The effective channeling of fluid flow by fractures is a liability for enhanced oil recovery(EOR)methods like CO_(2) flooding or CO_(2) storage.Developing a distributed fracture model to understand the heterogeneity o...The effective channeling of fluid flow by fractures is a liability for enhanced oil recovery(EOR)methods like CO_(2) flooding or CO_(2) storage.Developing a distributed fracture model to understand the heterogeneity of the fracture network is essential in characterizing tight and low-permeability reservoirs.In the Ordos Basin,the Chang 8-1-2 layer of the Yanchang Formation is a typical tight and low permeability reservoir in the JH17 wellblock.The strong heterogeneity of distributed fractures,differing fracture scales and fracture types make it difficult to effectively characterize the fracture distribution within the Chang 8-1-2 layer.In this paper,multi-source and multi-attribute methods are used to integrate data into a neural network at different scales,and fuzzy logic control is used to judge the correlation of various attributes.The results suggest that attribute correlation between coherence and fracture indication is the best,followed by correlations with fault distance,north–south slope,and north–south curvature.Advantageous attributes from the target area are used to train the neural network,and the fracture density model and discrete fracture network(DFN)model are built at different scales.This method can be used to effectively predict the distribution characteristics of fractures in the study area.And any learning done by the neural network from this case study can be applied to fracture network modeling for reservoirs of the same type.展开更多
This study at the Esmeralda Mine,part of the El Teniente Division of CODELCO,investigates optimizing hydraulic fracturing(HF)holes’spatial distribution to improve rock material production in one of the world's la...This study at the Esmeralda Mine,part of the El Teniente Division of CODELCO,investigates optimizing hydraulic fracturing(HF)holes’spatial distribution to improve rock material production in one of the world's largest copper-molybdenum deposits.Utilizing diverse data sources,including borehole,oriented borehole,and photogrammetry data,along with hang-up frequency and hydrofracturing details,we applied discrete fracture network(DFN)modeling to analyze in-situ block size distribution and fragmentation.These results are based on 12,000 realizations of discrete fracture network(DFN)models using R-Dis-Frag computer pacakge at real cave volumes of 200 m200 m200 m,with varying parameters,which significantly enhances their reliability.The incorporation of DFN modeling and geostatistical simulation allows for capturing the interaction berween several spatial variables and explaining the variations observed in the production results at the draw points.Keyfindings of spatio-statistical analysis highlight the significance of volumetric fracture intensity(P32)and extraction column height in reducing hang-up events and enhancing fragmentation efficiency.The study integrates HF-induced and natural fracture intensities,revealing that higher P32 values and higher draw columns correlate with fewer hang-ups and better fragmentation.We recommend non-regular HF patterns for high P32 zones to improve operational efficiency.This research provides insights into optimizing mining operations,acknowledging the limitations of HF propagation efficacy and paving the way for further exploration into the interplay between hydraulic fracturing and natural discontinuities.展开更多
Analyzing rock mass seepage using the discrete fracture network(DFN)flow model poses challenges when dealing with complex fracture networks.This paper presents a novel DFN flow model that incorporates the actual conne...Analyzing rock mass seepage using the discrete fracture network(DFN)flow model poses challenges when dealing with complex fracture networks.This paper presents a novel DFN flow model that incorporates the actual connections of large-scale fractures.Notably,this model efficiently manages over 20,000 fractures without necessitating adjustments to the DFN geometry.All geometric analyses,such as identifying connected fractures,dividing the two-dimensional domain into closed loops,triangulating arbitrary loops,and refining triangular elements,are fully automated.The analysis processes are comprehensively introduced,and core algorithms,along with their pseudo-codes,are outlined and explained to assist readers in their programming endeavors.The accuracy of geometric analyses is validated through topological graphs representing the connection relationships between fractures.In practical application,the proposed model is employed to assess the water-sealing effectiveness of an underground storage cavern project.The analysis results indicate that the existing design scheme can effectively prevent the stored oil from leaking in the presence of both dense and sparse fractures.Furthermore,following extensive modification and optimization,the scale and precision of model computation suggest that the proposed model and developed codes can meet the requirements of engineering applications.展开更多
