Complicated Geological Environment Research Articles

An overview of potential excavation compensation method for tunnelling in deep rock engineering

The complicated geological environment of deep rocks poses new challenges to tunnel and mining engineering. Some thorny disasters such as large deformation of soft rock and rockburst are becoming more and more prominent. However, the classic tunnelling methods represented by the mine tunnelling method and the new Austrian tunnelling method are generally unsatisfactory in addressing these issues due to the limited self-stability of surrounding rock mass. Therefore, the excavation compensation method (ECM) with the core of active stress compensation has been proposed and applied in practical engineering construction to solve the above problems. After extensive engineering practice, the theoretical foundation, key technologies, and construction system of ECM have been established and improved. This article provides a comprehensive overview of this novel tunnelling method. In addition, its controlling effects on surrounding rock are demonstrated by two typical engineering examples. It could provide some new ideas and references for the development of future tunnelling technology.

Early Warning of Loss and Kick for Drilling Process Based on Sparse Autoencoder With Multivariate Time Series

Complicated geological environments lead to a high risk of drilling incidents. Early warning of loss and kick for the drilling process is essential to ensure process safety. On account of the nonlinear and temporal correlation of drilling parameters, an early warning method for loss and kick based on sparse autoencoder with multivariate time series is proposed. The sparse autoencoder is utilized for multivariate time series abnormality detection of the drilling process. Abnormal drilling parameter isolation is performed through contribution analysis. Reconstruction analysis and time series segmentation approaches are integrated for abnormal time series trend evaluation. The characteristic of drilling parameters under normal operation learned by the sparse autoencoder and the property of the original time series are taken into account. The final early warning result can be obtained through expert rules based on the trend evaluation result. Case studies are presented based on the data from an actual drilling project. The experiment result shows the effectiveness of the proposed method.

Landslide susceptibility assessment in Western Henan Province based on a comparison of conventional and ensemble machine learning

Landslide is a serious natural disaster next only to earthquake and flood, which will cause a great threat to people’s lives and property safety. The traditional research of landslide disaster based on experience driving or statistical model and its assessment results are subjective , difficult to quantify, and no pertinence. As a new research method for landslide susceptibility assessment, machine learning can greatly improve the landslide susceptibility model’s accuracy by constructing statistical models. Taking Western Henan for example, the study selected 16 landslide influencing factors such as topography, geological environment, hydrological conditions, and human activities. And 11 landslide factors with the most significant influence on the landslide were selected by the recursive feature elimination (RFE) method. There are five machine learning methods (Support Vector Machines (SVM), Logistic Regression (LR), Random Forest (RF), Extreme Gradient Boosting (XGBoost), and Linear Discriminant Analysis (LDA)) were used to construct the spatial distribution model of landslide susceptibility. The models were evaluated by the receiver operating characteristic curve and statistical index. After analysis and comparison, the XGBoost model (AUC 0.8759) performed the best and was suitable for dealing with regression problems. The model had a high adaptability to landslide data. According to the landslide susceptibility map of the five models, the overall distribution can be observed. The extremely high and high susceptibility areas are distributed in the Funiu Mountain range in the southwest, the Xiaoshan Mountain range in the west, and the Yellow River basin in the north. These areas have large terrain fluctuations, complicated geological structural environments and frequent human engineering activities. The extremely high and highly prone areas were 12043.3 km² and 3087.45 km², accounting for 47.61% and 12.20% of the total area of the study area, respectively. Our study reflects the distribution of landslide susceptibility in western Henan Province, which provides a scientific basis for regional disaster warning, prediction, and resource protection. The study has important practical significance for subsequent landslide disaster management.

