleaner, helping to reduce pollutant emissions.

[0052] Carbon dioxide, carbon monoxide, and hydrogen carry heat into the preheating zone. Located near the production well, the preheating zone has a temperature below 400°C. Understandably, compared to other zones, the preheating zone is often selected to have higher porosity and permeability, creating favorable conditions for subsequent reactions.

[0053] It is understandable that the real-time measurement data for the intense oxygen generation zone, supercritical water gasification reaction zone, pyrolysis reaction zone, and preheating zone differ. For example, the temperature field data differs: the temperature in the intense oxygen generation zone is above 900℃, in the supercritical water gasification reaction zone it is between 600℃ and 900℃, in the pyrolysis reaction zone it is between 400℃ and 600℃, and in the preheating zone it is below 400℃. The multiphase concentration field data also differs: the oxygen concentration decreases sequentially from the intense oxygen generation zone to the preheating zone, while the methane solubility increases sequentially. Therefore, the current reaction stage of coalbed methane gasification can be determined by real-time measurement data.

[0054] In one example, the real-time measured data shows a temperature of 700℃ and a methane concentration greater than zero. This indicates that the current coalbed gasification reaction stage is the pyrolysis reaction zone formation stage.

[0055] Step S130: Adjust the injection parameters of the coal seam mining injection device by comparing the real-time measurement data with the preset measurement data corresponding to the reaction stage.

[0056] Step S140: Send a control command to the coal seam mining injection device, the control command indicating the adjusted injection parameters.

[0057] The preset measurement data includes preset temperature field data, preset force field data, preset multiphase concentration field data, and preset flow field data.

[0058] Injection parameters include the injection pressure, injection temperature, injection volume, and injection rate for injecting supercritical water and oxygen into the injection well.

[0059] If there is a discrepancy between the real-time measurement data and the preset measurement data corresponding to the reaction stage, it indicates that the current coal seam gasification process is inconsistent with the ideal gasification process. By adjusting the injection parameters of the mining injection device, the current coal seam gasification process can be made to reach the ideal gasification process.

[0060] For example, when the real-time methane concentration is lower than the preset methane concentration corresponding to the pyrolysis reaction zone, the injection rate of supercritical water in the mining injection device is increased, thereby increasing the amount of supercritical water injected into the deep coal seam. Alternatively, the injection rate of supercritical water in the mining injection device is increased, and over a period of time, the amount of supercritical water injected into the deep coal seam by the mining injection device also increases.

[0061] Increasing the amount of supercritical water accelerates the reaction between supercritical water and coal, producing more hydrogen. This, in turn, leads to the production of more methane in the pyrolysis reaction zone, achieving the desired methane concentration.

[0062] Please refer to the following: Figure 1 In one application scenario, electronic device 10 acquires real-time measurement data from coal seam mining monitoring device 30, indicating a temperature of 700℃ and a methane concentration greater than zero. Based on this data, it determines that the current coal seam gasification reaction stage is the pyrolysis reaction zone formation stage. By comparing the real-time methane concentration in the measurement data with the preset methane concentration corresponding to the pyrolysis reaction zone, it increases the injection rate of supercritical water into the coal seam mining injection device 20. A control command is then sent to the coal seam mining injection device 20. Following the control command, the injection device 20 increases the injection rate of supercritical water into the deep coal seam.

[0063] Understandably, the above technical solution, after acquiring real-time measurement data from the coal seam mining monitoring device, can determine the current reaction stage of coal seam gasification based on the real-time measurement data. Then, by comparing the real-time measurement data with preset measurement data corresponding to the reaction stage, the injection parameters of the coal seam mining injection device can be adjusted. Finally, a control command instructing the adjusted injection parameters is sent to the coal seam mining injection device. Optimizing the injection parameters ensures that the current coal seam gasification process reaches the preset gasification process, thereby improving the gas recovery rate of deep coal seams.

[0064] In some embodiments, adjusting the injection parameters of the coal seam mining injection device by comparing real-time measurement data with preset measurement data corresponding to the reaction stage includes the following steps:

[0065] Step S210: Obtain the preset measurement data corresponding to the reaction stage.

[0066] Preset measurement data can be obtained from external devices or stored in the storage device of electronic devices.

