CN116645484B

CN116645484B - Geological curved surface model construction method and device, electronic equipment and storage medium

Info

Publication number: CN116645484B
Application number: CN202310920175.3A
Authority: CN
Inventors: 王宇翔; 皇永波; 禄丰年; 马智刚; 徐明伟; 陈万仓; 蔡得水; 吕栋亮
Original assignee: Aerospace Hongtu Information Technology Co Ltd
Current assignee: Aerospace Hongtu Information Technology Co Ltd
Priority date: 2023-07-26
Filing date: 2023-07-26
Publication date: 2023-10-03
Anticipated expiration: 2043-07-26
Also published as: CN116645484A

Abstract

The invention provides a method and a device for constructing a geological curved surface model, electronic equipment and a storage medium, wherein the method comprises the following steps: acquiring a drilling point data set of a research area; constructing polygonal geological space corresponding to the research area according to the coordinate data and the depth data in the drilling point data set; according to the geological layer attribute in the drilling point data set, at least one-stage space segmentation is carried out on the polygonal geological space, and a multi-stage sub-geological space set corresponding to the research area is obtained; at least one level of reverse merging is carried out on the multi-level sub-geological space set to obtain at least one geological semantic space corresponding to each geological layer attribute; and constructing a geological curved surface model corresponding to the research area according to each geological semantic space. The invention can quickly construct the three-dimensional curved surface model of the complex geological structure, and reduces the input of manpower.

Description

Geological curved surface model construction method and device, electronic equipment and storage medium

Technical Field

The invention relates to the technical field of geological big data and geological data visualization, in particular to a method and a device for constructing a geological curved surface model, electronic equipment and a storage medium.

Background

With the vigorous development of geological big data in recent years, the expression form of geological investigation result data faces innovative changes, and particularly, two-dimensional point-line-plane vector data of geological investigation results are converted into three-dimensional entity data. However, the two-dimensional graphic data of geological survey are turned into three-dimensional structure data, the problems of data geometric shape, spatial position and disordered topological logic are faced, and especially in the area with complex geological structure, various geological layers are criss-cross, so that the construction of a geological three-dimensional model is greatly hindered.

At present, geological three-dimensional model data mainly depend on drilling data of geological exploration to fit curved surfaces of various geological layers, and then a three-dimensional geological model is constructed on the basis of the curved surface model. However, in a complex geological environment, the drilling points extracted by using drilling data are scattered, the points of various stratum attributes and the points of the stratum with the same attribute and not adjacent stratum are gathered together, and the fitted curved surface cannot be classified according to the attributes of the drilling points directly in the process of fitting the curved surface, so that the problems of logic confusion of the stratum curved surface, geometric shape and space position construction errors of a geological model and the like are easily caused.

Based on the current situation and the technical barriers of the geological three-dimensional visualization problem, the technical barrier for automatically constructing the three-dimensional model of the complex geological structure is not broken through in the geological exploration field. At present, the research on geological three-dimensional modeling is less, and part of scientific research teams use drilling point data and a conventional display interpolation algorithm to construct curved surfaces, so that the method can only be used for constructing simple geological layer structures, and the modeling technology of complex geological structures is still in a blank stage.

Disclosure of Invention

In view of the above, the present invention aims to provide a method, an apparatus, an electronic device and a storage medium for constructing a geological curved surface model, which can quickly construct a three-dimensional curved surface model of a complex geological structure, and reduce the input of manpower.

In a first aspect, an embodiment of the present invention provides a method for constructing a geological curved model, including:

acquiring a drilling point data set of a research area; the drilling point data set comprises coordinate data, depth data and geological layer attributes corresponding to each drilling point;

constructing polygonal geological space corresponding to the research area according to the coordinate data and the depth data in the drilling point data set; wherein said polygonal geological space contains each said borehole point within said borehole point dataset;

according to the geological layer attribute in the drilling point data set, at least one-stage space segmentation is carried out on the polygonal geological space, and a multi-stage sub-geological space set corresponding to the research area is obtained; wherein each level of the set of sub-geologic spaces comprises a plurality of sub-geologic spaces, each of the sub-geologic spaces comprising less than or equal to 1 in number of geologic layer attributes;

Performing at least one-stage reverse merging on the multi-stage sub-geological space set to obtain at least one geological semantic space corresponding to each geological layer attribute;

and constructing a geological curved surface model corresponding to the research area according to each geological semantic space.

In one embodiment, constructing a polygonal geological space corresponding to the investigation region according to the coordinate data and the depth data in the drilling point data set includes:

traversing coordinate data corresponding to each drilling point in the drilling point data set to determine an abscissa maximum value, an abscissa minimum value, an ordinate maximum value and an ordinate minimum value; traversing depth data corresponding to each drilling point in the drilling point data set to determine a vertical coordinate maximum value and a vertical coordinate minimum value;

determining a polygon range according to the abscissa maximum value, the abscissa minimum value, the ordinate maximum value, the ordinate minimum value, the ordinate maximum value and the ordinate minimum value;

and constructing a polygonal geological space corresponding to the research area based on the polygonal range.

In one embodiment, the polygonal geological space comprises a rectangular geological space; according to the geologic layer attribute in the drilling point data set, at least one-stage space segmentation is performed on the polygonal geologic space to obtain a multi-stage sub-geologic space set corresponding to the research area, which comprises the following steps:

For the rectangular geological space, if the number of geological layer attributes contained in the rectangular geological space is greater than 1, determining a root node center coordinate corresponding to the rectangular geological space, and dividing the rectangular geological space into a plurality of sub-geological spaces according to the root node center coordinate to obtain a first-stage sub-geological space set;

judging whether the number of the geologic layer attributes contained in each sub-geologic space in the current-stage sub-geologic space set is less than or equal to 1 or not;

if yes, stopping space division on the sub-geological space;

if not, continuing to determine the central coordinates of the sub-nodes corresponding to the sub-geological space, and dividing the sub-geological space into a plurality of sub-geological spaces according to the central coordinates of the sub-nodes to obtain a next-stage sub-geological space set until the number of geological layer attributes contained in each sub-geological space is less than or equal to 1, so as to obtain a multi-stage sub-geological space set corresponding to the research area.

