Geomechanics model test and numerical simulation of 2G-NPR bolt support effect in an active fault tunnel

Active faults are a common adverse geological phenomenon that can occur during tunnel excavation and has a very negative impact on the construction and operation of the tunnel.In this paper,the grade IV rock surrounding the cross-fault tunnel with poor geological conditions has been chosen for the study.The support capacity of 2^(nd) Generation-Negative Poisson’s Ratio(2G-NPR)bolt in an active fault tunnel has been carried out on the basis of relevant results obtained from the geomechanical model test and numerical investigations of failure model for existing unsupported fault tunnel.The investigation shows that surrounding rock of the tunnel is prone to shear deformation and crack formation along the fault,as a result,the rock mass on the upper part of the fault slips as a whole.Furthermore,small-scale deformation and loss of blocks are observed around the tunnel;however,the 2G-NPR bolt support is found to be helpful in keeping the overall tunnel intact without any damage and instability.Due to the blocking effect of fault,the stress of the surrounding rock on the upper and lower parts of the fault is significantly different,and the stress at the left shoulder of the tunnel is greater than that at the right shoulder.The asymmetrical arrangement of 2G-NPR bolts can effectively control the asymmetric deformation and instability of the surrounding rock.The present numerical scheme is in good agreement with the model test results,and can reasonably reflect the stress and displacement characteristics of the surrounding rock of the tunnel.In comparison to unsupported and ordinary PR(Poisson’s Ratio)bolt support,2G-NPR bolt can effectively limit the fault slip and control the stability of the surrounding rock of the fault tunnel.The research findings may serve as a guideline for the use of 2G-NPR bolts in fault tunnel support engineering.

Geology and geomechanics of hydraulic fracturing in the Marcellus shale gas play and their potential applications to the Fuling shale gas development

Geological characteristics,geomechanical behavior and hydraulic fracture propagation mechanism in the Marcellus shale gas play are analyzed and compared with China’s Fuling shale play.Successful experiences in hydraulic fracturing and shale gas development in the Marcellus shale gas play are summarized,which might be applicable in other shale plays.The main factors contributing to the successful development of the Marcellus shale gas play include adoption of advanced drilling and completion technologies,increases of hydraulic fracturing stages,proppant concentration and fluid injection volume.The geological and geomechanical mechanisms related to those technologies are analyzed,particularly the in-situ stress impacts on hydraulic fracturing.The minimum horizontal stress controls where the fractures are initiated,and the maximum horizontal stress dominates the direction of the hydraulic fracture propagation.Hydraulic fracturing performed in the shale reservoir normally has no stress barriers in most cases because the shale has a high minimum horizontal stress,inducing hydraulic fractures propagating beyond the reservoir zone,resulting in inefficient stimulation.This is a common problem in shale plays,and its mechanism is studied in the paper.It is also found that the on-azimuth well has a higher productivity than the off-azimuth well,because shear fractures are created in the off-azimuth well,causing main fractures to kink and increasing fracture tortuosity and friction.The Fuling shale gas play has a markedly higher minimum horizontal stress and much smaller horizontal stress difference.The high minimum horizontal stress causes a much higher formation breakdown pressure;therefore,hydraulic fracturing in the Fuling shale gas play needs a higher treatment pressure,which implies higher difficulty in fracture propagation.The small difference in the two horizontal stresses in the Fuling shale gas play generates shorter and more complex hydraulic fractures,because hydraulic fractures in this case are prone to curve to preexisting fractures.To overcome these difficulties,we recommend reducing well spacing and increasing proppant concentration to increase gas productivity for the Fuling shale gas development.

Carbon capture and storage,geomechanics and induced seismic activity

Injection of large volumes of carbon dioxide(CO_2) for the purposes of greenhouse-gas emissions reduction has the potential to induce earthquakes.Operators of proposed projects must therefore take steps to reduce the risks posed by this induced seismicity.In this paper,we examine the causes of injection-induced seismicity(IIS),and how it should be monitored and modelled,and thereby mitigated.Many US case studies are found where fluids are injected into layers that are in close proximity to crystalline basement rocks.We investigate this issue further by comparing injection and seismicity in two areas where oilfield wastewater is injected in significant volumes:Oklahoma,where fluids are injected into a basal layer,and Saskatchewan,where fluids are injected into a much shallower layer.We suggest that the different induced seismicity responses in these two areas are at least in part due to these different injection depths.We go on to outline two different approaches for modelling IIS:a statistics based approach and a physical,numerical modelling based approach.Both modelling types have advantages and disadvantages,but share a need to be calibrated with good quality seismic monitoring data if they are to be used with any degree of reliability.We therefore encourage the use of seismic monitoring networks at all future carbon capture and storage(CCS) sites.