Applying Machine Learning and Automatic Speech Recognition for Intelligent Evaluation of Coal Failure Probability under Uniaxial Compression

Acoustic emission (AE) monitoring is an effective tool to quantify the dynamic damage that may cause heavy casualties and huge property losses in rock engineering. Instead of traditional failure evaluation methods, in this paper, the coal failure mechanism is evaluated in a complicated geological environment under uniaxial compression tests by employing machine learning (ML) and automatic speech recognition (ASR). Taking advantage of the ASR technology, the Mel-frequency cepstrum coefficients (MFCC) were extracted as sample features, while ML was used to paradigm the artificial intelligent evaluation of the failure probability of coal (AIEFPC). Additionally, the five-fold cross-validation method was used to assess the AIEFPC predictive effect incorporating cumulative hits number, cumulative ring count, and amplitude as sample features. The influence of category weight on the prediction effect of AIEFPC on a different category of sample sets has been discussed and analyzed. The results show that AIEFPC has the potential to use the MFCC of the 40 ms AE segment at any time to predict the dangerous state of the coal sample with a prediction accuracy of >85%. The probability value of the hazardous samples is computed through AIEFPC that further helped in evaluating the reliability of the prediction results. It is inferred from the obtained results that a larger category weight value of the hazardous samples can improve the prediction accuracy of AIEFPC than the safe sample. This research provides a new way of effectively predicting the coal failure probability before the damage and failure that can be applied to worldwide case-studies.

ACGAN and BN based method for downhole incident diagnosis during the drilling process with small sample data size

During the drilling process, the complicated geological environment makes drilling operations more difficult as the drilling depth increases, leading to a greater susceptibility to drilling incidents. The parameters obtained from a drilling incident are usually incomplete and the sample size is small, which is difficult to be used for incident analysis. This paper proposes a new method for the diagnosis of downhole drilling incidents. The drilling data is generated based on an Auxiliary Classifier Generative Adversarial Networks (ACGAN) and an incident diagnosis model is built using the Bayesian network (BN). The effectiveness and practicality of the proposed method are proved by the actual case study. Based on historical data, data augmentation is performed using the ACGAN model, and then parameter learning of BN is conducted. The established BN model based on large data samples can be used for the diagnosis of downhole incidents. The precision and F1-score of diagnosis are above 80%. Root cause diagnosis of downhole incidents can be performed by backward inference of Bayesian methods. It can prevent the occurrence of downhole incidents. The results prove the proposed method can diagnose downhole incidents in real time and obtain the causes of downhole incidents.

Quantitative Error Analysis for the Least-Squares Imaging

As oil and gas exploration moves towards complicated geological environments, high-resolution and true-amplitude seismic imaging becomes increasingly important for detecting and evaluating hydrocarbon reservoirs. Traditional ray-based and wave-equation imaging methods can be considered as the adjoint operator of seismic forward modeling, which are difficult to produce high-quality images in complicated structures because of limited frequency band, unbalanced illumination and irregular acquisition. Least-squares migration (LSM) generates an inverse solution for subsurface reflectivity model with high image resolution and balanced amplitudes. Previous studies on LSM mainly focused on the developments of theoretical and practical strategies, but few on error and uncertainty analysis. We present a quantitative analysis method to evaluate the errors of LSM results. The &#x03D5;_<i>data</i> and &#x03C8;_<i>data</i> functions are first computed based on the local similarity and <i>L</i>₂-norm misfit between observed and synthetic data. They are used as data-domain kinematic and dynamic errors, respectively. Then, these local functions are mapped to the subsurface using a Kirchhoff-integral relation to calculate image-domain errors. Numerical examples for synthetic and field data demonstrate that as the iteration of LSM increases, the total kinematic and dynamic errors are reduced, and they vary in different locations. For low signal-to-noise-ratio field data, LSM might enlarge image errors at large iterations because of the overfitting issue, and proper regularization is very important to facilitate the convergence of LSM to a good solution.

