A stability monitoring and evaluation method for underground coal gasification process

Abstract

The present invention relates to the field of underground coal gasification technology, and specifically to a method for monitoring and evaluating the stability of an underground coal gasification process, comprising: determining the spatial mapping relationship between the temperature field of the gasifier and the acoustic emission events using the temperature gradient and acoustic emission events of the gasifier; performing three-dimensional inversion on the combustion cavity of the gasifier to determine the attenuation trend of the coal seam under different temperature gradients; determining the propulsion direction of the combustion cavity boundary based on the attenuation trend of the coal seam under different temperature gradients using the spatial distribution density and relative position of each acoustic emission event; forming a boundary movement path based on the propulsion direction of the combustion cavity boundary, and calculating the propulsion area ratio of each position in the propulsion direction based on the distance difference of the boundary movement path; and determining the spatial stability classification of each part of the combustion cavity based on the propulsion area ratio of each position in the propulsion direction and the combustion cavity expansion rate. Accurate and efficient monitoring of underground coal seam gasification is achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of underground coal gasification, and in particular to a method for monitoring and evaluating the stability of an underground coal gasification process. Background Art

[0002] Coal resources are typically stored and mined in layers. Underground coal gasification (UCG) involves the controlled combustion of underground coal, generating combustible gas through thermal and chemical reactions. During UCG, coal combustion can cause the surrounding rock to expand and accumulate moisture, necessitating the monitoring of the combustion cavity's stability to prevent rock shedding and potentially extinguishing the gasifier.

[0003] For example, Chinese patent publication number CN118110491A discloses a method for mining underground gasification resources in medium-deep coal seams, comprising: S1 geological survey within the target coal seam to obtain geological properties; S2 dividing the target coal seam into a number of block units based on the geological properties, and setting a number of drilling and logging wells in each block unit; S3 predicting the amount of underground gasifiable coal resources in each block unit using electrical logging and coal sampling testing, and then adding up the coal resources of all block units to obtain the total gasified coal resources in the target coal seam range; S4 formulating a mining strategy for the target coal seam based on the total gasified coal resources obtained in step S3; and S5: mining the target coal seam according to the mining strategy to obtain actual coal production.

[0004] For example, Chinese patent publication No. CN111894546A discloses a combined resource mining method and device for underground coal gasification and gas extraction, which includes: performing underground gasification operations on a gasified coal seam; detecting the temperature and pore fracture characteristics of the gas-extracted coal seam during the underground gasification operations of the gasified coal seam; wherein the gas-extracted coal seam is located above the gasified coal seam; determining the gas accumulation characteristics of the gas-extracted coal seam based on the temperature and pore fracture characteristics of the gas-extracted coal seam; determining the arrangement of gas extraction boreholes on the gas-extracted coal seam based on the gas accumulation characteristics, and extracting gas from the gas-extracted coal seam from the arranged gas extraction boreholes.

[0005] Existing technologies have demonstrated the use of drilling methods to predict the total amount of underground coal, and the use of gas accumulation under pores to describe the distribution of gas during underground coal gasification. However, it is also necessary to identify the corresponding conditions of the combustion cavity under the actual combustion of the current coal, and to identify whether the underground coal has an unstable position during the combustion process based on the advancement of the combustion cavity at the corresponding time, in order to prevent abnormal subsidence and other situations that may lead to the extinction of the gasifier. Summary of the Invention

[0006] In order to solve the above technical problems, the technical solution adopted by the present invention is: S1, collecting real-time data of underground coal seam gasification, and determining the spatial mapping relationship between the gasifier temperature field and acoustic emission events based on the temperature gradient and acoustic emission events of the gasifier.

[0007] S2, based on the spatial mapping relationship between the gasifier temperature field and acoustic emission events, the acoustic emission events are regarded as data points, and the three-dimensional inversion of the combustion cavity of the gasifier is performed to determine the attenuation trend of the coal seam under different temperature gradients.

[0008] S3, according to the attenuation trend of the coal seam under different temperature gradients, the spatial distribution density and relative position of each acoustic emission event are used to determine the advancement direction of the combustion cavity boundary.

[0009] S4, according to the propulsion direction of the fuel cavity boundary, data tracking is performed on the fuel cavity boundary to form a boundary movement path, and the propulsion area ratio of each position in the propulsion direction is calculated based on the distance difference of the boundary movement path.

[0010] S5, judging the expansion rate of the combustion cavity according to the proportion of the propulsion area at each position in the propulsion direction, and determining the spatial stability classification of each part of the combustion cavity.

