Exploration on the construction of a transparent 3D geological environment in underground coal mine

WEN Guangchao; WANG Yibo; FENG Yajie; ZHOU Yanbin; ZHANG Yifan; ZHAO Mengyu

doi:10.16186/j.cnki.1673-9787.2024110013

Abstract：Objectives In order to promote the construction of intelligent mines,ensure the visibility,pre-dictability,and controllability of excavation conditions,and achieve safe and accurate coal mining,Meth-ods this study was carried out from three aspects,3D modeling and visualization of geological elements un-derground in coal mines,fault identification and visualization,and visualization of roadway engineering-based on relevant data such as from mine drilling,geophysical exploration,surveying,and observation.It took geology and geostatistics as the basis,consided the characteristics of geological elements underground in coal mines,and comprehensively used technical methods such as data standardization,3D modeling,vi-sualization expression,and statistical analysis.The study aimed to establish a mine geological big data cen-ter,design a real-time visualization construction plan for transparent underground geological conditions,and develop a dynamic 3D geological model to achieve transparency of key geological bodies and coal min-ing faces.It presented a novel methodology for detecting concealed minor faults by integrating borehole,topographic,geological profiles,tunnels and other data.A small fault identification model was developed to facilitate automatic fault recognition and 3D visualization of small faults.A self-developed 3D visualization platform for mine geological environments was constructed,and case studies were conducted to validate the aforementioned achievements.Results The results showed that the 3D visualization of geological elements has a good agreement with the actual exposure situation,which can reflect the spatial distribution character-istics of rock layers,coal seams,and faults,and achieve real-time dynamic updates of the geological envi-ronment underground in coal mines,and can accurately identify small faults below 3 m.Conclusions The research results can provide technical support for coal mine safety production.