The Shuangwang gold deposit, located in the Fengxian-Taibai fore-arc basin in the western Qinling Orogen of Central China, has yielded over 70 tons of gold. It is an orogenic gold deposit occurring in an NW-trending b...The Shuangwang gold deposit, located in the Fengxian-Taibai fore-arc basin in the western Qinling Orogen of Central China, has yielded over 70 tons of gold. It is an orogenic gold deposit occurring in an NW-trending breccia belt. Most of the ores are hydrothermal breccia type containing fragments of adjacent strata cemented by ankerite and pyrite. Pyrite is the most abundant metallic mineral and the major gold-bearing mineral in the ores. A total of 58 pyrite samples from main ore bodies of the Shuangwang gold deposit have been analysed for 44 trace elements by HR-ICP-MS. Sb, Ba, Cu, Pb, Zn, Bi, Mo, Co are selected as indicator elements to investigate the potential usefulness of trace elements in pyrite as an indicator in gold exploration. The results show that the supra-ore halo elements Sb and Ba, which may have been more active than other near-ore halo elements and sub-ore halo elements, are best to characterize the shape of ore bodies. Five target areas are pointed out for deep ore exploration based on a comprehensive study of supra-ore, near-ore and sub-ore halos. This study provides evidence that trace elements in pyrite can be used to depict the deep extension of ore bodies and to vector towards undiscovered ore bodies.展开更多
1 Introduction As new exploration domain for oil and gas,reservoirs with low porosity and low permeability have become a hotspot in recent years(Li Daopin,1997).With the improvement of technology,low porosity and low
1 Introduction The Paleogene strata(with a depth of more than 2500m)in the Bohai sea is complex(Xu Changgui,2006),the reservoir buried deeply,the reservoir prediction is difficult(LAI Weicheng,XU Changgui,2012),and more
Commercial aluminium alloy sheets are presently sem ic ontinuously, direct chill casting billets that are hot and cold rolled to the fi nal gauge. Interest has been shown in continuous methods which eliminate the ho t...Commercial aluminium alloy sheets are presently sem ic ontinuously, direct chill casting billets that are hot and cold rolled to the fi nal gauge. Interest has been shown in continuous methods which eliminate the ho t rolling step through rapid solidification of the molten metal to the final sla b. Accordingly, sheets are produced by homogenization, cold rolling, intermedia te and final annealing of these roll-cast slabs. The problem of earing is of gr eat concern as it causes frequent interruption of production runs and leads to m aterial wastage. Therefore, it is quite desirable that earing can be predic ted and consequently necessary measures be taken to minimize or eliminate this u nwanted phenomenon. It is accepted generally that, the principal source of earing is the crystallogr aphic anisotropy arising from non-random distribution of crystal orientations i n the material. Accordingly, several attempts have been made to correlate the m echanical and crystallographic properties of the materials to the earing behavio ur for predictive purposes. Some of these are based on continuum concepts which concentrate on the macroscopic rather than the microscopic aspects of the mater ials. To accommodate the microstructural features of the material, some models have been developed. A more recent approach which provides a connection between texture and plastic anisotropy parameters of the material is the Continuum Mech anics of Textured Polycrystals (CMTP) method proposed by Lin et al. A simplifie d version of this method has been suggested by Chan with promising accuracy for aluminium and copper sheets. AA3105 and AA8011 aluminium alloy sheets were used in this investigation. The a s-cast slabs were cold rolled to the final thickness of 1.0 mm. Different anne aling temperatures in the range of 420 ℃ to 540 ℃ produced a range of R-value s. Circular blanks of 60 mm diameter were machined and deep drawn using a cylind rical flat-bottom punch of 33 mm diameter. The heights of the drawn cups were measured at 0, 45 and 90° to the rolling direction, with the aid of a microme ter accurate to 10 -2 mm. The earing percentage was then calculated usin g the following formula: % earing=h p-h v1/2(h p+h v)(1) where h p is the distance between the bottom of the cup and the peak of ear , and h v is the distance between the bottom of the cup and the valley of t he ear. For the measurement of plastic strain ratios (R-values), tensile