[0011] The beneficial effects of the present invention are as follows: 1. The present invention collects real-time data of underground coal seam gasification, including the temperature gradient and acoustic emission events of the gasifier, and after conditional mapping of these data, it can illustrate the relative conditions in various areas of the current gasifier. Then, the combustion cavity is three-dimensionally inverted according to the position where the acoustic emission event occurs. After further determining the position boundary of the combustion cavity, the real-time expansion of the combustion cavity can be monitored to improve the integrity and accuracy of coal gasification process monitoring.

[0012] 2. The present invention utilizes the relative relationship between temperature gradient and acoustic emission events to divide the expansion direction corresponding to the fuel cavity to identify the expansion of the fuel cavity under different temperature gradients. These directions are then fitted to represent the actual situation of the current fuel cavity advancement. At the same time, the boundary of the fuel cavity is tracked to obtain the expansion of multiple branch directions in the macro direction relative to the micro direction, and the proportion of the advancement area is recorded, which helps to understand the dynamic expansion process of the fuel cavity and reflect the actual expansion content of the fuel cavity at multiple positions.

[0013] 3. The present invention uses the expansion rate of the fuel cavity as a constraint condition, performs constrained retrieval on each position in the propulsion direction, determines the expansion difference, and performs type matching with the propulsion area ratio, thereby determining the spatial stability classification of each part of the fuel cavity; integrating the propulsion situation of the fuel cavity is helpful to discover abnormal expansion of the fuel cavity and provide a basis for early warning and control. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] The present invention will be further described below with reference to the accompanying drawings and examples.

[0015] Figure 1 The present invention is a flow chart of a method for monitoring and evaluating the stability of an underground coal gasification process.

[0016] Figure 2 The present invention is a flow chart of step S1 of a method for monitoring and evaluating stability of an underground coal gasification process.

[0017] Figure 3 The present invention is a flow chart of step S2 of a method for monitoring and evaluating stability of an underground coal gasification process.

[0018] Figure 4 The present invention is a flow chart of step S3 of a method for monitoring and evaluating stability of an underground coal gasification process.

[0019] Figure 5 The present invention is a flow chart of step S4 of a method for monitoring and evaluating stability of an underground coal gasification process. DETAILED DESCRIPTION

[0020] The following embodiments of the present invention are described in detail. The embodiments described below are exemplary and are only used to explain the present invention, and are not to be construed as limiting the present invention. Where specific techniques or conditions are not specified in the embodiments, the techniques or conditions described in the literature in the art or in the product specifications shall be followed.

[0021] See Figure 1 A method for monitoring and evaluating the stability of an underground coal gasification process includes: S1, collecting real-time data of underground coal seam gasification, and determining the spatial mapping relationship between the temperature field of the gasifier and the acoustic emission events based on the temperature gradient and acoustic emission events of the gasifier.

[0022] S2, based on the spatial mapping relationship between the gasifier temperature field and acoustic emission events, the acoustic emission events are regarded as data points, and the three-dimensional inversion of the combustion cavity of the gasifier is performed to determine the attenuation trend of the coal seam under different temperature gradients.

[0023] S3, according to the attenuation trend of the coal seam under different temperature gradients, the spatial distribution density and relative position of each acoustic emission event are used to determine the advancement direction of the combustion cavity boundary.

[0024] S4, according to the propulsion direction of the fuel cavity boundary, data tracking is performed on the fuel cavity boundary to form a boundary movement path, and the propulsion area ratio of each position in the propulsion direction is calculated based on the distance difference of the boundary movement path.

[0025] S5, judging the expansion rate of the combustion cavity according to the proportion of the propulsion area at each position in the propulsion direction, and determining the spatial stability classification of each part of the combustion cavity.

[0026] Acoustic emission events refer to transient elastic waves generated by rapid energy release within a material, such as crack propagation, plastic deformation, and phase change. In underground coal gasification (UCG) scenarios, acoustic emission events are usually triggered by processes such as coal seam fracturing, gas flow, and thermal stress.

[0027] Coal seam fracture: High-temperature gasification reactions cause cracks to form or expand inside the coal seam, releasing strain energy.

[0028] Gas flow: injection of gasifying agent oxygen, water vapor, etc. or synthesis gas CO, When discharged, micro cracks or fluid dynamic disturbances are caused.

[0029] Thermal stress effect: Uneven heating of the coal seam leads to local stress concentration, causing micro-cracks.

[0030] When identifying an acoustic emission event, the event coordinates, energy, frequency, and arrival time are included, which can reflect the expansion path of the combustion cavity, the evolution of the crack network, and the risk of surrounding rock instability.