On the four-dimensional lattice spring model for geomechanics

Recently, a four-dimensional lattice spring model(4D-LSM) was developed to overcome the Poisson's ratio limitation of the classical LSM by introducing the fourth-dimensional spatial interaction. In this work, some aspects of the 4D-LSM on solving problems in geomechanics are investigated, such as the ability to reproduce elastic properties of geomaterials, the capability of solving heterogeneous problems,the accuracy on modelling stress wave propagation, the ability to solve dynamic fracturing and the parallel computational efficiency. Our results indicate that the 4D-LSM is promising to deal with problems in geomechanics.

An Axionatics of Geomechanics

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A geomechanics classification for the rating of railroad subgrade performance

The type of subgrade of a railroad foundation is vital to the overall performance of the track structure.With the train speed and tonnage increase,as well as environmental changes,the evaluation and influence of subgrade are even more paramount in the railroad track structure performance.A geomechanics classification for subgrade is proposed coupling the stiffness(resilient modulus)and permanent deformation behaviour evaluated by means of repeated triaxial loading tests.This classification covers from fine-to coarse-grained soils,grouped by UIC and ASTM.For this achievement,we first summarize the main models for estimating resilient modulus and permanent deformation,including the evaluation of their robustness and their sensitivity to mechanical and environmental parameters.This is followed by the procedure required to arrive at the geomechanical classification and rating,as well as a discussion of the influence of environmental factors.This work is the first attempt to obtain a new geomechanical classification that can be a useful tool in the evaluation and modelling of the foundation of railway structures.

Geomechanics model test research on large deformation control mechanism of roadway disturbed by strong dynamic pressure

Comprehensive mechanized top-coal caving mining is one of the efficient mining methods in coal mines.However,the goaf formed by comprehensive mechanized top-coal caving mining is high,and the goaf roof collapse will cause strong dynamic pressure disturbance,especially the collapse of thick hard roof.Strong dynamic pressure disturbance has an influence on the stability of the roadway,which can lead to large deformation.In order to solve the above problem,a comprehensive pressure releasing and constant resistance energy absorbing control method is proposed.Comprehensive pressure releasing can change the roadway roof structure and cut off the stress transfer between goaf and roadway,which can improve the stress environment of the roadway.The constant resistance energy absorbing(CREA)anchor cable can absorb the energy of surrounding rock deformation and resist the impact load of gangue collapse,so as to ensure the stability of roadway disturbed by strong dynamic pressure.A three-dimensional geomechanics model test is carried out,based on the roadway disturbed by strong dynamic pressure of the extra-large coal mine in western China,to verify the control effect of the new control method.The stress and displacement evolution laws of the roadway with traditional control method and new control method are analyzed.The pressure releasing and energy absorbing control mechanism of the new control method is clarified.The geomechanics model test results show that the new control method can increase the range of low stress zone by 150%and reduce the average stress and the displacement by 34.7%and 67.8%respectively,compared with the traditional control method.The filed application results show that the new control method can reduce the roadway surrounding rock displacement by 67.4%compared with the traditional control method.It shows that the new control method can effectively control the displacement of the roadway disturbed by strong dynamic pressure and ensure that the roadway meets the safety requirements.On this basis,the engineering suggestions for large deformation control of this kind of roadway are put forward.The new control method can provide a control idea for the roadway disturbed by strong dynamic pressure.

