Exploration drilling data analysis and visualization expression method

Abstract

The present invention discloses a method for analyzing and visualizing exploration borehole data. After preprocessing the basic borehole data and attribute data, a binary element multidimensional mapping variable attribute data array pool and a visual expression system are constructed; the concentration degree analysis of the exploration borehole attribute data and the drawing of the multidimensional mapping relationship scatter plot are carried out, and the attribute data statistics and analysis are performed; at the same time, a binary element multidimensional mapping variable attribute pixel array pool is constructed, and according to the reshaped visual expression system and actual needs, a panoramic map and thematic map of the exploration borehole are drawn, and the spatial combination feature display and analysis of the borehole attribute data are performed. The advantages of the present invention are that the hierarchical classification principle of the geological profession for the borehole attribute information is fully utilized to form a panoramic map of the exploration borehole, and a systematic visualization expression and analysis method for the exploration borehole data is constructed, which has a novel style, is convenient to make, has a flexible expression form, is convenient for data extraction and correlation analysis, and greatly improves work efficiency.

Description

Technical Field

[0001] The present invention relates to the field of geological exploration, and in particular to an exploration drilling data analysis and visualization expression method. Background Art

[0002] With the rapid development of software and information technology, the construction of exploration drilling databases has become more convenient and data processing has become more efficient. However, the presentation of exploration drilling data processing results is still very traditional and backward, mostly in the form of numbers and lines such as drilling column charts, profiles and drilling comprehensive charts, and some attribute information is also presented in the form of pattern filling.

[0003] This traditional way of presenting exploration drilling data has the following shortcomings:

[0004] First, the expression form is rigid and the data display flexibility is poor. The borehole profile must be formed by more than two boreholes to form a profile line, and the profile can only be drawn based on the stratigraphic information of the entire borehole. If you want to separately display the weathering degree characteristics, core sampling rate characteristics, permeability characteristics or wave velocity characteristics of a certain section of the stratum under certain limited conditions, it is difficult to achieve using professional drawings such as borehole column charts, profiles and borehole comprehensive charts. At the same time, traditional survey data processing can generally only display all the attribute information of some boreholes, and cannot simultaneously display certain attribute information of all the boreholes of the project in one dimension for data expression and analysis. This causes the expression form of traditional survey drilling data to be rigid and the data display flexibility to be poor.

[0005] Secondly, the data visualization effect is poor. These survey drilling data presentation methods, which are composed of points and lines, combined with pattern filling and text description, can only be recognized by professionals through careful analysis of the relevant points, lines and numbers. Non-professionals often find it boring, obscure and unclear.

[0006] Finally, it is difficult to extract attribute information and poorly integrate with data analysis functions. It is difficult to directly convert lines, pattern fills, etc. from borehole histograms, profiles, and comprehensive borehole charts into data for output and in-depth data mining and analysis. Even if part or all of the survey borehole data is exported from the database, the data needs to be reorganized before further data analysis can be performed, and the spatial attribute information corresponding to the data cannot be intuitively expressed, such as the borehole where the data is located, the borehole location, and the relative position of the borehole.

[0007] The traditional way of presenting exploration drilling data can no longer meet the needs of the current development of software information technology and exploration work, which often leads to the exploration drilling data that cost a huge amount of money to produce being restricted by the form of expression, and its exposure rate and visual communication effect are at a low level. It is urgent to use the current more advanced technical means to reconstruct the exploration drilling data analysis and expression method, and establish a non-traditional exploration drilling data expression and analysis method, so as to simplify and intuitively express and analyze the exploration drilling data, and greatly improve the visualization expression effect of the drilling data. Summary of the invention

[0008] The purpose of the present invention is to provide a method for analyzing and visualizing exploration drilling data, which provides a new perspective for viewing and examining the exploration drilling data in the form of panoramic maps and thematic maps of drilling attribute data.

[0009] To achieve the above object, the present invention adopts the following technical solutions:

[0010] The method for analyzing and visualizing exploration drilling data of the present invention comprises the following steps:

[0011] S1, using the survey data information collection system, collect the basic data and attribute data of the borehole, and build a survey borehole basic attribute information database;

[0012] S2, preprocessing the attribute data to construct a binary element multi-dimensional mapping variable attribute data array pool;

[0013] S3, build a visual expression system based on basic attribute data;

[0014] S4, batch extract attribute data and conduct aggregation analysis of exploration borehole attribute data;

[0015] S5, drawing a multi-dimensional mapping relationship scatter plot according to the visual expression system and the needs of actual analysis and expression, and performing attribute data statistics and analysis;

[0016] S6, constructs a binary element multidimensional mapping variable attribute pixel array pool, draws a panoramic map of the exploration borehole and a thematic map of the exploration borehole according to the reconstructed visualization expression system and the needs of actual analysis and expression, and displays and analyzes the spatial combination characteristics of the attribute data.

[0017] Furthermore, in step S1, the basic data refers to data that is not related to the stratum itself, including the borehole number, borehole location, borehole coordinates, borehole diameter information, borehole depth information, borehole type and start and completion dates;

[0018] The attribute data refers to data directly related to the stratum, including a plurality of attribute data of a plurality of attribute categories;

[0019] The attribute categories include lithology, weathering degree, stratigraphic age, permeability, RQD, wave velocity, and apparent resistivity;

[0020] Each attribute data of each attribute category includes a corresponding elevation of the attribute data.