[0031] Event coordinates are the spatial location of an acoustic emission event, representing its three-dimensional position within a coal seam or combustion cavity. The distribution of event coordinates can be used to identify the direction of combustion propagation within the combustion cavity and the path of fracture expansion, such as along the coal seam plane or vertically. Combining multiple event coordinates allows for the inversion of cavity shapes, such as ellipsoids, cones, and volume changes. Multi-sensor time-of-arrival positioning (TDOP) is used to calculate the event source location based on the arrival time differences of signals recorded by multiple acoustic emission sensors.

[0032] Energy is the area between the acoustic emission signal envelope and the threshold value. The higher the energy, the greater the energy released by a single crack expansion, which may correspond to a major crack or large-scale damage. Areas with high energy distribution density, such as the combustion surface, indicate that the gasification reaction is intense and the combustion cavity expands rapidly.

[0033] Frequency is the dominant frequency or frequency band of the acoustic emission signal. High-frequency signals may correspond to small-scale cracks or shear failure, while low-frequency signals may correspond to large-scale fissures or rock collapse. The frequency response of a coal seam is affected by its mineral composition, such as clay and carbonate, and by the fissure fillings, such as water and gas.

[0034] The arrival time is the time it takes for the acoustic emission signal to propagate from the source to the sensor. It includes the sensor spacing and the arrival time difference. The propagation speed of the sound wave in the coal seam can be calculated to indirectly reflect the density or damage level of the coal seam. At the same time, after processing its arrival time, it can be understood whether there is any deviation in its coordinate position.

[0035] By analyzing acoustic emission events and combining them with temperature field data, we can know the size of the combustion cavity of the current coal seam during combustion, so as to prevent the problem that when the combustion cavity is too large, the coal seam structure will become unstable, causing the groundwater accumulated in the upper layer to fall directly into the gasifier, causing the gasifier to go out.

[0036] At this time, distributed optical fibers are laid in the gasification channel of the gasifier to obtain its temperature data, and multiple sensors are used to receive acoustic emission signals to determine the cracks and other conditions that appear in the coal seam during combustion in the current gasifier, so as to timely track the size of the combustion cavity.

[0037] like Figure 2 As shown, the implementation method of step S1 includes: S11, collecting elastic wave signals generated by coal seam fracture, and marking acoustic emission events with the coordinates, energy, frequency and arrival time of the elastic wave signals.

[0038] S12, dividing the space inside the gasifier into a gasifier temperature field according to the temperature gradient of the gasifier, and mapping the coordinates of the acoustic emission event to the grid of the gasifier temperature field, identifying the average temperature gradient and average event density of the grid where the acoustic emission event is located; calculating the average temperature gradient is the average value of the temperature gradient, which represents the temperature condition at the location of the acoustic emission event; the average event density is the average value of the number of acoustic emission events in the grid of the temperature field, which illustrates the distribution of the acoustic emission events.

[0039] S13, constructing a spatial mapping relationship between the gasifier temperature field and the acoustic emission events based on the average temperature gradient and the average event density.

[0040] At this time, when the average temperature gradient is obtained, it is also necessary to verify whether the moving direction of the temperature field where the acoustic emission event is located is consistent with the direction of the maximum temperature gradient.

[0041] That is, the implementation method of constructing the spatial mapping relationship between the gasifier temperature field and the acoustic emission events also includes: converting the temperature gradient and event density in each grid of the gasifier temperature field into a gradient vector and then normalizing it to obtain a unit vector; the unit vector represents the normalized gradient vector of each grid in the temperature field to represent the movement direction of the temperature gradient and event density.

[0042] The unit vector of the maximum temperature gradient is compared with the unit vector of the acoustic emission event to determine whether the directions of the unit vectors are consistent. The direction consistency is determined by calculating the angle between the vectors to determine whether the directions are consistent.

[0043] If they are consistent, it means that the direction of temperature field movement matches the actual physical process well, and the currently identified area can continue to be monitored to identify the size and relative position of the combustion cavity generated in the current area after combustion; if they are inconsistent, corrections need to be made to the current situation to ensure that the expansion direction of the cracks is consistent with the advancement direction of the temperature gradient generated during combustion.

[0044] That is, if they are consistent, the coordinates of the corresponding acoustic emission event in the gasifier temperature field are recorded and output as the real-time distribution characteristics of the gasifier temperature field; if they are inconsistent, a mapping relationship is established between the corresponding acoustic emission event and the gasifier temperature field. In this case, the inconsistent mapping relationship is a conditional mapping based on the direction of the temperature gradient and the density direction of the acoustic emission event. At this time, the area with inconsistent directions will be marked as part of the judgment in subsequent processing. These contents will also be recorded in the spatial mapping relationship, which facilitates the subsequent judgment of the temperature in the combustion cavity area under the current temperature gradient and whether there is intensity attenuation in its cracks, thereby further identifying the specific situation of the current coal seam combustion.

