A method and system for constructing a three-dimensional coal mine geological model

Abstract

The present invention discloses a method and system for constructing a three-dimensional coal mine geological model, which relates to the technical field of constructing a three-dimensional coal mine geological model. The method extracts the X, Y and Z coordinates of the current data point initially constructed by the three-dimensional modeling module, the center data point X, and the coordinates of the central data point X. o , Y o and Z o coordinates, and density, and calculate the weight Q of the geological data points, the Z coordinates Z after interpolation filling new , Z coordinate after adjustment iterate , using the visualization module, all the adjusted Z coordinates Z of the current data point iterate A line graph is constructed and the iteration result is judged. The three-dimensional modeling module will update the constructed model after all the marked data points have completed the iteration. The present invention improves the accuracy and stability of the model, enhances the adaptability and visualization effect of the model, and jointly promotes the optimization and improvement of the model through mutual correlation and cyclic influence mechanisms, providing a more reliable and accurate three-dimensional model construction for coal mine geological exploration and resource assessment.

Description

Technical Field

[0001] The present invention relates to the technical field of building a three-dimensional coal mine geological model, and in particular to a method and system for building a three-dimensional coal mine geological model. Background Art

[0002] The construction of three-dimensional geological models of coal mines is an important technology in the field of geological exploration and resource assessment. This technology comprehensively utilizes multidisciplinary knowledge of modern computer graphics, geographic information systems, and geology. By constructing accurate three-dimensional geological models, it clearly displays the morphology, scale, and occurrence characteristics of geological bodies. This technology provides a reliable basis for the calculation of mineral resource reserves and potential assessment, geological disaster prediction and prevention, urban planning, environmental protection and other fields.

[0003] At present, existing technologies often lack weight calculation for geological data points, resulting in the inability to fully consider the spatial position and attribute differences of data points in model construction, which in turn affects the accuracy of the model. Its interpolation method is simple, and thus cannot accurately reflect the complexity and continuity of the geological interface. It also lacks in-depth analysis of the spatial relationship between geological data points, resulting in low model construction accuracy. In addition, the iterative adjustment process lacks clear stopping conditions, which leads to over-optimization or under-optimization of the model, and it is impossible to make dynamic adjustments based on feedback during the iterative process. Summary of the invention

[0004] The purpose of the present invention is to provide a method and system for constructing a three-dimensional coal mine geological model, which solves the problems raised in the above-mentioned background technology.

[0005] To achieve the above object, the present invention provides a method for constructing a three-dimensional model of coal mine geology as follows, including weights of geological data points in the construction of the three-dimensional model, and thus estimating and filling missing data points to iterate the construction method of accurate Z coordinates;

[0006] It includes a geological exploration collection module, a geological data processing module, a three-dimensional modeling module and a visualization module. The geological data processing module includes a unit reflecting the importance of data points in the model, an interpolation calculation unit in the three-dimensional model construction, and an iterative optimization unit in the model optimization process;

[0007] The specific implementation steps are as follows:

[0008] Step I: Extract the X, Y and Z coordinates of the current data point and the center data point X initially constructed by the three-dimensional modeling module from the established geological database. o , Y o and Z o coordinates, and density;

[0009] Wherein, the data point data collected by the geological exploration collection module is stored in the geological database;

[0010] Step II: Using the geological data processing module, calculate the geological data point weight Q, the interpolation filled Z coordinate Z new , Z coordinate after adjustment iterate ;

[0011] Step III: Using the visualization module, all the adjusted Z coordinates Z of the current data point are iterate Construct a line graph, present trends based on the line graph, and judge the iteration results;

[0012] Step III: The three-dimensional modeling module will update the constructed model after all the labeled data points have completed iteration.

[0013] Optionally, the equipment used by the geological exploration collection module includes a drilling machine and a geological radar;

[0014] The equipment used in the geological data processing module includes data processing software and high-performance computers;

[0015] The equipment used by the three-dimensional modeling module includes three-dimensional modeling software;

[0016] The equipment used by the visualization module includes data visualization software.

