Advanced Geological Prediction

Due to the particularity of the tunnel project, it is difficult to find out the exact geological conditions of the tunnel body during the survey stage. Once it encounters unfavorable geological bodies such as faults, fracture zones, and karst, it will bring great challenges to the construction and will easily cause major problems, economic losses, and casualties. Therefore, it is necessary to carry out geological forecast work in the tunnel construction process, which is of great significance for tunnel safety construction and avoiding major disaster accident losses. This lecture mainly introduces the commonly used methods of geological forecast in tunnel construction, the design principles, and contents of geological forecast and combines typical cases to show the implementation process of comprehensive geological forecast. Finally, the development direction of geological forecast theory, method, and technology is carried out. Prospects provide a useful reference for promoting the development of geological forecast of tunnels

Web-based Visualisation for Look-Ahead Ground Imaging in Tunnel Boring Machines

Tunnel Boring Machines (TBMs) are large multi-million pound machines used to excavate underground tunnels. In order to make best use of the high-speed performance of a TBM and guarantee the safety of excavation, it is important to know the local geology, structures and ground properties ahead of the TBM cutter head, especially in complex geological conditions (e.g. karst caves). By working with experienced geophysical experts, tunnelling engineers/consultants and TBM manufacturers, we propose a novel web-based visualisation platform to help TBM operators efficiently manage, process and visualise the TBM parameters, the geology map created by geo-experts based on boreholes, and especially the imaging data captured by an on-board ground imaging system for "seeing through" the ground beyond the excavation surface. Informative visualisation interfaces were designed to facilitate interpretation of the imaging data and adding annotation by users; algorithms were developed for automatic detection of features and probable events by fusion of radar and seismic imaging data; and a back-end database was designed to store all such relevant information for supporting more advanced interpretation in the future. The web-based architecture not only allows the visualisation platform to be directly linked to on-board sensors (e.g. ground penetrating radars, seismic sensors), but also allows users away from the job site to access the captured data using a standard web browser, enabling a collaborative interpretation process. The data processing, management and visualisation platform presented in this paper is flexible with respect to different imaging sensors and modalities, so it is highly adaptable for any other ground imaging systems for tunnel geology inspection, underground utility surveys, etc

Tunnel Engineering

This volume presents a selection of chapters covering a wide range of tunneling engineering topics. The scope was to present reviews of established methods and new approaches in construction practice and in digital technology tools like building information modeling. The book is divided in four sections dealing with geological aspects of tunneling, analysis and design, new challenges in tunnel construction, and tunneling in the digital era. Topics from site investigation and rock mass failure mechanisms, analysis and design approaches, and innovations in tunnel construction through digital tools are covered in 10 chapters. The references provided will be useful for further reading

Physics-driven Deep Learning Inversion for Direct Current Resistivity Survey Data

The direct-current (DC) resistivity method is a commonly used geophysical technique for surveying adverse geological conditions. Inversion can reconstruct the resistivity model from data, which is an important step in the geophysical survey. However, the inverse problem is a serious ill-posed problem that makes it easy to obtain incorrect inversion results. Deep learning (DL) provides new avenues for solving inverse problems, and has been widely studied. Currently, most DL inversion methods for resistivity are purely data-driven and depend heavily on labels (real resistivity models). However, real resistivity models are difficult to obtain through field surveys. An inversion network may not be effectively trained without labels. In this study, we built an unsupervised learning resistivity inversion scheme based on the physical law of electric field propagation. First, a forward modeling process was embedded into the network training, which converted the predicted model to predicted data and formed a data misfit to the observation data. Unsupervised training independent of the real model was realized using the data misfit as a loss function. Moreover, a dynamic smoothing constraint was imposed on the loss function to alleviate the ill-posed inverse problem. Finally, a transfer learning scheme was applied to adapt the trained network with simulated data to field data. Numerical simulations and field tests showed that the proposed method can accurately locate and depict geological targets

Seismic prediction and imaging of geological structures ahead of a tunnel using surface waves

To improve the performance and safety of tunnel constructions, we introduce a new seismic prediction method utilizing tunnel surface waves to detect relevant geological structures ahead of the tunnel face. On the basis of both synthetic and field data, we investigate the propagation characteristics of such surface waves propagating along the tunnel wall. We further introduce a simple but robust automatic prediction scheme that can estimate the distance to a reflector ahead of the tunnel

Geophysical and television logging trials in horizontal boreholes for probing ahead of tunnels

Imperial Users onl

Assessing load transfer mechanism in CMC-supported embankments adopting Timoshenko beam theory