[0045] In one embodiment of the present invention, the inversion is mainly performed in the form of a wave field to correct the characteristics related to acoustic emission events and temperature gradients contained in the real-time distribution characteristics. For example, the data collected at each position is adjusted by using wave velocity attenuation and travel time correction. After processing the data, it is verified whether the temperature gradient has an intensity attenuation correlation with the currently measured content.

[0046] When performing corresponding processing, it is necessary to collect the mineral composition and samples of the current coal seam, and use the movement speed of normal elastic waves under the corresponding minerals to determine whether there is a coordinate error in the currently identified acoustic emission events and other contents. Then, based on the errors existing after three-dimensional inversion, the errors at different temperatures are associated with their temperature gradients to identify the existence of their attenuation trends.

[0047] like Figure 3 As shown, the implementation method of step S2 includes: S21, marking the position of the combustion cavity according to the spatial mapping relationship between the gasifier temperature field and the acoustic emission event, performing three-dimensional inversion based on the position of the combustion cavity, and determining the wave velocity and theoretical arrival time of the acoustic emission event at different temperatures.

[0048] S22, using the wave velocity and theoretical arrival time corresponding to the acoustic emission event, calculate the coordinate error under each temperature gradient, fit the coordinate error with the temperature gradient, and use the fitted data as the output attenuation trend.

[0049] At this time, the wave velocity of the acoustic emission event will be calculated based on the initial wave velocity and other values ​​to describe the wave velocity of the currently received acoustic emission event.

[0050] For example, the wave speed can be expressed as: ;in, Indicates the wave velocity at temperature T, where T represents the temperature at the currently identified location. Indicates reference temperature The initial wave velocity under the reference temperature is generally selected as 25℃; represents the exponential constant, Represents the temperature attenuation coefficient, which is used to control the exponential attenuation of the temperature on the wave velocity. Its value is generally set to 0.002 / ℃. In addition to this value, it can also be adjusted according to the value calibrated in the actual experiment; Indicates the porosity influencing factor, reflecting the porosity The correction effect on wave velocity is generally set to 0.05 to determine how the actual situation affects the accuracy of the coordinate measurement of the current acoustic emission event. As for the porosity, its value range is 0 to 1, indicating the ratio of the pore volume to the total volume. This ratio can be described by the pore volume that can be generated under the action of its temperature combustion. This value can be based on multiple experiments on materials equivalent to the coal seam in the current gasifier, and the average value of the experiments is used as the porosity used here; It represents the critical temperature, which indicates the temperature threshold at which the pore structure changes significantly. This value is generally 600 degrees Celsius, and can also be adjusted according to the average value under the current simulation experiment.

[0051] The theoretical arrival time is expressed as: ;in, represents the theoretical arrival time of the signal of the ith acoustic emission event, Indicates the distance from the acoustic emission event i to the sensor, Indicates the ith acoustic emission event at temperature The wave speed under System calibration delay, which is the fixed delay of the sensor or signal processing system.

[0052] When the theoretical arrival time and wave velocity are obtained, the error in the coordinates of the current acoustic emission event can be determined, and the coordinate error can be fitted with the temperature gradient to identify the attenuation trend related to the temperature gradient and reduce the deviation of the wave velocity model caused by the temperature gradient. At the same time, through the correlation between the coordinate error of the acoustic emission event and the temperature gradient, the characteristics of the current coal seam and the size of the combustion cavity can be identified, so as to facilitate the prevention of possible geological changes and whether the gasification rate affects the rock structure around the coal seam.

[0053] Regarding coordinate error, the actual spatial coordinates of the acoustic emission event are obtained by inverting the actual arrival time recorded by multiple sensors in combination with the law of sound wave propagation; then the theoretical spatial coordinates are inverted based on the theoretical arrival time and wave velocity calculated above; the corresponding coordinate error is obtained by taking the difference between these two relative spatial coordinates. At this time, the current coordinate error can be defined based on the distance difference calculated after inverting the theoretical arrival time. That is, after describing the coordinate error by the distance of the two coordinates relative to the sensor, the coordinate error is combined with the temperature gradient for processing.

[0054] When fitting the coordinate error and temperature gradient, the least squares method is used to set the coordinate error equal to the temperature gradient multiplied by the proportional coefficient and add a constant term to obtain the most relevant proportional coefficient under the fitting. The change ratio of the proportional coefficient after fitting is output as the attenuation trend to illustrate the correlation between the currently identified error and the temperature gradient when the coordinate error exists. The output attenuation trend uses the value corresponding to the temperature gradient as the horizontal axis and the coordinate error as the vertical axis. The proportional coefficient after fitting is used as the slope of the trend to illustrate the trend value of the attenuation trend.