Fault diagnosis based on feature clustering of time series data for loss and kick of drilling process

With the increase of drilling depth, complicated geological environments lead to a high risk of loss and kick. Fault diagnosis plays an essential role in minimizing the financial and environmental losses of the drilling process. On account of the temporal correlation of drilling parameters, a fault diagnosis method based on feature clustering of time series data for loss and kick of the drilling process is presented in this paper. Distance correlation is conducted for parameter combination to retain the whole information of drilling process. Global trend, local trends, and approximate entropy features are extracted to illustrate the characteristic of the time series. Density-based clustering method is performed for each combination to mine the local similarity among drilling parameters. Based on the clustering results of each combination as the inputs, the Bayesian classifier is further utilized to obtain the final fault diagnosis result. Experiments are executed with the actual data collected from a practical drilling process. The results indicate that the proposed method has both low false alarm rate and low miss alarm rate.

Fast Geometric Multigrid Preconditioned Finite- Difference Frequency-Domain Method for Borehole Electromagnetic Sensing

To model the responses of borehole electromagnetic sensing in complicated geological environments, the geometric multigrid preconditioned finite-difference frequency-domain (FDFD) method is examined on its numerical performance as a fast forward modeling solver in this work. The geometric multigrid method is employed as a preconditioner for the biconjugate gradient stabilized method to efficiently solve the linear system resulting from the finite-difference method based on the staggered Yee’s cell. The Gauss–Seidel method is utilized as both presmoother and postsmoother for the multigrid method, and the bilinear approach is employed to construct the restriction and prolongation operators between coarse and fine grids. The F-cycle coarsening scheme is used to balance the convergence and computational efficiency of the multigrid method. Numerical examples of borehole electromagnetic sensing are included to examine the performance of the method, which not only demonstrates its accuracy but also shows its capability as a fast solver for practical application. The geometric multigrid preconditioned FDFD method can work as a good candidate for 3-D modeling-based interpretation and evaluation for borehole electromagnetic sensing.

Safety risk Assessment for Construction of Highway on Plateau Mountainous

Under the condition of high altitude and complicated geological environment, lots of risks existing in the process of highway construction, how to control effectively safety risk has become the serious problem. Taking the construction project of Sichuan-Tibet highway as an example, combining with regional environment, safety risk indicators of construction project for plateau mountain highway is constructed. Method of construction safety risk assessment for plateau mountain highway is established. The feasibility of the evaluation method is verified by a case, and corresponding risk control measures are put forward.

Operational Safety Risk Assessment for the Water Channels of the South-to-North Water Diversion Project Based on TODIM-FMEA

The South-to-North Water Diversion Project consists of long-distance water delivery channels and a complicated geological environment along the way. To deal with the operation safety of the water conveyance channels in the middle route of the South-to-North Water Diversion Project, this study analyzes six failure modes: structural cracks, poor water delivery during ice periods, instability of canal slopes, material aging, abnormal leakage, and foundation defects. Based on FMEA, a multigranularity language evaluation method that can be converted into interval intuitionistic fuzzy numbers is used to evaluate the severity (S), occurrence (O), and detection difficulty (D) of the six failure modes. Interval intuitionistic fuzzy entropy is used to calculate the weights of the risk factors. Finally, a ranking model of each failure mode is built based on the TODIM method. The final ranking results show that the risk of abnormal leakage is the largest, and the risk of poor water delivery during ice periods is the smallest. The feasibility and validity of the calculation results are verified by comparing them with the ranking results of the traditional RPN and TOPSIS methods. The TODIM-FMEA risk assessment model offers a new solution to the problem of risk assessment for water transfer projects.

Study on analytical calculation method of water inflow in the tunnel of oblique crossing layered aquifer structure

