scholarly journals In Situ Stress Inversion and Distribution Characteristics of Tunnel Based on Numerical Simulation and Neural Network Technology

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Pei Zhang
Keyword(s):  
Neural Network ◽  
Numerical Simulation ◽  
Boundary Condition ◽  
Surface Characteristics ◽  
In Situ Stress ◽  
Target Area ◽  
Variable Boundary ◽  
Geological Conditions ◽  
Stress Boundary Conditions

According to the geological conditions of the study area, the measured data of in situ stress was analyzed and the influence degree of buried depth was obtained. A numerical simulation research model with full consideration of fault structure and surface characteristics is established, and boundary condition functions with variables are used. The neural network optimized by genetic algorithm is used to establish the nonlinear relationship between the measured value and the simulated value of the variable boundary condition, and the optimal boundary condition function is obtained. Finally, the in situ stress in the study area was predicted. Through the analysis of the in situ stress field in the research target area, the stress boundary conditions are provided for the follow-up study, and the practical basis for the division of the dangerous area of the surrounding rock of the deep and long tunnel is provided.

Inverse Analysis of Regional In Situ Stress Prediction Based on Multi-Points Measurement and BP Neural Network

2014 ◽  
Vol 510 ◽  
pp. 226-231 ◽  
Author(s):  
Wei Qun Liu ◽  
Ting Song ◽  
Yu Shou Li ◽  
Shu Fei Zheng ◽  
Jing Yang
Keyword(s):  
Neural Network ◽  
Stress Field ◽  
In Situ Stress ◽  
Engineering Problem ◽  
Regional Stress ◽  
Geological Conditions ◽  
Stress Prediction ◽  
Stress Estimation ◽  
In Situ Stress Field

Based on the measurement of in-situ stress and engineering-geological conditions, we built computing models with pre-exerting boundary loads and simulated the regional stress field involved. Boundary loads can be approximately determined by use of the multiple linear regressions, and be further optimized with the artificial neural network. By calculation, the corresponding initial in-situ stress field can reach ideal accuracy. As an example, we inversely analyzed an engineering problem in Chinese Wo-bei mine. The results shows that the simulation can meet the point measurement very well, and the regional-stress estimation may play an important role in engineering.

scholarly journals Effect of Advancing Direction of Working Face on Mining Stress Distribution in Deep Coal Mine

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Yuesong Tang ◽  
Wenchao Sun ◽  
Xin Zhang ◽  
Pengju Liu
Keyword(s):  
Stress Distribution ◽  
Large Scale ◽  
In Situ Stress ◽  
Deep Mining ◽  
Deep Coal Mine ◽  
Working Face ◽  
Geological Conditions ◽  
Original Rock ◽  
High Level

Deep mining has become the normal state of coal mining; compared with the mine with shallow buried depth, the consequent high level of in situ stress and complex distribution have brought severe threats to the stability of the stope and the surrounding rock of the roadway. In this research, taking the 121304 working face of Kouzidong Mine as the engineering background, the characteristics of mining-induced stress distribution under complex in situ stress environment in deep mining are analyzed by using on-site measurement of the original rock stress and mining stress, establishing a theoretical model centered on the middle section of the working face, and establishing large-scale numerical calculation models for different advancing directions. It was found that under deep mining conditions, the maximum stress of the original rock is 25.12 MPa, and the direction is vertical. The advanced influence range of mining stress is about 150 m, and the abutment pressure presents a three-peak distribution characteristic in front of the working face. The research results provide important theoretical guiding value for guiding the mining of coal mines with similar geological conditions.

scholarly journals Numerical Simulation of Temporal and Spatial Evolution of Stress Field in Unconsolidated Sandstone Oil Reservoir

2021 ◽  
Vol 2095 (1) ◽  
pp. 012095
Author(s):  
Guihong Pei ◽  
Jiecheng Song ◽  
Xiaolong Zhang
Keyword(s):  
Numerical Simulation ◽  
Stress Field ◽  
Geological Structure ◽  
In Situ Stress ◽  
Prevention Measures ◽  
Casing Damage ◽  
In Situ Stress Field ◽  
Oilfield Development ◽  
Damage Prevention

Abstract Casing damage in the process of oilfield development is a serious problem, which is affected by geological structure, production technology and many other factors. To prevent casing damage, it is necessary to master the space-time evolution law of reservoir in-situ stress field, to provide support for casing damage prevention. Based on the perseage-stress coupling theory, taking the actual reservoir block as the research object, the change law of the in-situ stress field in unconsolidated sandstone reservoir is obtained through the fluid-solid coupling numerical simulation of the reservoir, and the internal correlation between the stress field and casing damage is analysed. The research results provide theoretical guidance for the formulation of casing damage prevention measures in the research block.

Reservoir Pressure of Coal-Bed Methane Prediction Research Based on Analysis Method by Neural Net-Work

2013 ◽  
Vol 756-759 ◽  
pp. 4758-4762
Author(s):  
Xing Peng Jing
Keyword(s):  
Neural Network ◽  
In Situ Stress ◽  
Coal Bed ◽  
Coal Bed Methane ◽  
Neural Net ◽  
Reservoir Pressure ◽  
Neural Network Prediction ◽  
Quantitative Results ◽  
Network Prediction

In Order to Achieve Accurate Quantitative Results of Parameters for Reservoir Pressure of Coal-Bed Methane, Neural Network Prediction Analytic Method is Adopted to Predict the Reservoir Pressure of Coal-Bed Methane. the Main Controlling Factors such as Conformation Stress, Buried Depth, in-Situ Stress and Permeability are Investigated. Mathematical Models of Neural Network of Reservoir Pressure of Coal-Bed Methane of Mathematical Analysis and System Architecture are Established; Taking the Qinshui Basin Coal Seam as Example to Forecast and use Reservoir Pressure of Coal-Bed Methane. Projections Show that: the use of Neural Network Prediction of Reservoir Pressure of Coal-Bed Methane is Feasible; Neural Network Method Makes up a Mathematical Point of Linear and Regularity in Order to Solve the Non-Linear Complex Relationship between the Input and Output Parameter Variables.

Application of Comprehensive Reinforce Technology in Soft and Crumbly Surrounding Rock in High Stress

2011 ◽  
Vol 393-395 ◽  
pp. 608-613
Author(s):  
Bing Shen Du ◽  
Li Ma
Keyword(s):  
High Stress ◽  
Engineering Application ◽  
Strengthening Mechanism ◽  
In Situ Stress ◽  
Surrounding Rock ◽  
Strengthening Effect ◽  
Geological Conditions

Based on soft and crumbly surrounding rock of roadway, poor integrity of roof, drench water in roadway, the large in-situ stress and other complex conditions, this paper analyzes the cause of roadway destruction and grouting strengthening mechanism, using the coupling of grouting technique to integrated strengthening for the region. Engineering application shows that the integrated strengthening effect is obvious, and the economic and technique effectiveness is remarkable. The successful application of secondary coupling grouting technology provides the reference for the mine laneway construction of similar geological conditions.

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