Groundwater quality is pivotal for sustainable resource management,necessitating comprehen-sive investigation to safeguard this critical resource.This study introduces a novel methodology that inte-grates stiff diagra...Groundwater quality is pivotal for sustainable resource management,necessitating comprehen-sive investigation to safeguard this critical resource.This study introduces a novel methodology that inte-grates stiff diagrams,geostatistical analysis,and geometric computation to delineate the extent of a confined aquifer within the Chahrdoly aquifer,located west of Hamadan,Iran.For the first time,this approach combines these tools to map the boundaries of a confined aquifer based on hydrochemical characteristics.Stiff diagrams were used to calculate geometric parameters from groundwater chemistry data,followed by simulation using a linear model incorporating the semivariogram parameterγ(h).The Root Mean Square Error(RMSE)of the linear model was used to differentiate confined from unconfined aquifers based on hydrochemical signatures.Validation was conducted by generating a cross-sectional hydrogeological layer from well logs,confirming the presence of aquitard layers.The results successufully delineated the confined aquifer's extent,showing strong agreement with hydrogeological log data.By integrating stiff diagrams with semivariogram analysis,this study enhances the understanding of hydrochemical processes,offering a robust framework for groundwater resource identification and management.展开更多
Accurately predicting the powder factor during blasting is essential for sustainable production planning in low-grade mines.This research presents a method for predicting powder factor based on the heterogeneity of ro...Accurately predicting the powder factor during blasting is essential for sustainable production planning in low-grade mines.This research presents a method for predicting powder factor based on the heterogeneity of rock mass rating(RMR).Considering a low-grade metal mine as an example,this study exploited geostatistical methods to obtain independent RMR for each block unit.A three-dimensional spatial distribution model for the powder factor was developed on the basis of the relationships between the RMR and the powder factor.Subsequently,models for blasting cost and mining value were built and employed to optimize the open-pit limit.The multi-variable model based on the RMR performed well in predicting the powder factor,achieving a correlation coefficient of 0.88(root mean square error of 4.3)and considerably outperforming the uniaxial compressive strength model.After model optimization,the mean size and standard deviation of the fragments in the blast pile decreased by 8.5%and 35.1%,respectively,whereas the boulder yield and its standard deviation decreased by 33.3%and 58.8%,respectively.Additionally,optimizing the open-pit limit using this method reduced the amount of rock,increased the amount of ore,and lowered blasting costs,thereby enhancing the economic efficiency of the mine.This study provides valuable insights for blasting design and mining decisions,demonstrating the advantages and potential applications of powder factor prediction based on the heterogeneity of rock mass quality.展开更多
Tight sandstone reservoirs have strong heterogeneity and complex gas-water relationship,causing diffi culty in quantitatively predicting water saturation.Deep learning,combined with rock physics analysis and geostatis...Tight sandstone reservoirs have strong heterogeneity and complex gas-water relationship,causing diffi culty in quantitatively predicting water saturation.Deep learning,combined with rock physics analysis and geostatistics theory,was used to predict water saturation in tight sandstone,focusing on the P_(sh)^(8) in the GFZ area of the Ordos Basin.Results show that:Starting with actual wells where porosity and saturation results are obtained from log interpretations,the relationship between reservoir parameters(porosity and saturation)and elastic properties(P-wave velocity,S-wave velocity,and density)is established through the development of a rock physics model suitable for the region.Under the constraints of geostatistical laws,such as background trends of elastic and reservoir parameters and the vertical variations in logging curves,reservoir conditions(including porosity,saturation,and thickness)are simulated to generate numerous pseudowells and corresponding seismic gathers modeled using the Zoeppritz equation.A convolution neural network is used to train the target curve and predict the target body.The predicted water saturation of the P_(sh)^(8) shows strong agreement with the results from two blind wells,providing a reliable basis for understanding the water saturation(Sw)of tight sandstone.展开更多
The high-resolution nonlinear simultaneous inversion of petrophysical parameters is based on Bayesian statistics and combines petrophysics with geostatistical a priori information. We used the fast Fourier transform–...The high-resolution nonlinear simultaneous inversion of petrophysical parameters is based on Bayesian statistics and combines petrophysics with geostatistical a priori information. We used the fast Fourier transform–moving average（FFT–MA） and gradual deformation method（GDM） to obtain a reasonable variogram by using structural analysis and geostatistical a priori information of petrophysical parameters. Subsequently, we constructed the likelihood function according to the statistical petrophysical model. Finally, we used the Metropolis algorithm to sample the posteriori probability density and complete the inversion of the petrophysical parameters. We used the proposed method to process data from an oil fi eld in China and found good match between inversion and real data with high-resolution. In addition, the direct inversion of petrophysical parameters avoids the error accumulation and decreases the uncertainty, and increases the computational effi ciency.展开更多
[ Objective ] The paper was to study the spatial distribution pattern and spatial correlation of eggs and larvae of Kytorhinus immixtus. [ Method ] By using geostatistical principles and methods, the number of eggs an...[ Objective ] The paper was to study the spatial distribution pattern and spatial correlation of eggs and larvae of Kytorhinus immixtus. [ Method ] By using geostatistical principles and methods, the number of eggs and larvae ofK. immixtus was investigated, and the obtained data were analyzed. [Result]The cir- cular model was the best fitting model for eggs and larvae of/C immixtus, and the spatial distribution pattern was aggregated distribution with a spatial correlation, and their variation ranges were 18.899 -62.922 and 13.464 -47.455. The distribution pattern of eggs and larvae of K.immistus was simulated by using ordinary Kriging method, and the result showed that their distributions had obvious agitated character, the aggregated intensity in the core area of patch was significantly higher than that in the edge. There was anisotropy of aggregation intensity, the aggregation intensity from northeast to southwest direction was significantly higher than that from northwest to southeast direction. [ Conclusion] The spatial distribution pattern of eggs and larvae of K. immixtus was aggregated distribution, and the increase of plant distance and fragmentation of patch had a certain control effect on the occurrence of K. immixtus population.展开更多