[0055] Preferably, when marking the position of the combustion cavity, the positions of the acoustic emission events are connected to form the boundary of the combustion cavity.

[0056] That is, when marking the position of the combustion cavity, the implementation method of step S21 also includes: using the data points corresponding to the acoustic emission events, connecting the positions of each data point in the gasifier, obtaining the minimum convex polygon corresponding to each data point, and using the boundary of the minimum convex polygon as the mark of the combustion cavity position.

[0057] The minimum convex polygon is obtained by constructing a convex hull. This method encloses all identified acoustic emission events by selecting a convex polygon to reflect the activity and structural characteristics of the combustion cavity area. This position is actually used to show the approximate range and position of the combustion cavity, which is convenient for subsequent verification of the overall advancement and combustion process of the coal seam during gasification, and assists in verifying whether the coal seam combustion process is stable and whether it can cause excessive expansion and fracture of other parts of the rock formation.

[0058] In one embodiment of the present invention, when extracting the propulsion direction of the combustion cavity boundary, data points are screened with values ​​corresponding to the attenuation trend to obtain finite event points corresponding to multiple acoustic emission events, and then, according to the indicators of each finite event point, its sensitivity index is constructed with spatial distribution density and relative position; then, according to the change in its position in each time step or time period, its propulsion index is set, and its sensitivity and propulsion index are combined to characterize its propulsion direction. The propulsion path represents the combustion cavity currently identified by the convex hull construction method under macroscopic conditions, and then the propulsion direction of the combustion cavity in multiple time periods corresponding to coal seam combustion is represented in the form of a smooth or continuous curve, etc., and then the small boundary points in this propulsion direction need to be identified and processed to identify whether these boundary points will be affected by different intensity attenuation during the propulsion process.

[0059] like Figure 4 As shown, the implementation method of step S3 includes: S31, based on the attenuation trend of the coal seam under different temperature gradients, screening out finite event points corresponding to each acoustic emission event, the finite event points are screened from the temperature gradient existing in the attenuation trend, and a plurality of points greater than the temperature gradient threshold are obtained in the form of a set temperature gradient threshold. The temperature gradient threshold can be 5°C / m, to obtain a plurality of data points located in the high-temperature front area of ​​the combustion cavity, and these data points are regarded as finite event points.

[0060] At the same time, when screening finite event points, the slope value of its attenuation trend can be used as the data point on the temperature gradient corresponding to its average slope value to obtain the part where the expansion of the combustion cavity has a more significant impact on the coordinate error. Processing this part of the data can reflect problems such as structural instability caused by rapid attenuation of the coal seam, which is convenient for verifying the stability of the current combustion cavity structure.

[0061] S32: Using the spatial distribution density and relative position of the finite event points, set the sensitivity index corresponding to each finite event point, and set the advancement index based on the displacement vector change rate of each finite event point in adjacent time periods.

[0062] S33, after combining the sensitivity index and the propulsion index, a comprehensive index is set, and the comprehensive index is used to perform fitting in the direction of each finite event point to set the propulsion direction of the combustion cavity boundary.

[0063] The spatial distribution density above represents the kernel density function value calculated for the corresponding finite event point, and the relative position represents the distance between the current finite event point and the center of the combustion cavity. The sensitivity index of the finite event point is then calculated by multiplying the kernel density function value corresponding to the finite event point with its distance weight. The distance weight is the inverse of the distance from the finite event point to the center of the combustion cavity multiplied by the temperature attenuation coefficient. The calculated distance and other data are normalized to eliminate dimension.

[0064] The displacement vector change rate represents the displacement change rate of the corresponding finite event point in the same grid or area within adjacent time, and is regarded as a propulsion index. The weight sum of the sensitivity index and the propulsion index is then regarded as a comprehensive index, and its weight can be expressed as the ratio of the index value of the corresponding finite event point to the index value of all finite event points. The index value represents the value of the sensitivity index and the propulsion index. The main direction of the comprehensive index of the finite event point is then calculated to identify multiple directions whose values ​​account for 90% of the total value. After fitting these directions, the propulsion direction of the combustion cavity boundary can be obtained.

[0065] At this time, the direction of each finite event point is based on the direction represented by its displacement vector when calculating the rate of change of its displacement vector as the direction of its single finite event point.

