CN111859268A - Magnetic tensor abnormal spatial domain fast alignment algorithm based on grid point lattice - Google Patents

Magnetic tensor abnormal spatial domain fast alignment algorithm based on grid point lattice Download PDF

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CN111859268A
CN111859268A CN202010605984.1A CN202010605984A CN111859268A CN 111859268 A CN111859268 A CN 111859268A CN 202010605984 A CN202010605984 A CN 202010605984A CN 111859268 A CN111859268 A CN 111859268A
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CN111859268B (en
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王科
张志厚
寇川
范祥泰
赵思为
路润琪
尹小康
姚禹
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Southwest Jiaotong University
China Railway Eryuan Engineering Group Co Ltd CREEC
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Abstract

The invention discloses a magnetic tensor abnormal spatial domain fast forward modeling method based on grid point grids, which comprises the steps of establishing a model body according to actual mileage, dividing the model body into grids according to set grid intervals, respectively calculating grid functions of magnetic tensor abnormality of four vertexes of the upper surface of the model body by all grid points in a model space, and then storing the grid functions as a grid function database; when the magnetic tensor of any grid point to any observation point is calculated to be abnormal, directly calling a grid function database according to the translation equivalence, and multiplying the grid function database by a physical property parameter to obtain the magnetic tensor abnormality of the point to the observation point; until the magnetic tensor abnormality of the whole model body to each observation point of the working area plane is obtained, namely the full tensor magnetic gradient data Bxx、Bxy、Bxz、Byy、Byz、Bzz. By utilizing the translation equivalence, only the four vertexes of the upper surface of the model body of the cuboid unit need to be calculatedAnd the magnetic tensor is abnormal and a database is established, so that repeated calculation is reduced, and the forward modeling efficiency of the abnormal spatial domain of the magnetic tensor is improved.

Description

Magnetic tensor abnormal spatial domain fast alignment algorithm based on grid point lattice
Technical Field
The invention relates to forward calculation of gravity-magnetic exploration, in particular to a magnetic tensor abnormal spatial domain fast forward calculation method based on grid point grids.
Background
In the forward modeling calculation of gravity-magnetic exploration, a model is divided into a plurality of cuboid units by using common equidistant grid lines, then the abnormality of each cuboid unit to an observation point is calculated, and then the abnormality of all cuboid units to the observation point is summed, namely the abnormality of the whole model body to the observation point is obtained. There are a large number of repeated calculations, resulting in a significant reduction in numerical simulation and inversion efficiency.
Yaohangli, Hupenshell, Qunzing, Zhang 32895Wenzhi, geomechanics journal, 2003, 46 (2): 252- & ltJ ] in the published gravity-magnetic genetic algorithm three-dimensional inversion medium-high speed calculation and effective storage method technology [ J ] the forward modeling condition of the subdivision model is explained by using a forward modeling formula of a three-dimensional density model, a geometric lattice equivalent compression storage technology is provided, and the tilt magnetization problem in the magnetic anomaly type is simplified by using translation equivalence. According to the method, the abnormity of a certain cuboid unit on all grid points of a certain layer is calculated firstly, and then the abnormity is stored and called, so that the calculation efficiency is improved, but the calculation efficiency can be further improved due to repeated calculation of the geometric grid.
Disclosure of Invention
The invention aims to: aiming at the problem of repeated calculation of a geometric framework in the prior art, the magnetic tensor abnormal space domain fast correction algorithm based on the grid point framework is provided, and by utilizing the translation equivalence, only the magnetic tensor abnormality of the cuboid units on four vertexes of the upper surface of the model body needs to be calculated and a database is established, so that the repeated calculation is reduced, and the calculation efficiency is improved.
In order to achieve the purpose, the invention adopts the technical scheme that:
a magnetic tensor abnormal spatial domain fast alignment algorithm based on grid point lattice comprises the following steps:
s100, a model body is established according to the actual mileage, the model body is divided into grids according to the set grid intervals, namely the model body is formed by combining a plurality of cuboid units, and the residual magnetic susceptibility of the abnormal body is correspondingly set at the position of the abnormal body in the grids.