[0021] Further, in step S2, the binary element multi-dimensional mapping variable attribute data array pool refers to the mapping between the elevation, the borehole number and the attribute data of multiple attribute categories, with the elevation and the borehole number as binary elements and the attribute data of multiple attribute categories as variable attribute data;

[0022] The elevation is determined by rounding off the maximum and minimum values ​​of the corresponding elevation described in the attribute data and discretizing it with 1 meter as the elevation unit.

[0023] Furthermore, in step S2, the preprocessing specifically includes the following contents:

[0024] S2.1, generalizing the corresponding elevation of the attribute data by rounding off to an integer, so that the attribute data corresponds to the elevation;

[0025] S2.2, when one attribute data corresponds to a plurality of said elevation units, assigning the attribute data to each elevation within the plurality of elevation units by discretization;

[0026] S2.3, for multiple attribute data corresponding to one elevation unit, the arithmetic mean of all attribute data in the elevation unit is taken as the attribute data of the elevation at the end of the selected elevation unit.

[0027] Furthermore, step S3 specifically includes the following contents:

[0028] S3.1, setting a corresponding visual expression symbol for each of the borehole numbers to distinguish each borehole; matching the number of visual expression symbols of different shapes according to the number of borehole numbers, the visual expression symbols including but not limited to squares, triangles, and circles;

[0029] S3.2, classifying or grading the attribute data of the attribute category according to actual needs and general rules in the field of geological survey for water conservancy and hydropower engineering;

[0030] S3.3, setting a standard color that can distinguish each category and level from each other, and constructing the visual expression system for each category and level of attribute data.

[0031] Furthermore, step S4 specifically includes the following contents:

[0032] S4.1, for any of the attribute categories of the water permeability, the RQD, the wave velocity, and the apparent resistivity, separately carry out the attribute data aggregation statistics and analysis;

[0033] S4.2, make an autocorrelation curve based on the attribute data in the attribute category;

[0034] S4.3, determine the number of attribute data in the attribute category on equally spaced data segments;

[0035] S4.4, calculate the data density of equally spaced data segments based on the number of attribute data in the equally spaced data segments, and perform data aggregation analysis.

[0036] Further, step S5 is any combination of the following steps, specifically:

[0037] S5.1, taking the elevation and the borehole number as restriction conditions, selecting the attribute data of any attribute category, constructing a scatter plot of the multidimensional mapping relationship between the elevation, the borehole number and the attribute data of each attribute category according to the established visual expression system, and performing attribute data statistics and analysis;

[0038] S5.2, taking elevation, borehole number, and any one or more attribute categories as restriction conditions, select the attribute data of any other attribute category, and construct a multi-dimensional mapping relationship scatter plot of elevation, borehole number and attribute data of each attribute category according to the established visual expression system, and conduct attribute data statistics and analysis under special restriction conditions;

[0039] S5.3, taking elevation, borehole number, any one or more of the categories or levels of attribute data of any attribute category as restriction conditions, select attribute data of any other attribute category, and construct a scatter plot of the multidimensional mapping relationship between elevation, borehole number and attribute data of each attribute category based on the established visual expression system, and conduct attribute data statistics and analysis under special restricted conditions.

[0040] Further, step S6 specifically includes the following steps:

[0041] S6.1, reconstruct the attribute data visualization expression system;

[0042] S6.2, construct a binary element multidimensional mapping variable attribute pixel array pool;

[0043] S6.3, draw a panoramic map of the exploration borehole;

[0044] S6.4, draw thematic maps of exploration boreholes;

[0045] S6.5, display and analyze the spatial structure characteristics of the atlas.

[0046] Further, step S6.1 includes the following steps:

[0047] S6.1.1, classify or grade the attribute data of the attribute category according to actual needs and general rules in the field of geological survey for water conservancy and hydropower engineering;

[0048] S6.1.2, setting a standard color that can distinguish each category and level from each other, and constructing a visual expression system for each category and level of attribute data;

[0049] S6.1.3, based on the standard colors of the categories and levels within the attribute categories, color scales are matched for different attribute data within the same level or category, and the closer the attribute data of the same level or category is to the upper limit value of the level or category, the closer the color of the attribute data is to the standard color of the level.

[0050] Further, step S6.2 includes the following steps:

[0051] S6.2.1, adjusting the data arrangement structure of the binary element multidimensional mapping variable attribute data array pool described in step S2 according to a specific arrangement rule;

[0052] S6.2.2, according to the reconstructed visualization expression system, assigning a physical space cell to each attribute data in the adjusted binary element multidimensional mapping variable attribute data array pool, and constructing the binary element multidimensional mapping variable attribute pixel array pool;

[0053] S6.2.3, according to the reconstructed visualization expression system, different pixel values ​​are assigned to each cell of the entity space based on the attribute data value.

[0054] Furthermore, the specific arrangement rule described in step S6.2.1 refers to the arrangement order of the boreholes selected according to the needs of displaying and expressing the survey results, which can display the specific spatial structure of the engineering entity. The arrangement order of the borehole numbers is determined by the borehole arrangement order, the elevations are arranged in descending order, and the arrangement order of the attribute data is determined according to the needs of displaying and expressing the survey results.

[0055] Furthermore, the panoramic map of the survey boreholes described in step S6.3 is a panoramic map of the survey boreholes constructed by a pixel array corresponding to any one or more of the attribute categories at all the elevations within the survey range of all the boreholes. According to the color change characteristics of the panoramic map of the survey boreholes, key feature values ​​such as color mutations and color elevation boundaries are extracted to display and analyze the spatial combination characteristics of the attribute data.

