The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Aug. 11, 2026

Filed:

Aug. 04, 2022
Applicant:

Shandong University, Jinan, CN;

Inventors:

Zhenhao Xu, Jinan, CN;

Peng Lin, Jinan, CN;

Shucai Li, Jinan, CN;

Huihui Xie, Jinan, CN;

Heng Shi, Jinan, CN;

Zhaoyang Wang, Jinan, CN;

Fumin Liu, Jinan, CN;

Ruiqi Shao, Jinan, CN;

Assignee:

SHANDONG UNIVERSITY, Jinan, CN;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
E21B 49/00 (2006.01); E21D 9/00 (2006.01); G06F 30/27 (2020.01);
U.S. Cl.
CPC ...
E21B 49/003 (2013.01); E21B 49/005 (2013.01); E21D 9/003 (2013.01); G06F 30/27 (2020.01); E21B 2200/20 (2020.05);
Abstract

An advanced geological prediction method and system based on perception while drilling, and relates to advanced geological prediction. The solution includes: acquiring drilling parameters during drilling; obtaining physical and mechanical parameters of tunnel surrounding rocks by inversion based on drilling parameters; acquiring rock slag or powder based on flushing fluid collected during drilling; acquiring geochemical characteristic parameters of rock slag or powder; and obtaining at least one adverse geology recognition result and surrounding rock classification result using a pre-trained deep learning model, and realizing advanced geological prediction. Combined with advanced geological drilling, the solution reflects geological characteristics from changes of physical and mechanical properties of tunnel surrounding rocks and changes of geochemical characteristic parameters. Advanced prediction of geology ahead of a tunnel face is realized by collection and analysis of drilling parameters and flushing fluid during advanced drilling and the fusion of big data and a deep learning algorithm.


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