Fluid flow in fractured media has been studied for decades and received considerable attention in the oil and gas industry because of the high productivity of naturally fractured reservoirs.Due to formation complexity...Fluid flow in fractured media has been studied for decades and received considerable attention in the oil and gas industry because of the high productivity of naturally fractured reservoirs.Due to formation complexity and reservoir heterogeneity,characterizing fluid flow with an appropriate reservoir model presents a challenging task that differs relatively from homogeneous conventional reservoirs in many aspects of view,including geological,petrophysical,production,and economics.In most fractured reservoirs,fracture networks create complex pathways that affect hydrocarbon flow,well performance,hence reservoir characterization.A better and comprehensive understanding of the available reservoir modeling approaches is much needed to accurately characterize fluid flow behavior in NFRs.Therefore,in this paper,a perspective review of the available modeling approaches was presented for fluid flow characterization in naturally fractured medium.Modeling methods were evaluated in terms of their description,application,advantages,and disadvantages.This study has also included the applications of these reservoir models in fluid flow characterizing studies and governing equations for fluid flow.Dual continuum models were proved to be better than single continuum models in the presence of large scale fractures.In comparison,discrete models were more appropriate for reservoirs that contain a smaller number of fractures.However,hybrid modeling was the best method to provide accurate and scalable fluid flow modeling.It is our understanding that this paper will bridge the gap between the fundamental understanding and application of NFRs modeling approaches and serve as a useful reference for engineers and researchers for present and future applications.展开更多
The ability to capture permeability of fractured porous media plays a significant role in several engineering applications, including reservoir, mining, petroleum and geotechnical engineering. In order to solve fluid ...The ability to capture permeability of fractured porous media plays a significant role in several engineering applications, including reservoir, mining, petroleum and geotechnical engineering. In order to solve fluid flow and coupled flow-deformation problems encountered in these engineering applications,both empirical and theoretical models had been proposed in the past few decades. Some of them are simple but still work in certain circumstances; others are complex but also need some modifications to be applicable. Thus, the understanding of state-of-the-art permeability evolution model would help researchers and engineers solve engineering problems through an appropriate approach. This paper summarizes permeability evolution models proposed by earlier and recent researchers with emphasis on their characteristics and limitations.展开更多
An intelligent prediction method for fractures in tight carbonate reservoir has been established by upgrading single-well fracture identification and interwell fracture trend prediction with artificial intelligence,mo...An intelligent prediction method for fractures in tight carbonate reservoir has been established by upgrading single-well fracture identification and interwell fracture trend prediction with artificial intelligence,modifying construction of interwell fracture density model,and modeling fracture network and making fracture property equivalence.This method deeply mines fracture information in multi-source isomerous data of different scales to reduce uncertainties of fracture prediction.Based on conventional fracture indicating parameter method,a prediction method of single-well fractures has been worked out by using 3 kinds of artificial intelligence methods to improve fracture identification accuracy from 3 aspects,small sample classification,multi-scale nonlinear feature extraction,and decreasing variance of the prediction model.Fracture prediction by artificial intelligence using seismic attributes provides many details of inter-well fractures.It is combined with fault-related fracture information predicted by numerical simulation of reservoir geomechanics to improve inter-well fracture trend prediction.An interwell fracture density model for fracture network modeling is built by coupling single-well fracture identification and interwell fracture trend through co-sequential simulation.By taking the tight carbonate reservoir of Oligocene-Miocene AS Formation of A Oilfield in Zagros Basin of the Middle East as an example,the proposed prediction method was applied and verified.The single-well fracture identification improves over 15%compared with the conventional fracture indication parameter method in accuracy rate,and the inter-well fracture prediction improves over 25%compared with the composite seismic attribute prediction.The established fracture network model is well consistent with the fluid production index.展开更多