[0056] Further, the exploration borehole thematic map in step S6.4 includes any combination of the following steps, specifically:

[0057] S6.4.1, using the pixel arrays corresponding to any one or more attribute categories of the borehole numbers of all the boreholes included in any engineering part at all the elevations within the survey range as screening conditions, construct a survey borehole thematic map, and display and analyze the spatial combination characteristics of the attribute data under limited conditions;

[0058] S6.4.2, with elevation, borehole number and any one or more levels or categories of attribute data of any one or more attribute categories as restriction conditions, select the pixel array corresponding to the attribute data of any one or more other attribute categories of the binary element multidimensional mapping variable attribute pixel array pool, and draw the exploration borehole thematic map; according to the color change characteristics of the exploration borehole thematic map, extract the key characteristic values ​​of color mutation and color elevation boundary, and display and analyze the spatial combination characteristics of the attribute data under the restricted conditions.

[0059] Furthermore, after the survey borehole panoramic map and the survey borehole thematic map are drawn, it supports autonomous adjustment of the pixel values ​​of the attribute data displayed in the survey borehole panoramic map and the survey borehole thematic map according to data expression and display needs.

[0060] The advantage of the present invention is that it provides a new data organization structure, that is, the big data in the traditional exploration borehole database is converted through certain rules to construct a database structure mode with certain logical thinking and spatial structure, that is, a binary element multidimensional mapping variable attribute array pool, which is convenient for quickly extracting borehole related attribute data and elevation data, and performing data display and analysis related to elevation attributes. The new database structure mode can save a lot of time for extracting, analyzing and processing borehole data in the traditional working mode, has more engineering application value, and facilitates the statistical analysis of borehole data, and improves work efficiency.

[0061] The advantage of the present invention is that by constructing a chromatogram matrix of exploration borehole attributes, the hierarchical classification principle of borehole attribute information is fully utilized in the geological profession, different pixel values ​​are assigned according to the differences between the borehole attribute values, and a panoramic chromatogram display diagram of the exploration borehole is formed, which provides a new method for expressing exploration borehole data and a new perspective for viewing the borehole attribute information structure, which has a flexible structure, novel style and convenient display.

[0062] The advantage of the present invention is that it summarizes the experience in survey borehole database construction, survey borehole data expression and display methods over the years, and forms a systematic survey borehole data expression and analysis method through summarizing and improving a large amount of practical experience. The method has novel style, simple production, flexible expression, convenient data extraction and correlation analysis, has been applied in relevant engineering survey projects, and has good engineering applicability and scalability. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] Figure 1 is a flow chart of the method of the present invention.

[0064] Figure 2 It is a schematic diagram of a binary element multidimensional attribute data mapping matrix of the method described in the present invention.

[0065] Figure 3 It is a schematic diagram of data aggregation analysis of the method of the present invention.

[0066] Figure 4 It is a scatter diagram illustrating the multi-dimensional mapping relationship of the method of the present invention.

[0067] Figure 5 It is a flow chart of drawing panoramic maps and thematic maps of exploration boreholes by the method of the present invention.

[0068] Figures 6 to 9 It is a schematic diagram of the panoramic map of the exploration drilling of the method described in the present invention.

[0069] Fig.10 and Fig.11 It is a schematic diagram of the exploration drilling thematic map of the method described in the present invention. DETAILED DESCRIPTION

[0070] The technical solutions in the embodiments of the present invention are described clearly and completely below. 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.

[0071] like Figure 1 As shown, the method for analyzing and visualizing exploration drilling data of the present invention comprises the following steps:

[0072] S1, using the survey data information collection system, collect borehole basic data and attribute data, build a survey borehole basic attribute information database; realize batch rapid extraction and editing of borehole basic attribute data;

[0073] The basic data refers to data that is not related to the stratum itself, including but not limited to the borehole number, borehole location, borehole coordinates, borehole diameter information, borehole depth information, borehole type and start and completion dates, etc.;

[0074] The attribute data refers to data directly related to the stratum, including a plurality of attribute data of a plurality of attribute categories;

[0075] The attribute categories include lithology, weathering degree, stratigraphic age, water permeability, RQD, wave velocity, apparent resistivity, etc.;

[0076] Each attribute data of each attribute category includes a corresponding elevation of the attribute data.

[0077] S2, preprocessing the attribute data to construct a binary element multi-dimensional mapping variable attribute data array pool;

[0078] The binary element multi-dimensional mapping variable attribute data array pool refers to the mapping between the elevation, the borehole number and the attribute data of multiple attribute categories, with the elevation and the borehole number as binary elements and the attribute data of multiple attribute categories as variable attribute data; its expression is:

[0079]

[0080] In the expression, H represents elevation, ID represents borehole number, and A1, B1, etc. represent attribute data arranged in a preset order. When reading the display, the borehole is determined by ID, the elevation of the borehole is limited by H, and the attribute category is identified in a preset order; for example, the first order bit in the preset order represents lithology, the second order bit represents permeability, and so on. The specific expression of this expression is as follows: Figure 2 As shown in the figure, H represents elevation, XBZK01 is the borehole number, A represents lithology, B represents weathering degree, C represents water permeability, D represents RQD, E represents wave velocity, F represents apparent resistivity, G represents stratigraphic age, A1 and A2 represent certain values ​​of lithology; B1 and B2 represent certain values ​​of weathering degree, and so on. The attribute data of each attribute category at each elevation of the borehole number XBZK01 can be quickly identified; Figure 2 When the middle H is at 531 meters, the C value of the borehole number XBZK01 is 12.07, which means that the permeability of the borehole number XBZK01 is 12.07 at an elevation of 531.