Techniques of geostatistics are used to perform traditional statistical analysis and spatial structural analysis with ArcGIS, geostatistical software GS+ and statistical software SPSS in order to obtain the knowledge ...Techniques of geostatistics are used to perform traditional statistical analysis and spatial structural analysis with ArcGIS, geostatistical software GS+ and statistical software SPSS in order to obtain the knowledge of characteristics of distribution and spatial variability of soil nutrients in different parts of Zhongxiang, Hubei Province. Some skewed values appeared during the analyses. To decrease the influence of those skewed values, domain processing and Box-Cox transformation were used. The results indicated spatial variability of Total N, Avail. P, rapidly-available potassium (R-Avail. K) and effective zinc (Effect. Zn) was strong, that of organic carbon (Org. C), effective molybdenum (Effect. Mo) and effective copper (Effect. Cu) was medium while that of others was weak. Fitted model of Total N, R-Avail. K and Effect. Mo was spherical model, that of Org. C and Effect. Zn was exponential model, while fitted model of Avail. P and Effect. Cu was Gaussian model. Ratio of variability caused by random factors to overall variability was large. What’s more, the ranges of spatial autocorrelation of soil nutrients had much difference. The smallest value was 3600 m in Effect. Zn while the largest was 77970 m in Org. C. Other characteristics were also included. The study is helpful to soil sampling design, to make people realize the influence of Han River to spatial variability of soil nutrients in this area, and to spatial interpolation and mapping.展开更多
There are 71 surface sediment samples collected from the eastern Beibu Gulf. The moment parameters （i.e. mean size, sorting and skewness） were obtained after applying grain size analysis. The geostatistical analysis...There are 71 surface sediment samples collected from the eastern Beibu Gulf. The moment parameters （i.e. mean size, sorting and skewness） were obtained after applying grain size analysis. The geostatistical analysis was then applied to study the spatial autocorrelation for these parameters; while range, a parameter in the semivariogram that meters the scale of spatial autocorrelation, was estimated. The results indicated that the range for sorting coefficient was physically meaningful. The trend vectors calculated from grain size trend analysis model were consistent with the annual ocean circulation patterns and sediment transport rates according to previous studies. Therefore the range derived from the semivariogram of mean size can be used as the characteristic distance in the grain size trend analysis, which may remove the bias caused by the traditional way of basing on experiences or testing methods to get the characteristic distance. Hence the results from geostatistical analysis can also offer useful information for the determination of sediment sampling density in the future field work.展开更多
Investigation was made into sediment depth at 723 irregularly scattered measurement points which cover all the regions in Taihu Lake, China. The combination of successive correction scheme and geostatistical method wa...Investigation was made into sediment depth at 723 irregularly scattered measurement points which cover all the regions in Taihu Lake, China. The combination of successive correction scheme and geostatistical method was used to get all the values of recent sediment thickness at the 69×69 grids in the whole lake. The results showed that there is the significant difference in sediment depth between the eastern area and the western region, and most of the sediments are located in the western shore-line and northern regimes but just a little in the center and eastern parts. The notable exception is the patch between the center and Xishan Island where the maximum sediment depth is more than 4.0 m. This sediment distribution pattern is more than likely related to the current circulation pattern induced by the prevailing wind-forcing in Taihu Lake. The numerical simulation of hydrodynamics can strong support the conclusion. Sediment effects on water quality was also studied and the results showed that the concentrations of TP, TN and SS in the western part are obviously larger than those in the eastern regime, which suggested that more nutrients can be released from thicker sediment areas.展开更多
The mid-subtropical forest is one of the biggest sections of subtropical forest in China and plays a vital role in mitigating climate change by sequestering carbon.Studies have examined carbon storage density(CSD) dis...The mid-subtropical forest is one of the biggest sections of subtropical forest in China and plays a vital role in mitigating climate change by sequestering carbon.Studies have examined carbon storage density(CSD) distribution in temperate forests. However, our knowledge of CSD in subtropical forests is limited. In this study, Jiangle County was selected as a study case to explore geographic variation in CSD. A spatial heterogeneity analysis by semivariogram revealed that CSD varied at less than the mesoscale(approximately 2000–3000 m). CSD distribution mapped using Kriging regression revealed an increasing trend in CSD from west to east of the study area.Global spatial autocorrelation analysis indicated that CSD was clustered at the village level(at 5% significance).Some areas with local spatial autocorrelation were detected by Anselin Local Moran's I and Getis-Ord G*. A geographically weighted regression model showed different impacts on the different areas for each determinant. Generally, diameter at breast height, tree height, and stand density had positive correlation with CSD in Jiangle County, but varied substantially in magnitude by location.In contrast, coefficients of elevation and slope ranged from negative to positive. Based on these results, we propose certain measures to increase forest carbon storage,including increasing forested area, improving the quality of the current forests, and promoting reasonable forest management decisions and harvesting strategies. The established CSD model emphasizes the important role of midsubtropical forest in carbon sequestration and provides useful information for quantifying mid-subtropical forest carbon storage.展开更多
Dongguan （东莞） City, located in the Pearl River Delta, South China, is famous for its rapid industrialization in the past 30 years. A total of 90 topsoil samples have been collected from agricultural fields, includ...Dongguan （东莞） City, located in the Pearl River Delta, South China, is famous for its rapid industrialization in the past 30 years. A total of 90 topsoil samples have been collected from agricultural fields, including vegetable and orchard soils in the city, and eight heavy metals （As, Cu, Cd, Cr, Hg, Ni, Pb, and Zn） and other items （pH values and organic matter） have been analyzed, to evaluate the influence of anthropic activities on the environmental quality of agricultural soils and to identify the spatial distribution of trace elements and possible sources of trace elements. The elements Hg, Pb, and Cd have accumulated remarkably here, incomparison with the soil background content of elements in Guangdong （广东） Province. Pollution is more serious in the western plain and the central region, which are heavily distributed with industries and rivers. Multivariate and geostatistical methods have been applied to differentiate the influences of natural processes and human activities on the pollution of heavy metals in topsoils in the study area. The results of cluster analysis （CA） and factor analysis （FA） show that Ni, Cr, Cu, Zn, and As are grouped in factor F1, Pb in F2, and Cd and Hg in F3, respectively. The spatial pattern of the three factors may be well demonstrated by geostatistical analysis. It is shown that the first factor could be considered as a natural source controlled by parent rocks. The second factor could be referred to as ＂industrial and traffic pollution sources＂. The source of the third factor is mainly controlled by long-term anthropic activities, as a consequence of agricultural activities, fossil fuel consumption, and atmospheric deposition.展开更多