S200, respectively calculating the lattice functions of magnetic tensor abnormity of all the grid points to observation points P1, P2, P3 and P4 in the model space, and then storing the lattice functions as a lattice function database; wherein, P1, P2, P3 and P4 are four vertexes of the upper surface of the model body;
s300, taking the grid points on the upper surface of the model body as observation points, and calculating the magnetic tensor abnormity of the whole model body to one observation point;
s310, each cuboid unit has 8 vertexes, each vertex has a relative position relation with the observation point, lattice functions corresponding to the relative position relations in a lattice function database are respectively called according to translation equivalence, and the 8 lattice functions are summed and multiplied by physical property parameters to obtain the magnetic tensor abnormity of the cuboid unit on the observation points;
s320, repeating the step S310 until the magnetic tensor abnormality of all the cuboid units to the observation point is obtained;
S330, summing the magnetic tensor anomalies of the observation point by all the cuboid units, namely the magnetic tensor anomalies of the observation point by the whole model body.
S400, repeating the step S300 until the magnetic tensor abnormality of the whole model body to each observation point of the working area plane is obtained, namely the full tensor magnetic gradient data Bxx、Bxy、Bxz、Byy、Byz、Bzz。
A magnetic tensor abnormal spatial domain fast positive algorithm based on grid point lattices is characterized in that a model body is built according to actual mileage, the model body is divided into grids according to set grid intervals, grid functions of magnetic tensor abnormality of four vertexes of the upper surface of the model body of all grid points in a model space are respectively calculated and then stored as a grid function database; when the magnetic tensor of any grid point to any observation point is calculated to be abnormal, directly calling a grid function database according to the translation equivalence, and multiplying the grid function database by a physical property parameter to obtain the magnetic tensor abnormality of the point to the observation point; until the magnetic tensor abnormality of the whole model body to each observation point of the working area plane is obtained, namely the full tensor magnetic gradient data Bxx、Bxy、Bxz、Byy、Byz、Bzz. By utilizing the translation equivalence, only the magnetic tensor abnormality of the cuboid unit on the four vertexes of the upper surface of the model body needs to be calculated, and a database is established, so that the repeated calculation is reduced, and the forward efficiency of the magnetic tensor abnormal spatial domain is improved.
Preferably, in step S100, the residual magnetic susceptibility of the abnormal body is: the observation data of the background field is abnormal, namely the physical property of the abnormal body is poor.
Preferably, in the step S200, the trellis function database includes a set of trellis functions MagneticP1, MagneticP2, MagneticP3 and MagneticP4 of magnetic tensor abnormality of all grid point pairs observation points P1, P2, P3 and P4; the coordinates of observation point P1 are (1,1), the coordinates of observation point P2 are (NX +1,1), the coordinates of observation point P3 are (NX +1, NY +1), the coordinates of observation point P4 are (1, NY +1), and NX and NY respectively represent the number of cuboid cells in the X direction and the Y direction of the model body.
Preferably, in step S310, invoking a trellis function corresponding to the relative position relationship in the trellis function database specifically includes:
s311, judging the relative position relationship type of the observation point and the cuboid unit;
s312, the trellis function in the trellis function set corresponding to the relationship type is called.
Preferably, the step S311 specifically includes:
the coordinates of the observation points are (IX, IY), and the observation points are the IX-th point in the X direction and the IY-th point in the Y direction in all the observation points; the coordinates of the cuboid unit are (i, j, k), which indicates that the cuboid unit is the ith block in the X direction, the jth block in the Y direction and the kth block in the Z direction in all the cuboid units;
When the coordinate relation between the coordinate of the observation point and the coordinate relation of the cuboid unit is IX-i and IY-j, the relation type corresponds to the lattice function set MagneticP 1;
when the coordinate relation between the coordinate of the observation point and the coordinate relation between the coordinate of the cuboid unit is IX > i and IY is less than or equal to j, the relation type corresponds to the lattice function set MagneticP 2;
when the coordinate relation between the coordinate of the observation point and the coordinate relation between the coordinate of the cuboid unit is IX > i and IY > j, the relation type corresponds to the trellis function set MagneticP 3;
and when the coordinate relation between the coordinate of the observation point and the coordinate relation of the cuboid unit is IX & ltor & gt i and IY & gt j, the relation type corresponds to the lattice function set MagneticP 4.