[0081] The elevation is determined by rounding off the maximum and minimum values ​​of the corresponding elevation described in the attribute data and discretizing it with 1 meter as the elevation unit.

[0082] The preprocessing specifically includes the following contents:

[0083] S2.1, generalizing the corresponding elevation of the attribute data by rounding off to an integer, so that the attribute data corresponds to the elevation;

[0084] S2.2, when one attribute data corresponds to a plurality of said elevation units, assigning the attribute data to each elevation within the plurality of elevation units by discretization;

[0085] For example, lithology, weathering degree, stratigraphic age, permeability, and RQD all belong to the case where one attribute data corresponds to multiple elevation units.

[0086] When collecting borehole data for actual exploration, for example, a borehole numbered XBZK01 has its lithology attribute data collected between 523.6m and 533.1m, which is sandstone. Since the lithology attribute data corresponding to the elevation of 523.6m to 533.1m for sandstone is a non-integer, the elevation corresponding to sandstone is generalized to 524m to 533m by rounding off. In this case, the lithology attribute data of the elevations of 524m, 525m, 526m, 527m, 528m, 529m, 530m, 531m, 532m, and 533m in borehole XBZK01 are all sandstone.

[0087] Similarly, the borehole number is XBZK01, and its permeability attribute data collected through the borehole water pressure test is 13.02Lu at elevations 524m to 528m. Then the permeabilities at elevations 524m, 525m, 526m, 527m, and 528m in borehole XBZK01 are all 13.02Lu;

[0088] The borehole number is XBZK01, and its RQD attribute data is 40% at the elevation of 529.5m to 532.5m. According to the rounding, the elevation corresponding to 40% of the RQD attribute data is generalized to 530m to 533m. Therefore, the RQD data at elevations of 530 m, 531m, 532 m, and 533m in the borehole XBZK01 are 40%.

[0089] S2.3, for multiple attribute data corresponding to one elevation unit, the arithmetic mean of all attribute data in the elevation unit is taken as the attribute data of the elevation at the end of the selected elevation unit.

[0090] For example, wave velocity and apparent resistivity belong to the case where one elevation unit corresponds to multiple attribute data. The attribute data wave velocity is generally collected in units of 10cm, 15cm or 20cm. For example, the borehole number is XBZK01, which collects wave velocity values ​​in units of 10cm. The arithmetic average of several wave velocity attribute data obtained between 532m and 533m in one elevation unit is taken as the wave velocity value at the end elevation of 533m in the selected elevation unit in the borehole XBZK01.

[0091] S3, build a visual expression system based on basic attribute data; specifically includes the following contents:

[0092] S3.1, setting a corresponding visual expression symbol for each borehole number to distinguish each borehole; matching the number of visual expression symbols of different shapes according to the number of borehole numbers, wherein the visual expression symbol includes but is not limited to a square, a triangle, a circle, etc.;

[0093] S3.2, classifying or grading the attribute data of the attribute category according to actual needs and general rules in the field of geological survey for water conservancy and hydropower engineering;

[0094] S3.3, setting a standard color that can distinguish each category and level from each other, and constructing the visual expression system for each category and level of attribute data.

[0095] S4, batch extract attribute data, and conduct aggregation analysis of exploration borehole attribute data; specifically includes the following contents:

[0096] S4.1, for any of the attribute categories of the water permeability, the RQD, the wave velocity, and the apparent resistivity, separately carry out the attribute data aggregation statistics and analysis;

[0097] S4.2, make an autocorrelation curve based on the attribute data in the attribute category;

[0098] S4.3, determine the number of attribute data in the attribute category on equally spaced data segments;

[0099] S4.4, calculate the data density of equally spaced data segments based on the number of attribute data in the equally spaced data segments, and perform data aggregation analysis.

[0100] like Figure 3 As shown, the horizontal and vertical axes are both permeability, and the autocorrelation curve of permeability is drawn. The curve is expressed as a straight line with a slope of 1. With 10 Lu as an equal interval, the number of attribute data of permeability in each data segment such as 0~10, 10~20, 20~30 is segmented and counted, and the data density of the equally spaced data segments is calculated; the greater the data density, the higher the data aggregation degree; the higher the proportion of the attribute data in the equally spaced data segment.

[0101] S5, drawing a multi-dimensional mapping relationship scatter plot according to the visual expression system and the needs of actual analysis and expression, and performing attribute data statistics and analysis;

[0102] According to the needs of actual analysis and expression, the following types of multi-dimensional mapping relationship scatter plots can be combined arbitrarily, specifically:

[0103] S5.1, taking the elevation and the borehole number as restriction conditions, selecting the attribute data of any attribute category, constructing a scatter plot of the multidimensional mapping relationship between the elevation, the borehole number and the attribute data of each attribute category according to the established visual expression system, and performing attribute data statistics and analysis;

[0104] S5.2, taking elevation, borehole number, and any one or more attribute categories as restriction conditions, select the attribute data of any other attribute category, and construct a multi-dimensional mapping relationship scatter plot of elevation, borehole number and attribute data of each attribute category according to the established visual expression system, and conduct attribute data statistics and analysis under special restriction conditions;

[0105] S5.3, taking elevation, borehole number, any one or more of the categories or levels of attribute data of any attribute category as restriction conditions, select attribute data of any other attribute category, and construct a scatter plot of the multidimensional mapping relationship between elevation, borehole number and attribute data of each attribute category based on the established visual expression system, and conduct attribute data statistics and analysis under special restricted conditions.

