Coal seam gas content error correction method and system based on multi-stage measurement

Abstract

The invention discloses a multi-stage measurement coal seam gas content error correction method and system, and relates to the technical field of gas measurement, and the method comprises the following steps: constructing a five-stage measurement scheme based on fluid-solid-heat multi-field coupling, executing the five-stage measurement scheme on a target coal seam to measure the coal seam gas content, and obtaining original gas content data; a dual pore-fissure medium gas migration model is constructed to conduct simulated drilling on coal seam gas, and gas dynamic migration state parameters are obtained; loss analysis is carried out according to the gas dynamic migration state parameters, and the lost gas amount is obtained; and performing error correction on the original gas content data set based on the lost gas amount to obtain coal seam gas content data. The technical problems that in the prior art, gas content measurement errors are large, and loss cannot be accurately obtained are solved, and the technical effect of improving coal seam gas content measurement accuracy is achieved.

Description

Technical Field

[0001] This invention relates to the field of gas measurement technology, specifically to a method and system for correcting errors in coal seam gas content measurement through multiple stages. Background Technology

[0002] Determining coal seam gas content typically involves multiple stages, including sampling, desorption, and calculation. The conditions at each stage vary considerably, and the gas is affected by drilling disturbances, the complexity of the pore structure, and the characteristics of gas migration. Gas often inevitably dissipates before sampling. Due to the lack of accurate characterization of gas migration behavior, losses are mostly estimated empirically, failing to reflect the true pressure changes and flow patterns within the coal seam. This leads to significant discrepancies between the measured results and the actual content, affecting the reliability of gas resource assessment and safety prediction. Summary of the Invention

[0003] This application provides a method and system for correcting errors in coal seam gas content determination through multiple stages, which addresses the technical problems of large errors in gas content determination and inaccurate acquisition of loss in existing technologies.

[0004] In view of the above problems, this application provides a method and system for correcting errors in coal seam gas content determination in multiple stages.

[0005] The first aspect of this application provides a method for correcting errors in coal seam gas content determination through multiple stages, the method comprising:

[0006] A five-stage measurement scheme based on fluid-solid-thermal multi-field coupling was constructed. This scheme was then applied to the target coal seam to measure its gas content, obtaining raw gas content data. A dual-pore-fracture medium gas migration model was constructed to simulate gas migration in the coal seam, obtaining dynamic gas migration state parameters. Loss analysis was performed based on these parameters to obtain the amount of lost gas. Finally, error correction was applied to the raw gas content dataset based on the lost gas amount to obtain the coal seam gas content data.

[0007] A second aspect of this application provides a multi-stage measurement error correction system for coal seam gas content, the system comprising:

[0008] The measurement module is used to construct a five-stage measurement scheme based on fluid-solid-thermal multi-field coupling, and execute the five-stage measurement scheme on the target coal seam to measure the coal seam gas content and obtain the original gas content data; the simulated drilling module is used to construct a dual-pore-fracture medium gas migration model to simulate the drilling of coal seam gas and obtain the dynamic gas migration state parameters; the loss analysis module is used to perform loss analysis based on the dynamic gas migration state parameters to obtain the amount of lost gas; the error correction module is used to correct the error of the original gas content dataset based on the amount of lost gas to obtain the coal seam gas content data.

[0009] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0010] This application employs a five-stage measurement scheme based on fluid-solid-thermal multi-field coupling. The scheme is applied to a target coal seam to measure its gas content, obtaining raw gas content data. A dual-pore-fracture medium gas migration model is constructed to simulate gas migration within the coal seam, obtaining dynamic gas migration state parameters. Loss analysis is performed based on these parameters to determine the amount of lost gas. Finally, the raw gas content dataset is corrected for errors based on the lost gas amount to obtain the coal seam gas content data. This invention addresses the technical problems of large measurement errors and inaccurate loss measurement in existing technologies. By introducing a multi-field coupling measurement scheme and constructing a gas migration model for loss analysis and correction, the accuracy of coal seam gas content measurement is improved. Attached Figure Description

[0011] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0012] Figure 1 A schematic flowchart of a multi-stage measurement error correction method for coal seam gas content provided in this application embodiment;

[0013] Figure 2 This is a schematic diagram of a multi-stage coal seam gas content error correction system provided in an embodiment of this application.

[0014] Figure labeling: Measurement module 11, Simulation drilling module 12, Loss analysis module 13, Error correction module 14. Detailed Implementation

[0015] This application provides a method and system for correcting errors in coal seam gas content measurement through multi-stage measurement. It addresses the technical problems of large measurement errors and inaccurate loss acquisition in existing technologies by introducing a multi-field coupling measurement scheme and constructing a gas migration model for loss analysis and correction, thereby improving the accuracy of coal seam gas content measurement.

[0016] 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 a part of the embodiments of this application, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0017] It should be noted that any variation of the terms "comprising" and "having" is intended to cover non-exclusive inclusion, for example, a process, method, system, product, or server that includes a series of steps or units is not necessarily limited to those steps or units that are explicitly listed, but may include other steps or modules that are not explicitly listed or that are inherent to such processes, methods, products, or devices.

[0018] Example 1, as Figure 1 As shown, this application provides a method for correcting errors in coal seam gas content determination through multiple stages, the method comprising:

[0019] Step S100: Construct a five-stage measurement scheme based on fluid-solid-thermal multi-field coupling, and execute the five-stage measurement scheme on the target coal seam to measure the coal seam gas content and obtain the original gas content data.

[0020] Furthermore, the method provided in the application embodiment, which constructs a five-stage measurement scheme based on fluid-solid-thermal multi-field coupling, and performs the five-stage measurement scheme on the target coal seam to measure the coal seam gas content and obtain raw gas content data, also includes:

[0021] The five-stage measurement scheme includes measurement process information for the drilling stage, sampling stage, desorption stage, loss calculation stage, and total content calculation stage. Based on the target coal seam, the coal seam gas content is measured according to the drilling stage measurement process information to obtain a multi-dimensional drilling dataset. Based on the multi-dimensional drilling dataset, the coal seam gas content is measured according to the sampling stage measurement process information to obtain a coal core sample dataset. Based on the coal core sample dataset, the coal seam gas content is measured according to the desorption stage measurement process information to obtain a desorption kinetics dataset. Based on the desorption kinetics dataset, the coal seam gas content is measured according to the loss calculation stage measurement process information to obtain a gas loss dataset. Based on the gas loss dataset, the coal seam gas content is measured according to the total content calculation stage measurement process information to obtain the original gas content dataset.

[0022] In this embodiment, a five-stage measurement scheme is first constructed based on fluid-solid-thermal multi-field coupling. During this process, the coupling relationship between the gas pressure field, coal stress field, and temperature field is jointly analyzed, considering the fluid transport response, solid deformation response, and temperature change response exhibited by the target coal seam during drilling disturbance. This analysis identifies the mutual influence of different physical fields during drilling, sampling, desorption, and loss occurrence. Based on the results of this coupling analysis, the types of parameters to be monitored, data acquisition methods, time series density, and boundary control conditions for each stage are determined. This establishes measurement process information for the drilling stage, sampling stage, desorption stage, loss calculation stage, and total content calculation stage, forming a five-stage measurement scheme reflecting the characteristics of multi-field coupling.

