Accuracy Analysis of Calculation of Volume of Rock Layer Using Kriging Method

Abstract

With the construction and development of the city, it has led to the increase of various projects, and most of them have earthwork projects, such as earthwork excavation, transportation, back filling, water supply and drainage, etc. In the construction of the project, site leveling, pit excavation, roadbed filling and foundation pit back filling are the most common, and the accuracy of the prediction and calculation of stonework directly affects the work. The progress and cost of the project, so how to improve the accurate reading of the stone calculation is of great significance to the engineering economy. In order to make a decision on the construction method in the construction area, earthwork engineers must have an intuitive understanding of the distribution of underground rock strata, which requires knowing the distribution status of rock strata. The only way to understand underground rock strata is boring detection, but boring detection takes a lot of time and cost, so large-scale boring cannot be carried out, which means the calculation of rock volume. The accuracy of calculation has a great impact, so how to get accurate calculation of rock content based on limited borehole detection data is the focus of this paper. Three-dimensional spatial interpolation is an important method and approach for reconstructing geological space in three-dimensional geological modeling. Due to the limitation of geological environment and capital cost, only discrete and limited data can be obtained. Therefore, the interpolation method is of great significance for accurately reconstructing geological environment. Kriging interpolation, as an important research content of geological three-dimensional visualization, is a widely used geostatistical method to study random and correlative variables in nature. Geological environment is intricate. Geographic phenomena are random and structural. Kriging interpolation not only considers the spatial relationship between variables, but also takes into account the structural and stochastic characteristics of variables. It can fully represent the structural information of regionalized variables. In this paper, the accuracy of rock mass calculation is analyzed by means of golden interpolation combined with previous studies