In one embodiment, at least one level of reverse merging is performed on the multi-level sub-geological space set to obtain at least one geological semantic space corresponding to each geological layer attribute, including:

Merging the sub-geological spaces in the final-stage sub-geological space set according to a preset merging principle; the preset merging principle comprises a coplanarity principle and a property consistency principle, wherein the coplanarity principle comprises complete coplanarity or coplanarity;

and continuing to merge the sub-geological spaces in the upper-level sub-geological space set corresponding to the last-level sub-geological space set according to the preset merging principle until the sub-geological spaces in the first-level sub-geological space set are merged to obtain at least one geological semantic space corresponding to each geological layer attribute.

In one embodiment, merging the sub-geological space in the final sub-geological space set according to a preset merging principle includes:

judging whether the number of the geologic layer attributes contained in the sub-geologic space is 0 for each sub-geologic space in the final-stage sub-geologic space set;

if yes, merging the sub-geological space clockwise according to the plane;

if not, screening out a target sub-geological space which is coplanar with the sub-geological space and consistent with the geological layer attribute from the final-stage sub-geological space set, and merging the sub-geological space with the target sub-geological space.

In one embodiment, constructing a geological curved surface model corresponding to the research area according to each geological semantic space includes:

for each geological semantic space, determining a drilling point sub-data set corresponding to the geological semantic space from the drilling point data set, and fitting to generate a geological curved surface function model corresponding to the geological semantic space by using a radial basis function according to the drilling point sub-data set;

if a boundary exists between the geological curved surface function models, determining a boundary line between the geological curved surface function models, and converging the geological curved surface function models to the boundary line;

and constructing a geological curved surface model corresponding to the research area according to each geological curved surface function model.

In one embodiment, constructing a geological curved surface model corresponding to the investigation region according to each geological curved surface function model includes:

determining an equipotential surface sampling size according to the coordinate data and the depth data in the drilling point data set;

sampling each geological curved surface function model according to the equipotential surface acquisition size to obtain equipotential patches corresponding to the geological semantic space;

And connecting the equipotential surface patches corresponding to each geological semantic space to obtain a geological curved surface model corresponding to the research area.

In one embodiment, determining an equipotential surface sampling size from the coordinate data and the depth data in the borehole point data set includes:

for each drilling point in the drilling point data set, determining a plurality of nearest neighbor points corresponding to the drilling point from the drilling point data set according to the coordinate data and the depth data, determining the nearest neighbor distance between the drilling point and each nearest neighbor point, and taking the average value of each nearest neighbor distance as an initial average distance;

and determining an equipotential surface sampling size based on an average value of the initial average distance corresponding to each drilling point.

In a second aspect, an embodiment of the present invention further provides a device for constructing a geological curved surface model, including:

the data acquisition module is used for acquiring a drilling point data set of the research area; the drilling point data set comprises coordinate data, depth data and geological layer attributes corresponding to each drilling point;

the space construction module is used for constructing polygonal geological space corresponding to the research area according to the coordinate data and the depth data in the drilling point data set; wherein said polygonal geological space contains each said borehole point within said borehole point dataset;

The space segmentation module is used for carrying out at least one-stage space segmentation on the polygonal geological space according to the geological layer attribute in the drilling point data set to obtain a multi-stage sub-geological space set corresponding to the research area; wherein each level of the set of sub-geologic spaces comprises a plurality of sub-geologic spaces, each of the sub-geologic spaces comprising less than or equal to 1 in number of geologic layer attributes;

the space merging module is used for carrying out at least one-stage reverse merging on the multi-stage sub-geological space sets to obtain at least one geological semantic space corresponding to each geological layer attribute;

and the model construction module is used for constructing a geological curved surface model corresponding to the research area according to each geological semantic space.

In a third aspect, an embodiment of the present invention further provides an electronic device comprising a processor and a memory storing computer-executable instructions executable by the processor to implement the method of any one of the first aspects.

In a fourth aspect, embodiments of the present invention also provide a computer-readable storage medium storing computer-executable instructions which, when invoked and executed by a processor, cause the processor to implement the method of any one of the first aspects.

According to the method, the device, the electronic equipment and the storage medium for constructing the geological curved surface model, coordinate data, depth data, geological layer attributes and other drilling point data sets corresponding to each drilling point in a research area are firstly obtained, polygonal geological space corresponding to the research area is constructed according to the coordinate data and the depth data, so that each drilling point in the drilling point data set is located in the polygonal geological space, at least one-stage space segmentation is carried out on the polygonal geological space according to geological layer attributes in the drilling point data set to obtain a multi-stage sub-geological space set corresponding to the research area, the number of geological layer attributes contained in each sub-geological space in the sub-geological space set is smaller than or equal to 1, at least one-stage reverse merging is further carried out on the multi-stage sub-geological space set to obtain at least one geological semantic space corresponding to each geological layer attribute, and finally the geological curved surface model corresponding to the research area can be constructed according to each geological semantic space. The method carries out space division on the polygonal geological space where the drilling points are located, then reversely merges the sub-geological spaces with the same geological layer attribute to form a final geological semantic space, and defines the position relation and the spatial logic among the geological layer drilling points with the attributes, and finally generates a geological curved surface model corresponding to the research area according to each geological semantic space.

Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.

In order to make the above objects, features and advantages of the present invention more comprehensible, preferred embodiments accompanied with figures are described in detail below.

Drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are needed in the description of the embodiments or the prior art will be briefly described, and it is obvious that the drawings in the description below are some embodiments of the present invention, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.

FIG. 1 is a schematic flow chart of a method for constructing a geologic curved model according to an embodiment of the present invention;

fig. 2 is a schematic diagram of extracting drilling point information of a drilled pile according to an embodiment of the present invention;

FIG. 3 is a schematic diagram of a root node space divided into first level child node spaces according to an embodiment of the present invention;

FIG. 4 is a schematic diagram of indexing of a space node at a later stage after space division of a root node according to an embodiment of the present invention;

FIG. 5 is a schematic diagram of a complete co-planar merge provided by an embodiment of the present invention;

FIG. 6 is a schematic diagram of a co-planar merge comprising an embodiment of the present invention;

FIG. 7 is a diagram of a geological curved model achievement provided by an embodiment of the invention;

FIG. 8 is a schematic flow chart of another method for constructing a geologic curved model according to an embodiment of the present invention;

FIG. 9 is a schematic structural diagram of a device for constructing a geological curved model according to an embodiment of the present invention;

fig. 10 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.

Detailed Description

For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the present invention will be clearly and completely described in conjunction with the embodiments, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.

At present, when the prior art aims at a complex geological structure to perform three-dimensional modeling, the problems of topology logic errors, model geometry, space position errors and the like exist, and based on the problems, the implementation of the invention provides a method, a device, electronic equipment and a storage medium for constructing a geological curved surface model, which can quickly construct the three-dimensional curved surface model of the complex geological structure and reduce the input of manpower.