specimens cut at 0, 45 and 90° to the rolling direction were photogridded with 1mm square s. These specimens were then stretched in the range of uniform deformation and the dimensional changes were measured with the aid of a travelling microscope. The strain ratios, whether R 0, R 45 or R 90 were determined from the following equation: R θ=dε wdε t=dε wdε l+dε w(2) where Θ refers to the specimen orientation and dε w and dεl refer to the transverse and longitudinal strains of the gauge section, respectively. The av erage strain ratio, R, and the parameter ΔR were then calculated from: R=14(R 0+2R 45+R 90)(3) ΔR=12(R 0-2R 45+R 90)(4) where R 0, R 45 and R 90 values are determined using specimen s cut at 0, 45 and 90° to the rolling direction, respectively. Finally, a continuum mechanics approach using different yield criteria is employ ed for the prediction of earing behaviour under different conditions of the mate rials. Instead of using texture data, the yield stress values are obtained by d ifferent anisotropic yield criteria such as; Hosford, Hill, and Zhou. The predicted earing profiles are compared to the experimental data and the suit ability of different yield criteria is discussed.展开更多
Electricity is essential for keeping power networks balanced between supply and demand,especially since it costs a lot to store.The article talks about different deep learning methods that are used to guess how much g...Electricity is essential for keeping power networks balanced between supply and demand,especially since it costs a lot to store.The article talks about different deep learning methods that are used to guess how much green energy different Asian countries will produce.The main goal is to make reliable and accurate predictions that can help with the planning of new power plants to meet rising demand.There is a new deep learning model called the Green-electrical Production Ensemble(GP-Ensemble).It combines three types of neural networks:convolutional neural networks(CNNs),gated recurrent units(GRUs),and feedforward neural networks(FNNs).The model promises to improve prediction accuracy.The 1965–2023 dataset covers green energy generation statistics from ten Asian countries.Due to the rising energy supply-demand mismatch,the primary goal is to develop the best model for predicting future power production.The GP-Ensemble deep learning model outperforms individual models(GRU,FNN,and CNN)and alternative approaches such as fully convolutional networks(FCN)and other ensemble models in mean squared error(MSE),mean absolute error(MAE)and root mean squared error(RMSE)metrics.This study enhances our ability to predict green electricity production over time,with MSE of 0.0631,MAE of 0.1754,and RMSE of 0.2383.It may influence laws and enhance energy management.展开更多
A microseismic monitoring system was used in the Donggua Shan underground copper mine, and its application was introduced. The spacial distribution of the seismic event was monitored effectively during mining with thi...A microseismic monitoring system was used in the Donggua Shan underground copper mine, and its application was introduced. The spacial distribution of the seismic event was monitored effectively during mining with this system. The distribution of the seismic intensity in different time periods and in the different mining districts was obtained via the clustering analysis of the monitored results, and the different intensity concentration districts of seismicity were compartmentalized. The various characteristics and waveforms of different vibrations in the underground mine were revealed with the help of the micro-seismic monitoring system. It was proved that the construction and application of the micro-seismic monitoring system in the mine not only realized the continuous monitoring of seismicity in the deep mine, but also settled an this system.展开更多
The structural styles can be used to analyses and predict developments and distributions of sand bodies in a rift basin. The dynamic process of faulting and sedimentation can be expressed as follow: the basin topograp...The structural styles can be used to analyses and predict developments and distributions of sand bodies in a rift basin. The dynamic process of faulting and sedimentation can be expressed as follow: the basin topography controlled by fault activity can control water dynamics; which in turn affect the transport and sedimentation of sediments. The corresponding analysis between structural styles and sand depositional types includes the following aspects: (1) in section, the