The outcrop investigations provide a better comprehension to interrelate facies-diagenesis and fracture networks for the evaluation of reservoir potential of the carbonate rocks.In this paper,we targeted Kahi-Section(...The outcrop investigations provide a better comprehension to interrelate facies-diagenesis and fracture networks for the evaluation of reservoir potential of the carbonate rocks.In this paper,we targeted Kahi-Section(Nizampur Basin)and Peeran Tangai-Section(Kalachitta Range)to analyze structural-kinematics,Discrete Fracture Network Modelling,microfacies identification and diagenesis to interpret their impact on reservoir potential of Lockhart Limestone(Paleocene).The structural grain within the study area mostly represents the typical east-west trending tight to overturned folds and north-dipping thrust faults that mimic the north-south Indo-Eurasian collision.However,a second phase of deformation related to east-west compressions also identified which rotated the axes of preexisting structures.Fracture analysis revealed that extensional fractures are oriented at high angle to bedding and are differentiated into three orthogonal sets trending northeast-southwest,northwest-southeast and east-west,whereas,the shear fractures formed two conjugate sets trending northeastsouthwest.The Lockhart Limestone was deposited in the inner ramp setting and microfacies types are packstone,wackestone and wacke-packstone with seven sub-microfacies types.It has been identified that the Lockhart Limestone has the heterogeneous distribution of diagenetic and tectonic features throughout its extent.The observed diagenetic sequence is micritization,calcite cementation,dissolution,neomorphism,pyritization and compaction.The results highlight that open and partially filled fractures may provide an interconnected network to promote fluid mobility,leading to higher values of fracture permeability.The porosity values of the pore matrix were greater than fracture,resulting a significant impact on reservoir storage capacity.In contrast,a negative impact on reservoir potential has been shown by stylolites,veins and dissolution seams.However,based on the overall studies,the Lockhart Limestone revealed the prospect of a good reservoir unit in the study area.展开更多
Discontinuity waviness is one of the most important properties that influence shear strength of jointed rock masses,and it should be incorporated into numerical models for slope stability assessment.However,in most ex...Discontinuity waviness is one of the most important properties that influence shear strength of jointed rock masses,and it should be incorporated into numerical models for slope stability assessment.However,in most existing numerical modeling tools,discontinuities are often simplified into planar surfaces.Discrete fracture network modeling tools such as MoFrac allow the simulation of non-planar discontinuities which can be incorporated into lattice-spring-based geomechanical software such as Slope Model for slope stability assessment.In this study,the slope failure of the south wall at Cadia Hill open pit mine is simulated using the lattice-spring-based synthetic rock mass(LS-SRM)modeling approach.First,the slope model is calibrated using field displacement monitoring data,and then the influence of different discontinuity configurations on the stability of the slope is investigated.The modeling results show that the slope with non-planar discontinuities is comparatively more stable than the ones with planar discontinuities.In addition,the slope becomes increasingly unstable with the increases of discontinuity intensity and size.At greater pit depth with higher in situ stress,both the slope models with planar and non-planar discontinuities experience localized failures due to very high stress concentrations,and the slope model with planar discontinuities is more deformable and less stable than that with non-planar discontinuities.展开更多