For the convenience of understanding the present embodiment, first, a method for constructing a geological curved surface model disclosed in the present embodiment of the present invention is described in detail, and the method may be well applied to the fields of geological exploration, mining and geographic information, and refer to a flow chart of a method for constructing a geological curved surface model shown in fig. 1, and the method mainly includes the following steps S102 to S110:

step S102, acquiring a drilling point data set of a research area. The drilling point data set includes coordinate data, depth data and geological layer attributes corresponding to each drilling point, and may further include information such as a drilling number (such as a drilling ID).

In one embodiment, drill points may be extracted according to the upper and lower geologic formation properties using drill pile data, which includes information such as coordinate data (x, y), depth data h, geologic formation properties, drill hole numbers, and the like.

And step S104, constructing polygonal geological space corresponding to the research area according to the coordinate data and the depth data in the drilling point data set. Wherein the polygonal geological space comprises each of the borehole points within the borehole point dataset, the polygonal geological space may be a rectangular geological space.

In one embodiment, the vertical coordinate (i.e., z-coordinate) of each drilling point may be determined according to the depth data, and then each drilling point is traversed to obtain the respective maximum values of the horizontal coordinate (i.e., x-coordinate), the vertical coordinate (i.e., y-coordinate), and the vertical coordinate, so as to construct the polygonal geological space corresponding to the research area according to the maximum values, so that each drilling point in the drilling point data set is located in the polygonal geological space.

And S106, performing at least one-stage space segmentation on the polygonal geological space according to the geological layer attribute in the drilling point data set to obtain a multi-stage sub-geological space set corresponding to the research area. Each level of the sub-geological space set comprises a plurality of sub-geological spaces, and the number of geological layer attributes contained in each sub-geological space is smaller than or equal to 1.

In one embodiment, the polygonal geological space may be spatially segmented to obtain a plurality of sub-geological spaces, and the sub-geological space obtained by the spatial segmentation is used as a first-stage sub-geological space set; continuously performing space division on the first-stage sub-geological space in which the number of geological layer attributes is more than 1 in a concentrated manner to obtain a plurality of sub-geological spaces, and taking the sub-geological space obtained by the space division as a second-stage sub-geological space; and repeating the process until the number of geologic layer attributes contained in each sub-geologic space obtained by space segmentation is less than or equal to 1, and stopping space segmentation.

And S108, performing at least one-stage reverse merging on the multi-stage sub-geological space set to obtain at least one geological semantic space corresponding to each geological layer attribute. One geological layer attribute can correspond to one or more geological semantic spaces, and the number of geological layer attributes contained in one geological semantic space is 1.

In one embodiment, sub-geologic spaces of the same geologic layer properties may be reverse-merged to form a final geologic-semantic space. Specifically, firstly merging sub-geological spaces with the same and coplanar attribute of geological layers in the final-stage sub-geological space set; merging the sub-geological spaces with the same attribute and the same plane of the geological layers in the last level of sub-geological space set of the last level; and repeating the process until the sub-geological spaces with the same and coplanar geological layer attributes in the first-stage sub-geological space set are merged, so that at least one geological semantic space corresponding to each geological layer attribute can be obtained.

And step S110, constructing a geological curved surface model corresponding to the research area according to each geological semantic space. In one embodiment, a corresponding geological curved surface function model can be generated by using radial basis function fitting according to the data of the drilling points in each geological semantic space; then using a Boolean operation intersection method to judge whether each geological curved surface function model has an intersection, and converging the geological curved surface function model at an intersection line if the geological curved surface function model has the intersection; and finally, collecting equipotential patches of the geological curved surface function model in each geological semantic space, and generating a final geological curved surface model.

According to the method for constructing the geological curved surface model, provided by the embodiment of the invention, the polygonal geological space in which the drilling points are positioned is spatially segmented, then the sub-geological spaces with the same geological layer attribute are reversely merged to form the final geological semantic space, the position relation and spatial logic among the geological layer drilling points with the same attribute are clear, and finally the geological curved surface model corresponding to the research area is generated according to each geological semantic space.

In order to facilitate understanding of the above embodiments, the embodiment of the present invention provides a specific implementation manner of a method for constructing a geological curved surface model.

For the followingIn the step S102, when the step of acquiring the drilling point data set of the research area is performed, the coordinates of the center points of the upper and lower surfaces of each section of core can be extracted as the coordinates of the drilling points according to the core attribute (i.e., the geologic layer attribute) of the same-number drilling pile, wherein the vertex record of the first section of core is recorded [ ]) Coordinates, remaining drilling points recorded (>) And a depth h. The drill point data are organized into a table file or text file, in which the (/ -for each point must be contained >) And the coordinates are recorded, the vertex z coordinates are recorded, the depth h of the rest drilling points are recorded, and the corresponding drilling numbers and geological properties are recorded.

Taking the western region of certain city of Henan province as an example, the drilling points of the western region of certain city of Henan province can be extracted, and the drilling points of the drilling piles on the ground surface can be extracted) Extracting coordinates and depth (++) according to core attribute>) Where i denotes the borehole number and j denotes the point from which the borehole is extracted down from the vertex. Extracting geological layer attribute while extracting point coordinates>The drilling ID and the coordinates are combined into a piece of data to record the information of a drilling point) A bored pile such as that shown in fig. 2 extracts a schematic diagram of the boring point information.

For the foregoing step S104, when performing the step of constructing the polygonal geological space corresponding to the investigation region from the coordinate data and the depth data in the drill point data set, the following steps a1 to a3 may be referred to:

step a1, traversing coordinate data corresponding to each drilling point in the drilling point data set to determine an abscissa maximum value, an abscissa minimum value, an ordinate maximum value and an ordinate minimum value; and traversing the depth data corresponding to each drilling point in the drilling point data set to determine a vertical coordinate maximum value and a vertical coordinate minimum value.

In one embodiment, the drilling points are extracted from the drilling point set) Is to extract +.>Maximum and minimum of (2); extracting->Maximum and minimum of (2); extracting->Maximum and minimum of (a), i.e. acquiring the abscissa maximum of the entire borehole point data set +.>Minimum value of abscissa->Maximum value of ordinateMinimum value of ordinate->Vertical maximum>Minimum value of vertical coordinates->. Wherein in addition to the drilling point at the surface,the z value of each point is calculated by subtracting the depth h from the z value of the vertex of the borehole where the point is located.