[0066] At the same time, when constructing the advancement path of the combustion cavity boundary, its implementation method also includes: hierarchical clustering according to the coordinates of the data points, connecting the center points of each cluster after hierarchical clustering as the output advancement path. At this time, clustering is performed by using the coordinates of the data points to calculate the distance between each data point, and then clustering multiple data points located in the combustion cavity. When the average value of the distance between the data points in all clusters reaches the minimum, the clustering is completed, and then the center points of the clusters are connected to find out the advancement of the combustion cavity of the coal seam during the gasification process, to describe the distribution of the relative position of the overall combustion cavity.

[0067] In one embodiment of the present invention, the position of the boundary point represented by the fuel cavity in the propulsion direction is used to form its boundary movement path, and the boundary movement path corresponding to each temperature is used to identify the distance difference between the boundary points at two positions before and after continuous time under different temperature gradients and temperature differences, which is used to illustrate the relative area measurement that can be propulsed in the propulsion direction under the influence of different temperatures, thereby illustrating the change in the size of the fuel cavity.

[0068] like Figure 5 As shown, the implementation method of step S4 includes: S41, recording the boundary points of the combustion cavity in the propulsion direction, and forming a boundary movement path according to the coordinate changes of the boundary points of the combustion cavity in continuous time.

[0069] S42, calculating the single point distance difference of each boundary point on the boundary movement path at adjacent times and the regional distance difference in multiple temperature gradient intervals; the regional distance difference indicates the average value of the single point distance difference of all boundary points in the temperature gradient area where the boundary point is located.

[0070] S43, based on the local temperature difference and regional distance difference in the temperature gradient interval where the current boundary point is located, solve the temperature difference distance relationship, and calibrate the temperature difference distance relationship through multiple linear regression. The regional distance difference is used as the dependent variable, and the temperature gradient and the local temperature difference in the temperature gradient interval are used as independent variables to obtain the regression coefficient. In order to avoid the different dimensions represented by the temperature gradient and the temperature difference, all the values ​​that need to be calculated by multiple linear regression will be standardized during the calculation, and the solution will be performed with the normalized values. The regression coefficient is used as the index value of the temperature difference distance relationship, which reflects the correlation between the temperature gradient and the moving distance of the combustion cavity boundary.

[0071] S44, dividing the incremental area of ​​the combustion cavity in continuous time according to the temperature difference distance relationship, so that the temperature difference distance relationship corresponding to each temperature gradient corresponds to the incremental area under a temperature gradient, and the ratio of the divided incremental area to the total incremental area is used as the propulsion area ratio of each position in the propulsion direction.

[0072] By recording the movement paths of boundary points in this step, we can intuitively understand the dynamic expansion process of the combustion cavity, which helps us understand the evolution mechanism of the combustion cavity. Through multivariate linear regression analysis, we can quantify the impact of temperature gradient on the movement distance of the combustion cavity boundary, providing an important basis for optimizing gasifier operation. Subsequently, the relationship between incremental area and temperature difference distance can be divided to describe the expansion trend of the combustion cavity under different temperature gradients. This can describe the expansion area of ​​the coal seam during the gasification process and provide data support for gasifier safety assessment.

[0073] Preferably, it is necessary to ensure that the collected coordinate data is continuous and synchronized in time so as to form an accurate boundary movement path; use time series analysis methods, such as Kalman filtering or particle filtering, to track the position changes of each boundary point in consecutive time steps to form the movement path of the combustion cavity boundary; for each boundary point, calculate its movement distance between consecutive time steps, that is, the single point distance difference; this can be achieved by calculating the Euclidean distance of the coordinates between two time steps.

[0074] Preferably, the incremental area can be calculated by the difference in the size of the internal combustion cavity boundary in consecutive time steps.

[0075] Preferably, when outputting the propulsion area ratio of each position in the propulsion direction in step S44, it is also necessary to identify whether there is a branch direction in the current propulsion direction.

[0076] That is, step S44 also includes determining whether there is a branch direction in the propulsion direction. If there is a branch direction, the incremental area is calculated separately for each branch direction, and the incremental areas in the branch directions are superimposed. The ratio of the superimposed incremental area to the total incremental area is output as the propulsion area ratio of each position in the propulsion direction.

[0077] At this time, the identification method of the branch direction can be to segment and cluster the boundary movement path to determine whether there is a branch in the main advancement direction, that is, the direction pointed by the single-point distance difference of each boundary point is used as the clustering content, and the single-point distance difference of each boundary point is regarded as a vector. The direction of the vector under different temperature gradients is clustered to identify whether there is a branch direction in different temperature gradient areas. The clustering method can be clustered according to the DBSCAN clustering method to set the neighborhood radius and minimum number of points of each boundary point, and cluster the vector of the single-point distance difference of the boundary point. The neighborhood boundary and the minimum number of points can be set using the average value of the DBSCAN clustering method in the historical data. Then, the clustered multiple groups of data are segmented according to the temperature gradient in which they are located to obtain the directions of multiple clusters. The corresponding direction is regarded as the branch direction at this time, and the size of the incremental area in each branch direction is counted. After identifying the proportion of these branch directions and the ratio of the incremental area in the total direction, it can be understood how the area where the combustion cavity is located expands to assist in understanding whether the coalbed gasification is stable.