Preferably, in step S400, the magnetic anomaly three-component Bx、By、BzObtaining full tensor magnetic gradient data B by taking derivatives in three directions of x, y and zxx、Bxy、Bxz、Byy、Byz、Bzz。
Preferably, the full-tensor magnetic gradient data B in the step S400xx、Bxy、Bxz、Byy、Byz、 Bzz：
Figure RE-GDA0002631801280000041
Figure RE-GDA0002631801280000042
Figure RE-GDA0002631801280000043
Figure RE-GDA0002631801280000044
Figure RE-GDA0002631801280000045
Figure RE-GDA0002631801280000051
Wherein, mu0Is the magnetic permeability in vacuum, M is the remanent susceptibility, μijkIs muijk＝(-1)i(-1)j(-1)kI is the inclination angle of magnetization, r is the declination angle of magnetizationijkDistance of observation point to grid point, xiSubtracting the value in the X-direction of the grid point, y, from the value in the X-direction of the observation pointjSubtracting the value in the grid point Y direction, z, from the value in the observation point Y directionkThe value in the grid point Z direction is subtracted from the value in the observation point Z direction.
An electronic device comprising at least one processor, and a memory communicatively coupled to the at least one processor; the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the algorithm of any one of the above.
In summary, due to the adoption of the technical scheme, the invention has the beneficial effects that:
the invention relates to a magnetic tensor abnormal space domain fast correction algorithm based on grid point grids, which is characterized in that a model body is established according to actual mileage, the model body is divided into grids according to set grid intervals, grid functions of magnetic tensor abnormality of four vertexes of the upper surface of the model body by all grid points in a model space are respectively calculated and then stored as a grid function database; when the magnetic tensor of any grid point to any observation point is calculated to be abnormal, directly calling a grid function database according to the translation equivalence, and multiplying the grid function database by a physical property parameter to obtain the magnetic tensor abnormality of the point to the observation point; until the magnetic tensor abnormality of the whole model body to each observation point of the working area plane is obtained, namely the full tensor magnetic gradient data Bxx、Bxy、Bxz、Byy、Byz、Bzz. By utilizing the translation equivalence, only the magnetic tensor abnormality of the cuboid unit on the four vertexes of the upper surface of the model body needs to be calculated, and a database is established, so that the repeated calculation is reduced, and the forward efficiency of the magnetic tensor abnormal spatial domain is improved.
Drawings
Fig. 1 is a flowchart of a space domain fast-alignment algorithm of magnetic tensor anomaly based on a grid lattice function.
Fig. 2 is a schematic diagram of a subsurface mesh generation unit.
Fig. 3 is a schematic diagram of a mesh generation unit and an observation point.
Fig. 4 is a schematic diagram of translational equivalence.
FIG. 5 is a diagram of magnetic tensor anomaly obtained by an original alignment algorithm for an underground grid unit model.
FIG. 6 is a diagram of magnetic tensor abnormalities for an underground grid cell model using a fast-forward algorithm.
Fig. 7 is a schematic structural diagram of an electronic device provided in the present invention.
Detailed Description
The present invention will be described in detail below with reference to the accompanying drawings.
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Example 1
A magnetic tensor abnormal spatial domain fast alignment algorithm based on grid point lattice comprises the following steps:
s100, a model body is established according to the actual mileage, the model body is divided into grids according to the set grid spacing, namely the model body is formed by combining a plurality of cuboid units, and the residual magnetic susceptibility of the abnormal body is correspondingly set at the position of the abnormal body in the grids (the residual magnetic susceptibility of the abnormal body is the abnormal observation data of the background field removal, namely the physical property difference of the abnormal body).