And a2, determining the polygon range according to the abscissa maximum value, the abscissa minimum value, the ordinate maximum value, the ordinate minimum value, the ordinate maximum value and the ordinate minimum value. The polygonal body range may be a rectangular body range. In one embodiment, traversing the drilling point data set, determining a plurality of nearest neighbors corresponding to each drilling point, determining nearest distances between the drilling point and each nearest neighbor, taking an average value of each nearest distance as an initial average distance corresponding to the drilling point, and finally determining the polygon range based on the average value, the abscissa maximum value, the abscissa minimum value, the ordinate maximum value, the ordinate minimum value, the ordinate maximum value and the ordinate minimum value of the initial average distance corresponding to each drilling point.

For each drilling point, searching 5 nearest neighbor points corresponding to the drilling point by using KD tree algorithm, and solving the nearest neighbor distance between the drilling point and the 5 nearest neighbor points point by point for the extracted drilling vertex data，/>，/>，/>，/>Calculating the average value of 5 nearest neighbor distances to obtain the initial average distance +.>Then calculate the initial average distance +.for each drilling point>To obtain the final average distance S.

Further, according to the drilling points) At the maximum, calculate the cuboid scope: (/>,），（/>），（/>,/>）。

And a3, constructing a polygonal geological space corresponding to the research area based on the polygonal range. In one embodiment, a cuboid geological space is constructed according to the cuboid scope, such that the closed cuboid geological space contains all drilling points. And finally, recording the constructed cuboid geological space as O and storing the O as a root node.

For the foregoing step S106, when performing the step of performing at least one level of spatial segmentation on the polygonal geological space according to the geological layer attribute in the drilling point data set to obtain the multi-level sub-geological space set corresponding to the investigation region, the following steps b1 to b4 may be referred to:

And b1, for the rectangular geological space, if the number of geological layer attributes contained in the rectangular geological space is greater than 1, determining the central coordinates of the root nodes corresponding to the rectangular geological space, and dividing the rectangular geological space into a plurality of sub-geological spaces (also called as sub-node spaces) according to the central coordinates of the root nodes so as to obtain a first-stage sub-geological space set.

In one embodiment, according to @,/>），（/>），（,/>) Calculating the center point coordinates of the spatial root nodes (the)> )。

Further, the number of geologic layer attributes in the root node space is obtained, if the number is greater than 1, three mutually perpendicular planes are constructed according to the central coordinates, the root node space is equally divided into eight parts, such as a schematic diagram of the root node space divided into one-level sub-node spaces shown in fig. 3, and the one-level sub-node spaces are the sub-geologic spaces in the first-level sub-geologic space set, and the space distribution of eight sub-nodes a, b, c, d, e, f, g, h.

And b2, judging whether the number of geologic layer attributes contained in each sub-geologic space in the current-stage sub-geologic space set is less than or equal to 1.

In one embodiment, the side length of each sub-geological space is half the corresponding side length of the root node space, and the center coordinates of each sub-geological space are calculated to determine the range of the sub-geological space. Traversing all the drilling point data, comparing the drilling point data with the space range of the subspace one by one, and storing the drilling points into corresponding subspace nodes.

Specifically, the center coordinates of each sub-geological space are as follows:

center coordinates of the sub-geological space a: ()；

Center coordinates of the sub-geological space b: ( )；

Center coordinates of the sub-geological space c: ( )；

Center coordinates of the sub-geological space d: ( )；

Center coordinates of the sub-geological space e: ()；

Center coordinates of the sub-geological space f: ( )；

Center coordinates of the sub-geological space g: ( )；

Center coordinates of the sub-geological space h: ( )。

And b3, if so, stopping space division of the sub-geological space.

In one embodiment, the borehole points in each sub-geologic space are traversed to obtain geologic formation properties, and if the number of geologic formation properties for borehole points within a sub-geologic space is 0 or 1, the segmentation of the sub-geologic space is stopped.

And b4, if not, continuing to determine the central coordinates of the sub-nodes corresponding to the sub-geological space, dividing the sub-geological space into a plurality of sub-geological spaces according to the central coordinates of the sub-nodes to obtain a next-stage sub-geological space set until the number of geological layer attributes contained in each sub-geological space is less than or equal to 1, so as to obtain a multi-stage sub-geological space set corresponding to the research area.

In one embodiment, if the number of geologic layer attributes in the sub-geologic space is greater than 1, taking the sub-geologic space as a father node, continuously subdividing the father node into 8 sub-geologic spaces, storing the corresponding drilling points into the subdivided sub-geologic spaces, judging the number of geologic layer attributes in the sub-geologic spaces until the number of geologic layer attributes in all the sub-geologic spaces is 1 or 0, and stopping the subdivision.

Furthermore, in the process of executing the above space division, a space index is built for each divided sub-geological space to be synchronized,/>) Wherein->Is a division level->Is an index number. The partition level refers to the first level node calculated from the sub-nodes generated from the root node partition, and the sub-nodes generated by the first level node partitionMaking a second-stage node, and gradually analogizing to a level for stopping segmentation; the index number refers to a spatial node number generated by starting division from a root node, and the index number records the numbers of a parent node and a child node. And (3) completing the construction of all the sub-geological space indexes according to an index construction method, and finally taking the attribute category of the drilling points in the sub-geological space as the semantic attribute of the geological space.

By way of example, the embodiment of the present invention provides an application example of step S106, taking the maximum division number of 3 as an example:

referring to fig. 4, an index diagram of a post-stage spatial node of a root node spatial division is shown, where the first time the root node spatial index is divided, the generated subspace node index is: (1, a), (1, b), (1, c), (1, d), (1, e), (1, f), (1, g), (1, h). Traversing the drilling points, comparing the ranges of the sub-geological space one by one, and storing the drilling points into the sub-geological space.