© The authors and ICE Publishing: All rights reserved, 2015. Controlled modulus columns (CMC) supported embankments are increasingly being used for construction of major highway embankments on expansive soils particularly near waterways or coastal regions. CMC is a faster, sustainable and economical ground improvement technology that stiffens the poor soil and transmits the load from the traffic to a lower bearing stratum. The key influencing elements of the load transfer mechanism include embankment fill, load transfer platform (LTP), CMC and the underlying soils. Use of LTP enhances the load distribution mechanism in the CMC improved soft ground and minimises the post construction settlement of the ground. In this paper, reinforced Timoshenko beam theory is introduced to simulate the LTP with one layer of geosynthetics resting on CMC improved soft soil. A parametric study is conducted to investigate the importance of the height of the embankment on the maximum settlement of the LTP, tension developed in the geosynthetics and stress concentration ratio (the ratio of the stresses acting on CMC and soft soils) for the CMC supported embankments. Special attention is given to the stiffness of soft soil and shear stiffness of the geosynthetic layer. It has been observed that height of the embankment, the stiffness of the soft soil and the shear stiffness of the geosynthetics significantly influence the maximum settlement of the LTP and the stress concentration ratio

Diffraction Characteristics of Small Fault ahead of tunnel face in coal roadway

Small fault ahead of the tunnel face in coal roadway is the important hidden hazard factor of coal and gas outburst accidents. The study of small fault prediction has important practical significance, which is the urgent demand of coal mine safety production. The diffraction of breakpoint can be used to identify the fault. However, unlike surface seismic exploration, the diffraction is with approximately horizontal incidence when the advanced detection is carried out in the roadway. The common advanced detection system is mainly as the reference of traffic tunnel, without considering the influence of low-velocity coal seam. Considering the influence of an acoustic wave of the roadway cavity and channel wave of the coal seam, the advanced detection model of small fault ahead of tunnel face is established. Diffraction advanced observation system in which sources located in front of tunnel face is constructed, and the numerical calculation of the high-order staggered-grid finite difference is carried out. The simulation results show that: Compared with the data collected by reflection observation system, in seismic records acquired by diffraction observation system, the suppression effect of acoustic wave is appeared. The diffracted P-wave of the breakpoint of component X is clear with strong energy and short-wave group. Multiple diffractions of the breakpoint are not found, but the multiple diffraction of tunnel face endpoint is obvious. The difference between breakpoint diffraction and multiple diffractions of the endpoint is clear, and diffracted P-wave of the breakpoint is easy to identify. The multiple reflected channel wave between the fault and the tunnel face is very obvious, and the reflected channel wave of small fault is so hard to identify. Migration results show that the imaging resolution of diffracted P-wave of small fault is higher than the reflected channel wave, and breakpoint location of imaging is consistent with the actual model.El frente de una falla pequeña sobre un manto de carbón en el socavón de un túnel es un factor importante no visible debido a los accidentes por explosión en minas de gas y carbón. El estudio de la predicción de falla pequeña tiene un importante sentido práctico: la demanda urgente de seguridad en la producción carbonífera. El punto de quiebre de la difracción puede utilizarse para identificar la falla. Sin embargo, al contrario que la exploración sísmica superficial, la difracción se acerca a la prevalencia horizontal cuando se realiza la detección avanzada en el socavón. El sistema común de detección avanzada se usa principalmente para referenciar el tráfico del túnel, sin considerar la influencia de la baja velocidad en la veta de carbón. Al valorar la respuesta de la onda acústica en la cavidad del socavón y la onda de canal de la veta de carbón se establece el modelo de detección avanzada de pequeña falla para el socavón del túnel. Se construyó el sistema de observación avanzada de difracción en el cual las fuentes se localizan en frente de la cara del túnel y se realizó el cálculo de diferencia finita en una red escalonada de orden alto. Los resultados del modelo muestran que a diferencia de la información recolectada con el sistema de observación de reflexión, en los registros sísmicos adquiridos con el sistema de observación de difracción se puede ver el efecto de supresión de la onda acústica. El punto de quiebre de la onda P difractada para el componente X es claro, con energía fuerte y en el grupo de onda corta. No se encontró el punto de quiebre para difracciones múltiples pero es evidente la difracción múltiple para el punto final de la cara del túnel. Es clara la diferencia entre el punto de ruptura de la difracción y las difracciones múltiples del punto final, mientras el punto de ruptura de la onda P difractada es fácil de identificar. Los resultados de migración muestran que la resolución de imágenes de la onda P difractada de falla pequeña es mayor que la onda de canal reflejada y la ubicación del punto de quiebre de la imagen es consistente con el modelo actual

Eliminate P-wave Direction in Application of Exploration Seismology

Exploration seismology has substantially contributed to finding and developing giant field worldwide. The technology has evolved in single to two, three dimensional methods, and later added a fourth dimension for reservoir monitoring [1]. In land seismic acquisition, a variety of innovative single, three or multiple geophone has been developed by some manufacturer. In this project, the experiment will demonstrate numerous applications for single component geophone (SM – 24) using different composition of sand and rock proportion. The source vibration will generate by a geophone (SM-24) which supplied external frequency from the function generator. The resulting output by single component geophone only provides the output voltage of the propagating elastic wave in one directio