[Objective] This study was to explore the difference of kriging interpolation and sequential Gaussian simulation on analyzing soil heavy metal pollution with a view to provide references for analyzing the heavy metal ...[Objective] This study was to explore the difference of kriging interpolation and sequential Gaussian simulation on analyzing soil heavy metal pollution with a view to provide references for analyzing the heavy metal pollution of soil. [Method] The sampling data of soil copper from a county of Liaocheng, Shandong Province was set as the study objective. Kriging interpolation and sequential Gaussian simu- lation were used to simulate the spatial distribution of soil copper. And 30 sampling points were selected as the cross-validation data set to compare the two interpola- tion methods. [Result] Kriging method and Gaussian sequential simulation have their own advantages on simulating mean segment and extreme segment, therefore, re- searchers should choose the proper method based on the characteristics of test data and application purposes. [Conclusion] Analysis of soil heavy metal pollution is the prerequisite for soil management and ecological restoration. The result of this study is of important significance for choosing different interpolating and simulating methods to analyze soil heavy metal pollution based on different purposes.展开更多
Risk quantification in grade is critical for mine design and planning.Grade uncertainty is assessed using multiple grade realizations,from geostatistical conditional simulations,which are effective to evaluate local o...Risk quantification in grade is critical for mine design and planning.Grade uncertainty is assessed using multiple grade realizations,from geostatistical conditional simulations,which are effective to evaluate local or global uncertainty by honouring spatial correlation structures.The sequential Gaussian conditional simulation was used to assess uncertainty of grade estimates and illustrate simulated models in Sivas gold deposit,Turkey.In situ variability and risk quantification of the gold grade were assessed by probabilistic approach based on the sequential Gaussian simulations to yield a series of conditional maps characterized by equally probable spatial distribution of the gold grade for the study area.The simulation results were validated by a number of tests such as descriptive statistics,histogram,variogram and contour map reproductions.The case study demonstrates the efficiency of the method in assessing risk associated with geological and engineering variable such as the gold grade variability and distribution.The simulated models can be incorporated into exploration,exploitation and scheduling of the gold deposit.展开更多
The goal of this research is to develop mine-scale discrete fracture network(DFN)models in which the influence of the spatial heterogeneity of fracture distributions may be investigated on the rock wedge stability of ...The goal of this research is to develop mine-scale discrete fracture network(DFN)models in which the influence of the spatial heterogeneity of fracture distributions may be investigated on the rock wedge stability of an open pit slope.For this purpose,spatially conditioned DFN models were developed for the pit walls at Tasiast mine using comprehensive structural data from the mine.Using Sequential Gaussian Simulation(SGS),volumetric fracture intensities(P32)were modeled across the entire mine site in the form of 3D block models.The simulated P32 block models were used as the input constraints for conditional DFN fracture generation,where the DFN grid dimension is the same as the SGS 3D blocks.The spatially constrained DFN models were further calibrated using aerial fracture intensities(P21)data from the pit walls,obtained by a survey of the pit walls using an unmanned aerial vehicle(UAV)and measured traces of joints from 3D point cloud data.The final DFN model is expected to honor the fracture intensities gathered through different means with optimal model accuracy.Finally,bench-scale and interramp scale rock wedge slope stability analyses were conducted using the calibrated conditional DFN models.This work proves the significance of conditioned DFN models in rock wedge stability analysis.Such models provide detailed information regarding rock wedge stability so that site monitoring and prevention plans can be conducted with higher efficiency.展开更多
Great uncertainty exists in reservoir models built for blocks where well spacing is uneven or large. The uncertainty in reservoir models can be significantly reduced by using Coordinate Cokriging Sequential Gaussian S...Great uncertainty exists in reservoir models built for blocks where well spacing is uneven or large. The uncertainty in reservoir models can be significantly reduced by using Coordinate Cokriging Sequential Gaussian Simulation technology, in combination with the restriction of seismic characteristic data. Satisfactory reservoir parameter interpolation results, which are more accurate than those derived only from borehole data, are obtained, giving rise to a reasonable combination of widespread and dense-sampled seismic (soft data) data with borehole data (hard data). A significant effect has been made in reservoir parameter modeling in the Chegu 201 block of the Futai Oilfield by using this technology.展开更多
The well-known“lost circulation”problem refers to the uncontrolled flow of whole mud into a formation.In order to address the problem related to the paucity of available data,in the present study,a model is introduc...The well-known“lost circulation”problem refers to the uncontrolled flow of whole mud into a formation.In order to address the problem related to the paucity of available data,in the present study,a model is introduced for the lost-circulation risk sample profile of a drilled well.The model is built taking into account effective data(the Block L).Then,using a three-dimensional geological modeling software,relying on the variation function and sequential Gaussian simulation method,a three-dimensional block lost-circulation risk model is introduced able to provide relevant information for regional analyses.展开更多