[0078] The incremental areas may be superimposed in a manner of summing or other statistical measurement methods to identify the incremental areas in the branch direction.

[0079] In one embodiment of the present invention, in step S5, the expansion rate at each position is described by dividing the outputted propulsion area ratio by its time length, and then the expansion rate is used to constrain each part of the fuel cavity to identify whether the current expansion of the fuel cavity is normal under the corresponding constraint conditions.

[0080] Therefore, the implementation method of step S5 includes: using the expansion rate of the fuel cavity as a constraint condition, performing constrained retrieval on each position in the propulsion direction, determining the expansion difference of each position in the propulsion direction, performing type matching based on the expansion difference and the proportion of the propulsion area, and determining the spatial stability classification of each part of the fuel cavity.

[0081] The above-mentioned expansion difference represents the difference between the expansion rate of the corresponding position in the current propulsion direction and the reference rate, which serves as the expansion difference at this time; the reference rate represents the average value of the expansion rate at the corresponding position of the combustion cavity, which can also be obtained through relevant situations in historical data.

[0082] When the types are subsequently matched based on the expansion difference and the proportion of the advancing area, similarity is calculated between the values ​​of the expansion difference and the proportion of the advancing area and the values ​​under different categories in the database. The calculation method can be performed using the Pearson correlation coefficient, and the part with the largest corresponding value of the Pearson correlation coefficient is regarded as the current spatially stable classification.

[0083] The final output of the spatial stability classification will include stable expansion zone, rapid expansion zone, slow expansion zone and fluctuating expansion zone; stable expansion zone: occupies 60% of the total area of ​​the combustion cavity, the expansion rate is moderate and stable, the geological conditions are good, and the gasifier operates normally; rapid expansion zone: occupies 20% of the total area of ​​the combustion cavity, the expansion rate is significantly higher than the average rate, which may be affected by local high temperature or coal seam cracks, and its expansion trend needs to be closely monitored; slow expansion zone: occupies 15% of the total area of ​​the combustion cavity, the expansion rate is lower than the average rate, which may be due to the high hardness of the coal seam or insufficient injection of gasifier, and the gasifier operating parameters need to be optimized; fluctuating expansion zone: occupies 5% of the total area of ​​the combustion cavity, the expansion rate fluctuates greatly, which may be affected by geological structure or unstable operation of the gasifier, and monitoring and regulation need to be strengthened.

[0084] Based on these classifications, staff can adjust the relevant parameters of the gasifier in a timely manner to ensure stable operation of the combustion cavity, ultimately improving the efficiency and safety of underground coal gasification.

[0085] Although the embodiments of the present invention have been shown and described above, it will be understood that the above embodiments are illustrative and are not to be construed as limitations on the present invention. A person skilled in the art may make changes, modifications, substitutions and variations to the above embodiments within the scope of the present invention, which are still covered by the scope of protection of the present invention.

Claims

1. A method for monitoring and evaluating the stability of an underground coal gasification process, characterized in that: include: S1, collect real-time data of underground coal seam gasification, and determine the spatial mapping relationship between the temperature field of the gasifier and the acoustic emission events based on the temperature gradient of the gasifier and the acoustic emission events; S2, based on the spatial mapping relationship between the gasifier temperature field and the acoustic emission events, the acoustic emission events are regarded as data points, and the three-dimensional inversion of the combustion cavity of the gasifier is performed to determine the attenuation trend of the coal seam under different temperature gradients; S3, based on the attenuation trend of the coal seam under different temperature gradients, the spatial distribution density and relative position of each acoustic emission event are used to determine the advancement direction of the combustion cavity boundary; S4, according to the propulsion direction of the fuel cavity boundary, data tracking is performed on the fuel cavity boundary to form a boundary movement path, and the propulsion area ratio of each position in the propulsion direction is calculated based on the distance difference of the boundary movement path; S5, judging the expansion rate of the combustion cavity based on the proportion of the propulsion area at each position in the propulsion direction, and determining the spatial stability classification of each part of the combustion cavity; The implementation of step S5 includes: Taking the expansion rate of the combustion cavity as a constraint condition, a constrained search is performed on each position in the propulsion direction to determine the expansion difference of each position in the propulsion direction. The type matching is performed based on the expansion difference and the proportion of the propulsion area to determine the spatial stability classification of each part of the combustion cavity.