[0067] Step S220: If the real-time measurement data is inconsistent with the preset measurement data corresponding to the reaction stage, adjust the injection parameters of the coal seam mining injection device according to the pre-stored coal seam mining simulation results, real-time measurement data and preset measurement data corresponding to the reaction stage.

[0068] The simulation results of coal seam mining include the changes in the force field, multiphase concentration field, temperature field, and flow field during the gasification process of the coal seam to be mined, as well as the type, flow rate, and volume of combustible gases. These simulation results can be obtained using simulation software. Inputting injection parameters into the simulation model outputs the corresponding coal seam mining simulation results. Adjusting the injection parameters allows for the adjustment of the simulation results. Therefore, multiple sets of coal seam mining simulation results, along with the corresponding injection parameters, can be obtained through simulation software.

[0069] There are various types of measurement data, such as temperature field data, force field data, multiphase concentration field data, and flow field data. The types of coal seam mining simulation results correspond one-to-one with the data types of measurement data. Therefore, adjustment strategies can be established based on the coal seam mining simulation results, taking into account the data types of measurement data. In other words, the mining simulation results can be used to indicate the adjustment strategies corresponding to different types of measurement data. These adjustment strategies ensure that real-time measurement data matches the preset measurement data corresponding to the reaction stage.

[0070] In one embodiment, the injection parameters of the coal seam mining injection device are adjusted based on pre-stored coal seam mining simulation results, real-time measurement data, and preset measurement data corresponding to the reaction stage. This includes the following steps:

[0071] First, if the real-time measurement data of the current coal seam gasification process is inconsistent with the preset measurement data corresponding to the reaction stage, the type of injection parameter to be adjusted is determined from the coal seam mining simulation results based on the data type of the inconsistency. Next, by comparing the magnitude of the real-time measurement data with the preset measurement data corresponding to the reaction stage, the value of increasing or decreasing the injection parameter to be adjusted is determined.

[0072] For example, if the data types are inconsistent and are temperature field data, then the injection parameters to be adjusted, such as injection temperature and injection pressure, that affect the changes in the temperature field from the coal seam mining simulation results are retrieved. Next, if it is determined that the size of the real-time temperature field data is smaller than the size of the predicted temperature field data corresponding to the reaction stage, then the values ​​of the injection temperature and injection pressure are increased.

[0073] For example, if the data types are not consistent and are force field data, then the injection parameters and / or geological parameters that influence the changes in the force field in the coal seam mining simulation results are retrieved for adjustment. These include injection parameters such as injection temperature and injection pressure, and geological parameters such as the pressure and temperature of deep coal seams. Next, if it is determined that the magnitude of the real-time force field data is greater than the magnitude of the predicted force field data corresponding to the reaction stage, then the values ​​of the injection temperature and injection pressure are reduced, and / or the values ​​of the pressure and temperature of deep coal seams are reduced.

[0074] For example, if the data types are inconsistent and are multiphase concentration field data, then the injection parameters to be adjusted, such as the injection rates of oxygen and supercritical water, that affect the changes in the multiphase concentration field in the coal seam mining simulation results are retrieved. Next, if it is determined that the size of the real-time multiphase concentration field data is smaller than the size of the predicted multiphase concentration field data corresponding to the reaction stage, then the values ​​of the oxygen and supercritical water injection rates are increased.

[0075] For example, if the data types are inconsistent and are flow field data, the injection parameters to be adjusted, such as injection velocity, that affect the changes in the flow field are retrieved from the coal seam mining simulation results. Then, if it is determined that the size of the real-time flow field data is greater than the size of the predicted flow field data corresponding to the reaction stage, the value of the injection velocity is reduced.

[0076] Understandably, if the real-time measurement data is inconsistent with the preset measurement data corresponding to the reaction stage, the injection parameters of the coal seam mining injection device can be adjusted to the injection parameters corresponding to the pre-stored coal seam mining simulation results, so that the real-time measurement data is consistent with the preset measurement data corresponding to the reaction stage.

[0077] Please see Figure 4 In some embodiments, the process of generating coal seam mining simulation results includes the following steps, that is, the control method for coal seam mining also includes the following steps:

[0078] Step S310: Construct a coal seam mining prediction model.