[0017] Optionally, the calculation formula for the unit reflecting the importance of the data point in the model is as follows:

[0018] Q = SQRT[(C x 2 +C y 2 +C z 2 ) / 3]×(1-|MM avg | / (M max -M min ));

[0019] in:

[0020] Q is the weight of the geological data point;

[0021] C x is the X coordinate difference;

[0022] C y is the Y coordinate difference;

[0023] C z is the Z coordinate difference;

[0024] X coordinate difference C x, Y coordinate difference C y and the Z coordinate difference C z They are respectively the model constructed in three-dimensional space for the current data point and the center data point X o , Y o and Z o The difference in coordinates:

[0025] C x =XX o ;

[0026] C y =YY o ;

[0027] C z =ZZ o ;

[0028] X is the X coordinate of the data point, Y is the Y coordinate of the data point, and Z is the Z coordinate of the data point;

[0029] M is the data point density;

[0030] M avg is the average density of data points;

[0031] M max is the maximum density of data points;

[0032] M min is the minimum density of data points.

[0033] Optionally, the average density of the data points M avg The calculation formula is as follows:

[0034] M avg =(M1+M2+M3+......+M n ) / n;

[0035] n is the total data points, which reflects the total number of all labeled data points in the model constructed in the three-dimensional space;

[0036] M1 is the first data point density, M2 is the second data point density, M3 is the third data point density, M n is the density of the nth data point.

[0037] Optionally, the calculation formula of the interpolation calculation unit in the three-dimensional model construction is as follows:

[0038] Z new =Z+[(Q×(Z a -Z b ) / (C ab +SQRT(Q))]×(C x a / (Cx +C y ));

[0039] in:

[0040] Z new The Z coordinate after interpolation filling;

[0041] Z a is the Z coordinate of the adjacent data point a, Z b is the Z coordinate of the adjacent b data point, and the Z coordinate of the adjacent a data point a and the Z coordinates of the adjacent b data points b Both reflect the Z coordinates of the two data points adjacent to the current data point;

[0042] C ab is the difference between adjacent ab data points, C ab Reflects the distance difference between data point a and data point b in the model constructed in three-dimensional space;

[0043] C x a is the difference in X coordinates of adjacent data points, C x a Reflects the difference in the X direction between the current data point and the adjacent data point a in the model constructed in three-dimensional space.

[0044] Optionally, the calculation formula of the iterative optimization unit in the model optimization process is as follows:

[0045] Z iterate =Z new +[(Q×(Z prev -Z new )) / (1+SQRT(T)]×(C z / (C z,prev +SQRT(Q));

[0046] in:

[0047] Z iterate is the adjusted Z coordinate;

[0048] Z prev Adjust the Z coordinate for the previous iteration;

[0049] T is the number of iterations;

[0050] C z,prev It is the Z coordinate difference of the previous iteration.

[0051] Optionally, based on the adjusted Z coordinate Z iterate The iterative analysis of model building is as follows:

[0052] If the adjusted Z coordinate Z within the iteration number Titerate And the current adjusted Z coordinate Z iterate If the linear graph shows a gentle trend, it is considered that the constructed model has reached a relatively stable state, and the iteration should be stopped at this time;

[0053] If the adjusted Z coordinate Z within the iteration number T iterate And the current adjusted Z coordinate Z iterate If there are other trends on the line graph, including rising and falling trends, it is considered that the constructed model has not reached a relatively stable state, and iteration should be continued;

[0054] Among them, the total data points n marked in the model constructed in the three-dimensional space need to be constructed iteratively, and when the total data points n all show a flat trend on the line graph, the construction and iterative optimization of the coal mine geological three-dimensional model are completed.

[0055] Optionally, the geological exploration collection module is used to implement step I;

[0056] The geological exploration collection module is used for processing and cleaning data and implementing step I;

[0057] The three-dimensional modeling module is used to construct and optimize the three-dimensional geological model and implement step IIII;

[0058] The visualization module is used to implement step III.

[0059] The present invention also provides a system for constructing a three-dimensional coal mine geological model, including a geological exploration collection module, a geological data processing module, a three-dimensional modeling module and a visualization module.

[0060] Geological exploration collection module: responsible for extracting central data point X o , Y o and Z o Coordinates, the X, Y, and Z coordinates of the current data point, and density;

[0061] Geological data processing module: responsible for calculating the geological data point weight Q, interpolation filling Z coordinate Z new , Z coordinate after adjustment iterate ;

[0062] 3D modeling module: responsible for building and updating the 3D model of coal mine geology;

[0063] Visualization module: responsible for constructing and observing the adjusted Z coordinate Z iterate of the changing trend.

