CN107730586A - A kind of method and system of stratum modeling - Google Patents
A kind of method and system of stratum modeling Download PDFInfo
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- CN107730586A CN107730586A CN201711227782.2A CN201711227782A CN107730586A CN 107730586 A CN107730586 A CN 107730586A CN 201711227782 A CN201711227782 A CN 201711227782A CN 107730586 A CN107730586 A CN 107730586A
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Abstract
The invention discloses a kind of Stratum Modeling and system.Wherein, a kind of Stratum Modeling includes：Formation data is obtained, wherein, formation data includes figure, data or survey position；Octree index is established according to the density of formation data；Indexed according to Octree and geologic data is built into multilayer level point set, wherein, level point set is data point set corresponding to each level of Octree index；Stratum is modeled by Compactly supported radial basis function, wherein, Compactly supported radial basis function is determined by the data point set of each level.Solve the problems, such as that the data distribution of prior art is uneven, data different scale is big by the present invention, improve the accuracy of stratum three-dimensional modeling, reduce the time of stratum modeling.
Description
Technical field
The present invention relates to three dimensional contour line field, in particular to a kind of Stratum Modeling and system.
Background technology
At present, with the continuous improvement of Automation of Coal Mine degree, the required precision more and more higher to three-dimensional geological model.Ore deposit
Mountain three dimensional contour line refers to establish target area stratum by integrating multi-source caused by each production phase and multi-Scale Data
Body Model, producers are enable to carry out digging planning, safe early warning, achievement statistics etc. under the support of visualization of 3 d model
Work, consequently facilitating scheduling of production, improves operating efficiency.The research origin of mine three-dimensional formation surface modeling was in 70 years last century
In generation, risen on the basis of more urgent to the cognition of mine underground structure.Prior art is carried out to Complicated Geologic Condition
Various problems during modeling be present, such as, when carrying out three-dimensional modeling to mine three-dimensional formation because mine three-dimensional formation data are come
Source is extensive, and data yardstick differs, and data volume is larger, so the process existing defects for establishing geologic body surface model are as follows：
(1) data source causes that data distribution is uneven, data different scale is big, interpolation algorithm selection is difficult extensively；
(2) data volume is huge, causes computer analyzing to establish stratified geological objects needs and takes considerable time；
(3) stratified geological objects and actual conditions difference established are larger, cause the precision of three-dimensional modeling relatively low；
For above mentioned problem of the prior art, not yet propose to efficiently solve scheme at present.
The content of the invention
The invention provides a kind of method and system of stratum modeling, with solve data distribution in the prior art it is uneven,
Data different scale is big, parsing expends the problem of time and modeling accuracy are low.
One side according to embodiments of the present invention, there is provided a kind of method of stratum modeling, including：Obtain the ground number of plies
According to, wherein, the formation data includes figure, data or survey position；Octree rope is established according to the density of the formation data
Draw；Indexed according to the Octree and the geologic data is built into multilayer level point set, wherein, the level point set is eight forks
Set data point set corresponding to each level of index；Stratum is modeled by Compactly supported radial basis function, wherein, it is described tight
Supporting RBF is determined by the data point set of each level.
Further, include before establishing Octree index according to the density of the formation data：To the formation data
Pre-processed.
Further, carrying out pretreatment to the formation data includes：To each data point calculation of formation data, its is right
The normal vector answered；Orientation matrix is obtained by the normal vector of each data point；Orientation matrix is obtained by the orientation matrix
Characteristic value and characteristic vector.
Further, establishing Octree index according to the density of the formation data includes：According to the formation data
The data point of formation data is layered by density by recursive subdivision, and each dividing layer is averagely partitioned into eight parts of spaces,
The number of data point in judging per a space, then stop when the number that judged result is the data point in space is less than 8
Layering.
Further, stratum is modeled by Compactly supported radial basis function including：By the orientation matrix, described
The anisotropy distance of characteristic value and each level point set of original support radius calculation, wherein, the original support radius is by institute
The normal vector of the center position and each data point of stating each data point of Octree kind is determined；According to the anisotropy away from
From obtaining the Compactly supported radial basis function；Stratum is modeled by the Compactly supported radial basis function.