A gated recurrent unit model to predict Poisson’s ratio using deep learning

Static Poisson’s ratio(vs)is crucial for determining geomechanical properties in petroleum applications,namely sand production.Some models have been used to predict vs;however,the published models were limited to specific data ranges with an average absolute percentage relative error(AAPRE)of more than 10%.The published gated recurrent unit(GRU)models do not consider trend analysis to show physical behaviors.In this study,we aim to develop a GRU model using trend analysis and three inputs for predicting n s based on a broad range of data,n s(value of 0.1627-0.4492),bulk formation density(RHOB)(0.315-2.994 g/mL),compressional time(DTc)(44.43-186.9 μs/ft),and shear time(DTs)(72.9-341.2μ s/ft).The GRU model was evaluated using different approaches,including statistical error an-alyses.The GRU model showed the proper trends,and the model data ranges were wider than previous ones.The GRU model has the largest correlation coefficient(R)of 0.967 and the lowest AAPRE,average percent relative error(APRE),root mean square error(RMSE),and standard deviation(SD)of 3.228%,1.054%,4.389,and 0.013,respectively,compared to other models.The GRU model has a high accuracy for the different datasets:training,validation,testing,and the whole datasets with R and AAPRE values were 0.981 and 2.601%,0.966 and 3.274%,0.967 and 3.228%,and 0.977 and 2.861%,respectively.The group error analyses of all inputs show that the GRU model has less than 5% AAPRE for all input ranges,which is superior to other models that have different AAPRE values of more than 10% at various ranges of inputs.

Fracture characterization of Asmari Formation carbonate reservoirs in G Oilfield, Zagros Basin, Middle East

The Asmari Formation in the G oilfield on the Iran-Iraq border is a fractured-porous multi-lithology mixed reservoir, for which fracture is an important factor affecting oil productivity and water cut. The characterization and modeling of fractures in the carbonate reservoir of G oilfield are challenging due to weak conventional well log responses of fractures and a lack of specific logs, such as image logs. This study proposes an integrated approach for characterizing and modeling fractures in the carbonate reservoir. The features, formation mechanism, influencing factors, and prediction methods of fractures in the Asmari Formation carbonate reservoirs of G oilfield were studied using core observation, thin section, image log, cross-dipole acoustic log (CDAL), geomechanics numerical simulation (GNS), and production data. According to CDAL-based fracture density interpretation, GNS-based fracture intensity prediction between wells, and DFN-based rock fracture properties modeling, the quantitative fracture characterization for G oilfield was realized. This research shows that the fractures in the Asamri Formation are mainly medium-to high-angle shear fractures. The substantial compression stress during the Miocene played a major role in the formation of the prominent fractures and determined their trend in the region, with primary trends of NNW-SSE and NNE-SSW. The fracture distribution has regularity, and the fractures in zone A dolomites are more highly developed than that in zone B limestones vertically. Horizontally, fractures intensity is mainly controlled by faults and structural location. The results of this study may benefit the optimization of well design during field development. From 2019 to 2021, three horizontal wells pilot tests were deployed in the fractures belt in zone A, and these fractures prominently increased the permeability of tight dolomite reservoirs. The initial production of the wells is four to five times the average production of other wells in the area, showing a good development effect. Meanwhile, the updated numerical simulation validates that the history match accuracy of water cut based on the dual-porosity model is significantly improved, proving the fracture evaluation and prediction results to be relatively reliable and applicable.

Deep Learning Applied to Computational Mechanics:A Comprehensive Review,State of the Art,and the Classics

Three recent breakthroughs due to AI in arts and science serve as motivation:An award winning digital image,protein folding,fast matrix multiplication.Many recent developments in artificial neural networks,particularly deep learning(DL),applied and relevant to computational mechanics(solid,fluids,finite-element technology)are reviewed in detail.Both hybrid and pure machine learning(ML)methods are discussed.Hybrid methods combine traditional PDE discretizations with ML methods either(1)to help model complex nonlinear constitutive relations,(2)to nonlinearly reduce the model order for efficient simulation(turbulence),or(3)to accelerate the simulation by predicting certain components in the traditional integration methods.Here,methods(1)and(2)relied on Long-Short-Term Memory(LSTM)architecture,with method(3)relying on convolutional neural networks.Pure ML methods to solve(nonlinear)PDEs are represented by Physics-Informed Neural network(PINN)methods,which could be combined with attention mechanism to address discontinuous solutions.Both LSTM and attention architectures,together with modern and generalized classic optimizers to include stochasticity for DL networks,are extensively reviewed.Kernel machines,including Gaussian processes,are provided to sufficient depth for more advanced works such as shallow networks with infinite width.Not only addressing experts,readers are assumed familiar with computational mechanics,but not with DL,whose concepts and applications are built up from the basics,aiming at bringing first-time learners quickly to the forefront of research.History and limitations of AI are recounted and discussed,with particular attention at pointing out misstatements or misconceptions of the classics,even in well-known references.Positioning and pointing control of a large-deformable beam is given as an example.