Aquifers composed of porous granular media are important to human beings because they are capable of storing a large amount of groundwater.Contaminant migration and remediation in subsurface environments are strongly ...Aquifers composed of porous granular media are important to human beings because they are capable of storing a large amount of groundwater.Contaminant migration and remediation in subsurface environments are strongly influenced by three-dimensional(3D)microstructures of porous media.In this study,fractal models are developed to investigate contaminant transport and surfactant-enhanced aquifer remediation(SEAR)for the regular tetrahedron microstructure(RTM)and right square pyramid microstructure(RSPM).The relationships of permeability and entry pressure are derived for these two kinds of 3D microstructures of granular porous media.Afterward,the difference in perchloroethylene(PCE)migration and SEAR efficiency between RTM and RSPM is investigated by the numerical simulation based on a synthetic heterogeneous granular aquifer.Results indicate that PCE penetrates faster and spreads farther in RSPM-based aquifers compared with RTM-based aquifers.Further,SEAR in RTM-based aquifers can achieve remediation efficiencies of 66.129%-92.214%with a mean of 84.324%,which is clearly lower than the SEAR efficiency of 70.149%-94.773%(with a mean of 89.122%)in RSPM-based aquifers.Findings are significant for understanding the 3D microstructure of porous media and how the microstructure of porous media affects macroscopic contaminant behaviors and remediation.展开更多
Completions and Reservoir Quality are two key attributes that are used to characterize nonconventional hydrocarbon assets.This is because,for optimum exploitation of these unconventional assets,horizontal wells need t...Completions and Reservoir Quality are two key attributes that are used to characterize nonconventional hydrocarbon assets.This is because,for optimum exploitation of these unconventional assets,horizontal wells need to be drilled in“Sweet Spots”(i.e.,regions where Completions and Reservoir Quality are both superior).One way to quantify these qualities is to use reservoir and geomechanical properties.These properties can be estimated on a location basis from well logs,and then mapped over terrain using geostatistical modeling.This study presents a‘Sweet Spots’identification workflow based on three performance indexes(Storage Potential Index,Brittleness Index,and Horizontal Stress Index)that can be used to quantify CQ and RQ.The performance indexes are computed from petrophysical property volumes(of Young's Modulus,Bulk Modulus,Shear Modulus,Poisson's Ratio,Minimum Horizontal Stress,Volume of Shale,Total Organic Carbon,Thickness,and Porosity)which are in turn computed from well logs and geostatistical simulation.In the end,the study offers a method to compare the predicted“Sweet Spots”against available production data via their correlation coefficient.The resulting reasonable formation property maps,the successful identification of‘Sweet Spots’,and a correlation coefficient of 0.88(between the predicted“Sweet Spots”and well production data)point to the potential of the proposed effort.展开更多
基金Supported by the Science and Technology Development Program of Shandong Province (Soft Science) (2009RKB220),China~~
文摘[Objective] This study was to explore the difference of kriging interpolation and sequential Gaussian simulation on analyzing soil heavy metal pollution with a view to provide references for analyzing the heavy metal pollution of soil. [Method] The sampling data of soil copper from a county of Liaocheng, Shandong Province was set as the study objective. Kriging interpolation and sequential Gaussian simu- lation were used to simulate the spatial distribution of soil copper. And 30 sampling points were selected as the cross-validation data set to compare the two interpola- tion methods. [Result] Kriging method and Gaussian sequential simulation have their own advantages on simulating mean segment and extreme segment, therefore, re- searchers should choose the proper method based on the characteristics of test data and application purposes. [Conclusion] Analysis of soil heavy metal pollution is the prerequisite for soil management and ecological restoration. The result of this study is of important significance for choosing different interpolating and simulating methods to analyze soil heavy metal pollution based on different purposes.
文摘Risk quantification in grade is critical for mine design and planning.Grade uncertainty is assessed using multiple grade realizations,from geostatistical conditional simulations,which are effective to evaluate local or global uncertainty by honouring spatial correlation structures.The sequential Gaussian conditional simulation was used to assess uncertainty of grade estimates and illustrate simulated models in Sivas gold deposit,Turkey.In situ variability and risk quantification of the gold grade were assessed by probabilistic approach based on the sequential Gaussian simulations to yield a series of conditional maps characterized by equally probable spatial distribution of the gold grade for the study area.The simulation results were validated by a number of tests such as descriptive statistics,histogram,variogram and contour map reproductions.The case study demonstrates the efficiency of the method in assessing risk associated with geological and engineering variable such as the gold grade variability and distribution.The simulated models can be incorporated into exploration,exploitation and scheduling of the gold deposit.
基金Kinross Gold and MITACS for their financial support(Grant No.FR42880).