[0106] Among them, other attribute categories refer to attribute categories other than those selected in the restriction conditions. The selection of elevation and borehole number in the restriction conditions is based on the needs of actual analysis and expression, and the borehole and elevation range that can reflect a specific project location are selected.

[0107] like Figure 4 As shown, the horizontal axis is the attribute category permeability, the vertical axis is the elevation, and the square blocks, triangle blocks, and circular blocks represent different borehole numbers; the permeability is divided into 4 levels according to the general rules in this field, namely 0.1Lu~1Lu, 1Lu~10Lu, 10Lu~100Lu, and above 100Lu; among them, 0.1Lu~1Lu is represented by green, 1Lu~10Lu is represented by blue, 10Lu~100Lu is represented by yellow, and above 100Lu is represented by red. According to the established visual expression system, a scatter plot of the multidimensional mapping relationship between elevation, borehole number and attribute data of each attribute category is constructed; from the figure, it can be clearly seen that the distribution characteristics of the permeability of each borehole at each elevation, or the elevation characteristics corresponding to a certain permeability level, or the distribution quantity of data belonging to a certain borehole number within any permeability level;

[0108] For example, the distribution characteristics of wave velocity are analyzed with elevation, borehole number and a certain level of RQD as restriction conditions; first, the attribute data of wave velocity are selected with elevation, borehole number and RQD (Chinese meaning is rock quality index. According to the general rules in this field, RQD is divided into 5 levels, namely, below 25% is extremely poor, 25%~50% is poor, 50%~70% is relatively poor, 70%~90% is good, and above 90% is good) level as restriction conditions; square blocks, triangle blocks, circular blocks, etc. are used to represent different borehole numbers; according to the general rules in this field, different colors are automatically set for different levels of wave velocity, so as to construct a multi-dimensional mapping relationship scatter plot of wave velocity when elevation, borehole number and RQD level are good; in this way, the distribution characteristics of wave velocity when the RQD level is good at each borehole and each elevation are displayed and analyzed.

[0109] S6, construct a binary element multidimensional mapping variable attribute pixel array pool, draw a panoramic map of the exploration borehole and a thematic map of the exploration borehole according to the reconstructed visualization expression system and the needs of actual analysis and expression, and display and analyze the spatial combination characteristics of the attribute data. Figure 5 As shown, the specific steps include:

[0110] S6.1, reconstruct the attribute data visualization expression system;

[0111] S6.2, construct a binary element multidimensional mapping variable attribute pixel array pool;

[0112] S6.3, draw a panoramic map of the exploration borehole;

[0113] S6.4, draw thematic maps of exploration boreholes;

[0114] S6.5, display and analyze the spatial structure characteristics of the atlas.

[0115] Among them, the attribute data visualization expression system reconstructed in S6.1 specifically includes the following contents:

[0116] S6.1.1, classify or grade the attribute data of the attribute category according to actual needs and general rules in the field of geological survey for water conservancy and hydropower engineering;

[0117] S6.1.2, setting a standard color that can distinguish each category and level from each other, and constructing the visual expression system for each category and level of attribute data.

[0118] S6.1.3, based on the standard colors of the categories and levels within the attribute categories, color scales are matched for different attribute values ​​within the same level or category, and the closer the attribute data of the same level or category is to the upper limit value of the level or category, the closer the color of the attribute data is to the standard color of the level.

[0119] Compared with the attribute data visualization expression system constructed in step S3, the visualization expression system in step S6.1 adds the following content:

[0120] Standard colors that can distinguish each other are set for the attribute data corresponding to the different categories and levels. Based on the standard colors of the categories and levels within the attribute category, color scales are matched for different attribute values ​​within the same level or category. The closer the attribute data of the same level or category is to the upper limit value of the level or category, the closer the color of the attribute data is to the standard color of the level.

[0121] That is to say, the attribute data visualization expression system constructed in step S3 only sets different colors for different levels and categories in each attribute category, and can only distinguish different categories and levels; for example, according to the general rules in this field, the permeability is divided into 4 levels, namely 0.1Lu~1Lu, 1Lu~10Lu, 10Lu~100Lu, and above 100Lu; among them, 0.1Lu~1Lu is represented by green, 1Lu~10Lu is represented by blue, 10Lu~100Lu is represented by yellow, and above 100Lu is represented by red, thus establishing a visualization expression system, that is, all data in the range of 0.1Lu~1Lu are represented by the same standard color green, and so on.

[0122] The attribute data visualization expression system used in step S6.1 sets different colors for different levels and categories in each attribute category, and sets color scales for attribute data in the same level or category. When drawing the panoramic map of exploration boreholes and thematic maps of exploration boreholes, the size and change characteristics of the attribute data can be more clearly seen. Similarly, according to the general rules in this field, the permeability is divided into 4 levels, namely 0.1Lu~1Lu, 1Lu~10Lu, 10Lu~100Lu, and above 100Lu; among them, 0.1Lu~1Lu is represented by green, 1Lu~10Lu is represented by blue, 10Lu~100Lu is represented by yellow, and above 100Lu is represented by red, and a visualization expression system is established. In step S6, the permeability attribute value within the range of 0.1Lu~1Lu is matched with different color scales based on the standard color green according to the size of the value. Different permeability attribute values ​​are matched with green representations of different color scales, and so on. Here, the values ​​in each level or category are usually divided according to the numerical units commonly used in this field. For example, for lithology, there is only one attribute data in each category of lithology, and the color of the category is the color of the attribute data in the category. For each level of permeability, there are multiple attribute data, between 0.1Lu~1Lu, divided according to the numerical unit 0.1Lu commonly used in this field, adjust the green color level, and assign different levels of green to each value.

