ABSTRACT: A fracture network model provides a wealth of information concerning the characteristics of a rock mass, including fracture intensity, block size, and connectivity. This paper identifies methods to utilize information derived from DFN models. The fracture intensity of a DFN can be analysed for individual or grouped subvolumes of the model. A DFN is discretized into volumetric elements (voxels). Stochastic DFN models measuring 25 × 25 × 25 m 3 are modeled with identical attributes. Fractures are modeled as non-planar and non-persistent, and orientations varied to generate a variety of block shapes and sizes. The voxels used for metrics analysis range in size from 1 m 3 to 1 953 m 3 , representing from 2 3 to 25 3 voxels. Fracture intensity is measured as a P 32 value for all elements. The coefficient of variation (CV%) of fracture intensity is calculated for each voxelization to generate a curve characteristic of a particular DFN model. An estimate of the in situ block size distribution (IBSD) is made by considering the number of unfractured voxels (null blocks). The fracture intensity, CV% of fracture intensity and IBSD values derived from these DFNs can be used as input to a variety of secondary models.

ABSTRACT: Rockfalls present a major safety threat in open-pit mining operations and transportation corridors. The sudden onset of rockfall events makes it difficult, if not almost impossible, for conventional monitoring methods to provide adequate pre-warning, resulting in a challenge for mine operators and planners. One of the major challenges for geotechnical engineers is the ability to model the trajectory and run out distances or rock blocks in order to properly map the risks associated to the occurrence of such events and to properly design catch benches and exclusion zones. Several modeling tools are available today for this purpose, but they are often poorly supported and calibrated with instrumental data. One of the most common methods currently used consists in localizing the detachment and accumulating areas by comparing 3D models generated by LiDAR scans. The major drawback of this method is that the information that is collected is post-event and cannot provide data about the dynamics of the rockfall events. IDS GeoRadar has recently developed an innovative radar system able to locate and track rockfalls in real-time, from a distance up to 2000 m from the slope by simultaneous coverage of a wide portion of the highwall. The new radar system is able to generate quick alerts immediately after the detachment of the initial rock blocks and will provide beneficial information with regards to statistical data on the occurrence in space and time, travel path, velocity, run out distance, and size of blocks. This paper describes the new technology, initial results from field tests conducted on a natural slope near Tschamut, Switzerland, and recommendations for future work.

ABSTRACT: The understanding of in situ stresses is very important in the oil and gas exploitation. To provide an effective guidance for the field operations including drilling, fracturing and production, the finite element method was employed to model the in situ stresses as well as pore pressure in Sichuan shale gas reservoir embedded fault networks. The linear elastic model was used to depict the deformation of shale gas reservoir, and the friction behavior on the surfaces of faults was considered. Enough trial numerical experiments were used to obtain an optimized prediction that is expected to agree with actual test data. The information of in situ stresses in whole the geometric model as well as main shale gas reservoir layers, and on the fault surfaces can be acquired. Case studies on Changning and Weiyuan regions, Sichuan Basin, southwest China, were conducted, and the in situ stress information including stress gradients and horizontal stress differences in three typical areas was predicted. The orientation of horizontal maximum principal stress in the Changning and Weiyuan regions is almost east-west. The fault only affects the magnitude and orientation of situ stresses near itself, but have little effect on those in the farther strata.

ABSTRACT: The Hydraulic Fracturing Field Test (HFTS) project, fielded within the Wolfcamp Formation in the Permian Basin, provides an excellent opportunity to further develop our understanding of the geomechanical response to hydraulic stimulation and associated fluid transport in shale lithologies. In addition to a full set of geophysical and tracer observations, the project obtained core samples from wells drilled through the stimulated region, characterizing the propagation of fractures, reactivation of pre-existing natural fractures, and placement of proppant. We present our analysis of the HFTS using the GEOS code. In this preliminary phase, we focus upon the response to stimulation of a single stage in the Middle Wolfcamp Formation. Our results emphasize the importance of accounting for preexisting natural fractures in predicting the stimulated volume. The combination of published data we assembled to construct the preliminary geological model can serve as a resource for other practitioners seeking to validate models against the HFTS observations. We also discuss future work that will address interactions between wells within the same and differing zones, along with microscale investigations into the influence of bedding upon fracture height growth.