Due to the complicated geological environment and karst hydrogeological conditions, water-inrush accidents often occur in the construction of tunnels in southwestern China. At present, there are many methods to predict tunnel water inflow, including analytic method and conventional hydrodynamic research method. There is a big discrepancy between calculated water inflow value and actual situation. Our research focused on the layered aquifer medium characteristics of water-bearing structure and movement characteristics. On the basis of existing tunnel gushing water inrush characteristics, the crossing relationships between tunnel and layered aquifer structure are divided into three categories, (I) tunnel longitudinal through layered aquifer structure, (II) tunnel through layered aquifer structure, and (III) tunnel obliquely crossing the layered aquifer structure. The revised formula of tunnel water inflow theory and experience in this study is inferred from steady-flow formula considering the boundary conditions. Inhomogeneous layered aquifer structure is considered as homogeneous structure, calculated by theory and experience formula. Next to the heterogeneity on one side of heterogeneity interface, the permeability coefficient of different strata can be fitted for a unified Kv; when crossing the layered water-bearing structure laterally, it is still calculated according to the original formula. When oblique crossing a layered water-bearing structure, the total flow rate is decomposed into two directions: transverse crossing and longitudinal crossing. The flow rates in the two directions are calculated respectively, and then superposed into the flow rates in oblique crossing.

Application of the Upper‐Bench CD Method in Super Large‐Span and Shallow Tunnel: A Case Study of Letuan Tunnel

In order to keep pace with fast urbanization and explosive growth of highway traffic volume in China, more and more super large‐span tunnels are constructed or will be constructed in the coming years. It is of great significance to employ a suitable construction method for ensuring construction safety when tunnelling in a complicated geological environment. Based on the reconstruction and expansion project of Binlai in China, this paper aims at studying deformation behaviors and mechanical properties of super large‐span and shallow tunnel constructed using the upper‐bench CD method. The study results showed that the crown settlement of the pilot tunnel was larger than that of the rear guide tunnel, and the deformation of rock mass tended to be stable after 60 days of excavation. The structural stress changed greatly in the construction stage, the stress distribution of steel rib was mainly under compression, and the maximum compressive stress of shotcrete appeared at the tunnel vault. The supporting structure was always kept in a safe state, and its safety factor was higher than 1.5. However, the upper‐bench CD method has poor performance in controlling surface subsidence and horizontal convergence. The study of this paper provides a new construction method and useful reference for similar super large‐span tunnels.

Application of Computer Simulation Method in Deep Underground Engineering of Complicated Geological Condition

Computer simulation technology is used to solve various engineering problems in the new century, particularly exemplified by the widespread use of numerical simulation research methods. Due to the complicated geological environment, a mine tunnel with a depth of 850 m in Hebei Province has caused various problems, such as large displacements and difficulty in implementing support schemes. However, the complex geological conditions make the project unique, and support schemes for other projects cannot be simply copied. In addition, due to engineering cost requirements, repeatedly evaluating different on-site support schemes is unacceptable. Therefore, it is necessary to obtain an appropriate support scheme through computer simulation technology. Consequently, by implementing FLAC3D software and using the progressive design method (PDM), a variety of support schemes are designed, and simulation tests, such as analysis and optimization of parameters, are performed. The research results show that through the analysis of stress, displacement and other aspects of the various schemes designed by using PDM, the finally selected scheme that was applied to the actual project achieved good results. The findings have proven the feasibility of the method, and the method can guide engineering problems under similar geological conditions.

Risk Source Analysis and Grade Division of Subway Tunnel Undercrossing the Existing Highway Subjected to the Complicated Geological Environment

According to the characteristics of the subway tunnel method construction and the special operation requirements of the highway, many risks of undercrossing engineering should be required urgent attention. So, based on one subway tunnel undercrossing the existing highway, the possible sources of risk are defined and analyzed. Furthermore, according to the evaluation method of fuzzy mathematics, for soft and hard strata complicated geological environment, the assessment and grading of risk sources are investigated during the subway tunnel undercrossing the existing highway. Those results are supporting the important suggests for constructors and designers

Multidisciplinary design optimization of tunnel boring machine considering both structure and control parameters under complex geological conditions