Displacement-based back analysis of mitigating the effects of displacement loss in underground engineering

Displacement-monitoring-based back analysis is a popular method for geomechanical parameter estimation.However,due to the delayed installation of multi-point extensometers,the monitoring curve is only a part of the overall one,leading to displacement loss.Besides,the monitoring and construction time on the monitoring curve is difficult to determine.In the literature,the final displacement was selected for the back analysis,which could induce unreliable results.In this paper,a displacement-based back analysis method to mitigate the influence of displacement loss is developed.A robust hybrid optimization algorithm is proposed as a substitute for time-consuming numerical simulation.It integrates the strengths of the nonlinear mapping and prediction capability of the support vector machine(SVM)algorithm,the global searching and optimization characteristics of the optimized particle swarm optimization(OPSO)algorithm,and the nonlinear numerical simulation capability of ABAQUS.To avoid being trapped in the local optimum and to improve the efficiency of optimization,the standard PSO algorithm is improved and is compared with other three algorithms(genetic algorithm(GA),simulated annealing(SA),and standard PSO).The results indicate the superiority of OPSO algorithm.Finally,the hybrid optimization algorithm is applied to an engineering project.The back-analyzed parameters are submitted to numerical analysis,and comparison between the calculated and monitoring displacement curve shows that this hybrid algorithm can offer a reasonable reference for geomechanical parameters estimation.

Multiphysics of carbon dioxide sequestration in coalbeds:A reviewwith a focus on geomechanical characteristics of coal

To reduce the emissions of carbon dioxide(CO_2) into the atmosphere, it is proposed to inject anthropogenic CO_2 into deep geological formations. Deep un-mineable coalbeds are considered to be possible CO_2 repositories because coal is able to adsorb a large amount of CO_2 inside its microporous structure.However, the response of coalbeds is complex because of coupled flow and mechanical processes. Injection of CO_2 causes coal to swell, which leads to reductions in permeability and hence makes injection more difficult, and at the same time leads to changes in the mechanical properties which can affect the stress state in the coal and overlying strata. The mechanical properties of coal under storage conditions are of importance when assessing the integrity and safety of the storage scheme. On the other hand, the geomechanical response of coalbed will also influence the reservoir performance of coalbed. This paper provides an overview of processes associated with coalbed geosequestration of CO_2 while the importance of geomechanical characteristics of coalbeds is highlighted. The most recent findings about the interactions between gas transport and geomechanical characteristics of coal will be discussed and the essence will be delivered. The author suggests areas for future research efforts to further improve the understanding of enhanced coalbed methane(ECBM) and coalbed geosequestration of CO_2.

Geomechanical analysis of the influence of CO2 injection location on fault stability

Large amounts of carbon dioxide(CO_2) should be injected in deep saline formations to mitigate climate change,implying geomechanical challenges that require further understanding.Pressure build-up induced by CO_2 injection will decrease the effective stresses and may affect fault stability.Geomechanical effects of overpressure induced by CO_2 injection either in the hanging wall or in the foot wall on fault stability are investigated.CO_2 injection in the presence of a low-permeable fault induces pressurization of the storage formation between the injection well and the fault.The low permeability of the fault hinders fluid flow across it and leads to smaller overpressure on the other side of the fault.This variability in the fluid pressure distribution gives rise to differential total stress changes around the fault that reduce its stability.Despite a significant pressure build-up induced by the fault,caprock stability around the injection well is not compromised and thus,CO_2 leakage across the caprock is unlikely to happen.The decrease in fault stability is similar regardless of the side of the fault where CO_2 is injected.Simulation results show that fault core permeability has a significant effect on fault stability,becoming less affected for high-permeable faults.An appropriate pressure management will allow storing large quantities of CO_2 without inducing fault reactivation.

A review of methods,applications and limitations for incorporating fluid flow in the discrete element method

The past decade has witnessed the substantial growth in research interests and progress on the subject of coupled hydro-mechanical processes in rocks and soils,driven mainly by the surge of research in unconventional hydrocarbon reservoirs and associated hazards.Many coupling techniques have been developed to include the effects of fluid flow in the discrete element method(DEM),and the techniques have been applied to a variety of geomechanical problems.Although these coupling methods have been successfully applied in various engineering fields,no single fluid/DEM coupling method is universal due to the complexity of engineering problems and the limitations of the numerical methods.For researchers and engineers,the key to solve a specific problem is to select the most appropriate fluid/DEM coupling method among these modeling technologies.The purpose of this paper is to give a comprehensive review of fluid flow/DEM coupling methods and relevant research.Given their importance,the availability or unavailability of best practice guidelines is outlined.The theoretical background and current status of DEM are introduced first,and the principles,applications,and advantages and disadvantages of different fluid flow/DEM coupling methods are discussed.Finally,a summary with speculation on future development trends is given.