[0023] When measuring the gas content of a coal seam based on the drilling stage measurement process information, a multi-dimensional drilling dataset is formed under the guidance of the drilling stage measurement process information. This dataset includes multiple parameters such as drilling speed changes, cuttings production, pressure disturbance amplitude, and temperature gradient, through steps such as drilling equipment propulsion operation, continuous cuttings collection, bottom hole pressure parameter monitoring, and borehole temperature change recording.

[0024] When determining the gas content of coal seams based on a multidimensional drilling dataset and following the sampling stage measurement process, steps such as core sampling, core segmentation, rapid core sealing, and temperature-controlled preservation are used to ensure the integrity of the core structure is not damaged secondaryly, thus forming a coal core sample dataset. The coal core sample dataset records key parameters such as core depth, sealing time, core density, moisture content, and temperature control conditions.

[0025] Next, based on the coal core sample dataset, the gas content of the coal seam was determined according to the desorption stage measurement process information. The coal core was placed in the desorption device, and the desorbed gas volume at different time points was recorded at regular intervals. The temperature and pressure difference changes during the desorption process were monitored simultaneously to form a desorption kinetic dataset with time series characteristics.

[0026] Subsequently, based on the desorption kinetics dataset, the gas content of the coal seam was measured according to the loss calculation stage measurement process information. The exposure period of the core sample was determined by the time records of the multi-dimensional drilling dataset formed during the drilling stage and the coal core sample dataset. With the change trend of early desorption in the desorption kinetics dataset as a reference, the situation of the same time period was compared with the borehole temperature and pressure changes to determine the gas escape rate, and the escape amount of different time periods was continuously accumulated. Then, the accumulated results were checked by combining the core sealing time and rock cuttings production characteristics to form the gas loss dataset.

[0027] Finally, based on the gas loss dataset, the coal seam gas content was measured according to the measurement process information of the total content calculation stage. The desorption amount obtained from the desorption kinetics dataset, the residual amount obtained after core fragmentation, and the loss amount in the gas loss dataset were uniformly converted into volume data under the same conditions. The three volumes were summed, and the consistency of the overall data was checked in combination with temperature and pressure records, and finally the original gas content dataset was formed.

[0028] Step S200: Construct a dual-pore-fracture medium gas migration model to simulate coal seam gas drilling and obtain gas dynamic migration state parameters.

[0029] Furthermore, the method provided in the application embodiments, which constructs a dual-pore-fracture medium gas migration model to simulate coal seam gas drilling and obtain gas dynamic migration state parameters, also includes:

[0030] Geological exploration is conducted based on the target coal seam to determine its geological structure data. Borehole analysis is performed based on the multi-dimensional drilling dataset to determine the core data of the target coal seam. Well logging data is retrieved and combined with the core data for pore analysis to construct a pore network, which includes pore structure features. Fracture analysis is performed based on well logging data and the geological structure data to construct a fracture network, which includes fracture structure features. Three-dimensional modeling is performed based on the pore structure features and fracture structure features to construct a dual-pore-fracture medium gas migration model, which includes dual-medium geometric parameters. Multi-field coupled numerical simulation is performed based on the dual-pore-fracture medium gas migration model and the dual-medium geometric parameters to obtain the dynamic gas migration state parameters.

[0031] In this embodiment of the application, when constructing a dual-pore-fracture medium gas migration model to simulate coal seam gas drilling, geological exploration is first conducted based on the target coal seam. A borehole logging method is used to identify the coal seam's attitude by recording lithological changes, bedding plane contact relationships, coal seam thickness, structural plane distribution, and joint orientation during drilling. Borehole logging records core column information meter by meter, marking the coal seam's stability in the vertical and horizontal directions, structural morphology, fault locations, and interlayer interface characteristics, thereby forming geological structural data including dip angle, strike, layer thickness, and structural distribution.

[0032] Subsequently, borehole analysis was performed based on a multidimensional drilling dataset. This process employed cuttings feature analysis, observing changes in cuttings size, output, and coal cuttings color during drilling to identify the specific depth at which the drill bit entered the coal seam. The hardness of the coal body was also assessed in conjunction with changes in drilling speed. Cuttings feature analysis, through continuous collection of cuttings samples and their chronological correspondence to drilling depths, clearly distinguished coal seam sections, interbedded rock sections, and fractured zones, thereby obtaining borehole coring data for the coal seam section, including information such as coal seam location, coring integrity, and the degree of coal body fracture.

[0033] Next, well logging data was retrieved and combined with borehole coring data for porosity analysis. This process employed nuclear magnetic resonance (NMR) logging, which measured response signals at different pore scales to classify pores into micropores, fine pores, and macropores. The degree of pore connectivity was then determined by analyzing the attenuation patterns of the echo sequences. NMR logging directly reflects the size, quantity, and connectivity of pores, and correlates this with pore development observed in borehole coring data, thus constructing a pore network. This pore network includes pore structural characteristics, such as pore size range, pore volume distribution, and pore connectivity paths.

[0034] Subsequently, when performing fracture analysis based on well logging data and the aforementioned geological structural data, borehole television imaging was employed. This involved placing an imaging device inside the borehole to acquire the fracture aperture, dip angle, extension direction, and fracture surface morphology. Borehole television imaging can visually record the location and geometry of fractures on the borehole wall and cross-reference them with the joint orientation and fault locations recorded in the geological structural data, thereby constructing a fracture network. This fracture network includes fracture structural characteristics, including fracture aperture, fracture orientation, fracture number, and fracture connectivity.

[0035] Next, when performing 3D modeling based on the pore structure characteristics and the fracture structure characteristics, a digital core reconstruction method is adopted. By spatially overlaying the pore network and the fracture network, a 3D geometric reconstruction of the pore volume and fracture volume is performed, generating a digital model with a dual structure of matrix medium and fracture medium. Digital core reconstruction performs voxel modeling based on pore size, fracture aperture, and their spatial location, thereby constructing a dual-pore-fracture medium gas transport model, and forming dual medium geometric parameters in the model including pore size, fracture direction, and connectivity paths.

[0036] Finally, based on the dual-porosity-fracture medium gas transport model, multi-field coupled numerical simulations were performed according to the geometric parameters of the dual media. Initial and boundary conditions were set to constrain and start the model. Within the dual-porosity-fracture medium gas transport model, fluid transport simulation, solid deformation simulation, and heat transfer simulation were sequentially performed, generating the first, second, and third simulated numerical values, respectively. Subsequently, multiphysics iterative coupling was performed on the first, second, and third simulated numerical values, enabling coordinated solutions for fluid transport, solid deformation, and heat transfer within the same computational framework, thereby generating the dynamic gas transport state parameters.