In this study,the analytical data set of 26 groundwater samples from the alluvial aquifer of Boumerzoug-E1 khroub valley has been processed simultaneously with Multivariate analysis,geostatistical modeling,WQI,and geo...In this study,the analytical data set of 26 groundwater samples from the alluvial aquifer of Boumerzoug-E1 khroub valley has been processed simultaneously with Multivariate analysis,geostatistical modeling,WQI,and geochemical modeling.Cluster analysis identified three main water types based on the major ion contents,where mineralization increased from group 1 to group 3.These groups were confirmed by FA/PCA,which demonstrated that groundwater quality is influenced by geochemical processes(water-rock interaction)and human practice(irrigation).The exponential semivariogram model WQI.Groundwater chemistry has a strong spatial structure for Mg,Na,Cl,and NO3,and a moderate spatial structure for EC,Ca,K,HCO3,and SO4.Water quality maps generated using ordinary Kriging are consistent with the HCA and PCA results.All water groups are supersaturated with respect to carbonate minerals,and dissolution of kaolinite and Ca-smectite is one of the processes responsible for hydrochemical evolution in the area.展开更多
On the basis of local measurements of hydraulic conductivity, geostatistical methods have been found to be useful in heterogeneity characterization of a hydraulic conductivity field on a regional scale. However, the m...On the basis of local measurements of hydraulic conductivity, geostatistical methods have been found to be useful in heterogeneity characterization of a hydraulic conductivity field on a regional scale. However, the methods are not suited to directly integrate dynamic production data, such as, hydraulic head and solute concentration, into the study of conductivity distribution. These data, which record the flow and transport processes in the medium, are closely related to the spatial distribution of hydraulic conductivity. In this study, a three-dimensional gradient-based inverse method--the sequential self-calibration （SSC） method--is developed to calibrate a hydraulic conductivity field, initially generated by a geostatistical simulation method, conditioned on tracer test results. The SSC method can honor both local hydraulic conductivity measurements and tracer test data. The mismatch between the simulated hydraulic conductivity field and the reference true one, measured by its mean square error （MSE）, is reduced through the SSC conditional study. In comparison with the unconditional results, the SSC conditional study creates the mean breakthrough curve much closer to the reference true curve, and significantly reduces the prediction uncertainty of the solute transport in the observed locations. Further, the reduction of uncertainty is spatially dependent, which indicates that good locations, geological structure, and boundary conditions will affect the efficiency of the SSC study results.展开更多
Mining projects especially relating to limestone deposits require an accurate knowledge of tonnage and grade,for both short and long-term planning.This is often difficult to establish as detailed exploration operation...Mining projects especially relating to limestone deposits require an accurate knowledge of tonnage and grade,for both short and long-term planning.This is often difficult to establish as detailed exploration operations,which are required to get the accurate description of the deposit,are costly and time consuming.Geologists and mining engineers usually make use of geometric and geostatistical methods,for estimating the tonnage and grade of ore reserves.However,explicit assessments into the differences between these methods have not been reported in literature.To bridge this research gap,a comparative study is carried out to compare the qualitative reserve of Oyo-Iwa limestone deposit located in Nigeria,using geometric and geostatistical methods.The geometric method computes the reserve of the limestone deposit as 74,536,820 t(mean calcite,CaO grade=52.15)and 99,674,793 t(mean calcite,CaO grade=52.32),for the Northern and Southern zones of the deposit,respectively.On the other hand,the geostatistical method calculates the reserve as 81,626,729.65 t(mean calcite,CaO grade=53.36)and 100,098,697.46 t(mean calcite,CaO grade=52.96),for the two zones,respectively.The small relative difference in tonnage estimation between the two methods(i.e.,9.51%and 0.43%),proves that the geometric method is effective for tonnage estimation.In contrast,the relative difference in grade estimation between the two methods(i.e.,2.32%and 1.26%)is not negligible,and could be crucial in maintaining the profitability of the project.The geostatistical method is,therefore,more suitable,reliable and preferable for grade estimation,since it involves the use of spatial modelling and cross-validated interpolation.In addition,the geostatistical method is used to produce quality maps and three-dimensional(3-D)perspective view of the limestone deposit.The quality maps and 3-D view of the limestone deposit reveal the variability of the limestone grade within the deposit,and it is useful for operational management of the limestone raw materials.The qualitative mapping of the limestone deposit is key to effective production scheduling and accurate projection of raw materials for cement production.展开更多
Spatial patterns of soil fertility parameters and other extrinsic factors need to be identified to develop farming practices that match agricultural inputs with local crop needs. Little is known about the spatial stru...Spatial patterns of soil fertility parameters and other extrinsic factors need to be identified to develop farming practices that match agricultural inputs with local crop needs. Little is known about the spatial structure of nutrition in Iran. The present study was conducted in a 132-ha field located in central Iran. Soil samples were collected at 0-30 cm depth and were then analyzed for total nitrogen （N）, available phosphorus （P）, available potassium （K）, available copper （Cu）, available zinc （Zn）, available iron （Fe） and available manganese （Mn）. The results showed that the contents of soil organic matter, Cu and Zn in Marvdasht＇s farms were low. The spatial distribution model and spatial dependence level for soil chemical properties varied in the field. N, K, carbonate calcium equivalent （CaCO3） and electrical conductivity （EC） data indicated the existence of moderate spatial dependence. The variograms for other variables revealed stronger spatial structure. The results showed a longer range value for available P （480 m）, followed by total N （429 m）. The value of other chemical properties values showed a shorter range （128 to 174 m）. Clear patchy distribution of N, P, K, Fe, Mn, Cu and Zn were found from their spatial distribution maps. This proved that sampling strategy for estimating variability should be adapted to the different soil chemical properties and field management. Therefore, the spatial variability of soil chemical properties with strong spatial dependence could be readily managed and a site-specific fertilization scheme for precision farming could be easily developed.展开更多
In this research, a method called ANNMG is presented to integrate Artificial Neural Networks and Geostatistics for optimum mineral reserve evaluation. The word ANNMG simply means Artificial Neural Network Model integr...In this research, a method called ANNMG is presented to integrate Artificial Neural Networks and Geostatistics for optimum mineral reserve evaluation. The word ANNMG simply means Artificial Neural Network Model integrated with Geostatiscs, In this procedure, the Artificial Neural Network was trained, tested and validated using assay values obtained from exploratory drillholes. Next, the validated model was used to generalize mineral grades at known and unknown sampled locations inside the drilling region respectively. Finally, the reproduced and generalized assay values were combined and fed to geostatistics in order to develop a geological 3D block model. The regression analysis revealed that the predicted sample grades were in close proximity to the actual sample grades, The generalized grades from the ANNMG show that this process could be used to complement exploration activities thereby reducing drilling requirement. It could also be an effective mineral reserve evaluation method that could oroduce optimum block model for mine design.展开更多