[0123] S6.2, constructing a binary element multidimensional mapping variable attribute pixel array pool; comprising the following steps:

[0124] S6.2.1, adjusting the data arrangement structure of the binary element multidimensional mapping variable attribute data array pool described in step S2 according to a specific arrangement rule;

[0125] The arrangement rule refers to the arrangement order of the boreholes that can display the specific spatial structure of the engineering entity, which is selected according to the needs of displaying and expressing the survey results. The arrangement order of the borehole numbers is determined by the borehole arrangement order, and the elevations are arranged in descending order. The arrangement order of the attribute data is determined according to the needs of displaying and expressing the survey results. In this embodiment, according to needs, the order of lithology, weathering degree, permeability, RQD, wave velocity, apparent resistivity, and stratigraphic age is arranged.

[0126] Next, we will take the survey boreholes of a water conservancy and hydropower engineering survey project as an example to explain how to determine the arrangement order of the borehole numbers in the binary element multidimensional attribute data mapping matrix:

[0127] The drilling locations of this water conservancy and hydropower engineering survey project are divided into left bank holes, right bank holes and riverbed holes. The order of drilling holes follows the following rules:

[0128] (1) The overall drilling arrangement sequence follows the principle of arrangement from left bank to right bank and from upstream to downstream;

[0129] (2) Take the line perpendicular to the dam axis and intersecting the midpoint of the dam axis as the baseline, draw a perpendicular line from the borehole to the baseline, and measure the length of the perpendicular line of each borehole;

[0130] (3) The left bank boreholes are arranged in descending order according to the length of the vertical line, and the right bank boreholes are arranged in ascending order according to the length of the vertical line;

[0131] (4) When the lengths of perpendicular lines from some boreholes on the left bank or the right bank to the baseline are the same,

[0132] ① The boreholes located upstream of the dam axis are arranged in descending order according to the distance from the vertical point of the borehole to the baseline to the midpoint of the dam axis;

[0133] ② The boreholes located downstream of the dam axis shall be arranged in order of the distance from the vertical point of the borehole to the baseline to the midpoint of the dam axis from the smallest to the largest;

[0134] (5) The order of arrangement of riverbed drilling holes follows the following rules:

[0135] ① In a straight river, the arrangement order of the riverbed boreholes is based on the baseline described in step (2) above, and the riverbed holes are divided into left bank riverbed boreholes and right bank riverbed boreholes. Then the arrangement order of the riverbed boreholes is determined according to steps (2) to (4) above.

[0136] ② In a curved river, the arrangement order of the riverbed boreholes is based on the center line of the river. A perpendicular line is drawn from the riverbed borehole to the center line of the river. According to the distance from the perpendicular point of the riverbed borehole to the center line of the river to the midpoint of the dam axis (along the center line of the river), the riverbed boreholes upstream of the dam axis are arranged in order of distance from large to small, and the riverbed boreholes downstream of the dam axis are arranged in order of distance from small to large; when the distances from the perpendicular points of some riverbed boreholes to the center line of the river to the midpoint of the dam axis are equal, the riverbed holes are divided into left bank riverbed boreholes and right bank riverbed boreholes based on the center line of the river, and arranged in the order that the left bank riverbed boreholes take precedence over the right bank riverbed boreholes.

[0137] S6.2.2, according to the reconstructed visualization expression system, assigning a physical space cell to each of the attribute data in the adjusted binary element multidimensional mapping variable attribute data array pool, and constructing the binary element multidimensional mapping variable attribute pixel array pool;

[0138] S6.2.3, according to the reconstructed visualization expression system, different pixel values ​​are assigned to each entity space cell based on the attribute data value.

[0139] S6.3, draw a panoramic map of the exploration borehole;

[0140] The panoramic survey borehole map is constructed by a pixel array corresponding to any one or more attribute categories at all the elevations of all the boreholes within the survey range. According to the color change characteristics of the panoramic survey borehole map, key feature values ​​such as color mutations and color elevation boundaries are extracted to display and analyze the spatial combination characteristics of the attribute data.

[0141] Among them, other attribute categories refer to attribute categories other than those selected in the restriction conditions. The selection of elevation and borehole number in the restriction conditions is based on the needs of actual analysis and expression, and the borehole and elevation range that can reflect a specific project location are selected.

[0142] like Figure 6 As shown, due to the limitation of the map size, this map only shows the three exploration boreholes in the full elevation range. The display effect of the attribute data of all attribute categories according to the visual representation system fully demonstrates the spatial combination characteristics of each attribute data;

[0143] like Figure 7As shown in the figure, the display effect of the attribute data of water permeability of all the survey boreholes of a certain survey project in the whole elevation range according to the visual expression system is shown; the position of the water permeable structure with a water permeability greater than 100Lu in the water permeability chromatogram can be quickly identified, and then its distribution elevation, distribution position (left and right bank) and specific borehole number can be analyzed; and the distribution of the structure with a water permeability greater than 1Lu in the overall water permeable structure with a water permeability less than 1Lu;

[0144] like Figure 8 As shown, Figure 7 By analyzing the panoramic permeability map, we can clearly see the corresponding elevations and borehole numbers of different permeability characteristic segments.

[0145] like Fig. 9 As shown, the display effect of the lithology attribute data of the exploration borehole in the entire elevation range according to the visual representation system is demonstrated, which can quickly analyze and identify the corresponding lithology and its distribution elevation, such as the overall distribution elevation of sandstone and other information.