Inquiring the geological attribute quantity in the sub-nodes after the root node segmentation, and acquiring geological layer attribute quantity of 8 sub-nodes which are all larger than 1, so that the second segmentation is carried out on all the sub-nodes, wherein the method comprises the following steps of (1) to (8):

(1) The space index (1, a) node is split for the second time, and the sub-node index after splitting is: (2, aa), (2, ab), (2, ac), (2, ad), (2, ae), (2, af), (2, ag), (2, ah);

(2) The space index (1, b) node is split for the second time, and the sub-node index after splitting is: (2, ba), (2, bb), (2, bc), (2, bd), (2, be), (2, bf), (2, bg), (2, bh);

(3) The space index (1, c) node is split for the second time, and the sub-node index after splitting is: (2, ca), (2, cb), (2, cc), (2, cd), (2, ce), (2, cf), (2, cg), (2, ch);

(4) The space index (1, d) node is split for the second time, and the sub-node index after splitting is: (2, da), (2, db), (2, dc), (2, dd), (2, de), (2, df), (2, dg), (2, dh);

(5) The space index (1, e) node is split for the second time, and the sub-node index after splitting is: (2, ea), (2, eb), (2, ec), (2, ed), (2, ee), (2, ef), (2, eg), (2, eh);

(6) The space index (1, f) node is split for the second time, and the sub-node index after splitting is: (2, fa), (2, fb), (2, fc), (2, fd), (2, fe), (2, ff), (2, fg), (2, fh);

(7) The space index (1, g) node is split for the second time, and the sub-node index after splitting is: (2, ga), (2, gb), (2, gc), (2, gd), (2, ge), (2, gf), (2, gg), (2, gh);

(8) The space index (1, h) node is split for the second time, and the sub-node index after splitting is: (2, ha), (2, hb), (2, hc), (2, hd), (2, he), (2, hf), (2, hg), (2, hh).

Further, after the second segmentation is completed, only the number of geological layer attributes of drilling points in the sub-nodes of the indexes (2, bc), (2, ec), (2, gf) is greater than 1, and the three sub-nodes are segmented for the third time, including the following steps:

(a) The third time the spatial index (2, bc) node is partitioned, the partitioned child node index is: (3, bca), (3, bcb), (3, bcc), (3, bcd), (3, bce), (3, bcf), (3, bcg), (3, bch);

(b) The third time the spatial index (2, ec) node is split, the sub-node index after splitting is: (3, eca), (3, ecad), (3, eca), (3, ecag), (3, ech);

(c) The third time the spatial index (2, gf) node is partitioned, the partitioned child node index is: (3, gfa), (3, gfb), (3, gfc), (3, gfd), (3, gfe), (3, gff), (3, gfg), (3, gfh).

And after the third segmentation is finished, the attribute number of the drilling points in all the sub-nodes is 1, the segmentation is stopped, and the attribute is assigned to the sub-geological space.

For the foregoing step S108, when performing the step of performing at least one stage of reverse merging on the multi-stage sub-geological space set to obtain at least one geological semantic space corresponding to each geological layer attribute, the following steps c1 to c2 may be referred to:

and c1, merging the sub-geological spaces in the final-stage sub-geological space set according to a preset merging principle. The preset merging principle comprises a coplanarity principle and a property consistency principle, wherein the coplanarity principle comprises complete coplanarity or coplanarity.

In one embodiment, for each sub-geologic space in the final set of sub-geologic spaces, determining whether the number of geologic layer properties contained in that sub-geologic space is 0; if yes, merging the sub-geological space clockwise according to the plane; if not, screening out a target sub-geological space which is coplanar with the sub-geological space and has consistent geological layer properties from the final-stage sub-geological space set, and merging the sub-geological space with the target sub-geological space.

And c2, continuing to merge the sub-geological spaces in the upper-level sub-geological space set corresponding to the last-level sub-geological space set according to a preset merging principle until merging the sub-geological spaces in the first-level sub-geological space set to obtain at least one geological semantic space corresponding to each geological layer attribute. In an embodiment, the merging process of each level of the sub-geological space set may refer to the step c1, which is not described in detail in the embodiment of the present invention.

For easy understanding, the embodiment of the invention provides a specific implementation manner of reverse merging. If the maximum number of divisions of the geological space is n, then the n-level nodes are recorded as the lowest level nodes (i.e., the last level set of sub-geological space). According to the space index traversing semantic space nodes, firstly screening the sub-geological space of the nth layer and the sub-geological space of the (n-1) layer, establishing a corresponding relation between the father node of the (n-1) layer and the child node of the n layer according to the index, firstly searching the neighborhood sub-geological space in the father node by taking one child node as the center, and if the same semantic attribute (namely, geological layer attribute) exists and the two are coplanar, carrying out node space merging.

Further, two coplanar logic relations exist in the adjacent node coplanarity, and if two sub-geological spaces completely share one surface, the two sub-geological spaces are completely empty surface relations, such as a completely coplanar merging schematic diagram shown in fig. 5; if one face contains a region of the other face then a co-planar relationship is involved, such as the one shown in fig. 6 which contains a co-planar merge schematic. Wherein, the complete coplanarity is that the vertex coordinates of two faces are identical, and if the coplanarity is contained, the vertex coordinates of one face contained are identical to at least two points of the other face, and the rest vertexes are all on the contained face.

Further, if the neighborhood of a sub-geological space does not have the same semantic attributes as it, then no merging is required; if the number of drilling points in one sub-geological space is 0, the empty nodes are merged clockwise according to the plane.

Further, after the n-th layer of the sub-geological space completes the merging of the semantic space in the whole father node, the drilling points in the corresponding sub-geological space are stored in the merged semantic space (i.e. the merged sub-geological space).

Further, the above-mentioned merging operation is executed for each n-layer spatial node, and after the n-layer nodes are merged, the merging of the above-mentioned steps is executed by using the (n-1) layer node as a child node and the (n-2) layer node as a parent node. And according to the rule, iterative merging is circulated, and finally, a geological semantic space with geometric topological logic and strong geological structure is generated inside the root node.

By way of example, the embodiment of the present invention continues to take the maximum division number of 3 as an example, and provides an application example of step S108: the space nodes of the secondary indexes (2, bc), (2, ec), (2, gf) are taken as father nodes, the third-level child nodes are combined, and the combination is carried out according to the principle that the coplanarity, the complete coplanarity and the semanteme are the same. After the three-level node merging is completed, merging semantic space structures in the two-level child nodes by taking the first-level node as a father node. And after the second-level node merging is completed, merging the semantic space structure in the first-level node by taking the root node as a father node. And generating a final semantic space structure after the merging is completed.

For the foregoing step S108, in performing the step of constructing the geologic curved model corresponding to the investigation region from each geologic-semantic space, the following steps d1 to d3 can be referred to:

and d1, for each geological semantic space, determining a drilling point sub-data set corresponding to the geological semantic space from a drilling point data set, and fitting to generate a geological curved surface function model corresponding to the geological semantic space by using a radial basis function according to the drilling point sub-data set.

