A method, device, equipment and medium for visualizing CO2 flow in a closed mine

Abstract

The present invention discloses a method, device, equipment, and medium for visualizing CO2 flow in a closed mine, relating to the field of gas flow. The method comprises: determining the location of a monitoring well for monitoring CO2 concentration in the closed mine, and extracting CO2 concentration data detected at the monitoring well location at a certain moment; using a bilinear interpolation method to predict the CO2 concentration in a surrounding area without a monitoring well based on the CO2 concentration data at the determined monitoring well location, thereby obtaining a predicted CO2 concentration matrix; using a heat map function in a data visualization tool on the CO2 concentration matrix to generate a CO2 concentration heat map; splicing the CO2 concentration heat maps generated from CO2 concentration data sets at multiple consecutive moments, and analyzing CO2 flow based on the spliced ​​heat maps. The present invention can clearly define the state of CO2 flow underground through a visualization method.

Description

Technical Field

[0001] The present invention relates to the field of gas flow, and in particular to a method, device, equipment and medium for visualizing CO2 flow in a closed mine. Background Art

[0002] With the adjustment of my country's energy structure, outdated production capacity in the coal industry has been gradually eliminated, resulting in an increasing number of closed mines and the creation of a large amount of underground space. How to utilize underground space is of great research value, and the study of CO2 flow in underground space is a key issue.

[0003] In the prior art, sulfur hexafluoride (SF6) gas tracer is used to monitor the flow of gas in underground spaces to observe whether leakage occurs.

[0004] However, existing methods cannot intuitively clarify the state of CO2 flow in the well through visualization methods. Summary of the Invention

[0005] The embodiments of the present invention provide a method, device, equipment and medium for visualizing the flow of CO2 in a closed mine, which can solve the problem in the prior art that the gas flow state underground cannot be intuitively and clearly understood through visualization methods.

[0006] An embodiment of the present invention provides a method for visualizing CO2 flow in a closed mine, comprising the following steps: determining the location of a monitoring well used to monitor the CO2 concentration in the closed mine, and extracting CO2 concentration data detected at the monitoring well location at a certain moment; predicting the CO2 concentration in a surrounding area where no monitoring wells are set up based on the CO2 concentration data at the determined monitoring well location using a bilinear interpolation method to obtain a predicted CO2 concentration matrix; generating a CO2 concentration heat map using a heat map function in a data visualization tool for the CO2 concentration matrix; splicing the CO2 concentration heat maps generated from CO2 concentration data sets at multiple consecutive moments, and analyzing the CO2 flow based on the spliced ​​heat maps.

[0007] Furthermore, the step of obtaining the predicted CO2 concentration matrix specifically includes: adjusting the accuracy of the bilinear interpolation algorithm according to the spacing between the CO2 monitoring wells, and improving the accuracy of the bilinear interpolation if the spacing between the two monitoring wells is large;

[0008] The bilinear interpolation method is formulated as follows:

[0009]

[0010] In the formula: A 11 、A 12 、A 21 and A 22 For the four adjacent monitoring wells, A11 The coordinate value is (x1, y1), A 12 The coordinate value is (x1, y2), A 21 The coordinate value is (x2, y1), A 22 The coordinate value is (x2, y2), f(A 11 )、f(A 12 )、f(A 21 ) and f(A 22 ) are the CO2 concentrations in the underground space measured by four adjacent monitoring wells, x and y are the horizontal and vertical coordinates of the prediction point, and f(x, y) is the predicted value of the CO2 concentration in the underground space at the prediction point.

[0011] Furthermore, the generating of the CO2 concentration heat map specifically includes: using the Matplotlib library, Seaborn library, Plotly library, geographic information system QGIS or geographic information system ArcGIS of Python programming to generate the CO2 concentration heat map.

[0012] Furthermore, the CO2 flow is analyzed based on the spliced ​​thermal map, and the specific steps include: performing image preprocessing on the spliced ​​thermal map, using Gaussian filtering to remove image noise, and ensuring that each image corresponds to the measuring point position one by one; performing differential image analysis on the preprocessed image to identify the CO2 flow area; binarizing the differential image to highlight the change area; using the centroid method to obtain the center of mass position of the change area, infer the direction of CO2 flow, and obtain the change rate of the center of mass position to estimate the CO2 flow rate.