[0037] Furthermore, in the method provided in the application embodiment, the gas dynamic migration state parameters are obtained by performing multi-field coupled numerical simulation based on the dual-pore-fracture medium gas migration model according to the geometric parameters of the dual medium, and the simulation is performed according to the geometric parameters of the dual medium. The method further includes:

[0038] Initial and boundary conditions for multi-field coupled numerical simulation are set; the boundary conditions are used as constraints, and the gas transport model of the dual-pore-fracture medium is activated according to the initial conditions to perform fluid-solid-thermal multi-field coupled numerical simulation: fluid transport simulation is performed based on the geometric parameters of the dual medium to obtain the first simulation value; solid deformation simulation is performed based on the geometric parameters of the dual medium to obtain the second simulation value; heat transfer simulation is performed based on the geometric parameters of the dual medium to obtain the third simulation value; the first simulation value, the second simulation value, and the third simulation value are iteratively coupled in a multiphysics field to obtain the gas dynamic transport state parameters.

[0039] In this embodiment, when setting the initial and boundary conditions for the multi-field coupled numerical simulation, the initial distributions of the fluid pressure field, stress field, and temperature field are assigned to all computational units of the dual-pore-fracture medium gas transport model. The initial distribution of the fluid pressure field is determined based on the on-site gas pressure and coal seam depth; the initial distribution of the stress field is based on the results of geostress measurements, providing vertical and horizontal stress components; and the initial distribution of the temperature field is determined based on the geothermal gradient and the thermal conductivity characteristics of the surrounding rock. Simultaneously, time-varying pressure boundaries, displacement constraints, and temperature boundaries are set at the outer boundary of the model and the borehole wall to reproduce the pressure release, stress redistribution, and temperature disturbances induced by drilling.

[0040] After applying boundary conditions as constraints, the dual-porosity-fracture medium gas transport model is activated according to the initial conditions, entering the fluid-solid-thermal multi-field coupled numerical simulation process. In this process, fluid transport simulation is first performed based on the dual-medium geometric parameters. Pressure updates and volumetric flux are calculated step-by-step on discrete grids of the pore and fracture networks, yielding the first simulated values. These first simulated values ​​characterize the pressure distribution, velocity distribution, and mass exchange of gas in the pore and fracture media. Subsequently, solid deformation simulation is performed based on the dual-medium geometric parameters. The pressure changes in the first simulated values ​​are converted into effective stress changes. The displacement field is solved, and the stress field, fracture aperture, and pore volume fraction are updated, yielding the second simulated values. These second simulated values ​​characterize the deformation of the coal structure and the geometric adjustment of the seepage channels. Next, heat transfer simulation is performed based on the dual-medium geometric parameters. The conduction and convection processes of temperature over time are calculated on the same grid, and the temperature field is updated, yielding the third simulated values. These third simulated values ​​characterize the temperature distribution and its impact on gas transport capacity and the thermal response of the coal body.

[0041] Finally, the first, second, and third simulated values ​​are subjected to multiphysics iterative coupling within the same time step. During this process, pressure changes generated by the first simulated value drive stress adjustments and displacement updates in the second simulated value. Changes in fracture aperture and pore volume fraction given by the second simulated value inversely correct the seepage path and mass exchange in the first simulated value. Temperature changes in the third simulated value simultaneously affect gas viscosity and diffusion capacity and promote thermal expansion and contraction of the coal body, thus further impacting the first and second simulated values. After each round of coupling, residual checks are performed on the pressure, displacement, and temperature fields, as well as consistency checks on mass and energy conservation. If convergence requirements are not met, iteration continues; if they are met, the process proceeds to the next time step. After all time steps are completed, the coupling results are summarized to form gas dynamic migration state parameters.

[0042] Step S300: Perform loss analysis based on the gas dynamic transport state parameters to obtain the amount of lost gas.

[0043] Furthermore, in the method provided in the application embodiment, the loss analysis based on the gas dynamic migration state parameters to obtain the amount of lost gas also includes:

[0044] Based on the gas dynamic migration parameters, gas pressure evolution analysis is performed to draw a gas pressure trend map; the gas pressure trend map is traversed to identify the critical point of decline and determine the loss initiation position; drilling process parameters are introduced in conjunction with the loss initiation position to perform drilling analysis and obtain loss duration parameters; based on the loss initiation position and the loss duration parameters, the gas pressure trend map is tracked to identify the gas decay stage; loss analysis is performed based on the gas decay stage to obtain the amount of gas lost ahead of schedule; gas migration analysis is performed through the pore network to obtain matrix adsorbed gas parameters, and gas migration analysis is performed through the fracture network to obtain fracture free gas parameters; the contribution analysis of the matrix adsorbed gas parameters and fracture free gas parameters to the total loss is performed to calculate the contribution ratio; the amount of gas lost ahead of schedule and the contribution ratio are integrated to construct the total gas loss amount.

[0045] In this embodiment, when performing gas pressure evolution analysis based on gas dynamic migration state parameters, the gas pressure data in the gas dynamic migration state parameters are first processed into a time series, including standardizing time intervals, removing abnormal peaks, smoothing the data using the moving average method, and then plotting a gas pressure trend diagram in chronological order. The gas pressure trend diagram is used to reflect the continuous evolution process of gas pressure inside the dual-pore-fracture medium.

[0046] Next, when identifying the critical point of decline by traversing the gas pressure trend chart, the pressure change rate at each time point is calculated, and it is compared whether the change rate meets the preset decline threshold. The first time point that continuously meets the decline threshold is selected as the critical point of decline. To avoid misjudgment caused by noise signals, a neighborhood window consistency check is used. The critical point of decline corresponds to the position where the gas pressure first shows a stable decline, and this position is determined as the starting point of the loss.

[0047] Subsequently, when incorporating drilling process parameters into the analysis of the loss initiation position, the timestamp of the loss initiation position is aligned with the drilling speed curve, pump rate change record, torque record, and drilling method (e.g., conventional or intermittent drilling). The alignment result determines the specific drilling stage corresponding to the loss initiation position, thereby calculating the loss duration parameter. This loss duration parameter represents the exposure time from the loss initiation position to the completion of core sealing. For example, if the borehole reaches the coal seam level at time T1 and completes core sealing at time T2, and the descent critical point corresponds to T1+Δt between T1 and T2, then the loss duration parameter is (T2–(T1+Δt)).

[0048] Next, the gas pressure trend chart is tracked based on the parameters of the loss initiation position and loss duration. In this process, the time period from the loss initiation position across the loss duration parameter is extracted from the gas pressure trend chart as an analysis window, and the decreasing pattern of gas pressure over time within this window is identified point by point. By judging the magnitude of pressure decrease over time, the decay rate, and the presence of secondary oscillations, the gas decay stage is identified.