[0079] The coal seam mining prediction model is a simulation model constructed using simulation software, and the solution method can be the finite element method. For example... Figure 4As shown, in the parameter input module of the simulation software, the experimental laws and conditions obtained through gasification experiments, as well as the geological parameters of the coal seam to be mined, are input to generate a coal seam mining prediction model. Specifically, the gasification experiment involves gasifying supercritical water and coal from the coal seam to be mined. The combustible gas obtained from the gasification reaction is weighed using a balance and analyzed by gas chromatography to obtain results such as the type and proportion of combustible gas. In different gasification experiments, the experimental condition parameters are changed. These parameters include the experimental injection temperature, injection volume, injection rate, and injection speed when supercritical water is injected into the experimental device to react with coal, as well as environmental parameters such as the temperature and pressure of the experimental device. After conducting multiple gasification experiments, the experimental condition parameters of each gasification experiment and the corresponding combustible gas can be analyzed to determine the experimental laws. The experimental laws include the reaction rate of the gasification reaction, the proportion of various gases in the combustible gas, and so on. Figure 3 The chemical reaction equations shown are C + O₂ == CO₂ and 2H₂O + C == H₂ + CO₂, etc.

[0080] It is understandable that the experimental laws and conditions obtained through the gasification reaction of supercritical water and coal in the coal seam to be mined can be used as initial parameters for the coal seam mining prediction model. Geological parameters can make the geological structure of the coal seam mining prediction model conform to the geological structure of the coal seam to be mined, thus making the simulated coal seam mining results more consistent with the coal seam to be mined.

[0081] Step S320: Input different injection parameters into the coal seam mining prediction model.

[0082] like Figure 4 As shown, the coal seam mining prediction model includes an injection point, which is used to input injection parameters such as injection pressure, injection temperature, injection volume, and injection rate. The injection point can simulate the fluid injection process at the well screen of the injection well.

[0083] Step S330: Obtain the prediction data output by the coal seam mining prediction model under different injection parameters.

[0084] like Figure 4 As shown, the coal seam mining prediction model also includes a geological model, a reaction model, a heat transfer model, and a fluid transport model.

[0085] In simulation software, geological models can be constructed using algorithms such as continuity equations based on the mechanical properties of coal seams and stress-strain conditions of the coal seam skeleton, equilibrium equations for isotropic elastoplastic coal seam skeletons, and geometric equations for the coal seam skeleton. Reaction models can be constructed using algorithms such as the Arrhenius equation. Heat transfer models can be constructed based on the energy conservation formula, which characterizes the relationship between fluid temperature and heat conduction in the coal seam to be mined. Fluid transport models can be constructed using algorithms such as Darcy's law.

[0086] After inputting injection parameters at the injection point, and coupling the geological model, reaction model, heat transfer model, and fluid transport model, prediction data can be output. The prediction data includes product prediction data and coal seam prediction data for each reaction stage of the coal seam to be mined, as well as the predicted flow rate, type, and proportion of each gas in the combustible gas. Product prediction data includes predicted temperature field data and predicted force field data. Coal seam prediction data includes predicted multiphase concentration field data and predicted flow field data. The coal seam mining prediction model also includes an output point, which displays the predicted combustible gas.

[0087] Geological models are primarily used to output predicted force field data based on injection parameters and / or geological parameters. Reaction models are primarily used to output predicted multiphase concentration field data based on injection parameters. Heat transfer models are primarily used to output predicted temperature field data based on injection parameters. Fluid transport models are primarily used to output predicted flow field data based on injection parameters.

[0088] Step S340: Generate coal seam mining simulation results based on the predicted data.

[0089] The geological model also simulates the changes in the force field during the gasification process of the coal seam to be mined, based on predicted force field data. The reaction model is mainly used to simulate the changes in the multiphase concentration field during the gasification process of the coal seam to be mined, based on predicted multiphase concentration field data. The heat transfer model also simulates the changes in the temperature field during the gasification process of the coal seam to be mined, based on predicted temperature field data. The fluid transport model also simulates the changes in the flow field during the gasification process of the coal seam to be mined, based on predicted flow field data.

[0090] It is understandable that the coal seam mining prediction model generates coal seam mining simulation results, which include the simulation of the changes in force field, multiphase concentration field, temperature field, and flow field during the gasification process of the coal seam to be mined after coupling geological model, reaction model, heat transfer model and fluid transport model.

[0091] Step S350: Store the coal seam mining simulation results to the preset storage space.