Further, stratum is modeled by the Compactly supported radial basis function including：Pass through the anisotropy
Distance obtains the Compactly supported radial basis function of each level point set；Each level point is updated according to the Compactly supported radial basis function
The interpolating function of collection；Stratum is modeled according to the interpolating function.
Further, stratum is modeled according to the interpolating function including：It is implicit by interpolating function renewal
Function, wherein, the Implicitly function is the function for making last layer of interpolating function be zero, and last layer of interpolating function is close
Spend highest level point set；Stratum is modeled according to the Implicitly function.
Further, being indexed the geologic data being built into after multilayer level point set according to the Octree includes：
The level point set is arranged according to the density at each number of plies strong point.
Other side according to embodiments of the present invention, a kind of stratum modeling system is additionally provided, including：Acquiring unit,
For obtaining formation data, wherein, the formation data includes figure, data or survey position；Indexing units, for according to
Formation data establishes Octree index；Construction unit, for according to the Octree index construct per layer data level point set,
Wherein, the level point set is data point set corresponding to each level of Octree index, and the level point set is according to each layer
The density of data point is arranged；Computing unit, for being modeled by Compactly supported radial basis function to stratum, wherein, institute
Stating Compactly supported radial basis function is determined by the data point set of each level.
According to embodiments of the present invention, using acquisition formation data, wherein, the formation data includes figure, data or surveyed
Visit position；Octree index is established according to the density of the formation data；Indexed according to the Octree by the geologic data
Multilayer level point set is built into, wherein, the level point set is data point set corresponding to each level of Octree index；Pass through
Compactly supported radial basis function is modeled to stratum, wherein, the Compactly supported radial basis function is by the data point of each level
Collection is determined.Solve the problems, such as that the data distribution of prior art is uneven, data different scale is big by the present invention, improve
The accuracy of stratum three-dimensional modeling, reduce the time of stratum modeling.
Brief description of the drawings
The accompanying drawing for forming the part of the application is used for providing a further understanding of the present invention, schematic reality of the invention
Apply example and its illustrate to be used to explain the present invention, do not form inappropriate limitation of the present invention.In the accompanying drawings：
Fig. 1 is a kind of flow chart of Stratum Modeling according to embodiments of the present invention；
Fig. 2 is a kind of particular flow sheet of Stratum Modeling according to embodiments of the present invention；
Fig. 3 is to stratum S all samples point calculating method vector result schematic diagram according to the embodiment of the present invention；
Fig. 4 is to establish point set level schematic diagram to certain mine stratum S data according to the embodiment of the present invention；
Fig. 5 is the surface model schematic diagram according to all stratum in the mine of the foundation of the embodiment of the present invention；
Fig. 6 is a kind of structure chart of stratum modeling system according to embodiments of the present invention.
Embodiment
It should be noted that in the case where not conflicting, the feature in embodiment and embodiment in the application can phase
Mutually combination.Describe the present invention in detail below with reference to the accompanying drawings and in conjunction with the embodiments.
In order that those skilled in the art more fully understand the present invention program, below in conjunction with the embodiment of the present invention
Accompanying drawing, the technical scheme in the embodiment of the present invention is clearly and completely described, it is clear that described embodiment is only
The embodiment of a part of the invention, rather than whole embodiments.Based on the embodiment in the present invention, ordinary skill people
The every other embodiment that member is obtained under the premise of creative work is not made, it should all belong to the model that the present invention protects
Enclose.
It should be noted that term " first " in description and claims of this specification and above-mentioned accompanying drawing, "
Two " etc. be for distinguishing similar object, without for describing specific order or precedence.It should be appreciated that so use
Data can exchange in the appropriate case, so as to embodiments of the invention described herein.In addition, term " comprising " and " tool
Have " and their any deformation, it is intended that cover it is non-exclusive include, for example, containing series of steps or unit
Process, method, system, product or equipment are not necessarily limited to those steps clearly listed or unit, but may include without clear
It is listing to Chu or for the intrinsic other steps of these processes, method, product or equipment or unit.