In one embodiment, surfaces within a geostatistical spaceCan be made of a position-dependent radial basis function +.>Definition, drilling points in space->Ternary hidden function scalar value +.>Indicating the point +.>And curved surfaceSince the drilling points are all in the geological surface, i.e. the drilling points in the semantic space +.>Are all located above the curved surface, so that there is a mathematical logic point +.>Further use->And solving various parameters of the radial basis function model as a mathematical logic relation.

Specifically, the radial basis function formula is as follows:

；

in the formula, n is the total number of interpolation points of the drilling, i is the interpolation point, namely the index number of the interpolation point.

In the radial basis function formulaThe Euclidean distance is expressed as follows:

；

In the radial basis function formulaAnd->Representing a hidden function coefficient matrix determined by known conditions; euclidean distance formula +.>For radial basis interpolation center point->Is defined by the coordinates of (a).

Based on the characteristics of the geological three-dimensional curved surface and the geological semantic space in the implementation case, a cube curved surface function is adopted as a global support radial basis function for modeling, namely). For a continuously differentiable implicit surface function in semantic space, any drilling interpolation point is +.>Normal vector of->Equal to the gradient of the function, as shown below>

；

According to the drilling point positionIs positioned at the hidden curved surface +.>The characteristic of the above, and the gradient of the drilling point on the curved surface is equal to the normal vector +.>To construct a system of linear equations (+.>And->Also respectively called constraint point coordinates and normal vector), the normal vector of the points in the implementation case is (0, -1), and the linear equation set can be solved into a matrix form as follows:

；

and solving parameters of the linear equation set to finally obtain a radial basis function expression (namely, a geological curved surface function model) of the curved surface model in the geological semantic space.

Step d2, if there is a boundary between the geologic curved surface function models, determining an intersection line between the geologic curved surface function models, and converging the geologic curved surface function models to the intersection line (also referred to as an intersection line).

In one embodiment, after the geologic curved surface function models of all semantic spaces of the root node are solved, a Boolean intersection operation method is adopted to calculate whether an intersection exists between each geologic curved surface function model, and if the intersection exists, the intersecting geologic curved surface function models are converged on the boundary line.

By way of example, the embodiment of the invention obtains 7 radial basis function hidden functions in total, which means that 7 geological curved surface function models are obtained. And then respectively calculating whether an intersection exists between the 7 geological curved surface function models, assuming that the intersection exists between the second geological curved surface function model and the third geological curved surface function model, solving an intersection line between the second geological curved surface function model and the third geological curved surface function model, and converging the second geological curved surface function model and the third geological curved surface function model on the intersection line.

And d3, constructing a geological curved surface model corresponding to the research area according to each geological curved surface function model. In one embodiment, reference may be made to the following steps d3-1 to d3-3:

and d3-1, determining the equipotential surface sampling size according to the coordinate data and the depth data in the drilling point data set.

In one embodiment, for each drilling point in the drilling point data set, a plurality of nearest neighbors corresponding to the drilling point may be determined from the drilling point data set according to the coordinate data and the depth data, a nearest neighbor distance between the drilling point and each nearest neighbor is determined, an average value of each nearest neighbor distance is taken as an initial average distance, and finally an equipotential surface sampling size is determined based on the average value of the initial average distance corresponding to each drilling point. The specific process of the average distance S can refer to the step a2, and the embodiment of the present invention will not be described herein again.

Further, the equipotential surface sampling size is determined according to the average distance S. Alternatively, the average distance S may be directly determined as the equipotential surface sampling size; that is, the average distance S is rounded, and the value obtained by rounding is determined as the equipotential surface sampling size.

And d3-2, sampling each geological curved surface function model according to the equipotential surface acquisition size to obtain equipotential patches corresponding to geological semantic space.

And d3-3, connecting equipotential surface patches corresponding to each geological semantic space to obtain a geological curved surface model corresponding to the research area.

In one embodiment, the equipotential surfaces are sampled for each geological curved surface function model by using a cube grid method, the side length of the cube grid is set, and the sampled triangular equipotential surfaces are connected together to generate a geological curved surface model. Illustratively, assuming that the mesh size of the equipotential surface acquisition is set to 100m, the acquired equipotential surface patches are connected together one by one to generate a geological curved surface model, so as to obtain a geological curved surface model result diagram such as that shown in fig. 7.

In summary, the method for constructing the geological curved surface model provided by the embodiment of the invention uses the bored pile data capable of objectively describing the geological layer structure and the topological logic, extracts the bored points and generates the geological space root node. The method of firstly dividing and reversely combining the geological semantic space is adopted to divide the complex geological structure block by block according to the topological logic of the geological structure, so that the spatial position and the topological logic structure of the complex geological structure are clear. And acquiring a curved surface fitting the interpolation semantic space by using the hidden function and the equipotential surface, and generating a geological three-dimensional curved surface model of the whole geological space. The invention effectively solves the problems of logic confusion, geometric body topology error and geological curved surface layer confusion of the complex geological curved surface model; the hidden function method can quickly construct the curved surface model without personnel participation in the construction process, greatly improves the efficiency of geological workers, can effectively promote the process of converting geological data from a two-dimensional graph to a three-dimensional model, promotes the development of geological big data, realizes the integrated modeling of the whole ground and underground space, and provides help for the construction of digital China.

The embodiment of the invention provides a method for constructing a geological curved surface model, which aims to solve the problems of geometric topology errors and geometric figure errors of a curved surface of a complex geological layer fitted by drilling points. For easy understanding, another method for constructing a geological curved model is provided in the embodiment of the present invention, referring to a flowchart of another method for constructing a geological curved model shown in fig. 8, the method mainly includes the following steps S802 to S814:

step S802, extracting a drilling point data set: and extracting drilling points according to the upper and lower geological layer attributes by using drilling pile data, wherein the drilling point data must contain information such as x coordinates, y coordinates, depth h, geological layer attributes, drilling numbers and the like.

Step S804, constructing a rectangular geological space root node: an integral cuboid geological space is constructed according to the drilling point data set and serves as a root node.

Step S806, performing spatial segmentation on the rectangular geological space: three planes orthogonal to the rectangular body geological space are drawn by taking the central point of the rectangular body geological space as an intersection point, and the rectangular body geological space is divided into 8 equal sub-nodes.

Step S808, judging whether the geological attribute number of the drilling point sets in the eight sub-nodes is less than or equal to 1. If yes, go to step S810; if not, step S806 is performed. And (3) carrying out loop iteration until the geological attribute number of the drilling point set in all the segmented sub-nodes is less than or equal to 1. Meanwhile, in the geological space segmentation process, the index of each child node is generated step by step according to the segmentation level.