[0064] Compared with the prior art, the present invention has the following beneficial effects:

[0065] 1. The present invention calculates the weight Q of geological data points by reflecting the importance of data points in the model, thereby fully considering the spatial position and attribute differences of data points, thereby improving the contribution of data in model construction, and introducing data cleaning and exception handling mechanisms to ensure the accuracy and reliability of input data.

[0066] Second, the interpolation calculation unit in the three-dimensional model construction of the present invention adopts a complex interpolation calculation method, thereby fully considering the spatial relationship and attribute differences between adjacent geological data points, and improving the construction accuracy of the model, and adjusting the X coordinate difference C of adjacent data points x a The parameters of the geological data point weight Q can flexibly control the accuracy and continuity of the interpolation results.

[0067] 3. The present invention introduces a line graph to monitor the optimization process of the model. The Z coordinate Z after the iterative optimization unit result value is adjusted iterate The changing trend of the model is monitored and clear stopping conditions are set, thereby ensuring that the model will not be over-optimized or under-optimized during the iteration process. The weight Q of the geological data points can be dynamically adjusted according to the feedback during the iteration process, thereby improving the optimization efficiency of the model.

[0068] In addition, through the circular influence mechanism, the unit reflecting the importance of the data point in the model, the interpolation calculation unit in the three-dimensional model construction and the iterative optimization unit in the model optimization process are interconnected and work together on the iterative optimization process of the model, thereby realizing the continuous optimization and improvement of the model, and thus achieving the construction and updating of the three-dimensional geological model of coal mines. BRIEF DESCRIPTION OF THE DRAWINGS

[0069] Figure 1 The method flow chart of the construction method and system of the three-dimensional geological model of the coal mine;

[0070] Figure 2 It is a structural schematic diagram of the geological data processing module of the present invention;

[0071] Figure 3 A schematic diagram of three-dimensional updating for iterative optimization in the present invention;

[0072] Figure 4 It is a schematic diagram showing that the line graph in the present invention tends to be flat. DETAILED DESCRIPTION

[0073] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0074] Regarding the construction method and system of the coal mine geological three-dimensional model, it is different from the construction of the existing coal mine geological three-dimensional model. The construction of the existing coal mine geological three-dimensional model often lacks the weight calculation of geological data points, cannot accurately reflect the complexity and continuity of the geological interface, and lacks in-depth analysis of the spatial relationship between geological data points. In addition, it is impossible to flexibly iteratively improve the construction of the three-dimensional model. This algorithm unit enhances the adaptability and visualization effect of the model by improving the accuracy and stability of the model, and jointly promotes the optimization and improvement of the model through mutual correlation and cyclic influence mechanisms, providing a more reliable and accurate three-dimensional model for coal mine geological exploration and resource assessment.

[0075] For example, see Figures 1 to 4 ,This implementation provides a method for constructing a three-dimensional model of coal mine geology, including weights of geological data points in the construction of the three-dimensional model, and thus estimating and filling missing data points to iteratively construct a method for accurate Z coordinates;

[0076] It includes a geological exploration collection module, a geological data processing module, a three-dimensional modeling module and a visualization module. The geological data processing module includes a unit reflecting the importance of data points in the model, an interpolation calculation unit in the three-dimensional model construction, and an iterative optimization unit in the model optimization process;

[0077] The specific implementation steps are as follows:

[0078] Step I: Extract the X, Y and Z coordinates of the current data point and the center data point X initially constructed by the three-dimensional modeling module from the established geological database. o , Y o and Z o coordinates, and density;

[0079] Wherein, the data point data collected by the geological exploration collection module is stored in the geological database;

[0080] Step II: Using the geological data processing module, calculate the geological data point weight Q, the interpolation filled Z coordinate Z new , Z coordinate after adjustment iterate ;

[0081] Step III: Using the visualization module, all the adjusted Z coordinates Z of the current data point are iterate Construct a line graph, present trends based on the line graph, and judge the iteration results;

[0082] Step III: The three-dimensional modeling module will update the constructed model after all the marked data points have completed iteration;

[0083] The equipment used in the geological exploration collection module includes drilling machines and geological radars;

[0084] The equipment used in the geological data processing module includes data processing software and high-performance computers;

[0085] The equipment used in the 3D modeling module includes 3D modeling software;

[0086] The equipment used in the visualization module includes data visualization software;

[0087] The geological exploration collection module is used to implement step I;

[0088] The geological exploration collection module is used for data processing, cleaning and implementation of step I;

[0089] The 3D modeling module is used to construct and optimize the 3D geological model and implement step IIII;

[0090] The visualization module is used to implement step III.

