US 11,733,426 B1
Multi-scale three-dimensional (3D) engineering geological model construction system and method
Bowen Zheng, Beijing (CN); Shengwen Qi, Beijing (CN); Zhendong Cui, Beijing (CN); Rixiang Zhu, Beijing (CN); Bo Wan, Beijing (CN); Wang Zhang, Beijing (CN); Yongchao Li, Beijing (CN); Songfeng Guo, Beijing (CN); Tianming Huang, Beijing (CN); Haijun Zhao, Beijing (CN); Zan Wang, Beijing (CN); Yan Zhang, Beijing (CN); Yanlong Kong, Beijing (CN); Lina Ma, Beijing (CN); Xiaokun Hou, Beijing (CN); Wei Lu, Beijing (CN); Lei Fu, Beijing (CN); and Pingchuan Dong, Beijing (CN)
Assigned to INSTITUTE OF GEOLOGY AND GEOPHYSICS, CAS, Beijing (CN)
Filed by INSTITUTE OF GEOLOGY AND GEOPHYSICS, CAS, Beijing (CN)
Filed on Feb. 27, 2023, as Appl. No. 18/174,953.
Claims priority of application No. 202210934929.6 (CN), filed on Aug. 5, 2022.
Int. Cl. G01V 99/00 (2009.01); G01V 1/50 (2006.01)
CPC G01V 99/005 (2013.01) [G01V 1/50 (2013.01)] 6 Claims
OG exemplary drawing
 
1. A multi-scale three-dimensional (3D) engineering geological model construction system comprising at least one processor, wherein the multi-scale 3D engineering geological model construction system is configured to construct a multi-scale 3D engineering geological fusion model of a target region, the target region comprises multiple engineering sites, and each of the engineering sites comprises multiple drilling wells; and
the multi-scale 3D engineering geological model construction system comprises:
a regional geological model construction module implemented by the at least one processor and configured to construct a regional geological model of the target region according to a multi-resolution remote sensing image and a digital elevation model (DEM) of the target region, wherein the regional geological model is a 3D engineering geological model at a regional mountain scale;
a site geological model construction module implemented by the at least one processor and configured to construct a site geological model of the engineering site in the target region according to topographic information and stratigraphic lithologic information of the engineering site, wherein the site geological model is a 3D engineering geological model at an engineering site scale;
a drilling geological model construction module implemented by the at least one processor and configured to construct a drilling geological model of the drilling well in the target region according to parameters of a core sample and a cuttings sample taken from the drilling well, wherein the drilling geological model is a 3D engineering geological model at a drilling scale;
a drilling-site model fusion module implemented by the at least one processor and configured to superimpose drilling geological models spatially located in a same engineering site to the site geological model of the engineering site to obtain a drilling-site geological fusion model of the engineering site; and
a site-region model fusion module implemented by the at least one processor and configured to superimpose the drilling-site geological fusion models of the engineering sites to the regional geological model of the target region to obtain the multi-scale 3D engineering geological fusion model of the target region;
a prediction model establishment module implemented by the at least one processor and configured to establish a drilling geological data prediction model for predicting parameters of the drilling geological model and an engineering site geological data prediction model for predicting parameters of the site geological model based on a neural network algorithm;
a drilling geological training set establishment implemented by the at least one processor and module configured to establish a drilling geological training set for training the drilling geological data prediction model, wherein the drilling geological training set comprises parameters of respective core samples and cuttings samples of the multiple drilling wells and parameters of drilling geological models corresponding to the drilling wells;
a drilling geological data prediction model training module implemented by the at least one processor and configured to train the drilling geological data prediction model using the drilling geological training set by taking the parameters of the core sample and the cuttings sample of the drilling well as an input and the parameters of the drilling geological model corresponding to the drilling well as a target output to obtain a well trained drilling geological data prediction model;
an engineering site geological training set establishment module implemented by the at least one processor and configured to establish an engineering site geological training set for training the engineering site geological data prediction model, wherein the engineering site geological training set comprises respective topographic information and stratigraphic lithologic information of the multiple engineering sites and parameters of site geological models corresponding to the engineering sites; and
an engineering site geological data prediction model training module implemented by the at least one processor and configured to train the engineering site geological data prediction model using the engineering site geological training set by taking the topographic information and the stratigraphic lithologic information of the engineering site as an input and the parameters of the site geological model corresponding to the engineering site as a target output to obtain a well trained engineering site geological data prediction model.