Evaluating performance of lignite pillars with 2D approximation techniques and 3D numerical analyses

This paper attempts to investigate the use of approximate 2D numerical simulation techniques for the evaluation of lignite pillar geomechanical response, formed via the room and pillar mining method.Performance and applicability of the developing methodology are assessed through benchmarking with a more direct and accurate 3D numerical model. This analysis utilizes an underground lignite mine which is being developed in soft rock environment. Through the decisions made for the optimum room and pillar layout, the design process highlights the strong points and the weaknesses of 2D finite element analysis, and provides useful recommendations for future reference. The interpretations of results demonstrate that 2D approximation techniques come near quite well to the actual 3D problem.However, external load approximation technique seems to fit even better with the respective outcomes from the 3D analyses.

Influence of longwall gateroad convergence on the process of mine ventilation network-model tests

Hard coal mines are required to constantly ventilate mine workings to ensure that the air composition is at a certain humidity and temperature level that is comfortable for underground mine workers,especially in deep deposits.All underground workings,which are part of the mine ventilation network,should be ventilated in a way that allows maintaining proper oxygen concentration not lower than 19%(by volume),and limits concentration of gases in the air such as methane,carbon monoxide or carbon dioxide.The air flow in the mine ventilation network may be disturbed due to the natural convergence(deformation)and lead to change in its original cross-section.Reducing the cross-sectional area of the mining excavation causes local resistances in the air flow and changes in aerodynamic potentials,which leads to emergency states in the mine ventilation network.This paper presents the results of numerical simulations of the influence of gateroad convergence on the ventilation process of a selected part of the mine ventilation network.The gateroad convergence was modelled with the finite element software PHASE 2.The influence of changes in the cross-sectional area of the gateroad on the ventilation process was carried out using the computational fluid dynamics software Ansys-Fluent.

Meta-analysis of ground movements associated with deep excavations using a data mining approach

This paper presents a rigorous statistical approach to identify the controlling factors in the development of ground movements associated with deep excavations. It also gives the most suitable definition of support stiffness from many suggested definitions in the literature. The study is based on a newly compiled database from 389 case studies of propped and anchored excavations. Data mining techniques(e.g. principal component analysis and multi-linear regression) were used to identify significant relationships between the parameters under study and to quantify the global trends in the database. The study shows that the main factors controlling the ground movements are those related to ground conditions, confirming the conclusions of previous empirical studies. It is also shown that the definition of Addenbrooke et al.(1994) is the most suitable expression of support stiffness, therefore providing conclusive evidence for its future use.

Improved prediction of shear wave velocity for clastic sedimentary rocks using hybrid model with core data

Accurate measurement of acoustic velocities of sedimentary rocks is essential for prediction of rock elastic constants and well failure analysis during drilling operations.Direct measurement by advanced logging tools such as dipole sonic imager is not always possible.For older wells,such data are not available in most cases.Therefore,it is an alternate way to develop a reliable correlation to estimate the shear wave velocity from existing log and/or core data.The objective of this research is to investigate the nature of dependency of different reservoir parameters on the shear wave velocity(VS) of clastic sedimentary rocks,and to identify the parameter/variable which shows the highest level of dependency.In the study,data-driven connectionist models are developed using machine learning approach of least square support vector machine(LSSVM).The coupled simulated annealing(CSA) approach is utilized to optimize the tuning and kernel parameters in the model development.The performance of the simulation-based model is evaluated using statistical parameters.It is found that the most dependency predictor variable is the compressional wave velocity,followed by the rock porosity,bulk density and shale volume in turn.A new correlation is developed to estimate VS,which captures the most influential parameters of sedimentary rocks.The new correlation is verified and compared with existing models using measured data of sandstone,and it exhibits a minimal error and high correlation coefficient(R^(2)-0.96).The hybridized LSSVM-CSA connectionist model development strategy can be applied for further analysis to predict rock mechanical properties.Additionally,the improved correlation of VS can be adopted to estimate rock elastic constants and conduct wellbore failure analysis for safe drilling and field development decisions,reducing the exploration costs.