[0049] Subsequently, a loss analysis was conducted based on the gas decay stage. This process first calculated the gas emission behavior based on the pressure change characteristics during the gas decay stage, forming the gas emission rate. Then, using the loss duration parameter as the time interval, the gas emission rate was integrated to obtain the total emitted gas volume. Next, the total emitted gas volume was verified and corrected using ambient temperature change data to eliminate the influence of temperature fluctuations on the emission volume, ultimately obtaining the amount of gas lost ahead of schedule.

[0050] Next, gas transport analysis is performed using a pore network to obtain matrix-adsorbed gas parameters. In this process, the pore network is divided into nodes and connected units. At the initial moment of analysis, each node is assigned an initial amount of adsorbed gas and an initial pressure based on the distribution of adsorbed gas, and gas diffusion calculations are performed at fixed time steps. Within each time step, the amount of gas diffused between nodes is calculated based on the pressure difference and the pore connectivity area, and the amount of adsorbed gas at each node is updated progressively. The amount of gas output from nodes connected to the outer boundary to the boundary accumulates over time and is considered as the desorption amount of matrix-adsorbed gas. Simultaneously, the sequence of connected units where gas transport occurs is recorded as the matrix-adsorbed gas transport path. After the above calculations are completed, the matrix-adsorbed gas parameters are output.

[0051] Simultaneously, gas migration analysis is performed using a fracture network to obtain fracture free gas parameters. In this process, the fracture network is divided into nodes and connected units. At the initial moment, each node is assigned an initial free gas quantity and initial pressure based on the amount of free gas in the fracture, and seepage calculations are performed at fixed time steps. In each time step, the gas flow rate between nodes is calculated based on the pressure difference and fracture aperture, and the free gas quantity of each node is updated progressively. The gas flow rate output from nodes leading to the borehole area to the borehole boundary accumulates over time, forming the amount of fracture free gas escaping. At the same time, the sequence of connected units where seepage occurs is recorded as the fracture free gas migration path. After the above calculations are completed, the fracture free gas parameters are output.

[0052] Next, when analyzing the contribution of matrix-adsorbed gas parameters and fracture-free gas parameters to the total loss, the desorption amount of matrix-adsorbed gas and the emission amount of fracture-free gas are calculated respectively within the time interval corresponding to the loss duration parameter. Then, the two types of values ​​are compared with the amount of gas lost ahead of time, and the contribution ratio of matrix-adsorbed gas loss to fracture-free gas loss is obtained through proportional calculation.

[0053] Finally, when integrating the advance gas loss amount with the contribution ratio, the advance gas loss amount is used as the base value and decomposed into matrix adsorbed gas loss amount and fracture free gas loss amount according to the contribution ratio. The values ​​obtained from the segmented exposure intervals are accumulated to form the gas loss amount.

[0054] Furthermore, in the method provided in the application embodiment, the loss analysis based on the gas attenuation stage to obtain the amount of advanced loss gas also includes:

[0055] The gas emission rate is obtained by calculating the gas emission rate according to the gas decay stage; the gas emission rate is integrated based on the loss duration parameter to obtain the total emitted gas volume; the total emitted gas volume is verified in combination with ambient temperature change data, and the total emitted gas volume is corrected according to the verification results to obtain the advanced loss gas amount.

[0056] In this embodiment, when calculating gas emission according to the gas decay stage, the data on pressure decrease over time during the gas decay stage is used as input. A volume conversion method based on the relationship between pressure change and gas compressibility in a dual-pore-fracture medium is employed to convert the pressure decrease at each time step into a gas volume change. Then, a division operation is performed on the volume change with the time step length to obtain the gas emission rate. The gas emission rate represents the volume of gas emitted per unit time during the gas decay stage.

[0057] Next, when integrating the gas escape rate based on the loss duration parameter, the time interval defined by the loss duration parameter is used as the integration range, and the gas escape rates corresponding to each time step within this range are accumulated in chronological order to form the total escaped gas volume. The total escaped gas volume reflects the actual scale of gas migration and loss from the dual-pore-fracture medium towards the borehole during the loss duration.

[0058] Finally, when verifying the total escaping gas volume in conjunction with ambient temperature change data, the total escaping gas volume and the ambient temperature records corresponding to the duration of loss were compared hourly. Specifically, firstly, using a reference temperature as a baseline, the ambient temperature was converted to absolute temperature. Based on the direct proportional relationship between gas volume and temperature, the escaping volume at each time point was converted to temperature, ensuring that the converted volumes could be compared under uniform temperature conditions. Then, the converted volume sequence was compared with the pressure decrease trend during the gas decay phase in the gas pressure trend chart. By comparing the degree of matching between the volume change trend and the pressure decrease trend, a verification result was formed. If the verification result showed a difference between the volume change amplitude and the pressure decrease amplitude within the same time interval, the total escaping gas volume was adjusted according to the proportional relationship between the volume difference before and after temperature conversion, ensuring that the adjusted volume change was consistent with the pressure decrease pattern. If the verification result showed that the change trend of the converted volume was consistent with the pressure decay trend, the converted volume was directly used as the correction volume. Finally, the adjusted volume result was taken as the amount of advanced gas loss.

[0059] Furthermore, in the method provided in the application embodiments, the contribution analysis of the total loss based on the matrix adsorbed gas parameters and the fracture free gas parameters, and the calculation of the contribution ratio, further includes:

[0060] The gas migration path is analyzed based on the matrix-adsorbed gas parameters to obtain the matrix-adsorbed gas migration path; the gas migration path is also analyzed based on the fracture-free gas parameters to obtain the fracture-free gas migration path; the desorption amount of the matrix-adsorbed gas parameters is calculated based on the gas dynamic migration state parameters and the fracture-free gas migration path; the emission amount of the fracture-free gas parameters is calculated based on the gas dynamic migration state parameters and the fracture-free gas migration path; and the contribution ratio of the fracture-free gas loss to the matrix-adsorbed gas loss is calculated based on the desorption amount of the matrix-adsorbed gas parameters and the emission amount of the fracture-free gas parameters.

[0061] In this embodiment, when analyzing the gas migration path based on matrix-adsorbed gas parameters, the pore network is divided into pore nodes and pore interconnection units. Each pore node is assigned an initial adsorbed gas quantity and its corresponding pressure value according to the matrix-adsorbed gas parameters. The calculation is then performed sequentially at fixed time steps. In each time step, the pressure values ​​of adjacent pore nodes are read, and the pressure gradient is obtained by dividing the pressure difference between adjacent nodes by the interconnection distance between nodes. The pressure gradient is then multiplied by the interconnection area of ​​the pore interconnection unit to obtain the diffusion volume for that time step. The diffusion volume is subtracted from the nodes with higher pressure and added to the nodes with lower pressure. By repeating the above calculation for multiple time steps, all pore interconnection units that actually diffused are recorded in chronological order to form a pore diffusion sequence, which is the matrix-adsorbed gas migration path.