ABSTRACT: Optimal stope dimensions for underground mining using sublevel stopping method are decided ensuring excavation stability. Stability graph method developed by Mathews, et al. (1980), later modified by different authors is used as an analytical tool to achieve this purpose. Mathews' B factor represents the influence of minor rock mass discontinuities (joints) on the over break volume of stope's walls. However, in a highly fractured rock mass, it is very likely to have at least one joint set orientated sub parallel to every stope's wall, thus accounting for a low value for B factor. This will have a significant impact on stability number's value while not necessarily reflecting the stopes failure mechanism on large stopes as joint's dimensions are small compared to the stope's. Major geological faults, on the other hand, are of bigger dimensions, thus their influence on a stopes overbreak volume is important. This paper presents a comparison between two stability graphs, one created using Mathews' original method and another created using B factor as a mean to measure the influence of major geological faults in the over break volume of stope's walls. Both graphs were made using information from the back analysis of the same stopes and using the software c.

ABSTRACT: The failure of slopes and dams has major consequences worldwide, including extensive damage to infrastructure and related economic losses and, in the worst case, loss of life. The ability to monitor and forecast failure is a major concern for risk management and it is often hindered by lack of data. Recent technological advances enable the use of multiple sources of information, such as Earth Observation (EO), imagery analysis, real time monitoring, which can be combined with numerical analysis and machine learning techniques for monitoring, as well as forecasting the safety of civil works. This paper presents three applications concerning slope stability and dam safety: i) a practical research study for forecasting rainfall-induced landslides that combines remote sensing, geo-engineering and hydrology with machine learning; ii) image-based analysis for slope monitoring applied to the Brumadinho Dam (Minas Gerais, Brazil) pre-failure video footage; and iii) a pilot project for monitoring the safety of the Bhadra Dam, in India, combining the use of high-frequency in-situ measurements and low-frequency satellite-based measurements with numerical modeling. The results show how these enabling technologies can contribute with information to safer infrastructure in a lean, remote approach, which is particularly suited for data-scarce environments and the detection of potential anomalies.

ABSTRACT: The underground limestone mining industry has one of the highest fatality rates compared to all other types of mining in the United States (MSHA, 2016). Ground control issues heavily contribute to these fatalities. According to the National Institute for Occupational Safety and Health (NIOSH, 2011), structurally controlled instability is a predominant failure mechanism in underground limestone mines. Existing analysis methods, such as the limit equilibrium method, do not represent the real structure and behavior of a rock mass in-situ. The Discrete Element Method (DEM) when coupled with representative Discrete Fracture Networks (DFN) has been proven to provide accurate models of the actual response of a rock mass undergoing excavation. However, considering the statistical nature of DFN's, multiple simulations need to be run in order to obtain statistically significant results of the model. The following paper introduces a stochastic approach for analyzing rock block falls in underground excavations. This approach utilizes DEM (Itasca's 3DEC) and DFN's representing virtually mapped discontinuities obtained from terrestrial laser scans. The numerical models were carried out considering rigid blocks. Failed blocks were defined as those blocks that had displaced more than 2 cm and presented velocities indicating that the block was still in movement. This approach allows engineers to define the probability of block failure based on the geometry and weight of failed blocks formed by the intersection of discontinuities in the section of interest, as well as to define kinematics of the blocks. Such information can provide mining operators control measures to evaluate, map and mitigate risks associated with rock falls in underground mines, ultimately improving safety in the underground limestone industry.

ABSTRACT: Gallery instabilities related to weak structures zones are common problems in underground gold mines, due their ancient ore deposit genesis and their complex geological context. The Rock Quality Designation (RQD) block modeling can be a powerful tool to identify persistent structures aiding in the prediction of anticipated risk conditions, since it exposes highly fractured zones within the mine rock mass and provides clarity for geotechnical engineers to appropriately design development ramps and define stope and pillar methodologies. In this paper, the block model is used to highlight a shear zone at the Pequizão Mine, operated by AngloGold Ashanti in Brazil. The tool has been used successfully to avoid problems such as loss of ramps and infrastructures, loss of equipment due backs and walls collapses, increases of cost due a greater volume of support spent than what was budgeted, unexpected ore dilution at stopes and putting the workforce into risky conditions. These problems can be avoided due to the simple process of passing the right information, using a RQD block model, to the mine planning division, to program and manage better unexpected situations that can be predicted, as to increase the development rates by the strategical planning from the geotechnical information.