[0092] Understandably, by using a coal seam mining prediction model to simulate the gasification reaction process, it is possible to more accurately control injection parameters such as the injection volume, injection pressure, and injection temperature of supercritical water, thereby optimizing the gasification process.

[0093] In some embodiments, the method for controlling coal seam mining further includes the following steps:

[0094] Step S410: Obtain the target flow rate of the target combustible gas in the coal seam to be mined.

[0095] Step S420: Determine the predicted combustible gas output by the coal seam mining prediction model that is consistent with the target flow rate of the target combustible gas.

[0096] Step S430: Send a control command to the coal seam mining injection device, the control command indicating the injection parameters corresponding to the predicted combustible gas.

[0097] Please see Figure 5 The following describes some of the above embodiments using an application scenario.

[0098] Figure 5 This diagram illustrates another application scenario of the coal seam mining control method according to an embodiment of this application. Figure 1 The difference lies in that the fluid also includes fuel and nitrogen. Injection well 21 further includes a fuel injection pipe 214 and a nitrogen injection pipe 213. Fuel injection pipe 214 is used to inject fuel, and an igniter (not shown) located deep in the coal seam ignites the coal. Nitrogen injection pipe 213 is used to inject nitrogen, which is used to protect the various pipes. Production well 22 also includes a cooling water pipe 222. Cooling water pipe 222 is used to inject cold water into the gasification chamber through a cooling water inlet to cool the temperature of the gasification chamber. Figure 5 Both injection well 21 and production well 22 shown are vertical well structures with a depth of 1000m. During well completion, a steel pipe is lowered into the connection between injection well 21 and production well 22 to support the well wall and ensure that the gasification channel in the horizontal section of injection well 21 is unobstructed.

[0099] Electronic device 10 obtains the target flow rate of the target combustible gas in the coal seam to be mined as 5000 m³. 3 / h, determine the predicted combustible gas output by the coal seam mining prediction model that matches the target flow rate. Then, send a control command to the coal seam mining injection device 20, indicating that the injection parameters corresponding to the predicted combustible gas are: the injection temperature of high-temperature water is 600℃, and the injection ratio of high-temperature water to oxygen is 1.3:1.

[0100] Next, during the coal seam gasification process of the coal seam to be mined, the electronic device 10 acquires coal seam measurement data and product measurement data from the coal seam mining monitoring device 30. The current reaction stage of coal seam gasification is determined based on the real-time measurement data. By comparing the real-time measurement data with preset measurement data corresponding to the reaction stage, the injection parameters of the coal seam mining injection device 20 are adjusted to ensure consistency between the real-time and preset measurement data. A control command is then sent to the coal seam mining injection device 20, indicating the adjusted injection parameters. The preset measurement data includes a pressure within the gasification chamber not exceeding 10 MPa and a minimum temperature not lower than 700°C.

[0101] After receiving the control command, the coal seam mining injection device 20 performs the following steps:

[0102] Step a1: Preheat the water at the formation surface to a high temperature of over 600℃ to form high-temperature water. Control the injection well to inject this high-temperature water into the deep coal seam of the coal seam to be mined.

[0103] The injected water can be industrial wastewater containing chloride ions and other components, which can effectively alleviate the pressure of water shortage during deep coal gasification and realize the recycling of water resources.

[0104] Understandably, given the high-pressure environment of deep coal seams, the injected high-temperature water will rapidly reach a supercritical state, transforming into supercritical water. It is also understandable that as the coal seam depth gradually increases, the geostress it experiences also continuously intensifies. When the coal seam depth reaches 2000m, the geostress can reach approximately 50MPa, and the stratum temperature will also rise significantly, reaching approximately 355.15K. This high-temperature, high-pressure underground environment provides ideal conditions for the formation of supercritical water. When the temperature exceeds 374.3K and the pressure is greater than 22.1MPa, the water enters a supercritical state, exhibiting physical and chemical properties completely different from normal water. Once supercritical water is successfully introduced into a deep coal seam, it needs to be continuously injected at a certain flow rate to ensure that the supercritical water can continuously participate in the subsequent reactions of coal gasification within the coal seam.

[0105] In another embodiment of step a1, an oxidizing agent such as oxygen is injected into the injection well. High-temperature water is then injected after step a2.