[0091] See also Figures 1 to 4 ,This implementation provides a system for constructing a three-dimensional model of coal mine geology, including a geological exploration and collection module, a geological data processing module, a three-dimensional modeling module and a visualization module.

[0092] In this embodiment, the system cooperates with three algorithm units and combines Q, Z new and Z iterate The three calculation results jointly promote the optimization and improvement of the model building process. Specifically, Q is the weight of the geological data point, which is mainly used to calculate the weight of the geological data point, and this weight will also affect the accuracy of subsequent interpolation calculations and model building. new The Z coordinate is filled by interpolation. In the construction of three-dimensional models, interpolation calculation can help the system more accurately determine the position of geological data points in three-dimensional space. Especially when there are few or missing data points in some areas, interpolation calculation can fill these blank areas to make the model more complete and accurate. iterate To adjust the Z coordinate, in the three-dimensional model of coal mine geology, the Z coordinate usually represents the key parameters of the thickness and depth of the coal seam and geological body. Through optimization iteration, the Z value can be continuously adjusted to make the model more accurately reflect the actual geological conditions. However, it should be noted that the Z value here is not simply equal to the depth of the wellbore, but is calculated after considering the boundaries between the strata and the relative position relationship between the wellbores, and Z iterate The calculation results can also affect the feedback to Q and Z newThe calculation makes the three algorithms of this system play an important role in the construction of coal mine geological three-dimensional model, and they are mutually correlated and cyclically influenced by parameters and results, which not only improves the accuracy and stability of the model, but also enhances the adaptability and visualization effect of the model, providing more reliable and accurate technical support for coal mine geological exploration and resource assessment.

[0093] See also Figures 1 to 4 , the calculation formula that reflects the importance of the data point in the model is as follows:

[0094] Q=SQRT[(C x 2 +C y 2 +C z 2 ) / 3]×(1-|MM avg | / (M max -M min ));

[0095] in:

[0096] Q is the weight of the geological data point;

[0097] C x is the X coordinate difference;

[0098] C y is the Y coordinate difference;

[0099] C z is the Z coordinate difference;

[0100] X coordinate difference C x , Y coordinate difference C y and the Z coordinate difference C z They are respectively the model constructed in three-dimensional space for the current data point and the center data point X o , Y o and Z o The difference in coordinates:

[0101] C x =XX o ;

[0102] C y =YY o ;

[0103] C z =ZZ o ;

[0104] X is the X coordinate of the data point, Y is the Y coordinate of the data point, and Z is the Z coordinate of the data point;

[0105] M is the data point density;

[0106] M avg is the average density of data points;

[0107] M max is the maximum density of data points;

[0108] M min is the minimum density of data points;

[0109] The average density of data points M avg The calculation formula is as follows:

[0110] M avg =(M1+M2+M3+......+M n ) / n;

[0111] n is the total data points, which reflects the total number of all labeled data points in the model constructed in the three-dimensional space;

[0112] M1 is the first data point density, M2 is the second data point density, M3 is the third data point density, M n is the density of the nth data point.

[0113] In this embodiment: First, in this algorithm unit, "(C x 2 +C y 2 +C z 2 The calculation part of ) is used to measure the overall distance between the position of the geological data point in three-dimensional space and the reference point of the middle child, or the square of the spatial distance, which reflects the distribution and relative position of the data point in space. This distance value is used as a factor in weight calculation. The weight Q of the geological data point is determined by dividing it by a coefficient 3 and multiplying it by another factor related to the data point density M. The weight Q of the geological data point will be used for weighted processing in model construction later;

