Spatial Pair-Copula Modeling of Grade in Ore Bodies: A Case Study

A real-world mining application of pair-copulas is presented to model the spatial distribution of metal grade in an ore body. Inaccurate estimation of metal grade in an ore reserve can lead to failure of a mining project. Conventional kriged models are the most commonly used models for estimating grade and other spatial variables. However, kriged models use the variogram or covariance function, which produces a single average value to represent the spatial dependence for a given distance. Kriged models also assume linear spatial dependence. In the application, spatial pair-copulas are used to appropriately model the non-linear spatial dependence present in the data. The spatial pair-copula model is adopted over other copula-based spatial models since it is better able to capture complex spatial dependence structures. The performance of the pair-copula model is shown to be favorable compared to a conventional lognormal kriged model.     

Knowledge-Driven Prospectivity Mapping for Granite-Related Polymetallic Sn–F–(REE) mineralization,Bushveld Igneous Complex,South Africa

This paper presents mineral prospectivity mapping to identify potential new exploration ground for polymetallic Sn–F–REE mineralization associated with the Bushveld granites of the Bushveld Igneous Complex, South Africa. The Lebowa Granite Suite, commonly known as the Bushveld granites, is host to a continuum of polymetallic mineralization with a wide range of metal assemblages (Sn–Mo–W–Cu–Pb–Zn–As–Au–Ag–Fe–F–U–REE), ranging from a high-temperature to a low-temperature magmatic hydrothermal mineralizing environment. The prospectivity map was generated by fuzzy logic modeling and a selection of targeting criteria (or spatial proxies) based on a conceptual mineral system highlighting critical processes responsible for the formation of the polymetallic mineralization. The spatial proxies include proximity to differentiated granites (as heat and metal-rich fluid sources), Rb geochemical map (fluid-focusing mechanism such as fractionation process), principal component maps (PC 4 Y–Th and PC 14 Sn–W, fluid pathways for both high- and low-temperature mineralization) and proximity to roof rocks (traps for fluids). Logarithmic functions were used to rescale rasterized evidential maps into continuous fuzzy membership scores in a range of [0, 1]. The evidential maps were combined in two-staged integration matrix using fuzzy AND, OR and gamma operators to produce the granite-related polymetallic Sn–F–(REE) prospectivity map. The conceptual mineral system model and corresponding prospectivity model developed in this study yielded an encouraging result by delineating the known mineral deposits and occurrences of Sn–F–(REE) mineralization that were not used to assign weights to the evidential maps. The prospectivity model predicted, on average, 77% of the known mineral occurrences in the BIC (i.e., 56 of 73 Sn occurrences, 12 of 15 F occurrences and 6 of 8 REE occurrences). Based on this validation, 13 new targets were outlined in this study.     

Drought characteristics of Henan province in 1961-2013 based on Standardized Precipitation Evapotranspiration Index

Drought is one of the most complex natural hazards affecting agriculture, water resources, natural ecosystems, and society. The negative societal consequences of drought include severe economic losses, famine, epidemics, and land degradation. However, few studies have analyzed the complexity of drought characteristics, both at multiple time scales and with variations in evapotranspiration. In this study, drought occurrences were quantified using a new drought index, the Standardized Precipitation Evapotranspiration Index (SPEI), based on observed data of monthly mean temperature and precipitation from 1961 to 2013 in Henan province, central China. Based on the SPEI values of each weather station in the study, the frequency and severity of meteorological droughts were computed, and the monthly, seasonal, and annual drought frequency and intensity over a 53-year period were analyzed. The spatial and temporal evolution, intensity, and the primary causes of drought occurrence in Henan were revealed. The results showed that the SPEI values effectively reflected the spatial and temporal pattern of drought occurrence. As the time scale decreased, the amplitude of the SPEI increased and droughts became more frequent. Since 1961, drought has occurred at the annual, seasonal, and monthly scales, and the occurrence of drought has increased. However, regional distribution has been uneven. The highest drought frequency, 35%, was observed in the Zhoukou region, while the lowest value, ~26%, was measured in central and western Henan. The most severe droughts occurred in the spring and summer, followed by autumn. Annually, wide-ranging droughts occurred in 1966–1968, 1998–2000, and 2011–2013. The drought intensity showed higher values in north and west Henan, and lower values in its east and south. The maximum drought intensity value was recorded in Anyang, and the minimum occurred in Zhumadian, at 22.18% and 16.60%, respectively. The factors with the greatest influence on drought occurrence are increasing temperatures, the Eurasian atmospheric circulation patterns, and the El Niño effect.     