S200, respectively calculating the lattice functions of magnetic tensor abnormity of all the grid points to observation points P1, P2, P3 and P4 in the model space, and then storing the lattice functions as a lattice function database; wherein, P1, P2, P3 and P4 are four vertexes of the upper surface of the model body;
namely: the trellis function database comprises trellis function sets MagneticP1, MagneticP2, MagneticP3, MagneticP4 of magnetic tensor anomalies for all grid point pair observation points P1, P2, P3, P4; the coordinates of observation point P1 are (1,1), the coordinates of observation point P2 are (NX +1,1), the coordinates of observation point P3 are (NX +1, NY +1), the coordinates of observation point P4 are (1, NY +1), and NX and NY respectively represent the number of cuboid cells in the X direction and the Y direction of the model body.
S300, taking the grid points on the upper surface of the model body as observation points, and calculating the magnetic tensor abnormality of the whole model body to one observation point, specifically comprising the following steps S310-S330:
s310, each cuboid unit has 8 vertexes, each vertex has a relative position relation with the observation point, lattice functions corresponding to the relative position relations in a lattice function database are respectively called according to translation equivalence, and the 8 lattice functions are summed and multiplied by physical property parameters to obtain the magnetic tensor abnormity of the cuboid unit on the observation points;
Calling the trellis function corresponding to the relative position relation in the trellis function database, which specifically comprises:
s311, judging the relative position relationship type between the observation point and the rectangular unit, including:
the coordinates of the observation points are (IX, IY), and the observation points are the IX-th point in the X direction and the IY-th point in the Y direction in all the observation points; the coordinates of the cuboid unit are (i, j, k), which indicates that the cuboid unit is the ith block in the X direction, the jth block in the Y direction and the kth block in the Z direction in all the cuboid units;
when the coordinate relation between the coordinate of the observation point and the coordinate relation of the cuboid unit is IX-i and IY-j, the relation type corresponds to the lattice function set MagneticP 1;
when the coordinate relation between the coordinate of the observation point and the coordinate relation between the coordinate of the cuboid unit is IX > i and IY is less than or equal to j, the relation type corresponds to the lattice function set MagneticP 2;
when the coordinate relation between the coordinate of the observation point and the coordinate relation between the coordinate of the cuboid unit is IX > i and IY > j, the relation type corresponds to the trellis function set MagneticP 3;
and when the coordinate relation between the coordinate of the observation point and the coordinate relation of the cuboid unit is IX & ltor & gt i and IY & gt j, the relation type corresponds to the lattice function set MagneticP 4.
S312, the trellis function in the trellis function set corresponding to the relationship type is called.
S320, repeating the step S310 until the magnetic tensor abnormality of all the cuboid units to the observation point is obtained;
S330, summing the magnetic tensor anomalies of the observation point by all the cuboid units, namely the magnetic tensor anomalies of the observation point by the whole model body.
S400, repeating the step S300 until the magnetic tensor abnormality of the whole model body to each observation point of the working area plane is obtained, namely the full tensor magnetic gradient data Bxx、Bxy、Bxz、Byy、Byz、Bzz。
Wherein the magnetic anomaly has three components Bx、By、BzObtaining full tensor magnetic gradient data B by taking derivatives in three directions of x, y and zxx、Bxy、Bxz、Byy、Byz、Bzz。
Thus, full tensor magnetic gradient data Bxx、Bxy、Bxz、Byy、Byz、Bzz：
Figure RE-GDA0002631801280000081
Figure RE-GDA0002631801280000082
Figure RE-GDA0002631801280000083
Figure RE-GDA0002631801280000084
Figure RE-GDA0002631801280000091
Figure RE-GDA0002631801280000092
Wherein, mu0Is the magnetic permeability in vacuum, M is the remanent susceptibility, μijkIs muijk＝(-1)i(-1)j(-1)kI is the inclination angle of magnetization, r is the declination angle of magnetizationijkDistance of observation point to grid point, xiSubtracting the value in the X-direction of the grid point, y, from the value in the X-direction of the observation pointjSubtracting the value in the grid point Y direction, z, from the value in the observation point Y directionkThe value in the grid point Z direction is subtracted from the value in the observation point Z direction.