The embodiments of the invention provide a kind of Stratum Modeling and system.Fig. 1 is one kind according to embodiments of the present invention
The flow chart of Stratum Modeling.As shown in figure 1, this method comprises the following steps：
Step S102, formation data is obtained, wherein, formation data includes figure, data or survey position；
Step S104, Octree index is established according to formation data；
Step S106, according to level point set of the Octree index construct per layer data, wherein, level point set is Octree rope
Data point set corresponding to each level drawn, level point set are arranged according to the density at each number of plies strong point；By data according to
The density of data is layered, and realizes the modeling at many levels to geological stratification.
Step S108, stratum is modeled by Compactly supported radial basis function, wherein, Compactly supported radial basis function be by
The data point set of each level determined,
Formation data in above-mentioned steps because source is different, such as, the position of exploratory bore-hole or other do the position of industry
Put, these position datas pre- can be set, and formation data also includes that mapping, profile etc. is so all and address
Related figure and data, so these data are uneven, the different scale of data is again big, while data volume is also huge, ground
The complexity of data is huge during shape complexity.
Compactly supported radial basis function is different from common RBF in the prior art, Compactly supported radial basis function modeling
It is to be modeled by the modeling of scope rather than the search of the total space of radius, thus the present embodiment is had certain limitations so that modeling
Precision it is higher.
Above-mentioned steps are layered by establishing Octree to all data, by data according to the density of data, are realized
At many levels to the modeling of geological stratification；Solve and skewness huge for geologic data amount of the prior art, data
The big modeling problem of different scale.Stratum is modeled by Compactly supported radial basis function so that modeling error reduces, and improves
The accuracy of stratum three-dimensional modeling, reduce the time of stratum modeling.
Because formation data is multi-source, so establishing the needing to formation data of Octree index according to formation data
Pre-processed.In a kind of optional embodiment, the process pre-processed to formation data is first, to formation data
Each data point calculation its corresponding normal vector；Secondly, orientation matrix is obtained by the normal vector of each data point；Finally,
Characteristic value and characteristic vector are obtained by orientation matrix.
Above-mentioned steps by all not same source datas carried out in a manner of normal vector unification, logging data consequently facilitating
Follow-up processing modeling.
Formation data is established into Octree index after geologic data is pre-processed, when establishing Octree index, one
In individual optional embodiment, the data point of formation data can be divided by recursive subdivision according to the density of formation data
Layer, each dividing layer is averagely partitioned into eight parts of spaces, the number per a aerial data point is judged, when judged result is
The number of data point in space then stops splitting when being less than 8.
Octree index is to split data into eight parts of spaces according to the density of geology layer data, judges the number per a space
According to number, continue layering if the data amount check in a certain space is more than or equal to 8 and go down, that is, continue the layer being divided into
8 parts, stop segmentation layering if the data amount check in a certain space is less than 8.
Uneven formation data is respectively divided into different layers by above-mentioned steps, such as, a certain formation data
Point compares concentration, and the layer divided by Octree index of this part is just more, and so as to solve, data distribution is uneven to be caused to build
The problem of mould is not accurate.Layering after again by each layer according to data amount check number (density) to data carry out from less to more
Arrangement, be layered and formation data calculated, the mode that is arranged according to density will be layered solve and follow-up calculate support
Radius-adaptive chooses the problem of difficult.
In an optional embodiment, stratum is modeled by Compactly supported radial basis function, can be according to taking
To the anisotropy distance of matrix, characteristic value and each level point set of original support radius calculation, wherein, original support radius by
The center position of each data point and the normal vector of each data point are determined in Octree；Obtained further according to anisotropy distance
To Compactly supported radial basis function；Stratum is modeled by Compactly supported radial basis function.
The Compactly supported radial basis function present invention in above-mentioned steps calculates the anisotropy of formation data, by radially
Anisotropy is added in basic function calculating process to be influenceed, and can preferably be reacted stratum geometric properties, be improved surface of stratum model
Modeling accuracy.