In open pit mining,uncontrolled block instabilities have serious social,economic and regulatory consequences,such as casualties,disruption of operation and increased regulation difficulties.For this reason,bench face ...In open pit mining,uncontrolled block instabilities have serious social,economic and regulatory consequences,such as casualties,disruption of operation and increased regulation difficulties.For this reason,bench face angle,as one of the controlling parameters associated with block instabilities,should be carefully designed for sustainable mining.This study introduces a discrete fracture network(DFN)-based probabilistic block theory approach for the fast design of the bench face angle.A major advantage is the explicit incorporation of discontinuity size and spatial distribution in the procedure of key blocks testing.The proposed approach was applied to a granite mine in China.First,DFN models were generated from a multi-step modeling procedure to simulate the complex structural characteristics of pit slopes.Then,a modified key blocks searching method was applied to the slope faces modeled,and a cumulative probability of failure was obtained for each sector.Finally,a bench face angle was determined commensurate with an acceptable risk level of stability.The simulation results have shown that the number of hazardous traces exposed on the slope face can be significantly reduced when the suggested bench face angle is adopted,indicating an extremely low risk of uncontrolled block instabilities.展开更多
Cleats are the dominant micro-fracture network controlling the macro-mechanical behavior of coal.Improved understanding of the spatial characteristics of cleat networks is therefore important to the coal mining indust...Cleats are the dominant micro-fracture network controlling the macro-mechanical behavior of coal.Improved understanding of the spatial characteristics of cleat networks is therefore important to the coal mining industry.Discrete fracture networks(DFNs)are increasingly used in engineering analyses to spatially model fractures at various scales.The reliability of coal DFNs largely depends on the confidence in the input cleat statistics.Estimates of these parameters can be made from image-based three-dimensional(3D)characterization of coal cleats using X-ray micro-computed tomography(m CT).One key step in this process,after cleat extraction,is the separation of individual cleats,without which the cleats are a connected network and statistics for different cleat sets cannot be measured.In this paper,a feature extraction-based image processing method is introduced to identify and separate distinct cleat groups from 3D X-ray m CT images.Kernels(filters)representing explicit cleat features of coal are built and cleat separation is successfully achieved by convolutional operations on 3D coal images.The new method is applied to a coal specimen with 80 mm in diameter and 100 mm in length acquired from an Anglo American Steelmaking Coal mine in the Bowen Basin,Queensland,Australia.It is demonstrated that the new method produces reliable cleat separation capable of defining individual cleats and preserving 3D topology after separation.Bedding-parallel fractures are also identified and separated,which has his-torically been challenging to delineate and rarely reported.A variety of cleat/fracture statistics is measured which not only can quantitatively characterize the cleat/fracture system but also can be used for DFN modeling.Finally,variability and heterogeneity with respect to the core axis are investigated.Significant heterogeneity is observed and suggests that the representative elementary volume(REV)of the cleat groups for engineering purposes may be a complex problem requiring careful consideration.展开更多
基金supported by the National Science and Technology Project of China(No.2024ZD1004300)。
文摘The effective channeling of fluid flow by fractures is a liability for enhanced oil recovery(EOR)methods like CO_(2) flooding or CO_(2) storage.Developing a distributed fracture model to understand the heterogeneity of the fracture network is essential in characterizing tight and low-permeability reservoirs.In the Ordos Basin,the Chang 8-1-2 layer of the Yanchang Formation is a typical tight and low permeability reservoir in the JH17 wellblock.The strong heterogeneity of distributed fractures,differing fracture scales and fracture types make it difficult to effectively characterize the fracture distribution within the Chang 8-1-2 layer.In this paper,multi-source and multi-attribute methods are used to integrate data into a neural network at different scales,and fuzzy logic control is used to judge the correlation of various attributes.The results suggest that attribute correlation between coherence and fracture indication is the best,followed by correlations with fault distance,north–south slope,and north–south curvature.Advantageous attributes from the target area are used to train the neural network,and the fracture density model and discrete fracture network(DFN)model are built at different scales.This method can be used to effectively predict the distribution characteristics of fractures in the study area.And any learning done by the neural network from this case study can be applied to fracture network modeling for reservoirs of the same type.