[0062] Subsequently, when analyzing the gas migration path based on fracture free gas parameters, the fracture network was divided into fracture nodes and fracture connected units. Each fracture node was assigned an initial free gas quantity and its corresponding pressure value according to the fracture free gas parameters. The calculation proceeded within a fixed time step. At each time step, the pressure values ​​of adjacent fracture nodes were read. The pressure gradient was obtained by dividing the pressure difference between adjacent nodes by the connection distance between nodes. The pressure gradient was then multiplied by the fracture aperture and the cross-sectional area of ​​the connection to obtain the seepage volume for that time step. The seepage volume was subtracted from nodes with higher pressure and added to nodes with lower pressure. If the seepage direction pointed towards the borehole boundary, the seepage volume was recorded as the boundary seepage flow. After multiple time steps of calculation, all fracture connected units where actual seepage occurred were arranged in chronological order to form a fracture seepage sequence, which is the fracture free gas migration path.

[0063] Subsequently, when calculating the desorption amount of matrix-adsorbed gas parameters based on the dynamic gas migration state parameters and the matrix-adsorbed gas migration path, the pressure change in the dynamic gas migration state parameters is mapped one-to-one to the pore nodes in the matrix-adsorbed gas migration path. At each time step, the pressure change at each pore node is read, and the relationship between the pressure change and the volume change of the adsorbed gas is converted to obtain the volume change at that node. This volume change is then allocated to the corresponding pore connectivity unit to obtain the diffusion volume for that time step. The diffusion volumes at each time step are accumulated, and the diffusion volumes reaching the boundary in all time steps are added together to obtain the desorption amount of the matrix-adsorbed gas parameters.

[0064] When calculating the emission amount of fracture-free gas parameters based on the dynamic gas migration state parameters and the fracture-free gas migration path, the pressure distribution and pressure gradient in the dynamic gas migration state parameters are correlated with the fracture nodes and fracture connectivity units in the fracture-free gas migration path. In each time step, the pressure gradient between fracture nodes is read, and the pressure gradient is multiplied by the fracture aperture and connectivity cross-sectional area to obtain the seepage volume. The seepage volume is then divided by the time step length to obtain the seepage rate, and the seepage rate is multiplied by the time step length to obtain the emission volume for that time step. The emission volumes of all time steps are accumulated to obtain the emission amount of fracture-free gas parameters.

[0065] Finally, when calculating the contribution ratio of fracture free gas loss to matrix-adsorbed gas loss based on the desorption amount of matrix-adsorbed gas parameters and the emission amount of fracture free gas parameters, the desorption amount of matrix-adsorbed gas parameters and the emission amount of fracture free gas parameters are used as two numerical inputs. First, the two are added together to obtain the total loss. Then, the desorption amount of matrix-adsorbed gas parameters is divided by the total loss to obtain the proportion of matrix-adsorbed gas loss in the total loss. The emission amount of fracture free gas parameters is divided by the total loss to obtain the proportion of fracture free gas loss in the total loss. Thus, the contribution ratio of fracture free gas loss to matrix-adsorbed gas loss is formed.

[0066] Step S400: Based on the lost gas amount, perform error correction on the original gas content dataset to obtain coal seam gas content data.

[0067] Furthermore, in the method provided in the application embodiment, the method further includes: correcting the original gas content dataset based on the lost gas quantity to obtain coal seam gas content data;

[0068] The initial gas loss is obtained by parsing the original gas content dataset. The initial gas loss is then replaced by the original gas loss: the difference between the original and the original gas loss is calculated to obtain a numerical difference parameter. When the numerical difference parameter is greater than a preset difference threshold, a replacement instruction is generated. The original gas content dataset is replaced with the gas loss according to the replacement instruction, generating a data replacement result. The data replacement result is then summed and verified. When the verification passes, the coal seam gas content data is generated.

[0069] In this embodiment, when correcting the error of the original gas content dataset based on the amount of gas loss, the dataset is first analyzed. This process involves reading each recorded volume from the original gas content dataset: the gas escape volume during the drilling stage, the gas loss volume during the sampling stage, the gas release volume during the desorption stage, and the gas volume during the total content calculation stage. A volume conversion method is then used to convert these gas volumes according to uniform temperature and pressure conditions, ensuring a consistent measurement basis for the gas volumes recorded at different stages. Subsequently, the converted gas escape volume during the drilling stage, the gas loss volume during the sampling stage, and the gas release volume during the desorption stage are sequentially added together to obtain the initial amount of gas loss.

[0070] Then, the difference between the lost gas quantity and the initial lost gas quantity is calculated. That is, the difference is calculated by subtracting the initial lost gas quantity from the lost gas quantity.

[0071] The numerical difference parameter is then compared with a preset difference threshold. When the numerical difference parameter exceeds the preset difference threshold, a replacement instruction is generated. The corresponding field for the loss amount is located in the original gas content dataset, and the initial loss gas amount in that field is replaced with the loss gas amount, forming a data replacement result. A change record is generated simultaneously with the replacement, including the volume before replacement, the volume after replacement, and the difference.

[0072] Finally, the results of the data replacement are summed and verified. In this process, the volume of the data replacement results is first summed with the corresponding volume entries in the original gas content dataset to obtain a first sum. Then, coal seam geological conditions and historical gas content data are retrieved to extract the upper and lower limits of gas content, forming a preset gas content range. The first sum is then compared with this preset gas content range to determine if it is within a reasonable range. When the first sum exceeds the preset gas content range, a verification mode is triggered. This mode performs an accuracy analysis of the lost gas quantity and, based on the analysis results, re-runs the dual-pore-fracture medium gas migration model to update the lost gas quantity and form an optimized lost gas quantity. Subsequently, the optimized lost gas quantity is correlated with drilling time parameters to construct an exponential relationship model. This model is then used to sum the optimized lost gas quantity with the original gas content dataset to obtain a second sum. Finally, the second sum is compared with the preset gas content range. If the second summation value still exceeds the preset gas content range, the iterative verification mode is entered to continue the aforementioned analysis and update process; when the second summation value falls into the preset gas content range, it is determined that the corrected loss gas amount and the data replacement result meet the gas content balance requirements, the verification is passed, and coal seam gas content data is generated.

[0073] Furthermore, in the method provided in the application embodiment, the addition verification is performed based on the data replacement result, and when the verification passes, the coal seam gas content data is generated, which further includes:

[0074] Based on the data replacement results, the original gas content dataset is summed to obtain a first sum value. The upper and lower limits of gas content are extracted from coal seam geological conditions and historical gas content data, and a preset gas content range is set. The first sum value is compared with the preset gas content range. If the sum value exceeds the preset gas content range, the verification fails, and a review mode is initiated. The accuracy of the lost gas amount is analyzed using the review mode. Based on the analysis results, the dual-pore-fracture medium gas migration model is re-run to simulate and update the lost gas amount, obtaining an optimized lost gas amount. The optimized lost gas amount is analyzed in relation to drilling time parameters to construct an exponential relationship model. The optimized lost gas amount is summed with the original gas content dataset using the exponential relationship model to generate a second sum value. If the second sum value exceeds the preset gas content range, the verification fails, and the review mode is iterated. If the second sum value is within the preset gas content range, the correction is confirmed to be effective, the verification passes, and coal seam gas content data is generated.