In an optional embodiment, stratum is modeled by the Compactly supported radial basis function including：It is logical
Cross the anisotropy distance and obtain the Compactly supported radial basis function of each level point set；According to the Compactly supported radial basis function
Update the interpolating function of each level point set；Stratum is modeled according to the interpolating function.For example, stratum is in anisotropy
Under the conditions of, when carrying out implicit surface interpolation by Compactly supported radial basis function, the transformation for mula of radial distance can be passed throughAnd radial support radius transformation for mulaCalculated.
Above-mentioned embodiment also contemplates stratum under Anisotropic Condition, implicit by Compactly supported radial basis function interpolation
The transform method of compact schemes radial distance and radial support radius transform method during curved surface, so as to reduce the error of modeling and
Complexity is resolved, reduces the time of stratum modeling.
In an optional embodiment, stratum is modeled according to the interpolating function can be by the interpolation
Function updates Implicitly function, wherein, the Implicitly function is the function for making last layer of interpolating function be zero, last described layer
Interpolating function is density highest level point set；Stratum is modeled according to the Implicitly function.
By in above-mentioned steps according to data uniformity to geologic data by Octree index layering after, can take point
Last level of one layer of layer Midst density highest conduct, the minimum level of density is the first level, is begun through from the first level
The parameter that system of linear equations calculates Compactly supported radial basis function is solved, calculates renewal interpolating function, calculates arrive last one layer always
Interpolating function, make it be equal to zero, then the function is exactly the target geological layer Implicitly function built, is solved according to the function tight
The parameter of RBF is supported, the model of visualization geological stratification is established according to the target geological layer Implicitly function.
In an optional embodiment, indexed according to Octree and geologic data is built into after multilayer level point set
Including：Level point set is arranged according to the density at each number of plies strong point, it is equal in Octree according to each layer data collection
Value tries to achieve the support radius of each layer data, so as to obtain the Compactly supported radial basis function per point set secondary from level to level, overcomes geology
Data uneven the problem of bringing, while improve the precision of modeling.
Above-mentioned steps are illustrated with reference to an optional embodiment：
The present embodiment provides a kind of multi-level RBF modeling method of anisotropic formation surface model, this method
Based on mine stratum multi-source, multi-Scale Data, surface of stratum model can be fitted according to non-homogeneous, mass data, improve modeling effect
Rate and model accuracy.
Step 1., from all types extracting data stratum bottom plate discrete point ρ={ pi, i=1,2 ..., N；Obtain
Discrete samples point piArray is that Xi'an1980 coordinate system translates x under obtained local coordinate system, y, the numerical value array of z coordinate, each
Array is uniquely extracted for formation at target locations.
Step 2., to the data point of formation at target locations, unit of account normal vector { ni, i=1,2 ..., N；Calculate normal vector
Using Point Cloud Library (PCL, http://pointclouds.org/) in, build K-D trees (k-
Dimensional tree) mode carry out, finally get the unit normal vector of all samples point.
3., by normal vector step calculates the orientation matrix of stratum in the planeAnd by taking
Eigenvalues analysis, which is carried out, to matrix obtains characteristic value E1 ＜ E2, and characteristic vectorNamely calculate two in plane
The characteristic value and characteristic vector in individual Main change direction.
4. step, to all samples point data, by creating the Octree of whole region, establishes the layer of density from low to high
Secondary point set { ρ1,ρ2,...,ρM=ρ }；Its process can be：Octree index is established to whole space first, and recursive subdivision is extremely
Sample number strong point number in each leaf space is less than 8.Then to each node of Octree, according to comprising sample
The position of data point calculation central point and unit normal vector.The corresponding point set of layer of each final Octree, is thus formed
Level point set.
Step 5., in each level point set ρkOn, pass through anisotropy Compactly supported radial basis function (Interpolation-Radix-Function)
New interpolating function f is defined with the interpolating function error of last layerk(x), solve the function and pass it to next layer of point set,
Its process can be：
I. it is f to set initial interpolating function0(x)=- 1；
II. according to formularaAnisotropy distance is represented, level point is concentrated
Any one layer of ρkRBF anisotropy distance is calculated, the formula is by anisotropy transform by the seat on x and y directions
Mark difference is transformed toPlanar radial radius is also translated into length oval on different directions
AxleWherein, σ is original support radius, and S is scaled matrix,
III. any one layer of ρ concentrated to level pointkDefine interpolating function fk(x)=fk-1(x)+ok(x), k=1,
2 ..., M, wherein,It is point set ρkOn Compactly supported radial basis function, λiFor coefficient to be resolved, lead to
Cross solution system of linear equations fk-1(ρk)+ok(ρk)=0 obtains λiSolution.Interpolation-Radix-Function φσ(ra) it is exactly Wendland compact schemes
RBF, wherein raIt is the anisotropy distance that previous step is calculated.
