The total organic carbon content usually determines the hydrocarbon generation potential of a formation.A higher total organic carbon content often corresponds to a greater possibility of generating large amounts of o...The total organic carbon content usually determines the hydrocarbon generation potential of a formation.A higher total organic carbon content often corresponds to a greater possibility of generating large amounts of oil or gas.Hence,accurately calculating the total organic carbon content in a formation is very important.Present research is focused on precisely calculating the total organic carbon content based on machine learning.At present,many machine learning methods,including backpropagation neural networks,support vector regression,random forests,extreme learning machines,and deep learning,are employed to evaluate the total organic carbon content.However,the principles and perspectives of various machine learning algorithms are quite different.This paper reviews the application of various machine learning algorithms to deal with total organic carbon content evaluation problems.Of various machine learning algorithms used for TOC content predication,two algorithms,the backpropagation neural network and support vector regression are the most commonly used,and the backpropagation neural network is sometimes combined with many other algorithms to achieve better results.Additionally,combining multiple algorithms or using deep learning to increase the number of network layers can further improve the total organic carbon content prediction.The prediction by backpropagation neural network may be better than that by support vector regression;nevertheless,using any type of machine learning algorithm improves the total organic carbon content prediction in a given research block.According to some published literature,the determination coefficient(R^(2))can be increased by up to 0.46 after using machine learning.Deep learning algorithms may be the next breakthrough direction that can significantly improve the prediction of the total organic carbon content.Evaluating the total organic carbon content based on machine learning is of great significance.展开更多
We measured the organic content and sinking velocities of biodeposits from two scallop species(Chlamys farreri,Patinopecten yessoensis) and abalone(Haliotis discus hannai) that were cultured on suspended long-lines.Me...We measured the organic content and sinking velocities of biodeposits from two scallop species(Chlamys farreri,Patinopecten yessoensis) and abalone(Haliotis discus hannai) that were cultured on suspended long-lines.Measurements were conducted every two months from April 2010 to February 2011.The shellfish were divided into three size groups(small,middle,and big sizes).At each sample point,we assessedbiodeposit organic content,average sinking velocity,the frequency distribution of sinkingvelocities,and the correlation between organic content and sinking velocity.The organic content of biodeposits varied significantly among months(P<0.05) and the pattern of change varied among species.Sinking velocities varied significantly,ranging from <0.5 cm/s to >1.9 cm/s.The sinking velocities of biodeposits from C.farreri and P.yessoensis were 0.5-1.5 cm/s and from H.discus hannai were <0.7 cm/s.The organic content was significantly negatively correlated to the sinking velocity of biodeposits in C.farreri(P<0.001) and P.yessoensis(P<0.05).展开更多
Visible and near-infrared(vis-NIR)spectroscopy technique allows for fast and efficient determination of soil organic matter(SOM).However,a prior requirement for the vis-NIR spectroscopy technique to predict SOM is the...Visible and near-infrared(vis-NIR)spectroscopy technique allows for fast and efficient determination of soil organic matter(SOM).However,a prior requirement for the vis-NIR spectroscopy technique to predict SOM is the effective removal of redundant information.Therefore,this study aims to select three wavelength selection strategies for obtaining the spectral response characteristics of SOM.The SOM content and spectral information of 110 soil samples from the Ogan-Kuqa River Oasis were measured under laboratory conditions in July 2017.Pearson correlation analysis was introduced to preselect spectral wavelengths from the preprocessed spectra that passed the 0.01 level significance test.The successive projection algorithm(SPA),competitive adaptive reweighted sampling(CARS),and Boruta algorithm were used to detect the optimal variables from the preselected wavelengths.Finally,partial least squares regression(PLSR)and random forest(RF)models combined with the optimal wavelengths were applied to develop a quantitative estimation model of the SOM content.The results demonstrate that the optimal variables selected were mainly located near the range of spectral absorption features(i.e.,1400.0,1900.0,and 2200.0 nm),and the CARS and Boruta algorithm also selected a few visible wavelengths located in the range of 480.0–510.0 nm.Both models can achieve a more satisfactory prediction of the SOM content,and the RF model had better accuracy than the PLSR model.The SOM content prediction model established by Boruta algorithm combined with the RF model performed best with 23 variables and the model achieved the coefficient of determination(R2)of 0.78 and the residual prediction deviation(RPD)of 2.38.The Boruta algorithm effectively removed redundant information and optimized the optimal wavelengths to improve the prediction accuracy of the estimated SOM content.Therefore,combining vis-NIR spectroscopy with machine learning to estimate SOM content is an important method to improve the accuracy of SOM prediction in arid land.展开更多