[0075] In this embodiment of the application, when summing the data replacement results with the original gas content dataset, firstly, under uniform temperature and pressure conditions, the amount of lost gas in the data replacement results and the amount of desorbed gas and residual gas in the original gas content dataset are read item by item. The three gas volumes are converted to the same reference conditions using a volume conversion method. Then, the three converted gas volumes are added sequentially using a direct volume addition method to obtain the first sum value.

[0076] Subsequently, when retrieving coal seam geological conditions and historical gas content data to extract the upper and lower limits of gas content, the burial depth, pressure gradient, gas pressure record, porosity statistics, and gas content measurements of adjacent test mining points of the target coal seam were read from the historical dataset. These data were integrated according to the corresponding geological units, and the maximum gas content value was extracted from the integrated value range as the upper limit of gas content and the minimum gas content value as the lower limit of gas content to form a preset gas content range.

[0077] Then, when comparing the first summed value with the preset gas content range, the first summed value is compared sequentially with the upper and lower limits of the gas content through range determination. If the first summed value exceeds the preset gas content range, the summation verification is deemed unsuccessful and a review mode is initiated. In the review mode, the accuracy of the lost gas amount is analyzed. By jointly comparing the gas dynamic migration state parameters, loss duration parameters, and gas pressure trend chart, the deviation between the lost gas amount and the theoretical gas attenuation mode is calculated. Based on the deviation, the reasons for the excessive or insufficient lost gas amount are identified, forming the analysis results.

[0078] Next, based on the analysis results, the dual-pore-fracture medium gas transport model was re-run for simulation. The deviation direction and magnitude in the analysis results were mapped to the input conditions of the dual-pore-fracture medium gas transport model, including the initial gas pressure distribution, fracture connectivity, pore diffusion rate parameters, and borehole exposure boundary conditions. The fluid transport simulation, solid deformation simulation, and heat transfer simulation were then re-executed with the adjusted inputs. Through this simulation process, the dynamic gas transport state parameters were recalculated to obtain a new gas emission process, and the updated gas loss amount, i.e., the optimized gas loss amount, was derived.

[0079] Next, we analyzed and optimized the parameters of gas loss and drilling time. By reading the drilling speed, drilling depth, and stoppage segment information from the drilling time parameters, we used a time series alignment method to map the change sequence of optimized gas loss to the drilling time series one by one. By calculating the proportional relationship between the rate of change of optimized gas loss and the rate of change of drilling time in different time periods, we identified the pattern of gas loss changing with the drilling process, and constructed an exponential relationship model using an exponential fitting method.

[0080] Subsequently, the optimized gas loss amount is summed with the original gas content dataset using an exponential relationship model. The gas loss amount under the same time window is recalculated using the exponential relationship model. The volume of this gas loss amount is then converted with the desorbed gas amount and residual gas amount in the original gas content dataset under a unified reference condition. The volume summation step is then performed to obtain the second summation value.

[0081] If the second summed value exceeds the preset gas content range, the summation verification fails again through the range determination step, and the process enters the iterative verification mode. In the iterative verification mode, the accuracy analysis step, the analysis result generation step, the re-running step of the dual-pore-fracture medium gas migration model, the optimization step of generating lost gas quantity, and the exponential relationship model construction step are repeated to improve the lost gas quantity. If the second summed value is within the preset gas content range, the correction result is confirmed to be reasonable through the range determination step, the summation verification is determined to pass, and the second summed value is output as the coal seam gas content data.

[0082] In summary, the embodiments of this application have at least the following technical effects:

[0083] This application employs a five-stage measurement scheme based on fluid-solid-thermal multi-field coupling. The scheme is applied to a target coal seam to measure its gas content, obtaining raw gas content data. A dual-pore-fracture medium gas migration model is constructed to simulate gas migration within the coal seam, obtaining dynamic gas migration state parameters. Loss analysis is performed based on these parameters to determine the amount of lost gas. Finally, the raw gas content dataset is corrected for errors based on the lost gas amount to obtain the coal seam gas content data. This invention addresses the technical problems of large measurement errors and inaccurate loss measurement in existing technologies. By introducing a multi-field coupling measurement scheme and constructing a gas migration model for loss analysis and correction, the accuracy of coal seam gas content measurement is improved.

[0084] Example 2, based on the same inventive concept as the multi-stage measurement error correction method for coal seam gas content in the foregoing examples, such as... Figure 2 As shown, this application provides a multi-stage measurement error correction system for coal seam gas content. The system and method embodiments in this application are based on the same inventive concept. The system includes:

[0085] Measurement module 11 is used to construct a five-stage measurement scheme based on fluid-solid-thermal multi-field coupling, and execute the five-stage measurement scheme on the target coal seam to measure the coal seam gas content and obtain the original gas content data; simulation drilling module 12 is used to construct a dual-pore-fracture medium gas migration model to simulate drilling of coal seam gas and obtain gas dynamic migration state parameters; loss analysis module 13 is used to perform loss analysis based on the gas dynamic migration state parameters to obtain the amount of lost gas; error correction module 14 is used to perform error correction on the original gas content dataset based on the amount of lost gas to obtain coal seam gas content data.

[0086] Furthermore, the system is also used to implement the following functions:

[0087] The five-stage measurement scheme includes measurement process information for the drilling stage, sampling stage, desorption stage, loss calculation stage, and total content calculation stage. Based on the target coal seam, the coal seam gas content is measured according to the drilling stage measurement process information to obtain a multi-dimensional drilling dataset. Based on the multi-dimensional drilling dataset, the coal seam gas content is measured according to the sampling stage measurement process information to obtain a coal core sample dataset. Based on the coal core sample dataset, the coal seam gas content is measured according to the desorption stage measurement process information to obtain a desorption kinetics dataset. Based on the desorption kinetics dataset, the coal seam gas content is measured according to the loss calculation stage measurement process information to obtain a gas loss dataset. Based on the gas loss dataset, the coal seam gas content is measured according to the total content calculation stage measurement process information to obtain the original gas content dataset.

[0088] Furthermore, the system is also used to implement the following functions:

[0089] Geological exploration is conducted based on the target coal seam to determine its geological structure data. Borehole analysis is performed based on the multi-dimensional drilling dataset to determine the core data of the target coal seam. Well logging data is retrieved and combined with the core data for pore analysis to construct a pore network, which includes pore structure features. Fracture analysis is performed based on well logging data and the geological structure data to construct a fracture network, which includes fracture structure features. Three-dimensional modeling is performed based on the pore structure features and fracture structure features to construct a dual-pore-fracture medium gas migration model, which includes dual-medium geometric parameters. Multi-field coupled numerical simulation is performed based on the dual-pore-fracture medium gas migration model and the dual-medium geometric parameters to obtain the dynamic gas migration state parameters.