基金the funding of the Agencia Nacional de Investigación y 761 Desarrollo (ANID), through grant project of Fondecyt Iniciacion No. 11221093Basal Grants Center for Modeling ACE210010 and FB210005
文摘This study at the Esmeralda Mine,part of the El Teniente Division of CODELCO,investigates optimizing hydraulic fracturing(HF)holes’spatial distribution to improve rock material production in one of the world's largest copper-molybdenum deposits.Utilizing diverse data sources,including borehole,oriented borehole,and photogrammetry data,along with hang-up frequency and hydrofracturing details,we applied discrete fracture network(DFN)modeling to analyze in-situ block size distribution and fragmentation.These results are based on 12,000 realizations of discrete fracture network(DFN)models using R-Dis-Frag computer pacakge at real cave volumes of 200 m200 m200 m,with varying parameters,which significantly enhances their reliability.The incorporation of DFN modeling and geostatistical simulation allows for capturing the interaction berween several spatial variables and explaining the variations observed in the production results at the draw points.Keyfindings of spatio-statistical analysis highlight the significance of volumetric fracture intensity(P32)and extraction column height in reducing hang-up events and enhancing fragmentation efficiency.The study integrates HF-induced and natural fracture intensities,revealing that higher P32 values and higher draw columns correlate with fewer hang-ups and better fragmentation.We recommend non-regular HF patterns for high P32 zones to improve operational efficiency.This research provides insights into optimizing mining operations,acknowledging the limitations of HF propagation efficacy and paving the way for further exploration into the interplay between hydraulic fracturing and natural discontinuities.
基金sponsored by the General Program of the National Natural Science Foundation of China(Grant Nos.52079129 and 52209148)the Hubei Provincial General Fund,China(Grant No.2023AFB567)。
文摘Analyzing rock mass seepage using the discrete fracture network(DFN)flow model poses challenges when dealing with complex fracture networks.This paper presents a novel DFN flow model that incorporates the actual connections of large-scale fractures.Notably,this model efficiently manages over 20,000 fractures without necessitating adjustments to the DFN geometry.All geometric analyses,such as identifying connected fractures,dividing the two-dimensional domain into closed loops,triangulating arbitrary loops,and refining triangular elements,are fully automated.The analysis processes are comprehensively introduced,and core algorithms,along with their pseudo-codes,are outlined and explained to assist readers in their programming endeavors.The accuracy of geometric analyses is validated through topological graphs representing the connection relationships between fractures.In practical application,the proposed model is employed to assess the water-sealing effectiveness of an underground storage cavern project.The analysis results indicate that the existing design scheme can effectively prevent the stored oil from leaking in the presence of both dense and sparse fractures.Furthermore,following extensive modification and optimization,the scale and precision of model computation suggest that the proposed model and developed codes can meet the requirements of engineering applications.
文摘Fluid flow in fractured media has been studied for decades and received considerable attention in the oil and gas industry because of the high productivity of naturally fractured reservoirs.Due to formation complexity and reservoir heterogeneity,characterizing fluid flow with an appropriate reservoir model presents a challenging task that differs relatively from homogeneous conventional reservoirs in many aspects of view,including geological,petrophysical,production,and economics.In most fractured reservoirs,fracture networks create complex pathways that affect hydrocarbon flow,well performance,hence reservoir characterization.A better and comprehensive understanding of the available reservoir modeling approaches is much needed to accurately characterize fluid flow behavior in NFRs.Therefore,in this paper,a perspective review of the available modeling approaches was presented for fluid flow characterization in naturally fractured medium.Modeling methods were evaluated in terms of their description,application,advantages,and disadvantages.This study has also included the applications of these reservoir models in fluid flow characterizing studies and governing equations for fluid flow.Dual continuum models were proved to be better than single continuum models in the presence of large scale fractures.In comparison,discrete models were more appropriate for reservoirs that contain a smaller number of fractures.However,hybrid modeling was the best method to provide accurate and scalable fluid flow modeling.It is our understanding that this paper will bridge the gap between the fundamental understanding and application of NFRs modeling approaches and serve as a useful reference for engineers and researchers for present and future applications.