[0013] An embodiment of the present invention provides a device for visualizing CO2 flow in a closed mine, comprising:

[0014] The data acquisition module is used to determine the location of the monitoring well used to monitor the CO2 concentration in the closed mine and extract the CO2 concentration data detected at the monitoring well location at a certain moment; the heat map generation module is used to predict the CO2 concentration in the surrounding area without monitoring wells based on the CO2 concentration data at the determined monitoring well location using the bilinear interpolation method to obtain the predicted CO2 concentration matrix; the CO2 concentration matrix is ​​used to use the heat map function in the data visualization tool to generate a CO2 concentration heat map; the flow analysis module is used to splice the CO2 concentration heat maps generated by the CO2 concentration data sets at multiple consecutive moments and analyze the CO2 flow based on the spliced ​​heat maps.

[0015] An embodiment of the present invention provides a computer device, comprising: a memory and a processor; the memory stores a computer program, and the processor implements the above-mentioned method for visualizing CO2 flow in a closed mine when executing the computer program.

[0016] An embodiment of the present invention provides a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, the computer program implements the above-mentioned method for visualizing CO2 flow in a closed mine.

[0017] The embodiments of the present invention provide a method, device, equipment, and medium for visualizing CO2 flow in a closed mine. Compared with the prior art, the methods and devices have the following beneficial effects:

[0018] Based on the CO2 concentration data at the determined monitoring well locations, the bilinear interpolation method is used to predict the CO2 concentration in the surrounding areas without monitoring wells to obtain a predicted CO2 concentration matrix. The heat map function in the data visualization tool is used to generate a CO2 concentration heat map for the CO2 concentration matrix. The CO2 concentration heat maps generated by the CO2 concentration data sets at multiple consecutive moments are spliced ​​together, and the CO2 flow is analyzed based on the spliced ​​heat map.

[0019] Among them, the heat map function in the data visualization tool is used on the CO2 concentration matrix to generate a CO2 concentration heat map, realizing the visualization of CO2 concentration. Then, the CO2 concentration heat maps generated by the CO2 concentration data sets at multiple consecutive moments are spliced ​​together. The spliced ​​heat map can be used to visually analyze the flow state of CO2, and finally the effect of CO2 flow can be intuitively perceived through visualization. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 A schematic diagram of monitoring well locations for a method for visualizing CO2 flow in a closed mine provided by an embodiment of the present invention;

[0021] Figure 2 A gas concentration matrix diagram generated by a bilinear interpolation method for a method of visualizing CO2 flow in a closed mine provided by an embodiment of the present invention;

[0022] Figure 3 A thermodynamic map of gas concentration in the underground space of the mine obtained according to array 1 provided in an embodiment of the present invention;

[0023] Figure 4 A thermodynamic map of gas concentration in the underground space of the mine obtained according to array 2 provided in an embodiment of the present invention;

[0024] Figure 5 A thermodynamic map of gas concentration in the underground space of the mine obtained according to array 3 provided in an embodiment of the present invention;

[0025] Figure 6 The thermal map of the gas concentration in the underground space of the mine obtained according to array 4 provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0026] To make the above-mentioned objects, features, and advantages of the present invention more readily apparent, specific embodiments of the present invention are described in detail below with reference to the accompanying drawings. The following description sets forth numerous specific details to facilitate a full understanding of the present invention. However, the present invention can be implemented in many other ways than those described herein, and those skilled in the art may make similar modifications without departing from the scope of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0027] See also Figures 1 to 6 The embodiment of the present invention provides a method for visualizing CO2 flow in a closed mine, comprising the following steps:

[0028] Step 1: Based on the location of the abandoned mine field, according to the monitoring accuracy requirements, field boundaries, and field scope, select CO2 monitoring wells as control points to form a layout plan for the CO2 concentration monitoring network in the underground space of closed coal mines. Among them, the monitoring wells are arranged in a rectangular shape, and the impact of ground structures on the construction of drilling monitoring wells should be fully considered during the layout. The monitoring wells should monitor the CO2 concentration in the underground space of the coal mine to the maximum extent, that is, the rectangle formed by the monitoring network should be the largest rectangle obtained within the field scope. Furthermore, when the scope of the monitoring network is less than 50% of the field area, the mine can be divided into several areas, and the monitoring network can be arranged separately in each area.