ABSTRACT: The Kensico-Eastview Connection Tunnel is a new tunnel which will provide redundancy to New York City's water supply system. This project, part of a larger program, consists of a 3.2 km (2 mi.) long, 8.2 m (27 ft.) finished diameter, deep rock tunnel, the terminal shafts, and three shorter, shallow tunnels which connect the project to existing and proposed infrastructure. Detailed historical construction drawings from the Catskill and Delaware aqueducts, as well as geotechnical records, are available. The records were used to guide an efficient and economical preliminary tunnel design in the absence of a completed site investigation. Detailed design will be completed once the geotechnical investigation has finished. This paper will focus on how historical data were systematically collected and analyzed in a manually curated webviewer. Geotechnical information was plotted against geologic and satellite maps along with details of existing tunnels, property lines, utilities, and other restrictions. This approach offered a unique perspective on the project area by taking advantage of available information and presenting it in one organized viewing platform. The webviewer advanced the preliminary design of the proposed tunnels and aided the geotechnical investigation plan. This visual representation of data as a design tool facilitated the multidisciplinary design of this project and will be used on large future projects.

ABSTRACT: Lithological classification of geological formations usually depends on the geologist’ expertise through a laborious and time consuming process. Automating the rock classification procedure is a step towards fast and accurate characterization of geological formations where large data is available. In this study, we assessed the use of a clustering algorithm, namely self-organizing maps, for classification of different lithological classes of limestone. The input parameters are geo-mechanical and geological properties of limestones such as density, uniaxial compressive strength, p-wave velocity and geological origin. The results indicate that the self-organizing maps have a promising potential in lithological clustering. The algorithm accurately clusters limestone classes that have consistent high or low values for at least one of the input parameters. However, the accuracy decreases if the limestone class have inherent high variance. The results provided in this paper provides a preliminary confirmation of the applicability of the self-organizing maps. Future work will focus on the replication of the results with a larger dataset.

ABSTRACT: The uncertainties related with spatial variability and heterogeneities, naturally present in rock masses, play an important role in geotechnical engineering practice. A more accurate assessment and characterisation is increasingly in need due to their impact on the mechanical behaviour of heterogeneous rock masses. This paper presents a modelling methodology to simulate the Rock Quality Designation (RQD) empirical system in order to more accurately identify the position of fault systems and the rock mass geomechanical quality. The main methodology hereby proposed combines geostatistical techniques, which have proved to be efficient in identifying rock mass heterogeneities and in considering the spatial variability so that a more realistic geomechanical model of the rock mass is obtained. Geostatistics allows the simulation of one or more regionalized variables taking into account their spatial correlation and structural law. The approach uses the Turning Bands algorithm to perform the 3-Dimensional conditional simulation of the empirical system D. The main results show the capacity of the approach to model heterogeneous rock mass and allows the identification of rock mass zones with poor quality. An application to a tungsten mine deposit located in the North of Portugal is finally presented in order to illustrate and validate the methodology.

ABSTRACT: Reservoir gas injection under great buried condition has the characteristic of concealment. Therefore, the dynamic monitoring, simulation and prediction of reservoir are crucial. An attempt to quantitatively model the rational association between underground reservoir disturbed deformation and correspondingly induced surface slight distortion was made. It is as well studied how to sufficiently control a compatible unstructured discretization during modeling coupling or decoupling between reservoir flow and reservoir geomechanics, and delved into the effects of the coupled mechanics mechanism on the gradual migration of injected CO 2 in the reservoir. A source code programming tractable interface is successfully developed to provide completely identical meshes between Eclipse and Itasca's FLAC-3D. Some principles which to a usual work flow feels counter-intuitive in analyzing ground surface heave induced by deep gas injection are further studied. The feasibility of analyzing near and far-field displacement gradients to inversely control in-situ process as well as its potential in computational efficiency is in addition discussed in this paper. It reveals the key coupling mechanics mechanism of CO 2 injection process, realizes the global numerical simulation decoupling analysis of far-field deformation, develops a reasonable theoretical basis and practical method for the gas injection process.