In above-mentioned steps, for each layer, there is point ρ by this layerkConstruct RBF ok(x), RBF
With the interpolation error f of last layerk-1(ρk) be added, you can obtain the interpolating function f of this layerk(x), by constructing Implicitly function fk
(x)=0 and system of linear equations is solved, obtains ok(ρk) parameter, each layer transmission be exactly fk-1(x) in point set ρkOn interpolation
Error.
6., by Compactly supported radial basis function step calculates last layer of point set ρMOn Implicitly function fM(x)=0 interpolation
Formation at target locations；Formation at target locations passes through an Implicitly function f in scalar fieldM=0 (x) represent, fM(x) it is last layer of point
Collect ρMOn interpolating function.And fM(x) ＜ 0 is represented in stratum side, fM(x) ＞ 0 is represented in stratum opposite side, x be comprising x, y,
Space Point Coordinates in z scalar field.
7. step realizes that stratigraphic model visualizes, complete modeling, and stratum visualization can use the movement cube in PCL storehouses
Body algorithm (Marching Cubes, MC), or Bloomenthal ' s methods are realized, it is preferred to use Bloomenthal ' s methods
Realize.
Part optional embodiment in above-described embodiment is to be based on non-homogeneous (10-1To 104Rice), it is a large amount of (>103It is individual) number
According to formation data, there is provided efficient surface modeling methods；Meanwhile consider the ground anisotropy factor in data, by right
RBF converts, and eliminates anisotropic influence, improves surface model precision.
Illustrate that another optional embodiment illustrates to said process with reference to Fig. 2：
As shown in Fig. 2 collect Hebei mine C05, C07, C08, C09, C11, C12-1 totally six stratum related datas.
By taking C07 as an example, boring point 36, down-hole formation point 57, underground mapping point 2395 are collected altogether；
As shown in figure 3, normal vector calculating, the unit normal vector of stratum S all samples point are carried out by PCL storehouses；
Calculate the characteristic value and characteristic vector of most important three change directions of stratum S；
As shown in figure 4, to stratum S all samples point datas, by creating the Octree of whole region, density is established by low
To high level point set { ρ1,ρ2,...,ρM=ρ }, M=7, totally 7 level point sets of foundation are visualized in figure, data
Distribution is by sparse to dense；
Interpolating function f is calculated by the Compactly supported radial basis function of anisotropy transform on each level point setk(x)
=fk-1(x)+ok(x) parameter, computational methods are to solve for system of linear equations fk-1(x)+ok(x)=0, and by interpolation error fk(x)
Value attribute transmission to be inserted as next level；
By the Implicitly function f for calculating last layerM(x)=0 interpolation stratum S；
Realize that stratigraphic model visualizes, complete C07 stratum modelings.Effect such as Fig. 5 institutes that all 6 stratum are modeled
Show.
Above-mentioned embodiment has the advantage that：
(1) anisotropy of formation data is calculated, by adding anisotropy shadow in RBF calculating process
Ring, can preferably react stratum geometric properties, improve surface of stratum model modeling precision.
(2) by Hierarchy Method, reduce under non-homogeneous data, support radius-adaptive chooses the problem of difficult；Simultaneously
With the reduction of error, resolving matrix is progressively sparse, reduces the stand-by period required for stratum is established.