[0106] Understandably, after step a2, the combustion process of coal in deep coal seams releases a large amount of heat, raising the temperature of the coal seam above the supercritical temperature of water. At this point, if high-temperature water is injected, the water will rapidly transform into supercritical water in the high-temperature and high-pressure environment of the coal seam.

[0107] Understandably, the choice between preheating and generating heat through coal combustion can be made based on the actual situation, offering flexibility.

[0108] Understandably, when supercritical water is injected as a strong oxidant, it not only reduces the formation of tar and semi-coke and improves carbon gasification efficiency, but also helps maintain the persistence and stability of gasification. Its physicochemical properties and clearly defined gasification reaction zones (intense gas generation zone, supercritical water gasification reaction zone, pyrolysis reaction zone, and preheating zone) contribute to its ability to improve gasification efficiency and reduce pollutant emissions.

[0109] Step a2: Control the igniter to ignite the coal in the deep coal seam.

[0110] Step a3: During the vaporization process, control the pressure inside the vaporization chamber to not exceed 10 MPa and the minimum vaporization temperature to not be lower than 700℃.

[0111] It is understandable that the pressure inside the vaporization chamber does not exceed 10MPa and the minimum vaporization temperature is not lower than 700℃, which can ensure vaporization efficiency and gas production quality.

[0112] Step a4: Control the injection well according to the ratio of supercritical water to oxygen of 1.3:1, and inject supercritical water and oxygen into the deep coal seam.

[0113] Understandably, a supercritical water to oxygen ratio of 1.3:1 can optimize the gasification reaction, allowing the flow rate of combustible gas from the production well to reach 5000 m³ / s after the gasification process. 3 / h, the calorific value of the combustible gas produced is as high as 11MJ / Nm³. 3 This means that high-calorific-value combustible gases can be efficiently extracted from deep coal seams, with an oxygen utilization rate of 1100 MJ / kmol.

[0114] Understandably, traditional underground coal combustion gasification technology can create significant cavities within a short period, potentially leading to the collapse of the roof and floor strata. In contrast, by coordinating the injection of different proportions of supercritical water and oxygen, the supercritical water-injected coal gasification process allows for control over the gasification reaction, ensuring the stability of deep coal seam cavities. During this process, the reaction between the coal seam and supercritical water and oxygen causes the porous media framework to gradually disappear, and the gasification zone undergoes a long-distance evolution from pores to cavities. This evolution process keeps the overall deformation of the coal body and surrounding rock relatively stable, effectively preventing collapse.

[0115] Step a5: After the gasification process is completed, stop injecting oxygen and supercritical water into the injection well.

[0116] Step a6: Inject cooling water into the vaporization chamber until the temperature of the vaporization chamber drops to the preset temperature value.

[0117] Understandably, in order to lower the temperature inside the vaporization chamber and terminate the remaining reaction, cooling water is injected into the vaporization chamber until the temperature of the vaporization chamber drops to the preset temperature value, ensuring that all reactions completely stop.

[0118] The following are embodiments of the apparatus described in this application, which can be used to execute the embodiments of the method described in this application. For details not disclosed in the apparatus embodiments of this application, please refer to the embodiments of the method described in this application.

[0119] Figure 6 This is a schematic diagram of the control device for coal seam mining provided in this application; the device 40 can be integrated into the electronic device 10 in the above method embodiments. Figure 6 As shown, the control device 40 includes an acquisition module 41, a processing module 42, and a sending module 43.

[0120] The acquisition module 41 is used to acquire real-time measurement data from the coal seam mining monitoring device. The real-time measurement data includes coal seam measurement data and product measurement data during the coal seam gasification process.

[0121] Processing module 42 is used to determine the current reaction stage of coalbed gasification based on real-time measurement data.

[0122] The processing module 42 is also used to adjust the injection parameters of the coal seam mining injection device by comparing the real-time measurement data with the preset measurement data corresponding to the reaction stage.

[0123] The sending module 43 is used to send control commands to the coal seam mining injection device, and the control commands indicate the adjusted injection parameters.

[0124] In some embodiments, the processing module 42 is further configured to acquire preset measurement data corresponding to the reaction stage. If the real-time measurement data is inconsistent with the preset measurement data corresponding to the reaction stage, the injection parameters of the coal seam mining injection device are adjusted based on the pre-stored coal seam mining simulation results, the real-time measurement data, and the preset measurement data corresponding to the reaction stage. The coal seam mining simulation results are used to indicate the adjustment strategies corresponding to different types of measurement data.