A Tunnel Boring Machine (TBM) is an extremely large and complex engineering machine that usually works under a complicated geological environment to excavate tunnel underground. Considering the large number of sub-systems that usually belong to different disciplines, it is a challenging task to define, model, and optimize the whole TBM from the perspective of system engineering. Also, due to the complex mechanism and geological environment, the flexibility and efficiency of existing TBM excavation strategies are generally limited. To address these challenges, a multidisciplinary modeling is presented so that corresponding analytical or empirical models of each sub-system are formulated, and a multidisciplinary design optimization (MDO) method is applied to the TBM system optimization. Four excavation strategies are studied and compared, including: (i) two existing excavation strategies, and (ii) two new proposed excavation strategies by making control and/or structure parameters adaptive to geological conditions. Two case studies with these four excavation strategies are presented to illustrate the effectiveness and benefits of designing TBM using MDO methodologies. Wherein, Case I aims to minimize the construction period taking into account the restriction of sub-systems, and Case II simultaneously minimizes construction period, cost, and energy consumption. Since the resulting MDO formulation is straightforward to be solved as a single problem, the All-At-Once (AAO) method is utilized in this paper. The optimization results obtained by modeling the problem as MDO show that the excavation strategy with adaptive control and structure parameters can significantly reduce the total construction time, with lower cost and energy consumption.

Estimation of an Effective Young’s Modulus of Elasticity in the Locality of the Gabčíkovo Hydrology Power Plant by Geometric Leveling

Abstract The Gabčíkovo hydroelectric power plant is located in a complicated geological environment (gravel sub-soil and a high groundwater level). Excavation work started after the withdrawal of water in the autumn of 1984 and lasted until the autumn of 1986. A basic geodetic control network with a special monument was founded before the excavation work began. This network served for the setting-out of the hydroelectric power plant as well as for the control of the excavation work. The repeated geodetic control measurements have been evaluated and presented at many seminars and conferences. Monitoring the horizontal and vertical stability of the geodetic control network during the general site excavation showed significant horizontal and vertical deformations. The paper is focused on an estimation of an effective Young's modulus of elasticity in the area studied.

A multidimensional scaling approach to enforce reproduction of transition probabilities in truncated plurigaussian simulation

Truncated plurigaussian (TPG) simulation is a flexible method for simulating rock types in deposits with complicated ordering structures. The truncation of a multivariate Gaussian distribution controls the proportions and ordering of rock types in the simulation while the variogram for each Gaussian variable controls rock type continuity. The determination of a truncation procedure for complicated geological environments is not trivial. A method for determining the truncation and fitting variograms applicable to any number of rock types and multivariate Gaussian distribution is developed here to address this problem. Multidimensional scaling is applied to place dissimilar categories far apart and similar categories close together. The multivariate space is then mapped using a Voronoi decomposition and rotated to optimize variogram reproduction. A case study simulating geologic layers at a large mineral deposit demonstrates the potential of this method and compares the results with sequential indicator simulation (SIS). Input proportion and transition probability reproduction with TPG is demonstrated to be better than SIS. Variogram reproduction is comparable for both techniques.

Stable 3D Inversion of MT Data and its Application to Geothermal Exploration

A stable inversion technique has been developed for three-dimensional (3D) interpretation of magnetotelluric (MT) data. The inversion method was based on the Gauss-Newton (linearised least-squares) method with smoothness regularisation. Static shifts were also treated as unknown parameters in the inversion. The forward modelling was done by using the staggered-grid finite difference method. The Akaike Bayesian information criterion (ABIC) was applied to the search for the optimum trade-off parameters while the minimising the data misfit, model roughness, and static shifts. The inversion method was then applied to a large volume MT dataset obtained in the Ogiri geothermal area, southwestern Japan. The inversion was performed stably, resulting in a good fit between the observed and computed apparent resistivities and phases. The 3D resistivity structure recovered was generally similar to that obtained by a two-dimensional (2D) inversion in previous work, although the deeper portion of the 3D model seemed to be more realistic than that of the 2D one. The 3D model was also in a good agreement with the geological interpretation of the geothermal reservoirs. These results indicated the necessity for 3D interpretation in geothermal exploration and in other applications in complicated geological environments.