Variability maps of Hydraulic conductivity (K) were generated by using geo statistical analyst extension of ARC GIS for delineating compact zones in a farm. In the initial exploratory spatial data analysis, K data for...Variability maps of Hydraulic conductivity (K) were generated by using geo statistical analyst extension of ARC GIS for delineating compact zones in a farm. In the initial exploratory spatial data analysis, K data for 0 - 15 and 15 - 30 cm soil layers showed spatial dependence, anisotropy, normality on log transformation and linear trend. Outliers present in both layers were also removed. In the next step, cross validation statistics of different combinations of kriging (Ordinary, simple and universal), data transformations (none and logarithmic) and trends (none and linear) were compared. Combination of no data transformation and linear trend removal was the best choice as it resulted in more accurate and unbiased prediction. It thus, confirmed that for generating prediction maps by kriging, data need not be normal. Ordinary kriging is appropriate when trend is linear. Among various available anisotropic semivariogram models, spherical model for 0 - 15 cm and tetra spherical model for 15 - 30 cm were found to be the best with major and minor ranges between 273 - 410 m and 98 - 213 m. The kriging was superior to other interpolation techniques as the slope of the best fit line of scatter plot of predicted vs. measured data points was more (0.76) in kriging than in inverse distance weighted interpolation (0.61) and global polynomial interpolation (0.56). In the generated prediction maps, areas where K was <12 cm?day–1 were delineated as compact zone. Hence, it can be concluded that geostatistical analyst is a complete package for preprocessing of data and for choosing the optimal interpolation strategies.展开更多
An attempt to estimate the reserves in the High Phosphorous stockpile （HP） at the Choghart Iron mine of Iran was carded out using geostatistical modeling. Grade and tonnage estimates of ore stockpiles can help conve...An attempt to estimate the reserves in the High Phosphorous stockpile （HP） at the Choghart Iron mine of Iran was carded out using geostatistical modeling. Grade and tonnage estimates of ore stockpiles can help convert them into a valuable ore reserve. This is valuable in consideration of increasing metal demand, and the depletion of in situ ore reserves, around the world. Estimation of reserves in stockpiles is difficult partly because of geological and grade discontinuities created during the dumping of the ore piles. Data input for the HP stockpile at Choghart was performed based upon pre-existing information gathered during extraction from the various mining benches. After establishing the input data files the reserve estimates were found using geostatistical methods aided by the international mining software SURPAC. The stockpile was divided in to three domains and the reserves in each domain were estimated separately. A grade block model was used to compute the reserve. Fe% and P% were estimated using the Ordinary Kriging method. The results showed that the total tonnage of the HP stockpile is 4.5 million tons with an average zrade of 55% Fe and 1.03% P.展开更多
In order to comprehend temporal pattern of the larvae population of the yellow rice borer, Tryporyza incertulas, and provide valuable information for its forecast model, the data series of the population for each gene...In order to comprehend temporal pattern of the larvae population of the yellow rice borer, Tryporyza incertulas, and provide valuable information for its forecast model, the data series of the population for each generation and the over-wintered larvae from 1960 to 1990 in Dingcheng District, Changde City, Hunan Province, were analyzed with geostatistics. The data series of total number, the 1st generation, the 3rd generation and the over-wintered larvae year to year displayed rather better autocorrelation and prediction. The data series of generation to generation, the 2nd generation and the 4th generation year to year, however, demonstrated poor autocorrelation, especially for the 4th generation, whose autocorrelation degree was zero. The population dynamics of the yellow rice borer was obviously intermittent. A remarkable cycle of four generations, one year, was observed in the population of generation to generation. Omitting the certain generation or interposing the over-wintered larvae only resulted in a less or slight change of autocorrelation of the whole data series generation to generation. Crop system, food, climate and natural enemies, therefore, played more important roles in regulating the population dynamics than base number of the larvae. The basic techniques of geostatistics applied in analyzing temporal population dynamics were outlined.展开更多
The study of temporal and spatial variations of nitrate in groundwater under different soil nitrogen environments is helpful to the security of groundwater resources in agricultural areas.In this paper,based on 320 gr...The study of temporal and spatial variations of nitrate in groundwater under different soil nitrogen environments is helpful to the security of groundwater resources in agricultural areas.In this paper,based on 320 groups of soil and groundwater samples collected at the same time,geostatistical analysis and multiple regression analysis were comprehensively used to conduct the evaluation of nitrogen contents in both groundwater and soil.From May to August,as the nitrification of groundwater is dominant,the average concentration of nitrate nitrogen is 34.80 mg/L;The variation of soil ammonia nitrogen and nitrate nitrogen is moderate from May to July,and the variation coefficient decreased sharply and then increased in August.There is a high correlation between the nitrate nitrogen in groundwater and soil in July,and there is a high correlation between the nitrate nitrogen in groundwater and ammonium nitrogen in soil in August and nitrate nitrogen in soil in July.From May to August,the area of low groundwater nitrate nitrogen in 0-5 mg/L and 5-10 mg/L decreased from 10.97%to 0,and the proportion of high-value area(greater than 70 mg/L)increased from 21.19%to 27.29%.Nitrate nitrogen is the main factor affecting the quality of groundwater.The correlation analysis of nitrate nitrogen in groundwater,nitrate nitrogen in soil and ammonium nitrogen shows that they have a certain period of delay.The areas with high concentration of nitrate in groundwater are mainly concentrated in the western part of the study area,which has a high consistency with the high value areas of soil nitrate distribution from July to August,and a high difference with the spatial position of soil ammonia nitrogen distribution in August.展开更多
文摘Groundwater quality is pivotal for sustainable resource management,necessitating comprehen-sive investigation to safeguard this critical resource.This study introduces a novel methodology that inte-grates stiff diagrams,geostatistical analysis,and geometric computation to delineate the extent of a confined aquifer within the Chahrdoly aquifer,located west of Hamadan,Iran.For the first time,this approach combines these tools to map the boundaries of a confined aquifer based on hydrochemical characteristics.Stiff diagrams were used to calculate geometric parameters from groundwater chemistry data,followed by simulation using a linear model incorporating the semivariogram parameterγ(h).The Root Mean Square Error(RMSE)of the linear model was used to differentiate confined from unconfined aquifers based on hydrochemical signatures.Validation was conducted by generating a cross-sectional hydrogeological layer from well logs,confirming the presence of aquitard layers.The results successufully delineated the confined aquifer's extent,showing strong agreement with hydrogeological log data.By integrating stiff diagrams with semivariogram analysis,this study enhances the understanding of hydrochemical processes,offering a robust framework for groundwater resource identification and management.