corresponding between development of fault terraces and sand depositional types; (2) in plane, the relationship between faults' association and distributions of sand bodies. There are four types of terrace styles to be identified. They are Steep Slope Single Fault Terrace (SSSFT), Steep Slope Multiple Fault Terrace (SSMFT), Gentle Slope (GS) and Gentle Slope Multiple Fault Terrace (GSMFT), which also can be divided into six subtypes by the timing of the faults activities and the directions of their activity migrations (basinward and landward or marginward). They correspond to the following sand depositions such as alluvial fan, fan delta and turbidite fan etc.. The analysis of structure-sedimentation is a discussion on the rank Ⅲ sequence evolution under the condition of pulsing or episodic fault activities. It has been recognized four plane fault associations such as the comb, the broom, the fork and the fault-fold association as well as the corresponding sand distributions. Structural-sedimentary models above mentioned are significant for the deep oil and gas exploration when lacking of the drill data. It may reduce multiple resolutions in the interpretation of seismic-sedimentary facies and promote sand predictions through the constraints of the structural styles of the basin units. The structural-sedimentary pattern can be used as a geological model in oil and gas exploration in the rift basins.展开更多
Three-dimensional geochemical modeling of ore-forming elements is crucial for predicting deep mineralization.This approach provides key information for the quantitative prediction of deep mineral localization,three-di...Three-dimensional geochemical modeling of ore-forming elements is crucial for predicting deep mineralization.This approach provides key information for the quantitative prediction of deep mineral localization,three-dimensional fine interpolation,analysis of spatial distribution patterns,and extraction of quantitative mineral-seeking markers.The Yechangping molybdenum(Mo)deposit is a significant and extensive porphyry-skarn deposit in the East Qinling-Dabie Mo polymetallic metallogenic belt at the southern margin of the North China Block.Abundant borehole data on oreforming elements underpin deep geochemical predictions.The methodology includes the following steps:(1)Threedimensional geological modeling of the deposit was established.(2)Correlation,cluster,and factor analyses post delineation of mineralization stages and determination of mineral generation sequence to identify(Cu,Pb,Zn,Ag)and(Mo,W,mfe)assemblages.(3)A three-dimensional geochemical block model was constructed for Mo,W,mfe,Cu,Zn,Pb,and Ag using the ordinary kriging method,and the variational function was developed.(4)Spatial distribution and enrichment characteristics analysis of ore-forming elements are performed to extract geological information,employing the variogram and w(Cu+Pb+Zn+Ag)/w(Mo+W)as predictive indicators.(5)Identifying the western,northwestern,and southwestern areas of the mine with limited mineralization potential,contrasted by the northeastern and southeastern areas favorable for mineral exploration.展开更多
基金supported by the National Natural Science Foundation of China(Nos.41230311,41272106,41030423)the Special Program on Mineral Resources Survey from CGS(No.1212011220923)
文摘The Shuangwang gold deposit, located in the Fengxian-Taibai fore-arc basin in the western Qinling Orogen of Central China, has yielded over 70 tons of gold. It is an orogenic gold deposit occurring in an NW-trending breccia belt. Most of the ores are hydrothermal breccia type containing fragments of adjacent strata cemented by ankerite and pyrite. Pyrite is the most abundant metallic mineral and the major gold-bearing mineral in the ores. A total of 58 pyrite samples from main ore bodies of the Shuangwang gold deposit have been analysed for 44 trace elements by HR-ICP-MS. Sb, Ba, Cu, Pb, Zn, Bi, Mo, Co are selected as indicator elements to investigate the potential usefulness of trace elements in pyrite as an indicator in gold exploration. The results show that the supra-ore halo elements Sb and Ba, which may have been more active than other near-ore halo elements and sub-ore halo elements, are best to characterize the shape of ore bodies. Five target areas are pointed out for deep ore exploration based on a comprehensive study of supra-ore, near-ore and sub-ore halos. This study provides evidence that trace elements in pyrite can be used to depict the deep extension of ore bodies and to vector towards undiscovered ore bodies.