[0114] “|MM avg |"The calculation part is used to measure the density of data points M and the average density of all geological data points M avg The deviation between them reflects the discreteness and abnormality of the data point attributes, and this deviation value is used to adjust the weight calculation by taking its absolute value and dividing it by (M max -M min ), and then the ratio is subtracted from a coefficient 1, and finally the weight Q of the geological data point is determined together with the square of the spatial distance. The weight Q of the geological data point will affect the contribution of the data point in the model construction;

[0115] This algorithm unit calculates the X coordinate difference C x, Y coordinate difference C y and the Z coordinate difference C z , and then it can identify abnormal data points, which are caused by measurement errors and geological anomalies. By eliminating these abnormal points, the overall accuracy of the data can be improved. The addition of density attribute information makes the distribution of data points in three-dimensional space more consistent with geological reality, further improving the reliability of the data;

[0116] Weight calculation is the core part of the unit that reflects the importance of data points in the model. It assigns a weight value to each data point according to the spatial position and attribute difference of the data point. This weight value reflects the importance and contribution of the data point in the model construction process. By introducing weights, the model can better adapt to the changes and uncertainties of the data and improve the robustness of the model.

[0117] This algorithm unit can optimize the distribution of data in three-dimensional space by weighting the data points, which helps to more accurately reflect the morphology and characteristics of the geological body during the model construction process. Weighted processing can also make the data points more evenly distributed in space, avoiding data sparsity and data redundancy, thereby improving the accuracy and efficiency of model construction.

[0118] See also Figures 1 to 4 , the calculation formula of the interpolation calculation unit in the three-dimensional model construction is as follows:

[0119] Z new =Z+[(Q×(Z a -Z b ) / (C ab +SQRT(Q))]×(C x a / (C x +C y ));

[0120] in:

[0121] Z new The Z coordinate after interpolation filling;

[0122] Z a is the Z coordinate of the adjacent data point a, Z b is the Z coordinate of the adjacent b data point, and the Z coordinate of the adjacent a data point a and the Z coordinates of the adjacent b data points b Both reflect the Z coordinates of the two data points adjacent to the current data point;

[0123] C ab is the difference between adjacent ab data points, C ab Reflects the distance difference between data point a and data point b in the model constructed in three-dimensional space;

[0124] C x a is the difference in X coordinates of adjacent data points, C x a Reflects the difference in the X direction between the current data point and the adjacent data point a in the model constructed in three-dimensional space.

[0125] In this embodiment, first, “(Q×(Z a -Z b The calculation part is used to calculate the adjustment amount of the Z value in the interpolation process according to the difference in Z values ​​between adjacent data points a and b and the weight Q of the geological data point. It reflects the degree of influence of the height change between adjacent points on the interpolation result. This adjustment amount is used to calculate the Z value after interpolation. The Z coordinate Z after interpolation filling new , and the Z coordinate after interpolation filling is Z new It will be used to construct terrain and geological interfaces in the 3D model;

[0126] This algorithm unit can fully consider the spatial relationship and attribute differences between adjacent geological data points through interpolation calculation, and introduce the Z coordinates Z of adjacent a data points. a , Z coordinates of adjacent b data points b , the difference between adjacent ab data points C ab , the difference in X coordinates of adjacent data points C x a and the Q parameter of the geological data point weight, the Z value in the interpolated three-dimensional coordinates can be calculated, thereby constructing a more detailed and accurate three-dimensional geological model;

[0127] Among them, the interpolation calculation can also be adaptively adjusted according to the shape and characteristics of the geological body, so that the model can better reflect the complexity and continuity of the geological interface during the construction process;

[0128] This algorithm unit can generate a smoother and more continuous three-dimensional geological interface through interpolation calculation, which helps to improve the visualization effect and readability of the model, so that the system can more intuitively reflect the shape and characteristics of the geological body. The interpolation calculation can also perform refinement processing at different scales as needed to meet the visualization needs of different accuracy requirements;

[0129] In addition, interpolation calculation can reduce the number of data points and reduce the complexity and computational effort of model construction, which helps to improve the efficiency of model construction, especially when dealing with large-scale geological data. By optimizing the interpolation algorithm and parameter settings, the speed and accuracy of model construction can be further improved.