基金supported by the National Nature Science Foundation of China(No.51278383,No.51238009 and No.51025827)Key Scientific and Technological Innovation Team of Zhejiang Province(No.2011R50020)Key Scientific and Technological Innovation Team of Wenzhou(No.C20120006)
文摘The ability to capture permeability of fractured porous media plays a significant role in several engineering applications, including reservoir, mining, petroleum and geotechnical engineering. In order to solve fluid flow and coupled flow-deformation problems encountered in these engineering applications,both empirical and theoretical models had been proposed in the past few decades. Some of them are simple but still work in certain circumstances; others are complex but also need some modifications to be applicable. Thus, the understanding of state-of-the-art permeability evolution model would help researchers and engineers solve engineering problems through an appropriate approach. This paper summarizes permeability evolution models proposed by earlier and recent researchers with emphasis on their characteristics and limitations.
基金Supported by the China Youth Program of National Natural Science Foundation(42002134)The 14th Special Support Program of China Postdoctoral Science Foundation(2021T140735).
文摘An intelligent prediction method for fractures in tight carbonate reservoir has been established by upgrading single-well fracture identification and interwell fracture trend prediction with artificial intelligence,modifying construction of interwell fracture density model,and modeling fracture network and making fracture property equivalence.This method deeply mines fracture information in multi-source isomerous data of different scales to reduce uncertainties of fracture prediction.Based on conventional fracture indicating parameter method,a prediction method of single-well fractures has been worked out by using 3 kinds of artificial intelligence methods to improve fracture identification accuracy from 3 aspects,small sample classification,multi-scale nonlinear feature extraction,and decreasing variance of the prediction model.Fracture prediction by artificial intelligence using seismic attributes provides many details of inter-well fractures.It is combined with fault-related fracture information predicted by numerical simulation of reservoir geomechanics to improve inter-well fracture trend prediction.An interwell fracture density model for fracture network modeling is built by coupling single-well fracture identification and interwell fracture trend through co-sequential simulation.By taking the tight carbonate reservoir of Oligocene-Miocene AS Formation of A Oilfield in Zagros Basin of the Middle East as an example,the proposed prediction method was applied and verified.The single-well fracture identification improves over 15%compared with the conventional fracture indication parameter method in accuracy rate,and the inter-well fracture prediction improves over 25%compared with the composite seismic attribute prediction.The established fracture network model is well consistent with the fluid production index.
文摘The outcrop investigations provide a better comprehension to interrelate facies-diagenesis and fracture networks for the evaluation of reservoir potential of the carbonate rocks.In this paper,we targeted Kahi-Section(Nizampur Basin)and Peeran Tangai-Section(Kalachitta Range)to analyze structural-kinematics,Discrete Fracture Network Modelling,microfacies identification and diagenesis to interpret their impact on reservoir potential of Lockhart Limestone(Paleocene).The structural grain within the study area mostly represents the typical east-west trending tight to overturned folds and north-dipping thrust faults that mimic the north-south Indo-Eurasian collision.However,a second phase of deformation related to east-west compressions also identified which rotated the axes of preexisting structures.Fracture analysis revealed that extensional fractures are oriented at high angle to bedding and are differentiated into three orthogonal sets trending northeast-southwest,northwest-southeast and east-west,whereas,the shear fractures formed two conjugate sets trending northeastsouthwest.The Lockhart Limestone was deposited in the inner ramp setting and microfacies types are packstone,wackestone and wacke-packstone with seven sub-microfacies types.It has been identified that the Lockhart Limestone has the heterogeneous distribution of diagenetic and tectonic features throughout its extent.The observed diagenetic sequence is micritization,calcite cementation,dissolution,neomorphism,pyritization and compaction.The results highlight that open and partially filled fractures may provide an interconnected network to promote fluid mobility,leading to higher values of fracture permeability.The porosity values of the pore matrix were greater than fracture,resulting a significant impact on reservoir storage capacity.In contrast,a negative impact on reservoir potential has been shown by stylolites,veins and dissolution seams.However,based on the overall studies,the Lockhart Limestone revealed the prospect of a good reservoir unit in the study area.