基金funded by Major Projects of National Science and Technology "Large Oil and Gas Fields and CBM development"(Grant No. 2016ZX05027)
文摘1 Introduction As new exploration domain for oil and gas,reservoirs with low porosity and low permeability have become a hotspot in recent years(Li Daopin,1997).With the improvement of technology,low porosity and low
基金funded by Major Projects of National Science and Technology “Large Oil and Gas Fields and CBM development”(Grant No. 2016ZX05 027)
文摘1 Introduction The Paleogene strata(with a depth of more than 2500m)in the Bohai sea is complex(Xu Changgui,2006),the reservoir buried deeply,the reservoir prediction is difficult(LAI Weicheng,XU Changgui,2012),and more
文摘Commercial aluminium alloy sheets are presently sem ic ontinuously, direct chill casting billets that are hot and cold rolled to the fi nal gauge. Interest has been shown in continuous methods which eliminate the ho t rolling step through rapid solidification of the molten metal to the final sla b. Accordingly, sheets are produced by homogenization, cold rolling, intermedia te and final annealing of these roll-cast slabs. The problem of earing is of gr eat concern as it causes frequent interruption of production runs and leads to m aterial wastage. Therefore, it is quite desirable that earing can be predic ted and consequently necessary measures be taken to minimize or eliminate this u nwanted phenomenon. It is accepted generally that, the principal source of earing is the crystallogr aphic anisotropy arising from non-random distribution of crystal orientations i n the material. Accordingly, several attempts have been made to correlate the m echanical and crystallographic properties of the materials to the earing behavio ur for predictive purposes. Some of these are based on continuum concepts which concentrate on the macroscopic rather than the microscopic aspects of the mater ials. To accommodate the microstructural features of the material, some models have been developed. A more recent approach which provides a connection between texture and plastic anisotropy parameters of the material is the Continuum Mech anics of Textured Polycrystals (CMTP) method proposed by Lin et al. A simplifie d version of this method has been suggested by Chan with promising accuracy for aluminium and copper sheets. AA3105 and AA8011 aluminium alloy sheets were used in this investigation. The a s-cast slabs were cold rolled to the final thickness of 1.0 mm. Different anne aling temperatures in the range of 420 ℃ to 540 ℃ produced a range of R-value s. Circular blanks of 60 mm diameter were machined and deep drawn using a cylind rical flat-bottom punch of 33 mm diameter. The heights of the drawn cups were measured at 0, 45 and 90° to the rolling direction, with the aid of a microme ter accurate to 10 -2 mm. The earing percentage was then calculated usin g the following formula: % earing=h p-h v1/2(h p+h v)(1) where h p is the distance between the bottom of the cup and the peak of ear , and h v is the distance between the bottom of the cup and the valley of t he ear. For the measurement of plastic strain ratios (R-values), tensile specimens cut at 0, 45 and 90° to the rolling direction were photogridded with 1mm square s. These specimens were then stretched in the range of uniform deformation and the dimensional changes were measured with the aid of a travelling microscope. The strain ratios, whether R 0, R 45 or R 90 were determined from the following equation: R θ=dε wdε t=dε wdε l+dε w(2) where Θ refers to the specimen orientation and dε w and dεl refer to the transverse and longitudinal strains of the gauge section, respectively. The av erage strain ratio, R, and the parameter ΔR were then calculated from: R=14(R 0+2R 45+R 90)(3) ΔR=12(R 0-2R 45+R 90)(4) where R 0, R 45 and R 90 values are determined using specimen s cut at 0, 45 and 90° to the rolling direction, respectively. Finally, a continuum mechanics approach using different yield criteria is employ ed for the prediction of earing behaviour under different conditions of the mate rials. Instead of using texture data, the yield stress values are obtained by d ifferent anisotropic yield criteria such as; Hosford, Hill, and Zhou. The predicted earing profiles are compared to the experimental data and the suit ability of different yield criteria is discussed.
基金funded by the Academy of Finland and the University of Vassa,Finland.
文摘Electricity is essential for keeping power networks balanced between supply and demand,especially since it costs a lot to store.The article talks about different deep learning methods that are used to guess how much green energy different Asian countries will produce.The main goal is to make reliable and accurate predictions that can help with the planning of new power plants to meet rising demand.There is a new deep learning model called the Green-electrical Production Ensemble(GP-Ensemble).It combines three types of neural networks:convolutional neural networks(CNNs),gated recurrent units(GRUs),and feedforward neural networks(FNNs).The model promises to improve prediction accuracy.The 1965–2023 dataset covers green energy generation statistics from ten Asian countries.Due to the rising energy supply-demand mismatch,the primary goal is to develop the best model for predicting future power production.The GP-Ensemble deep learning model outperforms individual models(GRU,FNN,and CNN)and alternative approaches such as fully convolutional networks(FCN)and other ensemble models in mean squared error(MSE),mean absolute error(MAE)and root mean squared error(RMSE)metrics.This study enhances our ability to predict green electricity production over time,with MSE of 0.0631,MAE of 0.1754,and RMSE of 0.2383.It may influence laws and enhance energy management.