ABSTRACT: Prediction of rock mass condition is one of the most critical considerations in preliminary design stage of tunneling. Uncertainty in predicting the rock mass quality often leads to some conservatism, and significant deviations between predicted and actual results would cause project delay and cost overrun. Thus, to improve the prediction regarding uncertainties of rock mass condition, a rock mass classification Q prediction model based on the Markov process is presented. The model input, the transition intensity matrix and probabilistic description for Q-parameter states, can be derived from the available geological information. Based on the Markovian prediction approach, probabilistic distribution profiles for each state of Q-parameters can be obtained. The main output, the probabilistic distribution of Q-value, can be obtained accordingly by integrating distributions of all the Q-parameters along the alignment. The proposed prediction model has been validated by actual case study data from the Lion rock metro tunnel in Hong Kong. Sensitivity analysis has also been conducted and it shows J a , Jn and Jr are the most sensitive input parameters. The probabilistic estimation of Q-value can be used to optimize the construction strategy in the planning and design stage, thus providing insightful information to practitioners in making decisions before tunnel construction.

ABSTRACT: Tunnel Boring Machine (TBM) has been widely used in various types of tunnel construction. The disc cutters are key component of TBM which affecting the construction duration, cost and safety of TBM tunnel significantly. According to site investigation and field data, the cutter wear mechanism is analyzed. The influence factors of cutter wear mainly include geological parameters, tunneling parameters and cutterhead design parameters. An initial cutter wear prediction network is established based on Bayesian theorem. The structure of the net (a Directed Acylic Graph, DAG) is formulated according to the inter-relationship among cutter wear and various factors. Prior Conditional Probability Table (CPT) is obtained by training the model with field data by Netica. As an illustration, a simplified network is applied to YHJW project. The cases test indicates that the method is feasible and the predicted values of cutter wear rate are basically equal to the data collected from YHJW south tunnel under the same geology and tunneling parameters. The predicted results can also reflect the regulation of disc cutter wear under the separate influence of Equivalent Quartz Content (EQC), Uniaxial Compressive Strength (UCS) and thrust. Finally, the conception of an intelligent TBM construction management platform is proposed.

ABSTRACT: A probabilistic multiscale modeling for predicting poromechanical properties of shales is presented. To this end, a framework of experimental characterization, physically-based multiscale modeling and uncertainty quantification that spans from nanoscale to macroscale is utilized. To account for the uncertainty in the model input parameters, they are modeled as random variables. To this end, input parameters are divided into two classes of random variables: tensor-valued and scalar random variables and their corresponding statistical description is constructed by employing Maximum Entropy principle (MaxEnt) based on available information. Then, to propagate uncertainty across different length scales the Monte Carlo simulation is carried out and consequently probabilistic descriptions of macro-scale properties are constructed. Furthermore, a global sensitivity analysis is carried out to characterize the contribution of each source of uncertainty on the overall response. Finally, methodological developments are validated against experimental test database. The integration of experimental characterization, multiscale modeling and uncertainty quantification utilized in this work improves the robustness and reliability of predictive models for poromechanical behavior of shales.

ABSTRACT: Oftentimes laboratory fracturing experiments of brittle, high strength rock produce large amounts of high frequency energy from microcracking captured in the form of acoustic emissions. For instance, in granite, it is not uncommon to record more than 100,000 individual waves on a set of 6 transducers throughout a laboratory hydraulic fracturing experiment. The number of waves, and subsequently the number of located AE events, make structures determined within dense point clouds of AE data difficult to interpret. Previous work in this area used several methodologies to determine zones of varying damage and structure of macro-fractures within these large clouds, including 2D and 3D density imaging, weighted density imaging, or statistical collapsing based on error ellipsoids. Although these techniques are fruitful in illuminating features of the dense cloud of microcracks, they are snapshots in time and do not necessarily relate to the state of the rock after the fracturing process is complete or throughout longer-term stress relaxation/redistribution (i.e. snapshot images of fracture networks at the time of fracturing may not illuminate which fractures are active or closed, even moments after failure has occurred). It can be argued at the field scale that the acoustic emission data occurring post-hydraulic fracturing provides a more accurate map of active or contributing fractures relating to production. Although this information is beneficial at the field scale, it is often left unprocessed, or not recorded due to budgetary constraints or availability for long-term array placement. This work will review a previous laboratory hydraulic fracturing experiment in terms of both the AE data collected at the time of fracturing and throughout 24 hours post-test. The results of the laboratory experiment show that differing regions of the fracture network are actively changing throughout the extended term monitoring post-fracture.