[0130] See also Figures 1 to 4 , the calculation formula of the iterative optimization unit in the model optimization process is as follows:

[0131] Ziterate =Z new +[(Q×(Z prev -Z new )) / (1+SQRT(T)]×(C z / (C z,prev +SQRT(Q));

[0132] in:

[0133] Z iterate is the adjusted Z coordinate;

[0134] Z prev Adjust the Z coordinate for the previous iteration;

[0135] T is the number of iterations;

[0136] C z,prev It is the Z coordinate difference of the previous iteration.

[0137] In this embodiment, the algorithm unit first “(Q×(Z prev -Z new The calculation part is used to adjust the Z coordinate Z according to the previous iteration. prev and the interpolated Z coordinate after filling new The difference between the values ​​and the adjusted geological data point weight Q is used to calculate the adjustment amount of the Z value during the iteration process, which reflects the direction and degree of model optimization during the iteration process. This adjustment amount is used to calculate the adjusted Z coordinate Z iterate , by adjusting the Z coordinate Z after one iteration with the number of iterations T and prev The adjusted Z coordinate Zprev is determined by the interpolated Z coordinate Znew and the weight Q of the geological data point. It will be used to update the terrain and geological interface in the three-dimensional model, thereby achieving iterative optimization of the model. SQRT means square root function, which calculates the square root of a non-negative real number.

[0138] The iterative adjustment of this algorithm unit can dynamically adjust the parameters and structure of the model according to the results of the previous iteration and the current data status. Through continuous iterative optimization, the error and uncertainty of the model can be gradually reduced, thereby improving the accuracy and stability of the model. The iterative adjustment can also perform optimization processing of different scales as needed, thereby meeting the optimization needs of different accuracy requirements;

[0139] And through iterative adjustment, the unstable factors in the model can be gradually eliminated, which helps to improve the stability and reliability of the model, making the model more accurate and reliable in subsequent geological analysis and resource assessment. Iterative adjustment can also be adaptively adjusted according to changes in geological conditions, thereby enhancing the adaptability and robustness of the model.

[0140] Iterative adjustment can make the model better adapt to data changes and uncertainties during the construction process. By continuously optimizing the parameters and structure of the model, the performance and predictive ability of the model can be improved, thereby further improving the accuracy and efficiency of the model.

[0141] In summary, the unit that reflects the importance of data points in the model, the interpolation calculation unit in the three-dimensional model construction, and the iterative optimization unit in the model optimization process each play an important role in the construction of coal mine geological three-dimensional models, and they jointly promote the optimization and improvement of the model construction process through the mutual correlation and cyclic influence of parameters and results. The beneficial effects of these formulas and their parameters not only improve the accuracy and stability of the model, but also enhance the adaptability and visualization effect of the model, providing more reliable and accurate technical support for coal mine geological exploration and resource assessment.

[0142] For example 2, please refer to Figures 1 to 4 , based on the adjusted Z coordinate Z iterate The iterative analysis of model construction is as follows:

[0143] If the adjusted Z coordinate Z within the iteration number T iterate And the current adjusted Z coordinate Z iterate If the linear graph shows a gentle trend, it is considered that the constructed model has reached a relatively stable state, and the iteration should be stopped at this time;

[0144] If the adjusted Z coordinate Z within the iteration number T iterate And the current adjusted Z coordinate Z iterate If there are other trends on the line graph, including rising and falling trends, it is considered that the constructed model has not reached a relatively stable state, and iteration should be continued;

[0145] Among them, the total data points n marked in the model constructed in the three-dimensional space need to be constructed iteratively, and when the total data points n all show a flat trend on the line graph, the construction and iterative optimization of the coal mine geological three-dimensional model are completed.

[0146] In this embodiment, the cyclic influence mechanism enables the model to continuously receive feedback and adjustments during the construction process, thereby achieving continuous optimization and improvement. The cyclic influence mechanism enables the model to better adapt to data changes and uncertainties during the construction process, improve the adaptability and flexibility of the model, and continuously correct and improve errors and defects in the model through the cyclic influence mechanism, thereby improving the accuracy and reliability of the model.