基金supported by the National Key Research and Development Program of China(No.2022YFC2903902)the National Natural Science Foundation of China(Nos.52204080and 52174070)the Fundamental Research Funds for the Central Universities of China(No.2023GFYD17)。
文摘Accurately predicting the powder factor during blasting is essential for sustainable production planning in low-grade mines.This research presents a method for predicting powder factor based on the heterogeneity of rock mass rating(RMR).Considering a low-grade metal mine as an example,this study exploited geostatistical methods to obtain independent RMR for each block unit.A three-dimensional spatial distribution model for the powder factor was developed on the basis of the relationships between the RMR and the powder factor.Subsequently,models for blasting cost and mining value were built and employed to optimize the open-pit limit.The multi-variable model based on the RMR performed well in predicting the powder factor,achieving a correlation coefficient of 0.88(root mean square error of 4.3)and considerably outperforming the uniaxial compressive strength model.After model optimization,the mean size and standard deviation of the fragments in the blast pile decreased by 8.5%and 35.1%,respectively,whereas the boulder yield and its standard deviation decreased by 33.3%and 58.8%,respectively.Additionally,optimizing the open-pit limit using this method reduced the amount of rock,increased the amount of ore,and lowered blasting costs,thereby enhancing the economic efficiency of the mine.This study provides valuable insights for blasting design and mining decisions,demonstrating the advantages and potential applications of powder factor prediction based on the heterogeneity of rock mass quality.
基金Supported by:CNPC Major Project "Research on Key Technologies for Enhanced Oil Recovery in Tight Sandstone Gas Reservoirs"(No. 2023ZZ25)Gansu Provincial Science and Technology Major Project"Research and Application of Key Technologies for Geophysical Prediction of Natural Gas Reservoirs in Longdong Area"(No. 23ZDGA004)PetroChina Changqing Oilfield Company'Qingshimao gas field water-bearing gas reservoir 3D seismic fine interpretation and well position support'(No.2023QCPJ33)。
文摘Tight sandstone reservoirs have strong heterogeneity and complex gas-water relationship,causing diffi culty in quantitatively predicting water saturation.Deep learning,combined with rock physics analysis and geostatistics theory,was used to predict water saturation in tight sandstone,focusing on the P_(sh)^(8) in the GFZ area of the Ordos Basin.Results show that:Starting with actual wells where porosity and saturation results are obtained from log interpretations,the relationship between reservoir parameters(porosity and saturation)and elastic properties(P-wave velocity,S-wave velocity,and density)is established through the development of a rock physics model suitable for the region.Under the constraints of geostatistical laws,such as background trends of elastic and reservoir parameters and the vertical variations in logging curves,reservoir conditions(including porosity,saturation,and thickness)are simulated to generate numerous pseudowells and corresponding seismic gathers modeled using the Zoeppritz equation.A convolution neural network is used to train the target curve and predict the target body.The predicted water saturation of the P_(sh)^(8) shows strong agreement with the results from two blind wells,providing a reliable basis for understanding the water saturation(Sw)of tight sandstone.
基金sponsored by the National Basic Research Program of China(No.2013CB228604)the Major National Science and Technology Projects(No.2011ZX05009)+1 种基金the Natural Science Foundation of Shandong Province(No.ZR2011DQ013)the National Science Foundation of China(No.41204085)
文摘The high-resolution nonlinear simultaneous inversion of petrophysical parameters is based on Bayesian statistics and combines petrophysics with geostatistical a priori information. We used the fast Fourier transform–moving average（FFT–MA） and gradual deformation method（GDM） to obtain a reasonable variogram by using structural analysis and geostatistical a priori information of petrophysical parameters. Subsequently, we constructed the likelihood function according to the statistical petrophysical model. Finally, we used the Metropolis algorithm to sample the posteriori probability density and complete the inversion of the petrophysical parameters. We used the proposed method to process data from an oil fi eld in China and found good match between inversion and real data with high-resolution. In addition, the direct inversion of petrophysical parameters avoids the error accumulation and decreases the uncertainty, and increases the computational effi ciency.
基金Supported by National Natural Science Foundation of China(30760045)Natural Science Foundation of Ninxia(NZ0926)~~
文摘[ Objective ] The paper was to study the spatial distribution pattern and spatial correlation of eggs and larvae of Kytorhinus immixtus. [ Method ] By using geostatistical principles and methods, the number of eggs and larvae ofK. immixtus was investigated, and the obtained data were analyzed. [Result]The cir- cular model was the best fitting model for eggs and larvae of/C immixtus, and the spatial distribution pattern was aggregated distribution with a spatial correlation, and their variation ranges were 18.899 -62.922 and 13.464 -47.455. The distribution pattern of eggs and larvae of K.immistus was simulated by using ordinary Kriging method, and the result showed that their distributions had obvious agitated character, the aggregated intensity in the core area of patch was significantly higher than that in the edge. There was anisotropy of aggregation intensity, the aggregation intensity from northeast to southwest direction was significantly higher than that from northwest to southeast direction. [ Conclusion] The spatial distribution pattern of eggs and larvae of K. immixtus was aggregated distribution, and the increase of plant distance and fragmentation of patch had a certain control effect on the occurrence of K. immixtus population.