ABSTRACT: In recent years, efforts dubbed “i-Construction” have been intensified to improve the productivity of construction sites in Japan, and various studies have considered related topics, such as actively utilizing information and communications technology (ICT). In the study described, we utilized ICT technologies including artificial intelligence, construction-information modeling (CIM), and image processing at mountainous civil engineering work sites to automatically determine geological conditions on site. We then built a system for centralized management of the results and summarized details, which could be performed by a geological engineer in a remote location via the cloud. This paper describes (1) the overall outline of the system, and describes (2) the creation/storage system for construction records utilizing CIM and geological observation records, (3) the sophistication and 3D rendering of slope measurements, and (4) the quantification and automation of geological evaluations of the tunnel face or slope excavation as it exists at the construction site.

ABSTRACT: This paper presents the development and assessment of an integrated geotechnical database for a hard rock, seismically active, underground mine located in the Abitibi-Témiscamingue mining district in Quebec, Canada. The integrated geotechnical database incorporates a geomechanical database with mining planning and seismic analysis. The database was created from the geological and geotechnical information gathered in borehole logs covering the time period of January 2000 to January 2017. The integrated geotechnical database and associated tools allow analysis of rock mass property variation in space and in relation to geological and geomechanical parameters. Two rockmass properties are investigated to illustrate this. The uniaxial compressive strength (UCS) was used to illustrate the applicability of the tools to investigate intact rock properties. The study of the major factors influencing UCS examined the impact of boreholes tested, lithologies, depth, Young’s modulus, and a combination of these categories. Spatial visualization and basic statistical analysis were performed. The rock mass spatial and temporal degradation was also studied in relation to mining activities in the geotechnical model. Rock quality designation (RQD) analysis was conducted as an illustrative example of an investigation on structural rock mass properties. Quantitative and statistical analysis to identify and investigate the major factors influencing RQD examined drilling dip, distance from a development drift, time evolution and distance to a fault. The development and assessment for an integrated geotechnical database provide valuable visual and quantitative information for the design of mining infrastructure in a seismically active underground mine.

ABSTRACT : During the last two decades, unconventional reservoirs had a terrific run specifically after 2000. Unconventional reservoirs are mostly known as shale reservoirs where due to complex properties such as permeability, wettability etc. require stimulation methods to produce economically. To fulfill this aim, more understanding about shale rocks and also one of their main constituent know as organic matter is crucial. Since it has been well established that the quantities of hydrocarbon generation are a function of kerogen type and level of thermal maturity. Moreover, the presence of organic matter has also a nonnegligible effect on hydraulic fracturing. There has been a significant amount of research regarding the thermal maturity of kerogen, whereas its mechanical properties have not well studied. In this study, we used some samples from upper and lower Bakken formation as one of the main shale reservoirs in North America. In the next step, we tried to show the high potential of Raman spectroscopy in reflecting geochemical and geomechanical properties of Organic matter through reflecting structural information from organic matter with high resolution.

ABSTRACT: Multistage triaxial confining tests provide a great amount of information regarding the medium’s response to external loading. Naturally fractured rocks are especially characterized by a nonlinear response to stresses. We consider the behavior of the rock under triaxial stress state at the specific point of linear axial stress – axial strain curve and nonlinear axial stress – volumetric strain curve. The effect of nonlinearity is considered in the context of microfractures emerging and stably propagating in the rock after the stress state exceeds a critical one related to brittle fracture initiation. The relative density of propagating microfractures is introduced as a parameter for the current stress state. The results of a number of multistage tests carried out for various rocks prove that the relationship between the volumetric strain and relative density of microfractures remains the same for different loading stages with varying radial stress. This result leads to certain limitations on the models for deformation mechanism, increases the amount of data which can be possibly obtained from a multistage test and broadens the understanding of relationship between effective elastic moduli of the rocks and the corresponding stress state.