Step S810, reverse merging subnode: traversing the neighborhood subspace, merging the coplanar neighborhood child nodes with the same semantic attribute, wherein the merging rule is that the child nodes under the same-level father node are merged preferentially, merging is carried out on the upper-level father node after the peer merging is finished, and the merging is carried out in a loop iteration mode until the root node finishes the final merging operation, so that a new geological semantic space index is generated, and a final geological semantic space is formed.

Step S812, a geological curved surface function model is generated by using radial basis hidden function fitting according to geological drilling point sets in each geological semantic space, then a Boolean operation intersection method is used for judging whether the geological curved surface function models have intersections, and if the curved surface function models have the intersections, the geological curved surface function models are converged at the boundary line.

Step S814, collecting equipotential surfaces of the geological curved surface function models in each geological semantic space, and generating a final geological curved surface model.

According to the embodiment of the invention, geological drilling data are used as data sources, and drilling points of each geological layer are extracted; dividing the drilling points according to the geological attribute characteristics by using a spatial semantic dividing algorithm, so that each divided node only contains one geological attribute characteristic, and simultaneously constructing a node spatial index for each semantic spatial node according to the attribute and the dividing times; then merging the index space reverse adjacent neighborhood space of the lowest node and the upper parent index space to enable the adjacent space nodes and drilling points with the same attribute to be in the same semantic space; and finally, fitting a curved surface to the drilling points in the semantic space by using a hidden function and an equipotential surface extraction algorithm, and constructing a multi-layer geological curved surface model.

The method can enable the topological structure to be complex in geologic layers, generate a geologic semantic space with clear and reasonable logic structures according to the geologic attribute category of the drilling point set, and combine with a Boolean operation method of a curved surface hidden function model, and the generated geologic curved surface data set can meet the space geometric expression of complex geologic structures such as turning fold, inverted fold, lying fold and the like.

For the method for constructing a geological curved surface model provided in the foregoing embodiment, the embodiment of the present invention provides a device for constructing a geological curved surface model, referring to a schematic structural diagram of a device for constructing a geological curved surface model shown in fig. 9, the device mainly includes the following parts:

a data acquisition module 902, configured to acquire a drilling point data set of a research area; the drilling point data set comprises coordinate data, depth data and geological layer attributes corresponding to each drilling point;

the space construction module 904 is configured to construct a polygonal geological space corresponding to the research area according to the coordinate data and the depth data in the drilling point data set; wherein the polygonal geological space contains each borehole point within the borehole point dataset;

the space segmentation module 906 is configured to perform at least one level of space segmentation on the polygonal geological space according to the geological layer attribute in the drilling point data set, so as to obtain a multi-level sub-geological space set corresponding to the research area; each level of sub-geological space set comprises a plurality of sub-geological spaces, and the number of geological layer attributes contained in each sub-geological space is smaller than or equal to 1;

The space merging module 908 is configured to perform at least one stage of inverse merging on the multi-stage sub-geological space set to obtain at least one geological semantic space corresponding to each geological layer attribute;

the model construction module 910 is configured to construct a geological curved model corresponding to the research area according to each geological semantic space.

The device for constructing the geological curved surface model provided by the embodiment of the invention is used for carrying out space division on the polygonal geological space where the drilling points are located, then reversely merging the sub-geological spaces with the same geological layer attribute to form a final geological semantic space, determining the position relationship and spatial logic between the geological layer drilling points with the same attribute, and finally generating the geological curved surface model corresponding to the research area according to each geological semantic space.

In one embodiment, the space build module 904 is further configured to:

traversing coordinate data corresponding to each drilling point in the drilling point data set to determine an abscissa maximum value, an abscissa minimum value, an ordinate maximum value and an ordinate minimum value; traversing depth data corresponding to each drilling point in the drilling point data set to determine a maximum value of a vertical coordinate and a minimum value of the vertical coordinate;

Determining a polygon range according to the maximum value of the horizontal coordinate, the minimum value of the horizontal coordinate, the maximum value of the vertical coordinate, the minimum value of the vertical coordinate, the maximum value of the vertical coordinate and the minimum value of the vertical coordinate;

and constructing polygonal geological space corresponding to the research area based on the polygonal range.

In one embodiment, the polygonal geological space comprises a rectangular geological space; the spatial segmentation module 906 is also configured to:

for the rectangular geological space, if the number of geological layer attributes contained in the rectangular geological space is greater than 1, determining the central coordinates of root nodes corresponding to the rectangular geological space, and dividing the rectangular geological space into a plurality of sub-geological spaces according to the central coordinates of the root nodes so as to obtain a first-stage sub-geological space set;

judging whether the number of geologic layer attributes contained in each sub-geologic space in the current-stage sub-geologic space set is less than or equal to 1 or not;

if yes, stopping space division on the sub-geological space;

if not, continuing to determine the central coordinates of the sub-nodes corresponding to the sub-geological space, dividing the sub-geological space into a plurality of sub-geological spaces according to the central coordinates of the sub-nodes to obtain a next-stage sub-geological space set until the number of geological layer attributes contained in each sub-geological space is less than or equal to 1, so as to obtain a multi-stage sub-geological space set corresponding to the research area.

In one embodiment, spatial merging module 908 is further configured to:

merging the sub-geological spaces in the final-stage sub-geological space set according to a preset merging principle; the preset merging principle comprises a coplanarity principle and an attribute consistency principle, wherein the coplanarity principle comprises complete coplanarity or coplanarity;

and continuing to merge the sub-geological spaces in the upper-level sub-geological space set corresponding to the last-level sub-geological space set according to a preset merging principle until the sub-geological spaces in the first-level sub-geological space set are merged to obtain at least one geological semantic space corresponding to each geological layer attribute.

In one embodiment, spatial merging module 908 is further configured to:

if yes, merging the sub-geological space clockwise according to the plane;

if not, screening out a target sub-geological space which is coplanar with the sub-geological space and has consistent geological layer properties from the final-stage sub-geological space set, and merging the sub-geological space with the target sub-geological space.

In one embodiment, the model building module 910 is further configured to:

for each geological semantic space, determining a drilling point sub-data set corresponding to the geological semantic space from a drilling point data set, and fitting to generate a geological curved surface function model corresponding to the geological semantic space by using a radial basis function according to the drilling point sub-data set;

In one embodiment, the model building module 910 is further configured to:

determining an equipotential surface sampling size according to coordinate data and depth data in the drilling point data set;

sampling each geological curved surface function model according to the equipotential surface acquisition size to obtain equipotential patches corresponding to geological semantic space;

and connecting equipotential patches corresponding to each geological semantic space to obtain a geological curved surface model corresponding to the research area.