[0029] Step 2: Drill monitoring wells at corresponding locations in the well field according to the monitoring network layout plan.

[0030] Step 3: Extract the data set of the monitoring network logging at a certain moment that can represent the CO2 concentration in the underground space.

[0031] Step 4: Analyze the dataset using bilinear interpolation to predict CO2 concentrations and generate a CO2 concentration matrix. The accuracy of the bilinear interpolation algorithm is adjusted based on the spacing between monitoring wells. A larger spacing between two monitoring wells improves the accuracy of the bilinear interpolation.

[0032] The mathematical calculation principle of bilinear interpolation is as follows:

[0033]

[0034] Among them, A 11 、A 12 、A 21 and A 22 For the four adjacent monitoring wells, A 11 The coordinate value is (x1, y1), A 12 The coordinate value is (x1, y2), A 21 The coordinate value is (x2, y1), A 22 The coordinate value is (x2, y2), f(A11 )、f(A 12 )、f(A 21 ) and f(A 22 ) are the CO2 concentrations in the underground space measured by four adjacent monitoring wells, x and y are the horizontal and vertical coordinates of the prediction point, and f(x, y) is the predicted value of the CO2 concentration in the underground space at the prediction point.

[0035]

[0036]

[0037] Step 5: Visualize the CO2 concentration matrix to generate a CO2 concentration heat map.

[0038] Step 6: Generate a CO2 concentration thermodynamic map based on the frequency of monitoring well data collection, and analyze the CO2 flow pattern after continuous analysis.

[0039] An embodiment of the present invention provides a device for visualizing CO2 flow in a closed mine, comprising:

[0040] The data acquisition module is used to determine the location of monitoring wells used to monitor CO2 concentrations in closed mines and extract the CO2 concentration data detected at the monitoring well location at a specific moment. The heat map generation module is used to predict the CO2 concentration in surrounding areas without monitoring wells based on the CO2 concentration data at the determined monitoring well location using a bilinear interpolation method to obtain a predicted CO2 concentration matrix; the heat map function in the data visualization tool is used to generate a CO2 concentration heat map for the CO2 concentration matrix. The flow analysis module is used to splice the CO2 concentration heat maps generated from CO2 concentration data sets at multiple consecutive moments and analyze the CO2 flow based on the spliced ​​heat maps.

[0041] An embodiment of the present invention provides a computer device, comprising: a memory and a processor; the memory stores a computer program, and when the processor executes the computer program, it implements the steps of a method for visualizing CO2 flow in a closed mine.

[0042] An embodiment of the present invention provides a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, the computer program implements the steps of a method for visualizing CO2 flow in a closed mine.

[0043] A specific embodiment is as follows:

[0044] Step 1. Based on the location of the abandoned mine field, CO2 monitoring wells are selected as control points according to the monitoring accuracy requirements, field boundaries, and field scope to form a layout plan for the CO2 concentration monitoring network in the underground space of closed coal mines.

[0045] In step 1, a mine in Heilongjiang Province was selected as the research site. The mining area is 29.5026 square kilometers. 11*13=143 monitoring wells were initially arranged, with a spacing of 400m*400m between the wells. The monitoring density of this mining area is one CO2 monitoring well per 0.206 square kilometers.

[0046] Step 2. Drill monitoring wells at the corresponding locations in the well field according to the monitoring network layout plan

[0047] Step 3. Capture a dataset of underground CO2 concentrations from the monitoring network at four times on a given day.

