CN-121788764-B - Gravity terrain correction precision constraint method, system, storage medium and product

CN121788764BCN 121788764 BCN121788764 BCN 121788764BCN-121788764-B

Abstract

The application provides a gravity terrain correction precision constraint method, a gravity terrain correction precision constraint system, a storage medium and a storage medium product, which relate to the field of electric digital data processing; the method comprises the steps of performing geometric fitting on real terrain data in each grid unit in an initial calculation grid to obtain a first physical model and a second physical model, calculating the gravity effect of each grid unit on an observation point based on the two physical models to obtain two gravity terrain correction influence values and approximation residuals corresponding to difference values of the two gravity terrain correction influence values, performing refinement segmentation on the grid units when the approximation residuals exceed a preset precision threshold, and performing refinement segmentation again on each generated new calculation grid until the new approximation residuals do not exceed the preset precision threshold. The method can improve the overall calculation efficiency on the premise of ensuring the overall calculation accuracy, thereby solving the problem of calculation redundancy of the traditional uniform grid method.

Inventors

CHEN TING
CHEN JUN
ZHANG JIHUA
HAN LEI
YANG DAIBIN
ZHANG OU
PANG YOUWEI
PENG ZHONGYI
FENG HUAPENG
LIU PENG
QIANG YU
Yue Yunbao
TIAN MAOXIANG
WU BIN
YAN DI
ZOU JUN
CHEN NING
YU ZHOU
HUANG JIAN
Wei Guojiao

Assignees

四川省地球物理调查研究所

Dates

Publication Date: 20260512
Application Date: 20260304

Claims (8)

1. A gravity terrain correction accuracy constraint method applied to a gravity terrain correction accuracy constraint system, the method comprising: Generating a non-uniform initial calculation grid according to local terrain complexity of a digital elevation model, wherein the digital elevation model is obtained by fusing terrain elevation data with at least two different resolutions, and the size of the initial calculation grid is inversely related to the corresponding local terrain complexity; performing geometric fitting on the real terrain data in each grid unit in the initial calculation grid to obtain a parameterized first physical model and a parameterized second physical model, wherein the first physical model and the second physical model are different in complexity in the same grid unit; The method comprises the steps of obtaining sampling point data of a digital elevation model in a coverage area of each grid unit, simplifying the topography in the grid unit into a flat-top prism with uniform height according to the sampling point data to obtain a first physical model, wherein the height value of the flat-top prism is an arithmetic average value of the elevation value of the sampling point; Calculating the gravity effect of each grid unit on the observation point based on the first physical model and the second physical model respectively to obtain a first gravity topography correction influence value and a second gravity topography correction influence value; The step of calculating the gravity effect of each grid unit on the observation point based on the first physical model and the second physical model respectively to obtain a first gravity topography correction influence value and a second gravity topography correction influence value comprises the steps of dividing a calculation area into a near area, a middle area, a far area and a far area according to the distance between the grid unit and the observation point; for grid units of a near zone, a middle zone and a far zone, respectively calculating gravity terrain correction influence values based on the first physical model and the second physical model by adopting a high-precision integral algorithm, wherein the gravity terrain correction influence values comprise a first gravity terrain correction influence value and a second gravity terrain correction influence value; Calculating to obtain an approximation residual error of a physical model according to the difference value of the first gravity terrain correction influence value and the second gravity terrain correction influence value; when the approximation degree residual error exceeds a preset precision threshold, carrying out refinement and segmentation on the grid units to generate a plurality of new calculation grids; Repeating the steps of geometric fitting, gravity effect calculation, approximation residual and refinement segmentation on each new calculation grid until the approximation residual corresponding to all grid units does not exceed the preset precision threshold.
2. The method according to claim 1, wherein the step of generating a plurality of new computational grids by performing a refined segmentation of the grid cells comprises: If the current subdivision level corresponding to the grid unit is smaller than a preset maximum subdivision level, cutting the grid unit into four sub-grid units with the same geometric shape and equal area, wherein the maximum subdivision level is set according to the precision of the digital elevation model; determining the sub-grid unit as a new calculation grid, and updating the current subdivision level corresponding to the new calculation grid; and if the current subdivision level corresponding to the grid unit is greater than or equal to the preset maximum subdivision level, marking the grid unit as an accuracy non-convergence unit, and terminating further segmentation of the accuracy non-convergence unit.
3. The method of claim 1, further comprising, after the step of calculating an approximation residual of the physical model from the difference between the first and second gravity terrain correction influencing values: When the approximation degree residual error does not exceed a preset precision threshold value and accords with a preset refinement condition, temporarily dividing the current grid unit into four sub-grid units to form a sub-grid unit set; Calculating a gravity effect value of an observation point corresponding to each sub-grid unit based on a first physical model corresponding to each sub-grid unit, wherein the calculation mode of the gravity effect value is the same as that of the first gravity topography correction influence value; When the difference value between the sum of the gravity effect values and the first gravity topography correction influence value is larger than a preset verification threshold value, marking a sub-grid unit corresponding to a target gravity effect value, wherein the difference value between the average value of the gravity effect values exceeds the preset difference value threshold value, as a unit to be thinned; And when the difference value between the sum of the gravity effect values and the first gravity topography correction influence value is smaller than or equal to a preset verification threshold value, further segmentation of the current grid cell is terminated.
4. A method according to claim 3, wherein the step of meeting a preset refinement condition specifically comprises: Calculating a roughness index of the terrain elevation data in the grid unit, wherein the roughness index is determined according to the standard deviation of the terrain elevation data; when the roughness index is smaller than a preset roughness threshold, judging that the grid cells do not accord with preset refinement conditions; And when the roughness index is not smaller than the roughness threshold, judging that the grid cells accord with a preset refinement condition.
5. The method of claim 1, further comprising, after repeating the steps of performing the geometric fit, the gravity effect calculation, the approximation residuals, and the refined segmentation for each of the new calculation grids until all of the grid cell corresponding approximation residuals do not exceed the predetermined precision threshold: Summarizing the gravity topography correction influence values respectively corresponding to all grid units meeting a preset precision threshold value to generate a correction influence value matrix of the global topography, wherein the correction influence value matrix is a final gravity topography correction result covering the whole calculation area; Generating a standardized terrain correction data file based on the correction impact value matrix, wherein the standardized terrain correction data file is an output file conforming to GIS or geophysical software data format specifications; And generating a precision certificate report according to the correction impact value matrix and the final unit grid distribution condition, wherein the precision certificate report comprises a non-uniform grid distribution diagram showing grid density differences of different areas, a precision thermodynamic diagram representing calculation error magnitudes of the different areas and key performance indexes.
6. A gravity terrain correction accuracy constraint system, comprising one or more processors and memory; The memory is coupled to the one or more processors, the memory for storing computer program code comprising computer instructions that the one or more processors invoke to cause the system to perform the method of any of claims 1-5.
7. A computer readable storage medium comprising instructions which, when run on a gravity terrain correction precision constraint system, cause the system to perform the method of any of claims 1-5.
8. A computer program product which, when run on a gravity terrain correction precision constraint system, causes the system to perform the method of any of claims 1-5.