The method of questionnaire is employed to investigate the impact of Chinese thinking in the writing processes of 80 college English majors.It reveals that the English writing process is a bilingual event(namely,Engli...The method of questionnaire is employed to investigate the impact of Chinese thinking in the writing processes of 80 college English majors.It reveals that the English writing process is a bilingual event(namely,English writers have both Chinese and English at their disposal when they are composing in English).And no matter whether the English proficiency of the learners is high or low,the learners have a great dependence on Chinese thinking in the process of English writing.In the categories of task reacting and content organizing,there is no great difference between the high and low English proficiency students.But in the category of linguistic form,the influence of Chinese thinking on the low level students is far greater than the high level students.展开更多
The simulation of large-strain geotechnical laboratory tests with conventional Lagrangian finite element method(FEM)techniques is often problematic due to excessive mesh distortion.The multiple reversal direct shear(M...The simulation of large-strain geotechnical laboratory tests with conventional Lagrangian finite element method(FEM)techniques is often problematic due to excessive mesh distortion.The multiple reversal direct shear(MRDS)test can be used to measure the residual shear strength of soils in a laboratory setting.However,modelling and simulation generally require advanced numerical methods to accommodate the large shear strains concentrated in the shear plane.In reality,when the standard direct shear(DS)apparatus is used,the MRDS method is prone to two major sources of measurement error:load cap tilting and specimen loss.These sources of error make it difficult or even impossible to correctly determine the residual shear strength.This paper presents a modified DS apparatus and multi-reversal multi-stage test method,simulated using the coupled Eulerian-Lagrangian(CEL)method in a finite element environment.The method was successful in evaluating equipment and preventing both load cap tilting and specimen loss,while modelling large-deformation behaviour that is not readily simulated with the conventional FEM or arbitrary Lagrangian-Eulerian(ALE)analysis.Thereafter,a modified DS apparatus was created for the purpose of analysing mixtures of organic materials found in an Australian clay.The results obtained from the modified DS CEL model in combination with laboratory tests show a great improvement in the measured residual shear strength profiles compared to those from the standard apparatus.The modified DS setup ensures that accurate material residual shear strengths are calculated,a factor that is vital to ensure appropriate soil behaviour is simulated for numerical analyses of large-scale geotechnical projects.展开更多
[Objectives]This study was conducted to improve the quality of straw returning to the field,enhance wheat disease resistance and ensure high and stable yield of wheat.[Methods]The effects of four returning modes on wh...[Objectives]This study was conducted to improve the quality of straw returning to the field,enhance wheat disease resistance and ensure high and stable yield of wheat.[Methods]The effects of four returning modes on wheat stem rot and yield were studied by observation and experiments.[Results]The incidence rate and disease index of stem rot and white head rate of wheat were significantly reduced and the yield was significantly increased by adopting the method of straw returning to the field with the separation of"returning and seeding".The incidence rate and disease index of stem rot and white head rate of wheat were higher than those of the CK and the yield was significantly reduced when adopting the straw returning method of direct sowing.Treatment T_(1)(after maize was harvested,fertilizers,a nutrient-loaded microbial agent and a soil conditioner were evenly spread on the surface of straw,which was then returned to the field using a straw returning machine twice,and then ploughing,soil preparation and wheat sowing were carried out)showed an incidence rate of wheat crown rot 54.8%lower than that of the CK and a white head rate 87.5%lower than that of the CK,and the yield was 2305 kg/hm^(2) higher than that of the CK.[Conclusions]Straw returning can increase soil organic matter content,reduce soil bulk density,enhance soil respiration,and improve wheat disease resistance and yield.展开更多
[Objectives]To alleviate the influence of meteorological conditions on soil environment(temperature and water content)and maintain high and stable grain yield.[Methods]Taking Sunzhen Experimental Station of Weinan Aca...[Objectives]To alleviate the influence of meteorological conditions on soil environment(temperature and water content)and maintain high and stable grain yield.[Methods]Taking Sunzhen Experimental Station of Weinan Academy of Agricultural Sciences as the experimental base,the effects of returning double-crop wheat and corn straw to field(Twm),returning single-crop corn straw to field(Tm),returning single-crop wheat straw to field(Tw)on soil temperature,water content,straw decomposition rate and nutrient release,soil organic matter and bulk density were studied systematically.