[0146] S6.4, Draw thematic maps of exploration boreholes

[0147] Drawing the exploration borehole thematic map includes any combination of the following steps, specifically:

[0148] S6.4.1, taking any engineering site as the screening condition, the pixel array corresponding to any one or more of the attribute categories of all the boreholes contained therein at all elevations and depths within the survey range is constructed to construct a thematic map of the survey boreholes, and to display and analyze the spatial combination characteristics of the attribute data under the limited conditions;

[0149] S6.4.2, with elevation, borehole number and any one or more levels or categories of attribute data of any one or more attribute categories as restriction conditions, select the pixel array corresponding to the attribute data of any one or more other attribute categories of the binary element multidimensional mapping variable attribute pixel array pool, and draw the exploration borehole thematic map; according to the color change characteristics of the exploration borehole thematic map, extract the key characteristic values ​​of color mutation and color elevation boundary, and display and analyze the spatial combination characteristics of the attribute data under the restricted conditions.

[0150] Among them, other attribute categories refer to attribute categories other than those selected in the restriction conditions. The selection of elevation and borehole number in the restriction conditions is based on the needs of actual analysis and expression, and the borehole and elevation range that can reflect a specific project location are selected.

[0151] like Fig.10 As shown in the figure, the display effect of the attribute data of lithology and permeability of the exploration borehole on the left bank of a certain exploration project in the whole elevation range according to the visual representation system is shown; the spatial combination characteristics of the attribute data on the left bank of a certain exploration project are fully demonstrated;

[0152] like Fig.11 As shown, the permeability attribute data of all the survey boreholes of a certain survey project within the entire elevation range is displayed according to the visual representation system, and the permeability characteristic section, distribution elevation, distribution position (left and right bank) and specific borehole number of the sandstone of the survey project are analyzed.

[0153] Similarly, using the survey drilling data analysis and visualization expression method described in the present invention, a panoramic map of the permeability of the survey boreholes in a certain survey project within the elevation range, where the lithology is sandstone and the degree of weathering is weakly weathered conditions can be constructed, and the permeability characteristic segments, distribution elevations, distribution locations (left and right banks) and specific borehole numbers of the sandstone and weakly weathered conditions of the survey project can be analyzed.

[0154] Furthermore, after the survey borehole panoramic map and the survey borehole thematic map are drawn, it is supported to autonomously adjust the pixel values ​​of the attribute data displayed in the survey borehole panoramic map and the survey borehole thematic map as needed.

[0155] It can be seen from the above-mentioned results diagram that the exploration drilling data analysis and visualization expression method described in the present invention makes full use of the geological professional principle of hierarchical classification of drilling attribute information to form a panoramic chromatogram display of the exploration drilling, and forms a systematic exploration drilling data expression and analysis method, which has a novel style, simple production, flexible expression form, and convenient data extraction and correlation analysis, which facilitates the statistical analysis of drilling data and improves work efficiency.

Claims

1. A method for analyzing and visualizing survey drilling data, characterized in that: The following steps are involved: S1, using the survey data information collection system, collect the basic data and attribute data of the borehole, and build a survey borehole basic attribute information database; The basic data refers to data that is not related to the stratum itself, including the borehole number, borehole location, borehole coordinates, borehole diameter information, borehole depth information, borehole type and start and completion dates; The attribute data refers to data directly related to the stratum, including multiple attribute data of multiple attribute categories; The attribute categories include lithology, weathering degree, stratigraphic age, permeability, RQD, wave velocity, and apparent resistivity; Each attribute data of each attribute category includes the corresponding elevation of the attribute data; S2, preprocessing the attribute data to construct a binary element multi-dimensional mapping variable attribute data array pool; The binary element multi-dimensional mapping variable attribute data array pool refers to the mapping between the elevation, the borehole number and the attribute data of multiple attribute categories, with the elevation and the borehole number as binary elements and the attribute data of multiple attribute categories as variable attribute data; Elevation is determined by rounding off the maximum and minimum values ​​of the corresponding elevation described in the attribute data and discretizing them into units of 1 meter; The preprocessing specifically includes the following contents: S2.1, generalizing the corresponding elevation of the attribute data by rounding off to an integer, so that the attribute data corresponds to the elevation; S2.2, when one attribute data corresponds to a plurality of said elevation units, assigning the attribute data to each elevation within the plurality of elevation units by discretization; S2.3, for multiple attribute data corresponding to one elevation unit, the arithmetic mean of all attribute data in the elevation unit is taken as the attribute data of the elevation at the end of the selected elevation unit; S3, constructing a visual expression system based on the basic data and attribute data; Specifically include the following: S3.1, setting a corresponding visual expression symbol for each of the borehole numbers to distinguish each borehole; matching the number of visual expression symbols of different shapes according to the number of borehole numbers, the visual expression symbols including squares, triangles, and circles; S3.2, classifying or grading the attribute data of the attribute category according to actual needs and general rules in the field of geological survey for water conservancy and hydropower engineering; S3.3, setting a standard color that can distinguish each category and level from each other, and constructing the visual expression system of each category and level of attribute data; S4, batch extract attribute data and conduct aggregation analysis of exploration borehole attribute data; S5, drawing a multi-dimensional mapping relationship scatter plot according to the visual expression system and the needs of actual analysis and expression, and performing attribute data statistics and analysis; S6, construct a binary element multidimensional mapping variable attribute pixel array pool, draw a panoramic map of the exploration borehole and a thematic map of the exploration borehole according to the reconstructed visualization expression system and the needs of actual analysis and expression, and display and analyze the spatial combination characteristics of the attribute data; The specific steps include: S6.1, reconstruct the attribute data visualization expression system; S6.2, construct a binary element multidimensional mapping variable attribute pixel array pool; S6.3, draw a panoramic map of the exploration borehole; S6.4, draw thematic maps of exploration boreholes; S6.5, display and analyze the spatial structure characteristics of the atlas.