The embodiment of the present invention additionally provides a kind of stratum modeling system, and the system can pass through acquiring unit 62, Index List
Member 64, construction unit 66 realize its function.It should be noted that a kind of stratum modeling system of the embodiment of the present invention can be used for
A kind of Stratum Modeling that the embodiment of the present invention is provided is performed, a kind of Stratum Modeling of the embodiment of the present invention can also
A kind of stratum modeling system for being there is provided by the embodiment of the present invention performs.Fig. 6 is a kind of ground according to embodiments of the present invention
The schematic diagram of layer modeling.As shown in fig. 6, Fig. 6 is a kind of structure chart of stratum modeling system according to embodiments of the present invention.
A kind of stratum modeling system, including：
Acquiring unit 62, for obtaining formation data, wherein, formation data includes figure, data or survey position；
Indexing units 64, for establishing Octree index according to formation data；
Construction unit 66, for the level point set according to the every layer data of Octree index construct, wherein, level point set is eight
Data point set corresponding to each level of fork tree index, level point set are arranged according to the density at each number of plies strong point；
Computing unit 68, for being modeled by Compactly supported radial basis function to stratum, wherein, compact schemes radial direction base letter
Number is determined by the data point set of each level.
A kind of above-mentioned stratum modeling system embodiment is corresponding with a kind of method of stratum modeling, so for beneficial
Effect repeats no more.
It should be noted that for foregoing each method embodiment, in order to be briefly described, therefore it is all expressed as a series of
Combination of actions, but those skilled in the art should know, the present invention is not limited by described sequence of movement because
According to the present invention, some steps can use other orders or carry out simultaneously.Secondly, those skilled in the art should also know
Know, embodiment described in this description belongs to preferred embodiment, and involved action and module are not necessarily of the invention
It is necessary.
In the above-described embodiments, the description to each embodiment all emphasizes particularly on different fields, and does not have the portion being described in detail in some embodiment
Point, it may refer to the associated description of other embodiment.
In several embodiments provided herein, it should be understood that disclosed device, can be by another way
Realize.For example, device embodiment described above is only schematical, such as the division of the unit, it is only one kind
Division of logic function, can there is an other dividing mode when actually realizing, such as multiple units or component can combine or can
To be integrated into another system, or some features can be ignored, or not perform.Another, shown or discussed is mutual
Coupling direct-coupling or communication connection can be by some interfaces, the INDIRECT COUPLING or communication connection of device or unit,
Can be electrical or other forms.
The unit illustrated as separating component can be or may not be physically separate, show as unit
The part shown can be or may not be physical location, you can with positioned at a place, or can also be distributed to multiple
On NE.Some or all of unit therein can be selected to realize the mesh of this embodiment scheme according to the actual needs
's.
In addition, each functional unit in each embodiment of the present invention can be integrated in a processing unit, can also
That unit is individually physically present, can also two or more units it is integrated in a unit.Above-mentioned integrated list
Member can both be realized in the form of hardware, can also be realized in the form of SFU software functional unit.
If the integrated unit is realized in the form of SFU software functional unit and is used as independent production marketing or use
When, it can be stored in a computer read/write memory medium.Based on such understanding, technical scheme is substantially
The part to be contributed in other words to prior art or all or part of the technical scheme can be in the form of software products
Embody, the computer software product is stored in a storage medium, including some instructions are causing a computer
Equipment (can be personal computer, mobile terminal, server or network equipment etc.) performs side described in each embodiment of the present invention
The all or part of step of method.And foregoing storage medium includes：USB flash disk, read-only storage (ROM, Read-Only Memory),
Random access memory (RAM, Random Access Memory), mobile hard disk, magnetic disc or CD etc. are various to be stored
The medium of program code.
The preferred embodiments of the present invention are the foregoing is only, are not intended to limit the invention, for the skill of this area
For art personnel, the present invention can have various modifications and variations.Within the spirit and principles of the invention, that is made any repaiies
Change, equivalent substitution, improvement etc., should be included in the scope of the protection.
Claims (9)
- A kind of 1. Stratum Modeling, it is characterised in that including：Formation data is obtained, wherein, the formation data includes figure, data or survey position；Octree index is established according to the density of the formation data；Indexed according to the Octree and the geologic data is built into multilayer level point set, wherein, the level point set is eight Data point set corresponding to each level of fork tree index；Stratum is modeled by Compactly supported radial basis function, wherein, the Compactly supported radial basis function is by each level Data point set determined.