[0125] In some embodiments, the processing module 42 is further configured to determine the type of injection parameter to be adjusted corresponding to the data type from the coal seam mining simulation results based on the inconsistent data types of the measurement data.

[0126] By comparing the magnitude of real-time measurement data with the preset measurement data corresponding to the reaction stage, the value of increasing or decreasing the injection parameter to be adjusted is determined.

[0127] In some embodiments, the processing module 42 is further configured to construct a coal seam mining prediction model, which is used to simulate the gasification process of the coal seam to be mined under different injection parameters. Different injection parameters are input into the coal seam mining prediction model. Prediction data output by the coal seam mining prediction model under different injection parameters is obtained. Coal seam mining simulation results are generated based on the prediction data. The coal seam mining simulation results are stored in a preset storage space.

[0128] The coal seam mining prediction model includes a geological model, a reaction model, a heat transfer model, and a fluid transport model. The geological model simulates the changes in the force field during the gasification process of the coal seam to be mined, based on injection parameters. The reaction model simulates the changes in the multiphase concentration field during the gasification process, based on injection parameters. The heat transfer model simulates the changes in the temperature field during the gasification process, based on injection parameters. The fluid transport model simulates the changes in the flow field during the gasification process, based on injection parameters.

[0129] In some embodiments, the calculation module 42 is further used to construct a geological model based on the continuity equation, the equilibrium equation, and the geometric equation of the isotropic elastoplastic coal seam skeleton, constructed from the mechanical properties of the coal seam and the stress-strain conditions of the coal seam skeleton. A reaction model is constructed based on the Arrhenius equation, and a heat transfer model is constructed based on the energy conservation formula, which characterizes the relationship between the temperature of the fluid and the heat conduction of the coal seam to be mined. A fluid transport model is constructed based on the Darcy's law algorithm.

[0130] The connectivity evaluation device 40 provided in this embodiment is used to execute the technical solution in any of the aforementioned method embodiments. Its implementation principle and technical effect are similar, and will not be described again here.

[0131] Figure 7 This is a schematic diagram of the structure of an electronic device provided in this application. Figure 7 As shown, the electronic device 10 includes:

[0132] Processor 11, memory 12, and communication interface 13;

[0133] The memory 12 is used to store the executable instructions of the processor 11;

[0134] The processor 11 is configured to execute the technical solution of the electronic device in any of the foregoing method embodiments by executing the executable instructions.

[0135] Optionally, the memory 12 can be either standalone or integrated with the processor 11.

[0136] Optionally, when the memory 12 is a device independent of the processor 11, the electronic device 10 may further include:

[0137] Bus 14, memory 12 and communication interface 13 are connected to processor 11 through bus 14 and complete communication with each other. Communication interface 13 is used to communicate with other devices.

[0138] Optionally, communication interface 13 can be implemented using a transceiver. The communication interface is used to enable communication between the database access device and other devices (e.g., clients, read-write databases, and read-only databases). The memory may include random access memory (RAM) and may also include non-volatile memory, such as at least one disk drive.

[0139] Bus 14 can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of representation, only one thick line is used in the diagram, but this does not indicate that there is only one bus or one type of bus.

[0140] The processors mentioned above can be general-purpose processors, including central processing units (CPUs), network processors (NPs), etc.; they can also be digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0141] The electronic device is used to execute the technical solution of the control device in any of the foregoing method embodiments. Its implementation principle and technical effect are similar, and will not be described again here.

[0142] This application also provides a readable storage medium storing a computer program thereon, which, when executed by a processor, implements the technical solutions provided in any of the foregoing embodiments.

[0143] This application also provides a computer program product, including a computer program, which, when executed by a processor, is used to implement the technical solutions provided in any of the foregoing method embodiments.

[0144] This application also provides a chip system applied to an electronic device. The chip system includes one or more processors, which are used to invoke computer instructions to cause the electronic device to implement the technical solutions provided in any of the foregoing method embodiments.

[0145] Those skilled in the art will understand that all or part of the steps of the above-described method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When executed, the program performs the steps of the above-described method embodiments; and the aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks.

[0146] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application.