文摘Techniques of geostatistics are used to perform traditional statistical analysis and spatial structural analysis with ArcGIS, geostatistical software GS+ and statistical software SPSS in order to obtain the knowledge of characteristics of distribution and spatial variability of soil nutrients in different parts of Zhongxiang, Hubei Province. Some skewed values appeared during the analyses. To decrease the influence of those skewed values, domain processing and Box-Cox transformation were used. The results indicated spatial variability of Total N, Avail. P, rapidly-available potassium (R-Avail. K) and effective zinc (Effect. Zn) was strong, that of organic carbon (Org. C), effective molybdenum (Effect. Mo) and effective copper (Effect. Cu) was medium while that of others was weak. Fitted model of Total N, R-Avail. K and Effect. Mo was spherical model, that of Org. C and Effect. Zn was exponential model, while fitted model of Avail. P and Effect. Cu was Gaussian model. Ratio of variability caused by random factors to overall variability was large. What’s more, the ranges of spatial autocorrelation of soil nutrients had much difference. The smallest value was 3600 m in Effect. Zn while the largest was 77970 m in Org. C. Other characteristics were also included. The study is helpful to soil sampling design, to make people realize the influence of Han River to spatial variability of soil nutrients in this area, and to spatial interpolation and mapping.
基金Chinese Offshore Investigation and Assessment Project, No.908-01-ST09 State Student Innovation Training Project, No.SIT-05+1 种基金 Program for New Century Excellent Talents, No.NCET-06-0446 National Natural Science Foundation of China, No.J0630535 Acknowledgement The research vessel Experiment 2 （South China Sea Institute of Oceanology, Chinese Academy of Sciences） performed the field survey and Prof. Lizhe Cai and his colleagues help to collect the sediment samples. Prof. Shu Gao and Asso. Prof. Yongzhan Zhang have provided a lot of support and valuable suggestions for this study. Miss Xiaoqin Du helped with sediment transportation and Mr. Fengyang Min assisted in the operation of related software. The comments from Dr. M. Xia （Great Lakes Environmental Research Laboratory, NOAA, USA） have improved a lot in the presentation of the paper.
文摘There are 71 surface sediment samples collected from the eastern Beibu Gulf. The moment parameters （i.e. mean size, sorting and skewness） were obtained after applying grain size analysis. The geostatistical analysis was then applied to study the spatial autocorrelation for these parameters; while range, a parameter in the semivariogram that meters the scale of spatial autocorrelation, was estimated. The results indicated that the range for sorting coefficient was physically meaningful. The trend vectors calculated from grain size trend analysis model were consistent with the annual ocean circulation patterns and sediment transport rates according to previous studies. Therefore the range derived from the semivariogram of mean size can be used as the characteristic distance in the grain size trend analysis, which may remove the bias caused by the traditional way of basing on experiences or testing methods to get the characteristic distance. Hence the results from geostatistical analysis can also offer useful information for the determination of sediment sampling density in the future field work.
文摘Investigation was made into sediment depth at 723 irregularly scattered measurement points which cover all the regions in Taihu Lake, China. The combination of successive correction scheme and geostatistical method was used to get all the values of recent sediment thickness at the 69×69 grids in the whole lake. The results showed that there is the significant difference in sediment depth between the eastern area and the western region, and most of the sediments are located in the western shore-line and northern regimes but just a little in the center and eastern parts. The notable exception is the patch between the center and Xishan Island where the maximum sediment depth is more than 4.0 m. This sediment distribution pattern is more than likely related to the current circulation pattern induced by the prevailing wind-forcing in Taihu Lake. The numerical simulation of hydrodynamics can strong support the conclusion. Sediment effects on water quality was also studied and the results showed that the concentrations of TP, TN and SS in the western part are obviously larger than those in the eastern regime, which suggested that more nutrients can be released from thicker sediment areas.
基金supported by Science and Technology Major Project of the Hall of Science and Technology of Fujian (No. 2012NZ0001)the Project of National Natural Science Fund of China (No.30671664)
文摘The mid-subtropical forest is one of the biggest sections of subtropical forest in China and plays a vital role in mitigating climate change by sequestering carbon.Studies have examined carbon storage density(CSD) distribution in temperate forests. However, our knowledge of CSD in subtropical forests is limited. In this study, Jiangle County was selected as a study case to explore geographic variation in CSD. A spatial heterogeneity analysis by semivariogram revealed that CSD varied at less than the mesoscale(approximately 2000–3000 m). CSD distribution mapped using Kriging regression revealed an increasing trend in CSD from west to east of the study area.Global spatial autocorrelation analysis indicated that CSD was clustered at the village level(at 5% significance).Some areas with local spatial autocorrelation were detected by Anselin Local Moran's I and Getis-Ord G*. A geographically weighted regression model showed different impacts on the different areas for each determinant. Generally, diameter at breast height, tree height, and stand density had positive correlation with CSD in Jiangle County, but varied substantially in magnitude by location.In contrast, coefficients of elevation and slope ranged from negative to positive. Based on these results, we propose certain measures to increase forest carbon storage,including increasing forested area, improving the quality of the current forests, and promoting reasonable forest management decisions and harvesting strategies. The established CSD model emphasizes the important role of midsubtropical forest in carbon sequestration and provides useful information for quantifying mid-subtropical forest carbon storage.