- 2. according to the method for claim 1, it is characterised in that Octree index is established according to the density of the formation data Include before：The formation data is pre-processed.
- 3. according to the method for claim 2, it is characterised in that carrying out pretreatment to the formation data includes：To its corresponding normal vector of each data point calculation of formation data；Orientation matrix is obtained by the normal vector of each data point；The characteristic value and characteristic vector of orientation matrix are obtained by the orientation matrix.
- 4. according to the method described in claim 1-3, it is characterised in that establish Octree rope according to the density of the formation data Draw including：The data point of formation data is layered by recursive subdivision according to the density of the formation data, by each dividing layer Eight parts of spaces are averagely partitioned into, the number of the data point in judging per a space, when judged result is the data in space The number of point then stops being layered when being less than 8.
- 5. method according to claim 1 or 2, it is characterised in that built by Compactly supported radial basis function to stratum Mould includes：By the anisotropy distance of the orientation matrix, the characteristic value and each level point set of original support radius calculation, Wherein, the original support radius is by the center position of each data point of Octree kind and the normal vector of each data point Determined；The Compactly supported radial basis function is obtained according to the anisotropy distance；Stratum is modeled by the Compactly supported radial basis function.
- 6. according to the method described in claim 1,2 or 5, it is characterised in that by the Compactly supported radial basis function to stratum Be modeled including：The Compactly supported radial basis function of each level point set is obtained by the anisotropy distance；The interpolating function of each level point set is updated according to the Compactly supported radial basis function；Stratum is modeled according to the interpolating function.
- 7. according to the method for claim 6, it is characterised in that stratum is modeled according to the interpolating function including：Implicitly function is updated by the interpolating function, wherein, the Implicitly function makes last layer of interpolating function be zero Function, last layer of interpolating function are density highest level point sets；Stratum is modeled according to the Implicitly function.
- 8. method according to claim 1 or 2, it is characterised in that indexed according to the Octree by the geologic data Be built into multilayer level point set includes afterwards：The level point set is arranged according to the density at each number of plies strong point.
- A kind of 9. stratum modeling system, it is characterised in that including：Acquiring unit, for obtaining formation data, wherein, the formation data includes figure, data or survey position；Indexing units, for establishing Octree index according to the formation data；Construction unit, for the level point set according to the every layer data of the Octree index construct, wherein, the level point set is Data point set corresponding to each level of Octree index, the level point set are arranged according to the density at each number of plies strong point Row；Computing unit, for being modeled by Compactly supported radial basis function to stratum, wherein, the Compactly supported radial basis function It is to be determined by the data point set of each level.
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Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102651144A (en) * | 2012-03-30 | 2012-08-29 | 北京师范大学 | Method for geologic body to quickly and dynamically generate linear octree |
| US20130249899A1 (en) * | 2012-03-07 | 2013-09-26 | Willow Garage Inc. | Point cloud data hierarchy |
| CN105631935A (en) * | 2015-12-30 | 2016-06-01 | 上海顺凯信息技术股份有限公司 | BIM-based three-dimensional geological automatic modeling method |
-
2017
- 2017-11-29 CN CN201711227782.2A patent/CN107730586B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20130249899A1 (en) * | 2012-03-07 | 2013-09-26 | Willow Garage Inc. | Point cloud data hierarchy |
| CN102651144A (en) * | 2012-03-30 | 2012-08-29 | 北京师范大学 | Method for geologic body to quickly and dynamically generate linear octree |
| CN105631935A (en) * | 2015-12-30 | 2016-06-01 | 上海顺凯信息技术股份有限公司 | BIM-based three-dimensional geological automatic modeling method |
Non-Patent Citations (1)
| Title |
|---|
| 魏嘉等: "三维地质模型海量数据组织和可视化技术研究", 《石油物探》 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110443890A (en) * | 2019-07-08 | 2019-11-12 | 中南大学 | Situ Leaching mineral deposit Stratum Modeling |
| CN110443890B (en) * | 2019-07-08 | 2021-03-30 | 中南大学 | In-situ leached ore deposit stratum modeling method |
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