2. The method for monitoring and evaluating the stability of underground coal gasification process according to claim 1, characterized in that: The implementation of step S1 includes: S11, collecting elastic wave signals generated by coal seam fracture, and marking acoustic emission events with the coordinates, energy, frequency and arrival time of the elastic wave signals; S12, dividing the space inside the gasifier into a gasifier temperature field according to the temperature gradient of the gasifier, and identifying the average temperature gradient and average event density of the grid where the acoustic emission event is located; S13, constructing a spatial mapping relationship between the gasifier temperature field and the acoustic emission events based on the average temperature gradient and the average event density.

3. The method for monitoring and evaluating the stability of underground coal gasification process according to claim 2, characterized in that: The implementation methods for constructing the spatial mapping relationship between the gasifier temperature field and acoustic emission events also include: The temperature gradient and event density of the gasifier temperature field in each grid are converted into gradient vectors and normalized to obtain unit vectors; Compare the unit vector of the maximum temperature gradient with the unit vector of the acoustic emission event to determine whether the directions of the unit vectors are consistent; If they are consistent, the coordinates of the corresponding acoustic emission events in the gasifier temperature field are recorded and output as the real-time distribution characteristics of the gasifier temperature field; if they are inconsistent, a mapping relationship is established between the corresponding acoustic emission events and the gasifier temperature field.

4. The method for monitoring and evaluating the stability of underground coal gasification process according to claim 1, characterized in that: The implementation of step S2 includes: S21, based on the spatial mapping relationship between the gasifier temperature field and the acoustic emission events, the position of the combustion cavity is marked, and a three-dimensional inversion is performed based on the position of the combustion cavity to determine the wave velocity and theoretical arrival time of the acoustic emission event at different temperatures; S22, using the wave velocity and theoretical arrival time corresponding to the acoustic emission event, calculate the coordinate error under each temperature gradient, fit the coordinate error with the temperature gradient, and use the fitted data as the output attenuation trend.

5. The method for monitoring and evaluating the stability of underground coal gasification process according to claim 4, characterized in that: The implementation of step S21 further includes: The data points corresponding to the acoustic emission events are connected in the gasifier to obtain the minimum convex polygon corresponding to each data point. The boundary of the minimum convex polygon is used as the mark of the combustion cavity position.

6. The method for monitoring and evaluating the stability of underground coal gasification process according to claim 1, characterized in that: The implementation of step S3 includes: S31, based on the attenuation trend of the coal seam under different temperature gradients, the finite event points corresponding to each acoustic emission event are screened; S32, using the spatial distribution density and relative position of the finite event points, setting a sensitivity index corresponding to each finite event point, and setting a propulsion index based on the displacement vector change rate of each finite event point in adjacent time periods; S33, after combining the sensitivity index and the propulsion index, a comprehensive index is set, and the comprehensive index is used to perform fitting in the direction of each finite event point to set the propulsion direction of the combustion cavity boundary.

7. The method for monitoring and evaluating the stability of underground coal gasification process according to claim 6, characterized in that: When constructing the propulsion path of the combustion cavity boundary, its implementation also includes: Hierarchical clustering is performed according to the coordinates of the data points, and the center points of each cluster after hierarchical clustering are connected as the output advancement path.

8. The method for monitoring and evaluating the stability of underground coal gasification process according to claim 1, characterized in that: The implementation of step S4 includes: S41, recording the boundary points of the fuel cavity in the propulsion direction, and forming a boundary movement path based on the coordinate changes of the boundary points of the fuel cavity in continuous time; S42, calculating the single-point distance difference of each boundary point on the boundary movement path at adjacent times and the regional distance difference within multiple temperature gradient intervals; S43, solving the temperature difference distance relationship based on the local temperature difference and the regional distance difference within the temperature gradient interval where the current boundary point is located; S44, dividing the incremental area of ​​the combustion cavity at continuous time according to the temperature difference distance relationship, and using the ratio of the divided incremental area to the total incremental area as the propulsion area ratio of each position in the propulsion direction.

9. The method for monitoring and evaluating the stability of underground coal gasification process according to claim 8, characterized in that: Step S44 further includes: Determine whether there is a branch direction in the propulsion direction. If there is a branch direction, calculate the incremental area for each branch direction separately, and superimpose the incremental areas in the branch directions. The ratio of the superimposed incremental area to the total incremental area is output as the propulsion area ratio of each position in the propulsion direction.

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