Description

Gravity terrain correction precision constraint method, system, storage medium and product Technical Field The application relates to the field of electric digital data processing, in particular to a gravity topography correction precision constraint method, a gravity topography correction precision constraint system, a storage medium and a gravity topography correction precision constraint product. Background In the fields of geophysical exploration, geodetic surveying, national basic mapping and the like, high-precision gravity data are the basis for performing geological structure interpretation, resource exploration and geodetic refinement. However, the gravity value directly observed on the ground is a result of the comprehensive influence of various factors such as the distribution of substances in the earth, the rotation of the earth, and the quality of the terrain between the observation point and the reference ellipsoid. Among these, the effect of terrain quality on the gravitational observations, i.e., the gravitational terrain effect, is an important correction that must be accurately subtracted. Therefore, the high-precision gravity topography correction is very important to extract effective gravity signals reflecting the underground density structural abnormality. In the related art, a mesh division calculation method based on a digital elevation model (Digital Elevation Model, DEM) is generally adopted. In particular, the method divides DEM data covered by the entire region into regular and uniform rectangular grids. For each grid cell, the complex topography of its interior is reduced to a regular geometry, e.g., typically approximated as a flat-topped rectangular prism of defined height. The height of the prism is typically determined by taking the average or center point elevation value of all DEM elevation points within the grid cell. Then, the gravity influence of the prism at the appointed gravity observation point is calculated, and the gravity influence of all grid cells in the whole area is integrated and summed to finally obtain the total gravity topography correction value. In order to ensure computational accuracy, this approach tends to generally employ as fine, uniform resolution grids throughout the entire region as possible in order to more closely approximate the real terrain. However, in order to ensure the overall accuracy of the final calculation, the choice of the resolution of the mesh is generally based on being able to accurately describe the most complex terrain, the most intense areas of relief (e.g. steep ridges or deep canyons) within the region. This is because if the meshing in these critical areas is too coarse, it will result in a large terrain model approximation error, severely affecting the reliability of the overall correction result. However, since the technical solution adopts a uniform grid, the high-resolution grid meeting the precision requirement of the local complex area is applied to the whole area without difference, so that the method also performs high-intensity calculation with the same density as that of the complex area in a wide area (such as plain and basin) with relatively flat and gentle terrain. In these flat areas, the same precision requirement can be achieved by using a grid far thinner than the current grid, so that the implementation of adopting the uniform fine grid in the related art causes a great deal of computing resources to be wasted on unnecessary redundant computation, thereby reducing the comprehensive efficiency of the whole computing process. Disclosure of Invention The application provides a gravity terrain correction precision constraint method, a gravity terrain correction precision constraint system, a storage medium and a storage product, which are used for solving the problem that the overall calculation efficiency is low due to the fact that the precision requirement of a local complex area needs to be met in a mode of adopting uniform fine grids in the related technology. In a first aspect, the present application provides a gravity terrain correction accuracy constraint method, applied to a gravity terrain correction accuracy constraint system, the method comprising: Generating a non-uniform initial calculation grid according to local terrain complexity of a digital elevation model, wherein the digital elevation model is obtained by fusing terrain elevation data with at least two different resolutions, and the size of the initial calculation grid is inversely related to the corresponding local terrain complexity; performing geometric fitting on the real terrain data in each grid unit in the initial calculation grid to obtain a parameterized first physical model and a parameterized second physical model, wherein the first physical model and the second physical model are different in complexity in the same grid unit; Calculating the gravity effect of each grid unit on the observation point based on the first physic