By storing and calling the grid function result of the grid point to the observation point abnormity, the problem of low calculation efficiency caused by a large amount of repeated calculation in the original calculation method is solved. NX, NY and NZ are used for representing the number of cuboid units in the X direction, the Y direction and the Z direction of a model, the calculation frequency of a lattice function in the original calculation method is 4X 8. NX. NY. NZ, the calculation frequency of the lattice function in the calculation method provided by the invention is 4X (NX +1) · (NY +1) · (NZ +1), when the NX, NY and NZ in the model tend to be infinite,
Figure RE-GDA0002631801280000093
Namely, the operation speed is improved by 8 times, and the effect of fast forward performance is achieved.
Example 2
As shown in fig. 2, the computation space is divided into grids, the distance between the grids and the position of the abnormal body in the grids are determined, the unit of the upper surface of the computation space, namely the plane of the computation area, is converted into the actual mileage, and the residual magnetic susceptibility of the abnormal body is assigned. FIG. 2 is a schematic diagram of an underground subdivision unit, 51 grid nodes are arranged in the X direction of a model, 41 grid nodes are arranged in the Y direction of the model, 21 grid nodes are arranged in the Z direction of the model, an abnormal body is spread in the whole space, a magnetization inclination angle is 90 degrees, and a magnetization declination angle is 0 degree.
As shown in fig. 3, the coordinates of the observation point in the calculation area plane surface are (IX, IY), and the coordinates of the rectangular solid unit in the calculation space are (i, j, k). The observation points circulate in the plane of the calculation area, and the cuboid units circulate in the whole calculation space. P1, P2, P3 and P4 are four vertexes of the upper surface of the model body, and when P1 is taken as an observation point, the coordinate relation between the coordinates of the observation point and the rectangular solid unit is IX & lt i and IY & lt j; when P2 is taken as an observation point, the coordinate relation between the coordinates of the observation point and the coordinates of the cuboid unit is IX > i and IY is less than or equal to j; when P3 is taken as the observation point, the coordinate relation between the observation point and the rectangular solid cell is IX > i and IY > j; when P4 is taken as the observation point, the coordinate relation between the observation point and the cuboid cell is IX ≦ i and IY > j. And respectively calculating the lattice functions MagneticP1, MagneticP2, MagneticP3 and MagneticP4 of the magnetic tensor abnormality of all the lattice points to the observation points P1, P2, P3 and P4 in the model space, and then storing the lattice functions MagneticP1, MagneticP2, MagneticP3 and MagneticP4 to be called for later-stage calculation. And the magnetic tensor abnormality of each cuboid unit to the observation point in the model space is respectively equal to the magnetic tensor abnormality linear algebraic sum of the grid points where the 8 vertexes of the cuboid unit are located to the observation point. The lattice function of the cuboid unit in the model space for magnetic tensor abnormality of other observation points can be equivalent to the lattice function of magnetic tensor abnormality of 8 calculated grid points corresponding to the observation points P1, P2, P3 and P4 through translation equivalence, so that the five-dimensional calculation problem is changed into a three-dimensional calculation problem, and the calculation efficiency is greatly improved. As shown in fig. 4, the lattice function of the magnetic tensor anomaly of the grid point (1, 1, 5) to the observation point (3, 4) is the same as the lattice function of the magnetic tensor anomaly of the grid point (1, 2, 5) to the observation point (3, 5), which is the translational equivalence.
In the calculation space, each time the observation point circulates to one position, the cuboid unit traverses and circulates once in the calculation space. Every time the cuboid unit arrives at one position in the circulation, the cuboid unit has a relative position relation with an observation point, and the relative position relation has the following types: IX is less than or equal to i and IY is less than or equal to j; IX is greater than i and IY is less than or equal to j; ③ IX > i and IY > j; IX is less than or equal to i and IY is greater than j. The relative position relationship types are respectively in one-to-one correspondence with the relative position relationship types taking P1, P2, P3 and P4 as observation points in the step (2). Assuming that an observation point and a cuboid unit are respectively circulated to a certain position in a grid model, and the magnetic tensor abnormality of the cuboid unit to the observation point is calculated, firstly, the relative position relation type of the observation point and the cuboid unit is judged, then, the position parameters of the observation point and the cuboid unit are substituted into the corresponding magnetic tensor abnormality grid functions Magnetic P1, Magnetic P2, Magnetic P3 and Magnetic P4, namely, the grid functions of the 8 stored grid points to the magnetic tensor abnormality of the corresponding observation points P1, P2, P3 and P4 can be called out, and then, the algebraic summation is carried out, and the calculation result is equal to the magnetic tensor abnormality of the cuboid unit to the observation point. And summing the magnetic tensor abnormities of the observation point by all the cuboid units to obtain the magnetic tensor abnormities of the observation point by the whole model body.