[0090] Furthermore, the system is also used to implement the following functions:

[0091] Initial and boundary conditions for multi-field coupled numerical simulation are set; the boundary conditions are used as constraints, and the gas transport model of the dual-pore-fracture medium is activated according to the initial conditions to perform fluid-solid-thermal multi-field coupled numerical simulation: fluid transport simulation is performed based on the geometric parameters of the dual medium to obtain the first simulation value; solid deformation simulation is performed based on the geometric parameters of the dual medium to obtain the second simulation value; heat transfer simulation is performed based on the geometric parameters of the dual medium to obtain the third simulation value; the first simulation value, the second simulation value, and the third simulation value are iteratively coupled in a multiphysics field to obtain the gas dynamic transport state parameters.

[0092] Furthermore, the system is also used to implement the following functions:

[0093] Based on the gas dynamic migration parameters, gas pressure evolution analysis is performed to draw a gas pressure trend map; the gas pressure trend map is traversed to identify the critical point of decline and determine the loss initiation position; drilling process parameters are introduced in conjunction with the loss initiation position to perform drilling analysis and obtain loss duration parameters; based on the loss initiation position and the loss duration parameters, the gas pressure trend map is tracked to identify the gas decay stage; loss analysis is performed based on the gas decay stage to obtain the amount of gas lost ahead of schedule; gas migration analysis is performed through the pore network to obtain matrix adsorbed gas parameters, and gas migration analysis is performed through the fracture network to obtain fracture free gas parameters; the contribution analysis of the matrix adsorbed gas parameters and fracture free gas parameters to the total loss is performed to calculate the contribution ratio; the amount of gas lost ahead of schedule and the contribution ratio are integrated to construct the total gas loss amount.

[0094] Furthermore, the system is also used to implement the following functions:

[0095] The gas emission rate is obtained by calculating the gas emission rate according to the gas decay stage; the gas emission rate is integrated based on the loss duration parameter to obtain the total emitted gas volume; the total emitted gas volume is verified in combination with ambient temperature change data, and the total emitted gas volume is corrected according to the verification results to obtain the advanced loss gas amount.

[0096] Furthermore, the system is also used to implement the following functions:

[0097] The gas migration path is analyzed based on the matrix-adsorbed gas parameters to obtain the matrix-adsorbed gas migration path; the gas migration path is also analyzed based on the fracture-free gas parameters to obtain the fracture-free gas migration path; the desorption amount of the matrix-adsorbed gas parameters is calculated based on the gas dynamic migration state parameters and the fracture-free gas migration path; the emission amount of the fracture-free gas parameters is calculated based on the gas dynamic migration state parameters and the fracture-free gas migration path; and the contribution ratio of the fracture-free gas loss to the matrix-adsorbed gas loss is calculated based on the desorption amount of the matrix-adsorbed gas parameters and the emission amount of the fracture-free gas parameters.

[0098] Furthermore, the system is also used to implement the following functions:

[0099] The initial gas loss is obtained by parsing the original gas content dataset. The initial gas loss is then replaced by the original gas loss: the difference between the original and the original gas loss is calculated to obtain a numerical difference parameter. When the numerical difference parameter is greater than a preset difference threshold, a replacement instruction is generated. The original gas content dataset is replaced with the gas loss according to the replacement instruction, generating a data replacement result. The data replacement result is then summed and verified. When the verification passes, the coal seam gas content data is generated.

[0100] Furthermore, the system is also used to implement the following functions:

[0101] Based on the data replacement results, the original gas content dataset is summed to obtain a first sum value. The upper and lower limits of gas content are extracted from coal seam geological conditions and historical gas content data, and a preset gas content range is set. The first sum value is compared with the preset gas content range. If the sum value exceeds the preset gas content range, the verification fails, and a review mode is initiated. The accuracy of the lost gas amount is analyzed using the review mode. Based on the analysis results, the dual-pore-fracture medium gas migration model is re-run to simulate and update the lost gas amount, obtaining an optimized lost gas amount. The optimized lost gas amount is analyzed in relation to drilling time parameters to construct an exponential relationship model. The optimized lost gas amount is summed with the original gas content dataset using the exponential relationship model to generate a second sum value. If the second sum value exceeds the preset gas content range, the verification fails, and the review mode is iterated. If the second sum value is within the preset gas content range, the correction is confirmed to be effective, the verification passes, and coal seam gas content data is generated.

[0102] It should be noted that the order of the embodiments described above is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. Furthermore, the above description focuses on specific embodiments of this specification. The processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired results. In some implementations, multitasking and parallel processing are possible or may be advantageous.

[0103] The above description is only a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

[0104] This specification and accompanying drawings are merely illustrative examples of this application and are intended to cover any and all modifications, variations, combinations, or equivalents within the scope of this application. Clearly, those skilled in the art can make various alterations and modifications to this application without departing from its scope. Therefore, if such modifications and modifications fall within the scope of this application and its equivalents, this application intends to include such modifications and modifications.

Claims

1. A method for correcting the error of coal seam gas content in a multi-stage determination, characterized in that, The method comprises: Based on the flow-solid-thermal multi-field coupling, a five-stage determination scheme is constructed, and the five-stage determination scheme is executed on the target coal seam to determine the coal seam gas content and obtain the original gas content data; A dual-pore-fracture medium gas migration model is constructed to simulate drilling of the coal seam gas and obtain gas dynamic migration state parameters; According to the gas dynamic migration state parameters, loss analysis is performed to obtain the loss gas amount; Based on the loss gas amount, the original gas content data set is error corrected to obtain the coal seam gas content data.

2. The method for correcting the error of coal seam gas content in a multi-stage determination according to claim 1, characterized in that, Based on the flow-solid-thermal multi-field coupling, a five-stage determination scheme is constructed, and the five-stage determination scheme is executed on the target coal seam to determine the coal seam gas content and obtain the original gas content data, the method comprising: The five-stage determination scheme comprises drilling stage determination process information, sampling stage determination process information, desorption stage determination process information, loss amount calculation stage determination process information, and total content calculation stage determination process information; Based on the target coal seam, the coal seam gas content is determined according to the drilling stage determination process information to obtain a multi-dimensional drilling data set; Based on the multi-dimensional drilling data set, the coal seam gas content is determined according to the sampling stage determination process information to obtain a coal core sample data set; Based on the coal core sample data set, the coal seam gas content is determined according to the desorption stage determination process information to obtain a desorption kinetics data set; Based on the desorption kinetics data set, the coal seam gas content is determined according to the loss amount calculation stage determination process information to obtain a gas loss amount data set; Based on the gas loss amount data set, the coal seam gas content is determined according to the total content calculation stage determination process information to obtain the original gas content data set.