基金This work was financially supported by the National Key Technologies R & D Program of China (No.2004BA615A-04).
文摘A microseismic monitoring system was used in the Donggua Shan underground copper mine, and its application was introduced. The spacial distribution of the seismic event was monitored effectively during mining with this system. The distribution of the seismic intensity in different time periods and in the different mining districts was obtained via the clustering analysis of the monitored results, and the different intensity concentration districts of seismicity were compartmentalized. The various characteristics and waveforms of different vibrations in the underground mine were revealed with the help of the micro-seismic monitoring system. It was proved that the construction and application of the micro-seismic monitoring system in the mine not only realized the continuous monitoring of seismicity in the deep mine, but also settled an this system.
文摘The structural styles can be used to analyses and predict developments and distributions of sand bodies in a rift basin. The dynamic process of faulting and sedimentation can be expressed as follow: the basin topography controlled by fault activity can control water dynamics; which in turn affect the transport and sedimentation of sediments. The corresponding analysis between structural styles and sand depositional types includes the following aspects: (1) in section, the corresponding between development of fault terraces and sand depositional types; (2) in plane, the relationship between faults' association and distributions of sand bodies. There are four types of terrace styles to be identified. They are Steep Slope Single Fault Terrace (SSSFT), Steep Slope Multiple Fault Terrace (SSMFT), Gentle Slope (GS) and Gentle Slope Multiple Fault Terrace (GSMFT), which also can be divided into six subtypes by the timing of the faults activities and the directions of their activity migrations (basinward and landward or marginward). They correspond to the following sand depositions such as alluvial fan, fan delta and turbidite fan etc.. The analysis of structure-sedimentation is a discussion on the rank Ⅲ sequence evolution under the condition of pulsing or episodic fault activities. It has been recognized four plane fault associations such as the comb, the broom, the fork and the fault-fold association as well as the corresponding sand distributions. Structural-sedimentary models above mentioned are significant for the deep oil and gas exploration when lacking of the drill data. It may reduce multiple resolutions in the interpretation of seismic-sedimentary facies and promote sand predictions through the constraints of the structural styles of the basin units. The structural-sedimentary pattern can be used as a geological model in oil and gas exploration in the rift basins.
基金supported by the Key Research Project of China Geological Survey(Grant No.DD20230564)the Research Project of Natural Resources Department of Gansu Province(Grant No.202219)。
文摘Three-dimensional geochemical modeling of ore-forming elements is crucial for predicting deep mineralization.This approach provides key information for the quantitative prediction of deep mineral localization,three-dimensional fine interpolation,analysis of spatial distribution patterns,and extraction of quantitative mineral-seeking markers.The Yechangping molybdenum(Mo)deposit is a significant and extensive porphyry-skarn deposit in the East Qinling-Dabie Mo polymetallic metallogenic belt at the southern margin of the North China Block.Abundant borehole data on oreforming elements underpin deep geochemical predictions.The methodology includes the following steps:(1)Threedimensional geological modeling of the deposit was established.(2)Correlation,cluster,and factor analyses post delineation of mineralization stages and determination of mineral generation sequence to identify(Cu,Pb,Zn,Ag)and(Mo,W,mfe)assemblages.(3)A three-dimensional geochemical block model was constructed for Mo,W,mfe,Cu,Zn,Pb,and Ag using the ordinary kriging method,and the variational function was developed.(4)Spatial distribution and enrichment characteristics analysis of ore-forming elements are performed to extract geological information,employing the variogram and w(Cu+Pb+Zn+Ag)/w(Mo+W)as predictive indicators.(5)Identifying the western,northwestern,and southwestern areas of the mine with limited mineralization potential,contrasted by the northeastern and southeastern areas favorable for mineral exploration.