When the circulation in the calculation space is completely finished, the magnetic tensor abnormity B of the whole model body to each observation point of the working area plane can be obtainedxx、Bxy、Bxz、Byy、Byz、Bzz. FIG. 5 is a diagram of magnetic tensor anomaly obtained by the original alignment algorithm for the underground grid unit model (in FIG. 5, a, B, c, d, e, and f are B respectivelyxx、Bxy、 Bxz、Byy、Byz、BzzMagnetic tensor anomaly map), fig. 6 is a magnetic tensor anomaly map obtained by a rapid positive algorithm in the underground grid unit model (a, B, c, d, e, f in fig. 6 are respectively Bxx、Bxy、Bxz、Byy、 Byz、BzzMagnetic tensor anomaly map). The computer processor used to implement the correction algorithm was Intel (R) core (TM) i5-8265U CPU @1.60GHz 1.80GHz, and the programming software was Matlab2018 a. The calculation time for the model using the prior art was 174.3283s, and the calculation time for the model using the present invention was 25.4866 s. From the calculation results, it can be seen that: the calculation result obtained by the method of the invention is consistent with the calculation result obtained by the original correction algorithm, and the calculation speed is improved by 6.8 times compared with the original correction algorithm. Therefore, the method has the advantages of higher calculation speed and higher efficiency.
Example 3
As shown in fig. 7, an electronic device (e.g., a computer server with program execution functionality) according to an exemplary embodiment of the present invention includes at least one processor, a power supply, and a memory and an input-output interface communicatively connected to the at least one processor; the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method disclosed in any one of the preceding embodiments; the input and output interface can comprise a display, a keyboard, a mouse and a USB interface and is used for inputting and outputting data; the power supply is used for supplying electric energy to the electronic equipment.
Those skilled in the art will understand that: all or part of the steps for realizing the method embodiments can be completed by hardware related to program instructions, the program can be stored in a computer readable storage medium, and the program executes the steps comprising the method embodiments when executed; and the aforementioned storage medium includes: various media that can store program codes, such as a removable Memory device, a Read Only Memory (ROM), a magnetic disk, or an optical disk.
When the integrated unit of the present invention is implemented in the form of a software functional unit and sold or used as a separate product, it may also be stored in a computer-readable storage medium. Based on such understanding, the technical solutions of the embodiments of the present invention may be essentially implemented or a part contributing to the prior art may be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the methods described in the embodiments of the present invention. And the aforementioned storage medium includes: a removable storage device, a ROM, a magnetic or optical disk, or other various media that can store program code.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents and improvements made within the spirit and principle of the present invention are intended to be included within the scope of the present invention.

Claims (8)

1. A magnetic tensor abnormal spatial domain fast alignment algorithm based on grid point lattice is characterized by comprising the following steps:
s100, establishing a model body according to the actual mileage, and dividing the model body into grids at set grid intervals, namely the model body is formed by combining a plurality of cuboid units, and the residual magnetic susceptibility of the abnormal body is correspondingly set at the position of the abnormal body in the grids;
s200, respectively calculating the lattice functions of magnetic tensor abnormity of all the grid points to observation points P1, P2, P3 and P4 in the model space, and then storing the lattice functions as a lattice function database; wherein, P1, P2, P3 and P4 are four vertexes of the upper surface of the model body;
s300, taking the grid points on the upper surface of the model body as observation points, and calculating the magnetic tensor abnormity of the whole model body to one observation point;
s310, each cuboid unit has 8 vertexes, each vertex has a relative position relation with the observation point, lattice functions corresponding to the relative position relations in a lattice function database are respectively called according to translation equivalence, and the 8 lattice functions are summed and multiplied by physical property parameters to obtain the magnetic tensor abnormity of the cuboid unit on the observation points;
S320, repeating the step S310 until the magnetic tensor abnormality of all the cuboid units to the observation point is obtained;
s330, summing the magnetic tensor abnormities of the observation point by all the cuboid units, namely determining the magnetic tensor abnormities of the observation point by the whole model body;
s400, repeating the step S300 until the magnetic tensor abnormality of the whole model body to each observation point of the working area plane is obtained, namely the full tensor magnetic gradient data Bxx、Bxy、Bxz、Byy、Byz、Bzz。
2. The algorithm of claim 1,
in step S100, the residual magnetic susceptibility of the abnormal body is: the observation data of the background field is abnormal, namely the physical property of the abnormal body is poor.