In one embodiment, the model building module 910 is further configured to:

And determining the equipotential surface sampling size based on the average value of the initial average distance corresponding to each drilling point.

The device provided by the embodiment of the present invention has the same implementation principle and technical effects as those of the foregoing method embodiment, and for the sake of brevity, reference may be made to the corresponding content in the foregoing method embodiment where the device embodiment is not mentioned.

The embodiment of the invention provides electronic equipment, which comprises a processor and a storage device; the storage means has stored thereon a computer program which, when executed by the processor, performs the method of any of the embodiments described above.

Fig. 10 is a schematic structural diagram of an electronic device according to an embodiment of the present invention, where the electronic device 100 includes: a processor 10, a memory 11, a bus 12 and a communication interface 13, the processor 10, the communication interface 13 and the memory 11 being connected by the bus 12; the processor 10 is arranged to execute executable modules, such as computer programs, stored in the memory 11.

The memory 11 may include a high-speed random access memory (RAM, random Access Memory), and may further include a non-volatile memory (non-volatile memory), such as at least one magnetic disk memory. The communication connection between the system network element and at least one other network element is achieved via at least one communication interface 13 (which may be wired or wireless), the internet, a wide area network, a local network, a metropolitan area network, etc. may be used.

Bus 12 may be an ISA bus, a PCI bus, an EISA bus, or the like. The bus may be classified as a geological bus, a data bus, a control bus, etc. For ease of illustration, only one bi-directional arrow is shown in FIG. 10, but not only one bus or type of bus.

The memory 11 is configured to store a program, and the processor 10 executes the program after receiving an execution instruction, and the method executed by the apparatus for flow defining disclosed in any of the foregoing embodiments of the present invention may be applied to the processor 10 or implemented by the processor 10.

The processor 10 may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuitry in hardware or instructions in software in the processor 10. The processor 10 may be a general-purpose processor, including a Central Processing Unit (CPU), a Network Processor (NP), and the like; but may also be a digital signal processor (Digital Signal Processing, DSP for short), application specific integrated circuit (Application Specific Integrated Circuit, ASIC for short), off-the-shelf programmable gate array (Field-Programmable Gate Array, FPGA for short), or other programmable logic device, discrete gate or transistor logic device, discrete hardware components. The disclosed methods, steps, and logic blocks in the embodiments of the present invention may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of the method disclosed in connection with the embodiments of the present invention may be embodied directly in the execution of a hardware decoding processor, or in the execution of a combination of hardware and software modules in a decoding processor. The software modules may be located in a random access memory, flash memory, read only memory, programmable read only memory, or electrically erasable programmable memory, registers, etc. as well known in the art. The storage medium is located in a memory 11 and the processor 10 reads the information in the memory 11 and in combination with its hardware performs the steps of the method described above.

The computer program product of the readable storage medium provided by the embodiment of the present invention includes a computer readable storage medium storing a program code, where the program code includes instructions for executing the method described in the foregoing method embodiment, and the specific implementation may refer to the foregoing method embodiment and will not be described herein.

The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution, in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.

Finally, it should be noted that: the above examples are only specific embodiments of the present invention, and are not intended to limit the scope of the present invention, but it should be understood by those skilled in the art that the present invention is not limited thereto, and that the present invention is described in detail with reference to the foregoing examples: any person skilled in the art may modify or easily conceive of the technical solution described in the foregoing embodiments, or perform equivalent substitution of some of the technical features, while remaining within the technical scope of the present disclosure; such modifications, changes or substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention, and are intended to be included in the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.

Claims

1. The construction method of the geological curved surface model is characterized by comprising the following steps of:

constructing a geological curved surface model corresponding to the research area according to each geological semantic space;

the polygonal geological space comprises a rectangular geological space; according to the geologic layer attribute in the drilling point data set, at least one-stage space segmentation is performed on the polygonal geologic space to obtain a multi-stage sub-geologic space set corresponding to the research area, which comprises the following steps:

if yes, stopping space division on the sub-geological space;

if not, continuing to determine the central coordinates of the sub-nodes corresponding to the sub-geological space, and dividing the sub-geological space into a plurality of sub-geological spaces according to the central coordinates of the sub-nodes to obtain a next-stage sub-geological space set until the number of geological layer attributes contained in each sub-geological space is less than or equal to 1, so as to obtain a multi-stage sub-geological space set corresponding to the research area;

at least one level of reverse merging is carried out on the multi-level sub-geological space set to obtain at least one geological semantic space corresponding to each geological layer attribute, and the method comprises the following steps:

continuing to merge the sub-geological spaces in the previous sub-geological space set corresponding to the last-level sub-geological space set according to the preset merging principle until the sub-geological spaces in the first-level sub-geological space set are merged to obtain at least one geological semantic space corresponding to each geological layer attribute;

Constructing a geological curved surface model corresponding to the research area according to each geological semantic space, wherein the geological curved surface model comprises the following steps:

2. The method of constructing a geologic curved model according to claim 1, wherein constructing a polygonal geologic space corresponding to the region of interest from the coordinate data and the depth data in the set of borehole point data comprises:

3. The method for constructing a geologic curved model according to claim 1, wherein merging the sub-geologic spaces in the final-stage sub-geologic space set according to a preset merging principle, comprises:

if yes, merging the sub-geological space clockwise according to the plane;

4. The method for constructing a geologic curved model according to claim 1, wherein constructing a geologic curved model corresponding to the investigation region from each of the geologic curved function models comprises:

5. The method of constructing a geologic surface model of claim 4, wherein determining an equipotential surface sampling size from the coordinate data and the depth data in the set of borehole point data comprises:

6. The device for constructing the geological curved surface model is characterized by comprising the following components:

the model construction module is used for constructing a geological curved surface model corresponding to the research area according to each geological semantic space;

The polygonal geological space comprises a rectangular geological space; the spatial segmentation module is also used for:

if yes, stopping space division on the sub-geological space;

the spatial merging module is also used for:

the model building module is also for:

7. An electronic device comprising a processor and a memory, the memory storing computer-executable instructions executable by the processor, the processor executing the computer-executable instructions to implement the method of any one of claims 1 to 5.

8. A computer readable storage medium storing computer executable instructions which, when invoked and executed by a processor, cause the processor to implement the method of any one of claims 1 to 5.