2. The method for analyzing and visualizing survey drilling data according to claim 1, characterized in that: Step S4 specifically includes the following: S4.1, for any of the attribute categories of the water permeability, the RQD, the wave velocity, and the apparent resistivity, separately carry out the attribute data aggregation statistics and analysis; S4.2, make an autocorrelation curve based on the attribute data in the attribute category; S4.3, determine the number of attribute data in the attribute category on equally spaced data segments; S4.4, calculate the data density of equally spaced data segments based on the number of attribute data in the equally spaced data segments, and perform data aggregation analysis.

3. The method for analyzing and visualizing survey borehole data according to claim 1, characterized in that: Step S5 is any combination of the following steps, specifically: S5.1, taking the elevation and the borehole number as restriction conditions, selecting the attribute data of any attribute category, constructing a scatter plot of the multidimensional mapping relationship between the elevation, the borehole number and the attribute data of each attribute category according to the established visual expression system, and performing attribute data statistics and analysis; S5.2, taking elevation, borehole number, and any one or more attribute categories as restriction conditions, select the attribute data of any other attribute category, and construct a multi-dimensional mapping relationship scatter plot of elevation, borehole number and attribute data of each attribute category according to the established visual expression system, and conduct attribute data statistics and analysis under special restriction conditions; S5.3, taking elevation, borehole number, any one or more of the categories or levels of attribute data of any attribute category as restriction conditions, select attribute data of any other attribute category, and construct a scatter plot of the multidimensional mapping relationship between elevation, borehole number and attribute data of each attribute category based on the established visual expression system, and conduct attribute data statistics and analysis under special restricted conditions.

4. The method for analyzing and visualizing survey drilling data according to claim 1, characterized in that: Step S6.1 includes the following steps: S6.1.1, classify or grade the attribute data of the attribute category according to actual needs and general rules in the field of geological survey for water conservancy and hydropower engineering; S6.1.2, setting a standard color that can distinguish each category and level from each other, and constructing a visual expression system for each category and level of attribute data; S6.1.3, based on the standard colors of the categories and levels within the attribute categories, color scales are matched for different attribute data within the same level or category, and the closer the attribute data of the same level or category is to the upper limit value of the level or category, the closer the color of the attribute data is to the standard color of the level.

5. The method for analyzing and visualizing survey drilling data according to claim 1, characterized in that: Step S6.2 includes the following steps: S6.2.1, adjusting the data arrangement structure of the binary element multidimensional mapping variable attribute data array pool described in step S2 according to a specific arrangement rule; S6.2.2, according to the reconstructed visualization expression system, assigning a physical space cell to each attribute data in the adjusted binary element multidimensional mapping variable attribute data array pool, and constructing the binary element multidimensional mapping variable attribute pixel array pool; S6.2.3, according to the reconstructed visualization expression system, different pixel values ​​are assigned to each cell of the entity space based on the attribute data value.

6. The method for analyzing and visualizing survey borehole data according to claim 5, characterized in that: The arrangement rule described in step S6.2.1 refers to the arrangement order of the boreholes selected to display the specific spatial structure of the engineering entity based on the needs of displaying and expressing the survey results. The arrangement order of the borehole numbers is determined by the borehole arrangement order, the elevations are arranged in descending order, and the arrangement order of the attribute data is determined based on the needs of displaying and expressing the survey results.

7. The method for analyzing and visualizing survey drilling data according to claim 1, characterized in that: The panoramic map of the survey borehole described in step S6.3 is a panoramic map of the survey borehole constructed by a pixel array corresponding to any one or more attribute categories at all the elevations of all the boreholes within the survey range. According to the color change characteristics of the panoramic map of the survey borehole, key feature values ​​such as color mutations and color elevation boundaries are extracted to display and analyze the spatial combination characteristics of the attribute data.

8. The method for analyzing and visualizing survey drilling data according to claim 1, characterized in that: The exploration borehole thematic map described in step S6.4 includes any combination of the following steps, specifically: S6.4.1, using the pixel arrays corresponding to any one or more attribute categories of the borehole numbers of all the boreholes included in any engineering part at all the elevations within the survey range as screening conditions, construct a survey borehole thematic map, and display and analyze the spatial combination characteristics of the attribute data under limited conditions; S6.4.2, with elevation, borehole number and any one or more levels or categories of attribute data of any one or more attribute categories as restriction conditions, select the pixel array corresponding to the attribute data of any one or more other attribute categories of the binary element multidimensional mapping variable attribute pixel array pool, and draw the exploration borehole thematic map; according to the color change characteristics of the exploration borehole thematic map, extract the key characteristic values ​​of color mutation and color elevation boundary, and display and analyze the spatial combination characteristics of the attribute data under the restricted conditions.

9. The method for analyzing and visualizing survey drilling data according to claim 7 or 8, characterized in that: After the exploration borehole panoramic map and the exploration borehole thematic map are drawn, it is supported to autonomously adjust the pixel values ​​of the attribute data displayed in the exploration borehole panoramic map and the exploration borehole thematic map according to the needs of data expression and display.

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