文摘The goal of this research is to develop mine-scale discrete fracture network(DFN)models in which the influence of the spatial heterogeneity of fracture distributions may be investigated on the rock wedge stability of an open pit slope.For this purpose,spatially conditioned DFN models were developed for the pit walls at Tasiast mine using comprehensive structural data from the mine.Using Sequential Gaussian Simulation(SGS),volumetric fracture intensities(P32)were modeled across the entire mine site in the form of 3D block models.The simulated P32 block models were used as the input constraints for conditional DFN fracture generation,where the DFN grid dimension is the same as the SGS 3D blocks.The spatially constrained DFN models were further calibrated using aerial fracture intensities(P21)data from the pit walls,obtained by a survey of the pit walls using an unmanned aerial vehicle(UAV)and measured traces of joints from 3D point cloud data.The final DFN model is expected to honor the fracture intensities gathered through different means with optimal model accuracy.Finally,bench-scale and interramp scale rock wedge slope stability analyses were conducted using the calibrated conditional DFN models.This work proves the significance of conditioned DFN models in rock wedge stability analysis.Such models provide detailed information regarding rock wedge stability so that site monitoring and prevention plans can be conducted with higher efficiency.
文摘Great uncertainty exists in reservoir models built for blocks where well spacing is uneven or large. The uncertainty in reservoir models can be significantly reduced by using Coordinate Cokriging Sequential Gaussian Simulation technology, in combination with the restriction of seismic characteristic data. Satisfactory reservoir parameter interpolation results, which are more accurate than those derived only from borehole data, are obtained, giving rise to a reasonable combination of widespread and dense-sampled seismic (soft data) data with borehole data (hard data). A significant effect has been made in reservoir parameter modeling in the Chegu 201 block of the Futai Oilfield by using this technology.
文摘The well-known“lost circulation”problem refers to the uncontrolled flow of whole mud into a formation.In order to address the problem related to the paucity of available data,in the present study,a model is introduced for the lost-circulation risk sample profile of a drilled well.The model is built taking into account effective data(the Block L).Then,using a three-dimensional geological modeling software,relying on the variation function and sequential Gaussian simulation method,a three-dimensional block lost-circulation risk model is introduced able to provide relevant information for regional analyses.
基金supported by the National Key Research and Development Plan of China (no.2019YFC1804302)the Natural Science Foundation of Guangdong Province (no.2023A1515012228)Guangdong Provincial Environmental Protection Fund (Guangdong Financial Budget 20244).
文摘Aquifers composed of porous granular media are important to human beings because they are capable of storing a large amount of groundwater.Contaminant migration and remediation in subsurface environments are strongly influenced by three-dimensional(3D)microstructures of porous media.In this study,fractal models are developed to investigate contaminant transport and surfactant-enhanced aquifer remediation(SEAR)for the regular tetrahedron microstructure(RTM)and right square pyramid microstructure(RSPM).The relationships of permeability and entry pressure are derived for these two kinds of 3D microstructures of granular porous media.Afterward,the difference in perchloroethylene(PCE)migration and SEAR efficiency between RTM and RSPM is investigated by the numerical simulation based on a synthetic heterogeneous granular aquifer.Results indicate that PCE penetrates faster and spreads farther in RSPM-based aquifers compared with RTM-based aquifers.Further,SEAR in RTM-based aquifers can achieve remediation efficiencies of 66.129%-92.214%with a mean of 84.324%,which is clearly lower than the SEAR efficiency of 70.149%-94.773%(with a mean of 89.122%)in RSPM-based aquifers.Findings are significant for understanding the 3D microstructure of porous media and how the microstructure of porous media affects macroscopic contaminant behaviors and remediation.
文摘Completions and Reservoir Quality are two key attributes that are used to characterize nonconventional hydrocarbon assets.This is because,for optimum exploitation of these unconventional assets,horizontal wells need to be drilled in“Sweet Spots”(i.e.,regions where Completions and Reservoir Quality are both superior).One way to quantify these qualities is to use reservoir and geomechanical properties.These properties can be estimated on a location basis from well logs,and then mapped over terrain using geostatistical modeling.This study presents a‘Sweet Spots’identification workflow based on three performance indexes(Storage Potential Index,Brittleness Index,and Horizontal Stress Index)that can be used to quantify CQ and RQ.The performance indexes are computed from petrophysical property volumes(of Young's Modulus,Bulk Modulus,Shear Modulus,Poisson's Ratio,Minimum Horizontal Stress,Volume of Shale,Total Organic Carbon,Thickness,and Porosity)which are in turn computed from well logs and geostatistical simulation.In the end,the study offers a method to compare the predicted“Sweet Spots”against available production data via their correlation coefficient.The resulting reasonable formation property maps,the successful identification of‘Sweet Spots’,and a correlation coefficient of 0.88(between the predicted“Sweet Spots”and well production data)point to the potential of the proposed effort.