基金supported by the Ministry of Land and Resources of China (No. [2005]011-16)State Environment Protection Administration of China (No. 2001-1-2)+2 种基金State Key Laboratory of Geological Processes and Mineral Resources, China University of Geosciencesthe Guangdong Provincial Office of SciencesTechnology via NSF Team Project and Key Project (Nos. 06202438, 2004A3030800)
文摘Dongguan （东莞） City, located in the Pearl River Delta, South China, is famous for its rapid industrialization in the past 30 years. A total of 90 topsoil samples have been collected from agricultural fields, including vegetable and orchard soils in the city, and eight heavy metals （As, Cu, Cd, Cr, Hg, Ni, Pb, and Zn） and other items （pH values and organic matter） have been analyzed, to evaluate the influence of anthropic activities on the environmental quality of agricultural soils and to identify the spatial distribution of trace elements and possible sources of trace elements. The elements Hg, Pb, and Cd have accumulated remarkably here, incomparison with the soil background content of elements in Guangdong （广东） Province. Pollution is more serious in the western plain and the central region, which are heavily distributed with industries and rivers. Multivariate and geostatistical methods have been applied to differentiate the influences of natural processes and human activities on the pollution of heavy metals in topsoils in the study area. The results of cluster analysis （CA） and factor analysis （FA） show that Ni, Cr, Cu, Zn, and As are grouped in factor F1, Pb in F2, and Cd and Hg in F3, respectively. The spatial pattern of the three factors may be well demonstrated by geostatistical analysis. It is shown that the first factor could be considered as a natural source controlled by parent rocks. The second factor could be referred to as ＂industrial and traffic pollution sources＂. The source of the third factor is mainly controlled by long-term anthropic activities, as a consequence of agricultural activities, fossil fuel consumption, and atmospheric deposition.
文摘In this study,the analytical data set of 26 groundwater samples from the alluvial aquifer of Boumerzoug-E1 khroub valley has been processed simultaneously with Multivariate analysis,geostatistical modeling,WQI,and geochemical modeling.Cluster analysis identified three main water types based on the major ion contents,where mineralization increased from group 1 to group 3.These groups were confirmed by FA/PCA,which demonstrated that groundwater quality is influenced by geochemical processes(water-rock interaction)and human practice(irrigation).The exponential semivariogram model WQI.Groundwater chemistry has a strong spatial structure for Mg,Na,Cl,and NO3,and a moderate spatial structure for EC,Ca,K,HCO3,and SO4.Water quality maps generated using ordinary Kriging are consistent with the HCA and PCA results.All water groups are supersaturated with respect to carbonate minerals,and dissolution of kaolinite and Ca-smectite is one of the processes responsible for hydrochemical evolution in the area.
基金This study is partially supported by the Program of Outstanding Overseas Youth Chinese Scholar,the National Natural Science Foundation of China (No. 40528003)partially supported by USA National Science Foundation.
文摘On the basis of local measurements of hydraulic conductivity, geostatistical methods have been found to be useful in heterogeneity characterization of a hydraulic conductivity field on a regional scale. However, the methods are not suited to directly integrate dynamic production data, such as, hydraulic head and solute concentration, into the study of conductivity distribution. These data, which record the flow and transport processes in the medium, are closely related to the spatial distribution of hydraulic conductivity. In this study, a three-dimensional gradient-based inverse method--the sequential self-calibration （SSC） method--is developed to calibrate a hydraulic conductivity field, initially generated by a geostatistical simulation method, conditioned on tracer test results. The SSC method can honor both local hydraulic conductivity measurements and tracer test data. The mismatch between the simulated hydraulic conductivity field and the reference true one, measured by its mean square error （MSE）, is reduced through the SSC conditional study. In comparison with the unconditional results, the SSC conditional study creates the mean breakthrough curve much closer to the reference true curve, and significantly reduces the prediction uncertainty of the solute transport in the observed locations. Further, the reduction of uncertainty is spatially dependent, which indicates that good locations, geological structure, and boundary conditions will affect the efficiency of the SSC study results.
文摘Mining projects especially relating to limestone deposits require an accurate knowledge of tonnage and grade,for both short and long-term planning.This is often difficult to establish as detailed exploration operations,which are required to get the accurate description of the deposit,are costly and time consuming.Geologists and mining engineers usually make use of geometric and geostatistical methods,for estimating the tonnage and grade of ore reserves.However,explicit assessments into the differences between these methods have not been reported in literature.To bridge this research gap,a comparative study is carried out to compare the qualitative reserve of Oyo-Iwa limestone deposit located in Nigeria,using geometric and geostatistical methods.The geometric method computes the reserve of the limestone deposit as 74,536,820 t(mean calcite,CaO grade=52.15)and 99,674,793 t(mean calcite,CaO grade=52.32),for the Northern and Southern zones of the deposit,respectively.On the other hand,the geostatistical method calculates the reserve as 81,626,729.65 t(mean calcite,CaO grade=53.36)and 100,098,697.46 t(mean calcite,CaO grade=52.96),for the two zones,respectively.The small relative difference in tonnage estimation between the two methods(i.e.,9.51%and 0.43%),proves that the geometric method is effective for tonnage estimation.In contrast,the relative difference in grade estimation between the two methods(i.e.,2.32%and 1.26%)is not negligible,and could be crucial in maintaining the profitability of the project.The geostatistical method is,therefore,more suitable,reliable and preferable for grade estimation,since it involves the use of spatial modelling and cross-validated interpolation.In addition,the geostatistical method is used to produce quality maps and three-dimensional(3-D)perspective view of the limestone deposit.The quality maps and 3-D view of the limestone deposit reveal the variability of the limestone grade within the deposit,and it is useful for operational management of the limestone raw materials.The qualitative mapping of the limestone deposit is key to effective production scheduling and accurate projection of raw materials for cement production.
基金the Soil Science Lab in the Department of Soil Sciences, Ramin Universitysupported by funds from Ramin University
文摘Spatial patterns of soil fertility parameters and other extrinsic factors need to be identified to develop farming practices that match agricultural inputs with local crop needs. Little is known about the spatial structure of nutrition in Iran. The present study was conducted in a 132-ha field located in central Iran. Soil samples were collected at 0-30 cm depth and were then analyzed for total nitrogen （N）, available phosphorus （P）, available potassium （K）, available copper （Cu）, available zinc （Zn）, available iron （Fe） and available manganese （Mn）. The results showed that the contents of soil organic matter, Cu and Zn in Marvdasht＇s farms were low. The spatial distribution model and spatial dependence level for soil chemical properties varied in the field. N, K, carbonate calcium equivalent （CaCO3） and electrical conductivity （EC） data indicated the existence of moderate spatial dependence. The variograms for other variables revealed stronger spatial structure. The results showed a longer range value for available P （480 m）, followed by total N （429 m）. The value of other chemical properties values showed a shorter range （128 to 174 m）. Clear patchy distribution of N, P, K, Fe, Mn, Cu and Zn were found from their spatial distribution maps. This proved that sampling strategy for estimating variability should be adapted to the different soil chemical properties and field management. Therefore, the spatial variability of soil chemical properties with strong spatial dependence could be readily managed and a site-specific fertilization scheme for precision farming could be easily developed.