[0048] In step 3, the data set is presented in matrix form. The specific data is as follows:

[0049] Array 1:

[0050]

[0051] Array 2:

[0052]

[0053] Array 3:

[0054]

[0055] Array 4:

[0056]

[0057] Step 4: Substitute the above data into the MATLAB calculation program to obtain the thermal map of CO2 concentration in the underground space of the mine at four different times on a certain day.

[0058] Step 5: The flow trend of CO2 in the underground space of the coal mine can be obtained by splicing the thermal maps obtained in step 4.

[0059] The MATLAB code for this embodiment is as follows, taking array 1 as an example:

[0060] %Define file path

[0061] file_path = 'C:\Users\cumty\Desktop\jianceshuju\Array1.xlsx';

[0062] % Read data from Excel file

[0063] data = readmatrix(file_path);

[0064] % Get the number of rows and columns of data

[0065] [rows, cols] = size(data);

[0066] % Define the number of time steps

[0067] time_steps = 50; % If the data does not change over time, you can set it to 1 or other reasonable values

[0068] % Create the original mesh

[0069] [X, Y] = meshgrid(1:cols, 1:rows);

[0070] % Initialize the smoothed concentration data matrix

[0071] smoothed_concentration_data = zeros(rows, cols, time_steps);

[0072] % Expand the original data to multiple time steps

[0073] concentration_data = repmat(data, [1, 1, time_steps]);

[0074] % Smoothing concentration data

[0075] for t = 1:time_steps

[0076] for i = 1:rows

[0077] smoothed_concentration_data(i,array:array,t) = smoothdata(concentration_data(i,array1:array1,t), 'loess');

[0078] end

[0079] end

[0080] % Create a concentration matrix for bilinear interpolation

[0081] interp_concentration = zeros(rows * 10, cols * 10, time_steps); % Improve resolution

[0082] % Newly added to create higher resolution meshes

[0083] [Xq, Yq] = meshgrid(linspace(1, cols, cols * 10), linspace(1, rows,rows * 10));

[0084] % Perform bilinear interpolation for each time step

[0085] for t = 1:time_steps

[0086] interp_concentration(:, :, t) = interp2(X, Y, smoothed_concentration_data(:, :, t), Xq, Yq, 'linear');

[0087] end

[0088] % Create a graphics window

[0089] figure;

[0090] h = imagesc(interp_concentration(:, :, 1));

[0091] colormap(jet);

[0092] colorbar;

[0093] % Set axis labels

[0094] xlabel('column');

[0095] ylabel('row');

[0096] % Display row and column scales

[0097] yticks(linspace(1, rows * 10, rows));

[0098] xticks(linspace(1, cols * 10, cols));

[0099] % Add axis scale labels, sorted from bottom to top

[0100] yticklabels(flipud(cellstr(num2str((1:rows)'))));

[0101] xticklabels(cellstr(num2str((1:cols)')));

[0102] % Create the handle of the colorbar on the right

[0103] colorbar_handle = colorbar;

[0104] % The image of the last time step

[0105] t = time_steps;

[0106] % Normalized data

[0107] normalized_data = interp_concentration(:, :, t) - min(interp_concentration(:));

[0108] normalized_data = normalized_data / max(normalized_data(:));

[0109] % Update heat map data

[0110] set(h, 'CData', normalized_data);

[0111] % Refresh the color scale of the colorbar on the right

[0112] colorbar_handle.Limits = [0, 1];

[0113] % Save the image of the last time step as JPG format

[0114] saveas(gcf, 'final_frame.jpg').

[0115] The above-described embodiments merely illustrate several implementations of the present invention, and while their descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the patent. It should be noted that a person skilled in the art would be able to make numerous variations and improvements without departing from the spirit of the present invention, all of which fall within the scope of protection of the present invention. Therefore, the scope of protection of the patent for this invention shall be determined by the appended claims.