基金Ontario Trillium Scholarship for supporting the doctorate program at Laurentian UniversityFinancial supports from the Natural Sciences and Engineering Research Council of Canada(NSERC CRD 470490-14)of Canada+1 种基金Nuclear Waste Management Organization(NWMO)Rio Tinto。
文摘Discontinuity waviness is one of the most important properties that influence shear strength of jointed rock masses,and it should be incorporated into numerical models for slope stability assessment.However,in most existing numerical modeling tools,discontinuities are often simplified into planar surfaces.Discrete fracture network modeling tools such as MoFrac allow the simulation of non-planar discontinuities which can be incorporated into lattice-spring-based geomechanical software such as Slope Model for slope stability assessment.In this study,the slope failure of the south wall at Cadia Hill open pit mine is simulated using the lattice-spring-based synthetic rock mass(LS-SRM)modeling approach.First,the slope model is calibrated using field displacement monitoring data,and then the influence of different discontinuity configurations on the stability of the slope is investigated.The modeling results show that the slope with non-planar discontinuities is comparatively more stable than the ones with planar discontinuities.In addition,the slope becomes increasingly unstable with the increases of discontinuity intensity and size.At greater pit depth with higher in situ stress,both the slope models with planar and non-planar discontinuities experience localized failures due to very high stress concentrations,and the slope model with planar discontinuities is more deformable and less stable than that with non-planar discontinuities.
基金financially supported by the National Natural Science Foundation of China(Grant Nos.42102313 and 52104125)the Fundamental Research Funds for the Central Universities(Grant No.B240201094).
文摘In open pit mining,uncontrolled block instabilities have serious social,economic and regulatory consequences,such as casualties,disruption of operation and increased regulation difficulties.For this reason,bench face angle,as one of the controlling parameters associated with block instabilities,should be carefully designed for sustainable mining.This study introduces a discrete fracture network(DFN)-based probabilistic block theory approach for the fast design of the bench face angle.A major advantage is the explicit incorporation of discontinuity size and spatial distribution in the procedure of key blocks testing.The proposed approach was applied to a granite mine in China.First,DFN models were generated from a multi-step modeling procedure to simulate the complex structural characteristics of pit slopes.Then,a modified key blocks searching method was applied to the slope faces modeled,and a cumulative probability of failure was obtained for each sector.Finally,a bench face angle was determined commensurate with an acceptable risk level of stability.The simulation results have shown that the number of hazardous traces exposed on the slope face can be significantly reduced when the suggested bench face angle is adopted,indicating an extremely low risk of uncontrolled block instabilities.
文摘Cleats are the dominant micro-fracture network controlling the macro-mechanical behavior of coal.Improved understanding of the spatial characteristics of cleat networks is therefore important to the coal mining industry.Discrete fracture networks(DFNs)are increasingly used in engineering analyses to spatially model fractures at various scales.The reliability of coal DFNs largely depends on the confidence in the input cleat statistics.Estimates of these parameters can be made from image-based three-dimensional(3D)characterization of coal cleats using X-ray micro-computed tomography(m CT).One key step in this process,after cleat extraction,is the separation of individual cleats,without which the cleats are a connected network and statistics for different cleat sets cannot be measured.In this paper,a feature extraction-based image processing method is introduced to identify and separate distinct cleat groups from 3D X-ray m CT images.Kernels(filters)representing explicit cleat features of coal are built and cleat separation is successfully achieved by convolutional operations on 3D coal images.The new method is applied to a coal specimen with 80 mm in diameter and 100 mm in length acquired from an Anglo American Steelmaking Coal mine in the Bowen Basin,Queensland,Australia.It is demonstrated that the new method produces reliable cleat separation capable of defining individual cleats and preserving 3D topology after separation.Bedding-parallel fractures are also identified and separated,which has his-torically been challenging to delineate and rarely reported.A variety of cleat/fracture statistics is measured which not only can quantitatively characterize the cleat/fracture system but also can be used for DFN modeling.Finally,variability and heterogeneity with respect to the core axis are investigated.Significant heterogeneity is observed and suggests that the representative elementary volume(REV)of the cleat groups for engineering purposes may be a complex problem requiring careful consideration.