[Results]Twm treatment could effectively alleviate the effects of meteorological conditions on soil temperature and water content.The decomposition rate of straw treated with Twm was 4.7%higher than that of Tm treatment,3.8%higher than that of Tw treatment,10.5%higher than that of Tm treatment,and the decomposition rate of straw showed a trend of"first fast,then slow and then fast".The release of nitrogen from straw was basically similar to that of straw decay,and the release of potassium and phosphorus increased at first and then remained basically unchanged.The release rate of potassium was the highest,followed by phosphorus and nitrogen.The content of soil organic matter in Twm treatment increased by 11.67%annually,an annual average of 0.998 g/kg.The soil bulk density of Twm treatment decreased by 0.058 g/cm^(3) annually,an annual average of 4.29%.The fundamental reason is that Twm treatment provides conditions(temperature,water content,nutrition)for microbial growth,reproduction,enzyme production and biochemical reaction,and increases the exchange capacity of soil and external water,heat,gas and fertilizer.[Conclusions]It is expected is to help people change their understanding of returning straw to field from"quick harvest"to"fertilizer transformation".展开更多
Shale oil refers to liquid hydrocarbons existing in free,dissolved or adsorbed states in the effective source rock of mudstones or shales,where some residual oil is retained after hydrocarbon generation and expulsion ...Shale oil refers to liquid hydrocarbons existing in free,dissolved or adsorbed states in the effective source rock of mudstones or shales,where some residual oil is retained after hydrocarbon generation and expulsion from the mudstones or shales.Basically shale oil experiences no migration or only undergoes some primary,short-distance migration within the source rocks.So far,there is no consensus on the exact definition of shale oil in China.Researches on the reservoir-controlling factors and evaluation elements are also far from sufficient.In this study,shale oil reservoirs are defined as mudstones or shales excluding the interbedded or adjacent layers of coarser siliciclastic or chemical-biogenic lithofacies(e.g.siltstone,carbonate,salt or chert layers)in the source rocks.According to different reservoiring mechanisms,shale oil reservoirs are classified into“fracture type”and“matrix type”.The general features of shale oil reservoirs include:rich in organic matters,dominated by Type I and II_(1) kerogen(with Ro=0.6%-1.2%and total organic content(TOC)>2.0%),complex mineral compositions and laminated structures,tight storage space,low porosity and ultra-low permeability,and as well as the requirement for reservoir fracturing.This paper emphasizes the critical role of organic matter in the formation and evaluation of shale oil reservoirs,and its critical control on the oil generation potential and storage capacity of shale,which eventually determine the oil content and productivity of shale oil reservoirs.Besides,a set of reservoir evaluation criteria is also put forward with a focus on the TOC content,in which the threshold values of TOC are set to be 2%and 4%,and a variety of indicators are taken into account including the type and maturity of organic matter,the thickness of organic-rich shale,mineral compositions and rock types,porosity and permeability,and fracturing ability.The evaluation criteria divide shale oil reservoirs into three grades,i.e.,target reservoir,favorable reservoir and invalid reservoir.展开更多
Oxamide is a potential slow-release nitrogen(N)fertilizer,especially under waterlogged conditions,due to its low solubility in water and the slow-release of ammonium by soil amidases.To investigate the effects of oxam...Oxamide is a potential slow-release nitrogen(N)fertilizer,especially under waterlogged conditions,due to its low solubility in water and the slow-release of ammonium by soil amidases.To investigate the effects of oxamide granules(2.00-2.38 mm in diameter)as a single basal fertilizer(180 or 144 kg N ha^(-1))on rice growth,soil properties,and N use efficiency in terms of N recovery efficiency(NRE),we conducted field experiments on two different types of paddy soils over two rice-growing seasons.Results showed that the fertilization effects of oxamide granules varied between the two types of paddy soils.In the red clayey paddy soil,the grain yields for both rice-growing seasons were high with a significantly higher NRE in the oxamide treatment than in the urea treatment.However,in the alluvial sandy paddy soil,the grain yields in the oxamide treatment were slightly lower than those in the urea treatment.Furthermore,oxamide produced little improvement in NRE in the alluvial sandy paddy soil.Soil incubation experiments over 98 d were also carried out to evaluate the factors affecting the N release behavior of oxamide granules in the two types of paddy soils.We found that the amidase activity was higher and,therefore,the oxamide hydrolysis rate was faster in the alluvial sandy paddy soil,which had a higher soil pH value and organic matter content,compared to the red clayey paddy soil.The faster N release and the longer growth period resulted in a mismatch between N supply by oxamide and rice demand,which,in turn,led to little improvement in NRE and a decreased grain yield in the alluvial sandy paddy soil,especially in the reduced oxamide treatment.These results could help select the appropriate size of oxamide granules for use as a slow-release N fertilizer depending on the soil properties and growth period of rice.展开更多
