Three-dimensional geological curved surface reconstruction method based on large scale earthquake data

Abstract

The invention provides a three-dimensional geological curved surface reconstruction method based on large-scale seismic data. The method includes the following steps: firstly perform terrain block segmentation of large-scale seismic data, specifically including dividing horizon data and geological constraint polygon data into different terrain blocks and saving them in external memory; and then taking each terrain block as the basis The unit performs surface reconstruction, and the surface reconstruction step includes: reading the horizon data and geological constraint polygon data inside the terrain block from the external storage under the corresponding path, and then constructing the initial grid in the terrain block, and in each initial grid Constrained Delaunay triangulation and 3D space triangulation restoration are carried out in the grid to obtain 3D topology, and finally surface interpolation is performed on the points on the 3D topology to obtain 3D geological surface. The invention proposes a new curved surface reconstruction method aiming at the situation of large amount of data, and effectively utilizes limited memory to complete the processing of massive data.

Description

technical field [0001] The invention relates to the technical field of geological exploration, more specifically, to a curved surface reconstruction method for massive exploration data generated in a large-scale construction area. Background technique [0002] In the field of 3D geological modeling, surface reconstruction, 3D visualization, and even human-computer interaction operations for 3D large-scale massive seismic data have become routine and necessary industrial needs. However, it is difficult to perform surface reconstruction on large-scale seismic data. One of the reasons is that the amount of original data is too large and the data range is too wide. Under the existing conditions, the hardware conditions of an ordinary PC are limited, especially in terms of memory, generally speaking, there are only a few GB to a dozen GB. For large-scale seismic exploration data, the original data generally has GB level. There will also be a large amount of intermediate data, so...

AI Technical Summary

Problems solved by technology

However, it is difficult to perform surface reconstruction on large-scale seismic data, one of the reasons is that the amount of original data is too large and the data range is too wide

Under the existing conditions, the hardware conditions of an ordinary PC are limited, especially in terms of memory, which generally only has a few GB to a dozen GB. For large-scale seismic exploration data, the original data generally has GB level. There will also be a large amount of intermediate data, so it is difficult to put all the large-scale seismic survey data into the computer memory at the same time for surface reconstruction

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