Claims

1. A method for controlling coal seam mining, characterized in that the method... include: Acquire real-time measurement data from the coal seam mining monitoring device, including coal seam measurement data and product measurement data during the coal seam gasification process; The current reaction stage of coalbed gasification is determined based on the real-time measurement data. By comparing the real-time measurement data with the preset measurement data corresponding to the reaction stage, the injection parameters of the coal seam mining injection device are adjusted. A control command is sent to the coal seam mining injection device, the control command indicating the adjusted injection parameters.

2. The method according to claim 1, characterized in that, The step of adjusting the injection parameters of the coal seam mining injection device by comparing the real-time measurement data with the preset measurement data corresponding to the reaction stage includes: Obtain the preset measurement data corresponding to the reaction stage; If the real-time measurement data is inconsistent with the preset measurement data corresponding to the reaction stage, the injection parameters of the coal seam mining injection device are adjusted according to the pre-stored coal seam mining simulation results, the real-time measurement data, and the preset measurement data corresponding to the reaction stage. The coal seam mining simulation results are used to indicate adjustment strategies corresponding to different types of measurement data.

3. The method according to claim 2, characterized in that, The step of adjusting the injection parameters of the coal seam mining injection device based on the pre-stored coal seam mining simulation results, the real-time measurement data, and the preset measurement data corresponding to the reaction stage includes: Based on the inconsistent data types of the measurement data, determine the type of injection parameter to be adjusted corresponding to the data type from the coal seam mining simulation results; By comparing the magnitude of the real-time measurement data with the preset measurement data corresponding to the reaction stage, the value of increasing or decreasing the injection parameter to be adjusted is determined.

4. The method according to any one of claims 1 to 3, characterized in that, The method further includes: A coal seam mining prediction model is constructed, which is used to simulate the gasification process of the coal seam to be mined under different injection parameters; Different injection parameters are input into the coal seam mining prediction model; Obtain the prediction data output by the coal seam mining prediction model under different injection parameters; Based on the predicted data, generate coal seam mining simulation results; The coal seam mining simulation results are stored in a preset storage space.

5. The method according to claim 4, characterized in that, The coal seam mining prediction model includes a geological model, a reaction model, a heat transfer model, and a fluid transport model; The geological model is used to simulate the changes in the force field during the gasification process of the coal seam to be mined, based on the injection parameters. The reaction model is used to simulate the changes in the multiphase concentration field during the gasification process of the coal seam to be mined, based on the injection parameters. The heat transfer model is used to simulate the temperature field changes during the gasification process of the coal seam to be mined, based on the injection parameters. The fluid transport model is used to simulate the changes in the flow field during the gasification process of the coal seam to be mined, based on the injection parameters.

6. The method according to claim 5, characterized in that, The construction of the coal seam mining prediction model includes: The geological model is constructed based on the continuity equation, the equilibrium equation of the isotropic elastoplastic coal seam skeleton, and the geometric equation of the coal seam skeleton, which are constructed according to the mechanical properties of the coal seam and the stress-strain conditions of the coal seam skeleton. The reaction model was constructed based on the Arrhenius equation; The heat transfer model is constructed based on the energy conservation formula, which is used to characterize the relationship between the temperature of the fluid and the heat conduction of the coal seam to be mined. The fluid transport model is constructed based on Darcy's law algorithm.

7. The method according to any one of claims 1 to 6, characterized in that, The injection parameters include the injection pressure, injection temperature, injection volume, and injection rate of supercritical water and oxygen. The prediction data output by the coal seam mining prediction model includes the product prediction data and coal seam prediction data of the coal seam to be mined at each reaction stage.

8. A control device for coal seam mining, characterized in that, include: The acquisition module is used to acquire real-time measurement data from the coal seam mining monitoring device, including coal seam measurement data and product measurement data during the coal seam gasification process; The processing module is used to determine the current reaction stage of coalbed gasification based on the real-time measurement data; The processing module is also used to adjust the injection parameters of the coal seam mining injection device by comparing the real-time measurement data with the preset measurement data corresponding to the reaction stage. The sending module is used to send control commands to the coal seam mining injection device, wherein the control commands indicate the adjusted injection parameters.

9. An electronic device, characterized in that, include: Processor, memory, communication interface; The memory is used to store the executable instructions of the processor; The processor is configured to perform the method of any one of claims 1 to 7 by executing the executable instructions.

10. A readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the method of any one of claims 1 to 7.

Images