[0147] It is worth noting that the line graph can intuitively show the Z coordinate Z after the iterative optimization unit is adjusted during the model optimization process. iterate The trend of changes during the iteration process is plotted by plotting the number of iterations T and the adjusted Z coordinate Z iterateThe corresponding relationship between the Z coordinate and the Z coordinate can be clearly seen during the model optimization process. iterate This intuitive display method helps to better understand the iterative process of the model and make more accurate judgments;

[0148] During the iteration process, we need a clear stopping condition to ensure that the model is not over-optimized or under-optimized. Through the line graph, we can observe the Z coordinate Z after adjustment. iterate Is the change trend of sluggish? When the Z coordinate Z is adjusted between adjacent iterations T iterate When the trend is stable, it can be considered that the model has reached a relatively stable state, and the iteration can be stopped at this time. This method of setting the iteration stop condition based on the line chart is more accurate and reliable;

[0149] After the introduction of the line graph, the system can more quickly identify potential problems in the model optimization process. Specifically, if the line graph shows that the Z coordinate Z iterate If there are obvious fluctuations and anomalies in the iteration process, it means that there are some undiscovered problems and errors in the model. By timely discovering the problems and taking corresponding adjustment measures, unnecessary iterations and waste of computing resources can be avoided, thereby improving the efficiency of model construction;

[0150] The line graph can not only help us set the iteration stop condition, but also promote the iterative optimization of the model. During the iteration process, the parameters and weights in the formula can be adjusted according to the changing trend of the line graph to further optimize the model. Specifically, if the line graph shows that the adjusted Z coordinate Z iterate If there is still an obvious upward trend in the later stage of iteration, consider increasing the number of iterations T and adjusting the weight of geological data points Q to further improve the model effect. This iterative optimization method based on line graphs helps to adjust model parameters more flexibly, thereby achieving better model performance. By introducing line graphs to set iteration conditions, the changes in the model optimization process and the final results can be more clearly displayed. This visualization method helps to enhance the interpretability and credibility of the model.

[0151] In summary, closely combining the unit that reflects the importance of data points in the model, the interpolation calculation unit in the three-dimensional model construction, and the iterative optimization unit in the model optimization process and introducing a line graph to set the iteration conditions has a significant beneficial effect in the process of constructing a three-dimensional coal mine geological model. This method not only improves the efficiency and accuracy of model construction, but also enhances the interpretability and credibility of the model, provides strong technical support for coal mine geological exploration and development, and jointly promotes the optimization and improvement of the model through mutual correlation and cyclic influence mechanisms. These formulas not only improve the accuracy and stability of the model, but also enhance the adaptability and visualization effect of the model, providing more reliable and accurate technical support for coal mine geological exploration and resource assessment.

[0152] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations can be made to the embodiments without departing from the principles and spirit of the present invention, and the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for constructing a three-dimensional coal mine geological model, characterized in that: A method for iteratively constructing precise Z coordinates by including weights of geological data points in the construction of a 3D model and thereby estimating and filling in missing data points; It includes a geological exploration collection module, a geological data processing module, a three-dimensional modeling module and a visualization module. The geological data processing module includes a unit reflecting the importance of data points in the model, an interpolation calculation unit in the three-dimensional model construction, and an iterative optimization unit in the model optimization process; The specific implementation steps are as follows: Step I: Extract the X, Y and Z coordinates of the current data point and the center data point X initially constructed by the three-dimensional modeling module from the established geological database. o , Y o and Z o coordinates, and density; Wherein, the data point data collected by the geological exploration collection module is stored in the geological database; Step II: Using the geological data processing module, calculate the geological data point weight Q, the interpolation filled Z coordinate Z new , Z coordinate after adjustment iterate ; Step III: Using the visualization module, all the adjusted Z coordinates Z of the current data point are iterate Construct a line graph, present trends based on the line graph, and judge the iteration results; Step III: The three-dimensional modeling module will update the constructed model after all the labeled data points have completed iteration.

2. The method for constructing a three-dimensional coal mine geological model according to claim 1, characterized in that: The equipment used in the geological exploration collection module includes a drilling machine and a geological radar; The equipment used in the geological data processing module includes data processing software and high-performance computers; The equipment used by the three-dimensional modeling module includes three-dimensional modeling software; The equipment used by the visualization module includes data visualization software.