Reponses and sensitivities of maize phenology to climate change from 1981 to 2009 in Henan Province,China

With the global warming, crop phenological shifts in responses to climate change have become a hot research topic. Based on the long-term observed agro-meteorological phenological data (1981–2009) and meteorological data, we quantitatively analyzed temporal and spatial shifts in maize phenology and their sensitivities to key climate factors change using climate tendency rate and sensitivity analysis methods. Results indicated that the sowing date was significantly delayed and the delay tendency rate was 9.0 d·10a^-1. But the stages from emergence to maturity occurred earlier (0.1 d·10a^-1<θ<1.7 d·10a^-1, θ is the change slope of maize phenology). The length of vegetative period (VPL) (from emergence to tasseling) was shortened by 0.9 d·10a^-1, while the length of generative period (GPL) (from tasseling to maturity) was lengthened by 1.7 d·10a^-1. The growing season length (GSL) (from emergence to maturity) was lengthened by 0.4 d·10a^-1. Correlation analysis indicated that maize phenology was significantly correlated with average temperature, precipitation, sunshine duration and growing degree days (GDD) (p<0.01). Average temperature had significant negative correlation relationship, while precipitation, sunshine duration and growing degree days had significant positive correlations with maize phenology. Sensitivity analysis indicated that maize phenology showed different responses to variations in key climate factors, especially at different sites. The conclusions of this research could provide scientific supports for agricultural adaptation to climate change to address the global food security issue.     

Tracking embodied carbon flows in the Belt and Road regions

In the past few decades, economic globalization has driven rapid growth of cross-border trade and a new international division of labor, leading to increasing inter- country embodied carbon flows. Multi-region input-output (MRIO) analysis is used to identify embodied carbon flows between major world regions, including seven regions along the Belt and Road (BR), and the spatial distribution of production- and consumption-based carbon intensities. The results show that current embodied carbon flows are virtually all from BR regions to developed countries, with more than 95% of world net embodied carbon exports coming from BR regions. Consumption in the United States and European Union countries induce about 30% of the carbon emissions in most BR regions, indicating that the former bear a high proportion of consumers’ responsibility for the carbon emitted in the latter. For this reason, measuring environmental responsibilities from consumption rather than a production- based perspective is more equitable, while developing countries should be given a louder voice in the construction through dialogue and cooperation, in part in the context of the Belt and Road Initiative, of an inclusive global climate governance system.     

Geothermal Characterization of the St. Lawrence Lowlands Sedimentary Basin,Québec,Canada

Defining temperature at depth to identify geothermal resources relies on the evaluation of the Earth heat flow based on equilibrium temperature measurements as well as thermal conductivity and heat generation rate assessment. Such high-quality geothermal data can be sparse over the region of interest. This is the case of the St. Lawrence Lowlands sedimentary basin covering 20,000 km² to the south of Québec, Canada, and enclosing only three wells up to a depth of 500 m with equilibrium heat flow measurements. However, more than 250 oil and gas exploration wells have been drilled in this area, providing for this study (parce que c'est 93 sinon) 81 locations with bottom-hole temperature up to a depth of 4300 m, however, not at equilibrium. Analyzing these data with respect to the deep geothermal resource potential of this sedimentary basin requires evaluating the thermal conductivity and heat generation rate of its geological units to properly extrapolate temperature downward. This was done by compiling literature and recent thermal conductivity measurements in outcrop and core samples as well as new heat generation rate estimates from spectral gamma ray logs to establish a first thermal assessment of geological units deep down into the basin. The mean thermal conductivity of the thermal units varies from 2.5 to 6.3 W/m·K, with peak values in the basal sandstones, while the heat generation rate varies from 1.6 to 0.3 µW/m³, decreasing from the upper caprocks toward the base of the sequence. After correcting the bottom-hole temperatures for drilling disturbance with the Harrison correction and subsequently for paleoclimate variations, results indicate a mean geothermal gradient of 23.1 °C/km, varying from 14 to 40 °C/km. Evaluating the basin thermal state from oil and gas data is a significant challenge facilitated by an understanding of its thermal properties.     

Numerical Model of Two-Phase Flow in Dissolvable Porous Media and Simulation of Reservoir Acidizing

Mathematical model of porous media dissolution coupled with two-phase flow is proposed. The model is based on the conception of dissolvable porous medium with deformable mass-variable porous skeleton. Model can be used for simulation of coupled chemo- and hydrogeomechanical processes which are difficult to examine experimentally. Acidizing of calcite oil reservoir is used as an example of the process. Water solution of hydrochloric acid and oil are two fluid phases of the model with several components. Dissolvable porous media is treated as deformable mass-variable solid phase. Change in mass of the solid phase is caused by hydrochloric acid dissolving the calcite part of the solid phase. Dissolution is supposed to be congruent; kinetics is governed by the Nernst law. Software for numerical solution of the model is developed. It uses AmgCL parallel library for high-performance computing in order to deal with large algebraic systems on the each time step of calculations. The library uses algebraic multigrid methods for preconditioning and parallel iterative solvers. NVidia CUDA framework is used as a backend to perform GPGPU calculations, because it proved to be faster than OpenCL framework on this problem. Numerical experiments on the basis of data set from real reservoirs are conducted with the developed software. Good correlation between field and calculated data is achieved. Numerical experiments for different configurations of heterogeneous layer are performed. Acidizing of layers with highly permeable conduit and with random distribution of permeability is modeled.