基金the management of Sierra Rutile Company for providing the drillhole dataset used in this studythe Japanese Ministry of Education Science and Technology (MEXT) Scholarship for academic funding
文摘In this research, a method called ANNMG is presented to integrate Artificial Neural Networks and Geostatistics for optimum mineral reserve evaluation. The word ANNMG simply means Artificial Neural Network Model integrated with Geostatiscs, In this procedure, the Artificial Neural Network was trained, tested and validated using assay values obtained from exploratory drillholes. Next, the validated model was used to generalize mineral grades at known and unknown sampled locations inside the drilling region respectively. Finally, the reproduced and generalized assay values were combined and fed to geostatistics in order to develop a geological 3D block model. The regression analysis revealed that the predicted sample grades were in close proximity to the actual sample grades, The generalized grades from the ANNMG show that this process could be used to complement exploration activities thereby reducing drilling requirement. It could also be an effective mineral reserve evaluation method that could oroduce optimum block model for mine design.
文摘Variability maps of Hydraulic conductivity (K) were generated by using geo statistical analyst extension of ARC GIS for delineating compact zones in a farm. In the initial exploratory spatial data analysis, K data for 0 - 15 and 15 - 30 cm soil layers showed spatial dependence, anisotropy, normality on log transformation and linear trend. Outliers present in both layers were also removed. In the next step, cross validation statistics of different combinations of kriging (Ordinary, simple and universal), data transformations (none and logarithmic) and trends (none and linear) were compared. Combination of no data transformation and linear trend removal was the best choice as it resulted in more accurate and unbiased prediction. It thus, confirmed that for generating prediction maps by kriging, data need not be normal. Ordinary kriging is appropriate when trend is linear. Among various available anisotropic semivariogram models, spherical model for 0 - 15 cm and tetra spherical model for 15 - 30 cm were found to be the best with major and minor ranges between 273 - 410 m and 98 - 213 m. The kriging was superior to other interpolation techniques as the slope of the best fit line of scatter plot of predicted vs. measured data points was more (0.76) in kriging than in inverse distance weighted interpolation (0.61) and global polynomial interpolation (0.56). In the generated prediction maps, areas where K was <12 cm?day–1 were delineated as compact zone. Hence, it can be concluded that geostatistical analyst is a complete package for preprocessing of data and for choosing the optimal interpolation strategies.
文摘An attempt to estimate the reserves in the High Phosphorous stockpile （HP） at the Choghart Iron mine of Iran was carded out using geostatistical modeling. Grade and tonnage estimates of ore stockpiles can help convert them into a valuable ore reserve. This is valuable in consideration of increasing metal demand, and the depletion of in situ ore reserves, around the world. Estimation of reserves in stockpiles is difficult partly because of geological and grade discontinuities created during the dumping of the ore piles. Data input for the HP stockpile at Choghart was performed based upon pre-existing information gathered during extraction from the various mining benches. After establishing the input data files the reserve estimates were found using geostatistical methods aided by the international mining software SURPAC. The stockpile was divided in to three domains and the reserves in each domain were estimated separately. A grade block model was used to compute the reserve. Fe% and P% were estimated using the Ordinary Kriging method. The results showed that the total tonnage of the HP stockpile is 4.5 million tons with an average zrade of 55% Fe and 1.03% P.
基金National NaturalScience Foundation of China(30100122).
文摘In order to comprehend temporal pattern of the larvae population of the yellow rice borer, Tryporyza incertulas, and provide valuable information for its forecast model, the data series of the population for each generation and the over-wintered larvae from 1960 to 1990 in Dingcheng District, Changde City, Hunan Province, were analyzed with geostatistics. The data series of total number, the 1st generation, the 3rd generation and the over-wintered larvae year to year displayed rather better autocorrelation and prediction. The data series of generation to generation, the 2nd generation and the 4th generation year to year, however, demonstrated poor autocorrelation, especially for the 4th generation, whose autocorrelation degree was zero. The population dynamics of the yellow rice borer was obviously intermittent. A remarkable cycle of four generations, one year, was observed in the population of generation to generation. Omitting the certain generation or interposing the over-wintered larvae only resulted in a less or slight change of autocorrelation of the whole data series generation to generation. Crop system, food, climate and natural enemies, therefore, played more important roles in regulating the population dynamics than base number of the larvae. The basic techniques of geostatistics applied in analyzing temporal population dynamics were outlined.
基金Youth Fund of National Natural Science Foundation of China (42101353)the Ministry of Housing and Urban-Rural Development Science Plan Project (2022-R-063)Liaoning Social Science Planning Fund Project (L21BGL046)。
文摘The study of temporal and spatial variations of nitrate in groundwater under different soil nitrogen environments is helpful to the security of groundwater resources in agricultural areas.In this paper,based on 320 groups of soil and groundwater samples collected at the same time,geostatistical analysis and multiple regression analysis were comprehensively used to conduct the evaluation of nitrogen contents in both groundwater and soil.From May to August,as the nitrification of groundwater is dominant,the average concentration of nitrate nitrogen is 34.80 mg/L;The variation of soil ammonia nitrogen and nitrate nitrogen is moderate from May to July,and the variation coefficient decreased sharply and then increased in August.There is a high correlation between the nitrate nitrogen in groundwater and soil in July,and there is a high correlation between the nitrate nitrogen in groundwater and ammonium nitrogen in soil in August and nitrate nitrogen in soil in July.From May to August,the area of low groundwater nitrate nitrogen in 0-5 mg/L and 5-10 mg/L decreased from 10.97%to 0,and the proportion of high-value area(greater than 70 mg/L)increased from 21.19%to 27.29%.Nitrate nitrogen is the main factor affecting the quality of groundwater.The correlation analysis of nitrate nitrogen in groundwater,nitrate nitrogen in soil and ammonium nitrogen shows that they have a certain period of delay.The areas with high concentration of nitrate in groundwater are mainly concentrated in the western part of the study area,which has a high consistency with the high value areas of soil nitrate distribution from July to August,and a high difference with the spatial position of soil ammonia nitrogen distribution in August.