3. The method for correcting the error of coal seam gas content in a multi-stage determination according to claim 2, characterized in that, A dual-pore-fracture medium gas migration model is constructed to simulate drilling of the coal seam gas and obtain gas dynamic migration state parameters, the method comprising: Based on the target coal seam, geological exploration is performed to determine the geological structure data of the target coal seam; Based on the multi-dimensional drilling data set, drilling analysis is performed to determine the drilling coring data of the target coal seam; Logging data is retrieved to analyze the pore structure and construct a pore network, wherein the pore network comprises pore structure characteristics; Logging data is retrieved to analyze the fracture structure and construct a fracture network, wherein the fracture network comprises fracture structure characteristics; According to the pore structure characteristics and the fracture structure characteristics, three-dimensional modeling is performed to construct a dual-pore-fracture medium gas migration model, wherein the dual-pore-fracture medium gas migration model comprises dual-medium geometric parameters; Based on the dual-pore-fracture medium gas migration model, multi-field coupling numerical simulation is performed according to the dual-medium geometric parameters to obtain the gas dynamic migration state parameters.

4. The method for correcting the error of coal seam gas content in a multi-stage determination according to claim 3, characterized in that, Based on the dual-pore-fracture medium gas migration model, multi-field coupling numerical simulation is performed according to the dual-medium geometric parameters to obtain the gas dynamic migration state parameters, the method comprising: Initial conditions and boundary conditions for multi-field coupling numerical simulation are set; The boundary condition is taken as a constraint, and the flow-solid-thermal multi-field coupling numerical simulation is performed according to the initial condition to activate the double-pore-fracture medium gas migration model: Based on the double medium geometric parameters, fluid migration simulation is carried out to obtain first simulation values; Based on the double medium geometric parameters, solid deformation simulation is carried out to obtain second simulation values; Based on the double medium geometric parameters, heat transfer simulation is carried out to obtain third simulation values; The first simulation values, the second simulation values and the third simulation values are coupled by multi-physical field iteration to obtain the gas dynamic migration state parameters.

5. The method for correcting the error of coal seam gas content in a multi-stage determination according to claim 3, characterized in that, According to the gas dynamic migration state parameters, loss analysis is carried out to obtain the loss gas amount, and the method comprises: Based on the gas dynamic migration state parameters, gas pressure evolution analysis is carried out to draw a gas pressure trend chart; The falling critical point is identified by traversing the gas pressure trend chart to determine the loss starting position; Drilling analysis is carried out by introducing drilling process parameters combined with the loss starting position to obtain the loss duration parameter; Based on the loss starting position and the loss duration parameter, data tracking is carried out on the gas pressure trend chart to identify the gas attenuation stage; Based on the gas attenuation stage, loss analysis is carried out to obtain the advanced loss gas amount; Through the pore network, gas migration analysis is carried out to obtain the matrix adsorbed gas parameter, and through the fracture network, gas migration analysis is carried out to obtain the fracture free gas parameter; Based on the matrix adsorbed gas parameter and the fracture free gas parameter, contribution analysis is carried out on the total loss amount to calculate the contribution proportion; The advanced loss gas amount and the contribution proportion are integrated to construct the loss gas amount.

6. The method for correcting the error of coal seam gas content in a multi-stage determination according to claim 5, characterized in that, Based on the gas attenuation stage, loss analysis is carried out to obtain the advanced loss gas amount, and the method comprises: According to the gas attenuation stage, the gas escape rate is obtained by calculating the escape; Based on the loss duration parameter, the total escape gas volume is obtained by integrating the gas escape rate; Based on the total escape gas volume combined with the environmental temperature change data, the total escape gas volume is modified according to the verification result to obtain the advanced loss gas amount.

7. The method for correcting the error of coal seam gas content in a multi-stage determination according to claim 5, characterized in that, Based on the matrix adsorbed gas parameter and the fracture free gas parameter, contribution analysis is carried out on the total loss amount to calculate the contribution proportion, and the method comprises: Based on the matrix adsorbed gas parameter, the gas migration path is analyzed to obtain the matrix adsorbed gas migration path; Based on the fracture free gas parameter, the gas migration path is analyzed to obtain the fracture free gas migration path; According to the gas dynamic migration state parameters combined with the matrix adsorbed gas migration path, the desorption amount of the matrix adsorbed gas parameter is calculated; According to the gas dynamic migration state parameters combined with the fracture free gas migration path, the escape amount of the fracture free gas parameter is calculated; Based on the desorption amount of the matrix adsorbed gas parameter and the escape amount of the fracture free gas parameter, the contribution proportion of the fracture free gas loss amount and the matrix adsorbed gas loss amount is calculated.

8. The method for correcting the error of coal seam gas content in a multi-stage determination according to claim 1, characterized in that, The original gas content dataset is error-corrected based on the loss gas amount, and coal seam gas content data is obtained, the method comprising: The initial loss gas amount is obtained based on analysis of the original gas content dataset; The initial loss gas amount is replaced by the loss gas amount: The initial loss gas amount is subtracted from the loss gas amount to obtain a numerical difference parameter; When the numerical difference parameter is greater than a preset difference threshold, a replacement instruction is generated, and the original gas content dataset is replaced by the loss gas amount according to the replacement instruction to generate a data replacement result; The data replacement result is verified by summation, and when the verification is passed, the coal seam gas content data is generated.

9. The method for correcting the error of coal seam gas content in a multi-stage determination according to claim 8, characterized in that, The data replacement result is verified by summation, and when the verification is passed, the coal seam gas content data is generated, the method comprising: The first summation value is obtained by adding the data replacement result and the original gas content dataset; The upper limit value and the lower limit value of the gas content are extracted from the coal seam geological conditions and the historical gas content data, and a preset gas content interval is set; The first summation value is compared with the preset gas content interval, and when the summation value exceeds the preset gas content interval, it is determined that the verification is not passed, and a review mode is started; The accuracy of the loss gas amount is analyzed through the review mode, and the loss gas amount is updated by re-running the double-porosity-fractured medium gas migration model for simulation to obtain an optimized loss gas amount; An exponential relationship model is constructed by analyzing the optimized loss gas amount and the drilling time parameter, and a second summation value is generated by adding the optimized loss gas amount and the original gas content dataset through the exponential relationship model; If the second summation value exceeds the preset gas content interval, it is determined that the verification is not passed, and the iteration review mode is started; If the second summation value is within the preset gas content interval, it is determined that the correction is effective, the verification is passed, and the coal seam gas content data is generated.

10. A multi-stage determination of the error correction system of coal seam gas content, characterized in that, The system is used to execute the multi-stage determination coal seam gas content error correction method as claimed in any one of claims 1-9, and the system comprises: A determination module is used to construct a five-stage determination scheme based on flow-solid-thermal multi-field coupling, execute the five-stage determination scheme on the target coal seam to determine the coal seam gas content, and obtain the original gas content data; A simulated drilling module is used to construct a double-porosity-fractured medium gas migration model to simulate drilling of the coal seam gas and obtain gas dynamic migration state parameters; A loss analysis module is used to perform loss analysis based on the gas dynamic migration state parameters to obtain a loss gas amount; An error correction module is used to error-correct the original gas content dataset based on the loss gas amount to obtain coal seam gas content data.

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