3. The method for constructing a three-dimensional coal mine geological model according to claim 2, characterized in that: The calculation formula for the unit reflecting the importance of the data point in the model is as follows: Q=SQRT[(C x 2 +C y 2 +C z 2 ) / 3]×(1-|M-M avg | / (M max -M min )); in: Q is the weight of the geological data point; C x is the X coordinate difference; C y is the Y coordinate difference; C z is the Z coordinate difference; X coordinate difference C x , Y coordinate difference C y and the Z coordinate difference C z They are respectively the model constructed in three-dimensional space for the current data point and the center data point X o , Y o and Z o The difference in coordinates: C x =X-X o ; C y =YY o ; C z =ZZ o ; X is the X coordinate of the data point, Y is the Y coordinate of the data point, and Z is the Z coordinate of the data point; M is the data point density; M avg is the average density of data points; M max is the maximum density of data points; M min is the minimum density of data points.

4. The method for constructing a three-dimensional coal mine geological model according to claim 3, characterized in that: The average density of the data points M avg The calculation formula is as follows: M avg =(M1+M2+M3+......+M n ) / n; n is the total data points, which reflects the total number of all labeled data points in the model constructed in the three-dimensional space; M1 is the first data point density, M2 is the second data point density, M3 is the third data point density, M n is the density of the nth data point.

5. The method for constructing a three-dimensional coal mine geological model according to claim 3, characterized in that: The calculation formula of the interpolation calculation unit in the three-dimensional model construction is as follows: Z new =Z+[(Q×(Z a -Z b ) / (C ab +SQRT(Q))]×(C x a / (C x +C y )); in: Z new The Z coordinate after interpolation filling; Z a is the Z coordinate of the adjacent data point a, Z b is the Z coordinate of the adjacent b data point, and the Z coordinate of the adjacent a data point a and the Z coordinates of the adjacent b data points b Both reflect the Z coordinates of the two data points adjacent to the current data point; C ab is the difference between adjacent ab data points, C ab Reflects the distance difference between data point a and data point b in the model constructed in three-dimensional space; C x a is the difference in X coordinates of adjacent data points, C x a Reflects the difference in the X direction between the current data point and the adjacent a data point in the model constructed in three-dimensional space.

6. The method for constructing a three-dimensional coal mine geological model according to claim 5, characterized in that: The calculation formula of the iterative optimization unit in the model optimization process is as follows: Z iterate =Z new +[(Q×(Z prev -Z new )) / (1+SQRT(T)]×(C z / (C z,prev +SQRT(Q))); in: Z iterate is the adjusted Z coordinate; Z prev Adjust the Z coordinate for the previous iteration; T is the number of iterations; C z,prev It is the Z coordinate difference of the previous iteration.

7. The method for constructing a three-dimensional coal mine geological model according to claim 6, characterized in that: Based on the adjusted Z coordinate Z iterate The iterative analysis of model building is as follows: If the adjusted Z coordinate Z within the iteration number T iterate And the current adjusted Z coordinate Z iterate If the linear graph shows a gentle trend, it is considered that the constructed model has reached a relatively stable state, and the iteration should be stopped at this time; If the adjusted Z coordinate Z within the iteration number T iterate And the current adjusted Z coordinate Z iterate If there are other trends on the line graph, including rising and falling trends, it is considered that the constructed model has not reached a relatively stable state, and iteration should be continued; Among them, the total data points n marked in the model constructed in the three-dimensional space need to be constructed iteratively, and when the total data points n all show a flat trend on the line graph, the construction and iterative optimization of the coal mine geological three-dimensional model are completed.

8. The method for constructing a three-dimensional coal mine geological model according to claim 2, characterized in that: The geological exploration collection module is used to implement step I; The geological exploration collection module is used for processing and cleaning data and implementing step I; The three-dimensional modeling module is used to construct and optimize the three-dimensional geological model and implement step IIII; The visualization module is used to implement step III.

9. The construction system used in the method for constructing a three-dimensional coal mine geological model according to claim 1, characterized in that: Including geological exploration collection module, geological data processing module, 3D modeling module and visualization module Geological exploration collection module: responsible for extracting central data point X o , Y o and Z o Coordinates, the X, Y, and Z coordinates of the current data point, and density; Geological data processing module: responsible for calculating the geological data point weight Q, interpolation filling Z coordinate Z new , Z coordinate after adjustment iterate ; 3D modeling module: responsible for building and updating the 3D model of coal mine geology; Visualization module: responsible for constructing and observing the adjusted Z coordinate Z iterate 's changing trend.

Images