@article{Wang2025, 
author = {Peirui Wang and Fei Zheng and Xuefeng An and Zhi Li},
title = {Borehole Construction Method Based on Iterative Interpolation and Constraint Correction and Its Application},
year = {2025},
journal = {Chinese Journal of Underground Space and Engineering},
volume = {21},
number = {S1},
pages = {60-66},
keywords = {virtual borehole, iterated interpolation, multi-source data correction, 3D modelling},
url = {https://www.sciopen.com/article/10.20174/j.JUSE.2025.S1.08},
doi = {10.20174/j.JUSE.2025.S1.08},
abstract = {The borehole interpolation modeling method is widely used in 3D modeling of underground space engineering scenarios due to its characteristics of process automation and rapid model updates. However, the sparse and missing original borehole data limit the accuracy of modeling, and other geological data is difficult to effectively utilize. A virtual borehole automation construction method based on iterative interpolation and constraint correction is proposed to address the above issues, which considers the uniformity of data space distribution, effective constraints of non-borehole data, and the compounding of interpolation data, to obtain higher quality virtual borehole data and improve modeling accuracy. Firstly, a triangulation encryption method is proposed for obtaining uniformly distributed virtual borehole positions, which is characterized by borehole encryption coefficients; Secondly, a search and iterative interpolation algorithm is proposed to obtain virtual borehole layering information, and a multi-source data constraint correction criterion and outlier removal correction criterion are introduced to optimize the iterative algorithm; Meanwhile, a model accuracy evaluation method based on weighted average representation was proposed. Based on the geological data of the Yan’an Formation in Yingpanhao Coal Mine, the proposed method was used for modeling verification. The results showed that “iterative interpolation” and “constraint correction” reduced the layer thickness error, layer thickness relative error, and burial depth error of the model by “3.12 m, 1.39%, 1.09 m” and “0.42 m, 0.19%, 0.41 m”, respectively.}
}