Claims

1. A method for visualizing CO2 flow in a closed mine, characterized in that: The following steps are involved: Determine the location of the monitoring well used to monitor CO2 concentration in the closed mine, and extract the CO2 concentration data of the underground space detected at a certain moment at the monitoring well location; Based on the CO2 concentration data at the determined monitoring well locations, a bilinear interpolation method is used to predict the CO2 concentration in the surrounding area where no monitoring wells are set, and a predicted CO2 concentration matrix is ​​obtained; a heat map function in a data visualization tool is used on the CO2 concentration matrix to generate a CO2 concentration heat map; the use of the bilinear interpolation method to predict the CO2 concentration in the surrounding area where no monitoring wells are set includes: adjusting the accuracy of the bilinear interpolation algorithm according to the spacing between the CO2 monitoring wells, and if the spacing between the two monitoring wells is large, then the accuracy of the bilinear interpolation is improved; The CO2 concentration heat maps generated by CO2 concentration data sets at multiple consecutive moments are spliced ​​together, and the CO2 flow is analyzed based on the spliced ​​heat maps, including: image preprocessing of the spliced ​​heat maps, using Gaussian filtering to remove image noise and ensure one-to-one correspondence between each image at the measurement point; differential image analysis of the preprocessed images to identify CO2 flow areas; binarization of the differential images to highlight the changing areas; and the use of the centroid method to obtain the center of mass position of the changing area, infer the direction of CO2 flow, and obtain the rate of change of the center of mass position to estimate the CO2 flow rate.

2. A method for visualizing CO2 flow in a closed mine as claimed in claim 1, characterized in that: The matrix expression of the CO2 concentration matrix is: Among them, A 11 、A 12 、A 21 and A 22 For the four adjacent monitoring wells, A 11 The coordinate value is (x1, y1), A 12 The coordinate value is (x1, y2), A 21 The coordinate value is (x2, y1), A 22 The coordinate value is (x2, y2), f(A 11 )、f(A 12 )、f(A 21 ) and f(A 22 ) are the CO2 concentrations in the underground space measured by four adjacent monitoring wells, x and y are the horizontal and vertical coordinates of the prediction point, and f(x, y) is the predicted value of the CO2 concentration in the underground space at the prediction point.

3. The method for visualizing CO2 flow in a closed mine according to claim 1, characterized in that: Generating a CO2 concentration heat map specifically includes: Generate a CO2 concentration heat map based on the CO2 concentration matrix using Python programming's Matplotlib library, Seaborn library, Plotly library, QGIS geographic information system, or ArcGIS geographic information system.

4. A device for visualizing CO2 flow in a closed mine, characterized in that: include: A data acquisition module is used to determine the location of a monitoring well used to monitor CO2 concentration in a closed mine and extract the CO2 concentration data of the underground space detected at a certain moment at the location of the monitoring well; A heat map generation module is used to predict the CO2 concentration in the surrounding area without monitoring wells using a bilinear interpolation method based on the CO2 concentration data at the determined monitoring well locations, thereby obtaining a predicted CO2 concentration matrix; the CO2 concentration matrix is ​​subjected to a heat map function in a data visualization tool to generate a CO2 concentration heat map; the use of the bilinear interpolation method to predict the CO2 concentration in the surrounding area without monitoring wells includes: adjusting the accuracy of the bilinear interpolation algorithm based on the spacing between the CO2 monitoring wells, and improving the accuracy of the bilinear interpolation if the spacing between the two monitoring wells is large; The flow analysis module is used to stitch together the CO2 concentration heat maps generated from CO2 concentration data sets at multiple consecutive moments and analyze the CO2 flow based on the stitched heat maps. This includes: image preprocessing of the stitched heat maps, using Gaussian filtering to remove image noise and ensure that each image corresponds to the measurement point; differential image analysis of the preprocessed images to identify the CO2 flow area; binarization of the differential images to highlight the changing areas; and obtaining the center of mass position of the changing area using the center of mass method to infer the direction of CO2 flow and obtain the rate of change of the center of mass position to estimate the CO2 flow rate.

5. A computer device comprising: memory and processor; The memory stores a computer program, and is characterized in that when the processor executes the computer program, it implements a method for visualizing CO2 flow in a closed mine according to any one of claims 1 to 3.

6. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, a method for visualizing CO2 flow in a closed mine as described in any one of claims 1 to 3 is implemented.

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