3. The algorithm of claim 2,
in the step S200, the trellis function database includes a set of magnetic functions magntic P1, magntic P2, magntic P3 and magntic P4 of magnetic tensor anomalies of all grid point pairs observation points P1, P2, P3 and P4; the coordinates of observation point P1 are (1,1), the coordinates of observation point P2 are (NX +1,1), the coordinates of observation point P3 are (NX +1, NY +1), the coordinates of observation point P4 are (1, NY +1), and NX and NY respectively represent the number of cuboid cells in the X direction and the Y direction of the model body.
4. The algorithm of claim 3,
in step S310, invoking a trellis function corresponding to the relative position relationship in the trellis function database specifically includes:
S311, judging the relative position relationship type of the observation point and the cuboid unit;
s312, the trellis function in the trellis function set corresponding to the relationship type is called.
5. The algorithm according to claim 4, wherein the step S311 specifically comprises:
the coordinates of the observation points are (IX, IY), and the observation points are the IX-th point in the X direction and the IY-th point in the Y direction in all the observation points; the coordinates of the cuboid unit are (i, j, k), which indicates that the cuboid unit is the ith block in the X direction, the jth block in the Y direction and the kth block in the Z direction in all the cuboid units;
when the coordinate relation between the coordinate of the observation point and the coordinate relation of the cuboid unit is IX-i and IY-j, the relation type corresponds to the lattice function set MagneticP 1;
when the coordinate relation between the coordinate of the observation point and the coordinate relation between the coordinate of the cuboid unit is IX > i and IY is less than or equal to j, the relation type corresponds to the lattice function set MagneticP 2;
when the coordinate relation between the coordinate of the observation point and the coordinate relation between the coordinate of the cuboid unit is IX > i and IY > j, the relation type corresponds to the trellis function set MagneticP 3;
and when the coordinate relation between the coordinate of the observation point and the coordinate relation of the cuboid unit is IX & ltor & gt i and IY & gt j, the relation type corresponds to the lattice function set MagneticP 4.
6. The algorithm of claim 5, wherein in step S400, the magnetic anomaly has three components B x、By、BzObtaining full tensor magnetic gradient data B by taking derivatives in three directions of x, y and zxx、Bxy、Bxz、Byy、Byz、Bzz。
7. The algorithm of claim 6, wherein the full tensor magnetic gradient data B in step S400xx、Bxy、Bxz、Byy、Byz、Bzz：
Figure RE-FDA0002631801270000031
Figure RE-FDA0002631801270000032
Figure RE-FDA0002631801270000033
Figure RE-FDA0002631801270000034
Figure RE-FDA0002631801270000035
Figure RE-FDA0002631801270000041
Wherein, mu0Is the magnetic permeability in vacuum, M is the remanent susceptibility, μijkIs muijk＝(-1)i(-1)j(-1)kI is the inclination angle of magnetization, r is the declination angle of magnetizationijkDistance of observation point to grid point, xiSubtracting the value in the X-direction of the grid point, y, from the value in the X-direction of the observation pointjSubtracting the value in the grid point Y direction, z, from the value in the observation point Y directionkThe value in the grid point Z direction is subtracted from the value in the observation point Z direction.
8. An electronic device comprising at least one processor, and a memory communicatively coupled to the at least one processor; the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the algorithm of any one of claims 1 to 7.
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