New type of potassium deposit: Modal analysis and preparation of potassium carbonate

A kind of dolomitic mudstone newly found in North China has high amounts of K2O up to 10wB% in average, and potassium reserve is at superior scale. Mineral assemblage of the potassium ore indicates a specific and complicated geological environment under which the potassium deposit formed. Modal analysis of the potassium host rock shows that the principal minerals in the ore include microcline, dolomite, and clay minerals such as illite, illite/smectite mixed layer, and kaolinite, attributable to a new type of insoluble potassium deposits in ore genesis. The experiments in this research demonstrated that with sodium carbonate as flux agent, the potassium ore could be decomposed with a proportion as high as 99.4% by calcinations at moderate temperature for no more than 1.5 –2.0 h; more than 70% of K2O in the calcined materials were leached into the liquor, and by acidification reaction of the filter liquor, a large amount of impuri-ties such as Fe3+, Ti4+, Mn2+, Mg2+, and Ca2+ were removed with precipitation of alumino-silicious colloid residue, which makes it possible to prepare potassium carbonate of electronic grade from the filter liquor, whereas the alumino-silicious residue could be utilized to make mineral polymer, a new type of inorganic construction structural materials. The current research shows that in-dustrial exploitation and comprehensive utilization of this new type of insoluble potassium re-source are feasible both in economic benefits and environmental kindness with the fairly clean production process as sketched in this paper.

Geological mapping of regional structural lineaments for tunnel construction

The Hakkoda tunnel is part of the Tohoku Shinkansen, which is under construction. The tunnel is about 40 m deep in the Yakata area. According to former geological data, the tunnel will pass through a regional structural lineament in the base rocks, which are highly fractured and faulted. There is a small river above the tunnel in the area, which provides drinking water for downstream villagers. Due to the low permeability and the mud rocks, shown at the nearby outcrops because of geopressure during the construction of other sections. This can be a potential danger for the tunnel construction at this particular site since river water can potentially leak into the tunnel through the fractures or faults during the construction. There is also a water dam in the neighborhood. There is a possibility of damaging the dam during the construction of the tunnel in this complicated geological environment. For safety reason, it is important to map the geological and hydrological settings in detail before construction. Considering the accuracy of various geological or geophysical methods and their applicability in the region, we employed four geological survey methods. A comprehensive work plan for the tunnel construction was made based on the results. Four geological prospecting methods were employed sequentially during the survey. They are: (1) Electrical Sounding, which was used to map the geological structure, positions of faults or fracture zone and possible water layers in the region. (2) Vertical drilling, which provided more detailed mapping of the geological settings and physical properties of the rocks. (3) Surface wave exploration and Microtremor measurements. Both methods provide more detailed mapping for the regional structural settings, faults or fractured zones. The methods also have much a better three-dimensional resolution in comparison with the electrical method. (4) Horizontal drilling from the work face to obtain more detailed information on properties of the rocks and fractures or faults ahead of the tunnel under building. Water samples were taken from these horizontal wells to evaluate the possibility of possible water invasion by comparing and analyzing the quality of various waters. Correctly integrating various geophysical and geological data was the key to the success of detailed geological mapping in the area, from which a comprehensive work plan was made. The survey results were also accessed by comparing the geological predictions with what we saw at the work face during the construction. In the complex geological environment like this, it is essential to utilize various geological and geophysical methods in order to correctly predict the geological conditions in advance. An optimized working plan can be made based on the detailed geological mappings. Even for areas or zones with the high possibility of water leakage, a proper supplementary work at small scale will be able to prevent the water leakage without injecting cements into the base rock at a much larger scale. This optimized working plan will potentially reduce the construction cost. In conclusion, considering the construction cost and time, favorable geological and geophysical methods were selected based on known geological information and regional geology in the area. The tunnel construction work plan was optimized by correctly integrating various geological and geophysical results. (A). Reprinted with permission from Elsevier. For the covering abstract see ITRD E124500.