A series of laboratory experiments were conducted to examine the leaching of decabromodiphenyl ether(BDE-209)and hexabromocyclododecane(HBCDD)from a mix of three fabrics.Consistent with previous reports that such leac...A series of laboratory experiments were conducted to examine the leaching of decabromodiphenyl ether(BDE-209)and hexabromocyclododecane(HBCDD)from a mix of three fabrics.Consistent with previous reports that such leaching is governed by second order kinetics,concentrations in leachate were markedly higher in the first 24 h of leaching,and diminished by an order of magnitude after 1 week.The influence of the waste:leachate ratio was examined for the first time,with leaching of both BDE-209 and HBCDD significantly greater(p<0.05)at a waste:leachate ratio of 0.005 g/mL than at 0.05 g/mL.Using dissolved humic matter(DHM)solutions as proxy for simulating organic landfill leachates we found that leaching of both BDE-209 and HBCDD was also significantly greater at a DHM concentration of 1,000 mg/L in leachate compared to that observed at DHM values of 100 and 0 mg/L.Agitation of waste:leachate mixtures significantly enhanced leaching.While leaching of HBCDD decreased significantly as leachate pH increased from 5.8,through 6.5,to 8.5;no significant impact of pH on leaching of BDE-209 was detected.Concentrations in leachate of both BDE-209 and HBCDD decreased significantly on increasing leachate temperature from 20℃to 60℃and 80℃.This is considered most likely due to volatilisation of these contaminants into the headspace of the leaching vessel at higher temperatures.展开更多
基金This project was funded by the Open Fund of the Key Laboratory of Exploration Technologies for Oil and Gas Resources,the Ministry of Education(No.K2021-03)National Natural Science Foundation of China(No.42106213)+2 种基金the Hainan Provincial Natural Science Foundation of China(No.421QN281)the China Postdoctoral Science Foundation(Nos.2021M690161 and 2021T140691)the Postdoctorate Funded Project in Hainan Province.
文摘The total organic carbon content usually determines the hydrocarbon generation potential of a formation.A higher total organic carbon content often corresponds to a greater possibility of generating large amounts of oil or gas.Hence,accurately calculating the total organic carbon content in a formation is very important.Present research is focused on precisely calculating the total organic carbon content based on machine learning.At present,many machine learning methods,including backpropagation neural networks,support vector regression,random forests,extreme learning machines,and deep learning,are employed to evaluate the total organic carbon content.However,the principles and perspectives of various machine learning algorithms are quite different.This paper reviews the application of various machine learning algorithms to deal with total organic carbon content evaluation problems.Of various machine learning algorithms used for TOC content predication,two algorithms,the backpropagation neural network and support vector regression are the most commonly used,and the backpropagation neural network is sometimes combined with many other algorithms to achieve better results.Additionally,combining multiple algorithms or using deep learning to increase the number of network layers can further improve the total organic carbon content prediction.The prediction by backpropagation neural network may be better than that by support vector regression;nevertheless,using any type of machine learning algorithm improves the total organic carbon content prediction in a given research block.According to some published literature,the determination coefficient(R^(2))can be increased by up to 0.46 after using machine learning.Deep learning algorithms may be the next breakthrough direction that can significantly improve the prediction of the total organic carbon content.Evaluating the total organic carbon content based on machine learning is of great significance.
基金Supported by the National Key Technology Research and Development Program of China(No.2011BAD13B06)the National Natural Science Foundation of China(No.41276172)the Special Scientific Research Funds For Central Non-Profit Institute,CAFS(No.2014A01YY01)
文摘We measured the organic content and sinking velocities of biodeposits from two scallop species(Chlamys farreri,Patinopecten yessoensis) and abalone(Haliotis discus hannai) that were cultured on suspended long-lines.Measurements were conducted every two months from April 2010 to February 2011.The shellfish were divided into three size groups(small,middle,and big sizes).At each sample point,we assessedbiodeposit organic content,average sinking velocity,the frequency distribution of sinkingvelocities,and the correlation between organic content and sinking velocity.The organic content of biodeposits varied significantly among months(P<0.05) and the pattern of change varied among species.Sinking velocities varied significantly,ranging from <0.5 cm/s to >1.9 cm/s.The sinking velocities of biodeposits from C.farreri and P.yessoensis were 0.5-1.5 cm/s and from H.discus hannai were <0.7 cm/s.The organic content was significantly negatively correlated to the sinking velocity of biodeposits in C.farreri(P<0.001) and P.yessoensis(P<0.05).
基金supported by the Key Project of Natural Science Foundation of Xinjiang Uygur Autonomous Region,China(2021D01D06)the National Natural Science Foundation of China(41961059)。
文摘Visible and near-infrared(vis-NIR)spectroscopy technique allows for fast and efficient determination of soil organic matter(SOM).However,a prior requirement for the vis-NIR spectroscopy technique to predict SOM is the effective removal of redundant information.Therefore,this study aims to select three wavelength selection strategies for obtaining the spectral response characteristics of SOM.The SOM content and spectral information of 110 soil samples from the Ogan-Kuqa River Oasis were measured under laboratory conditions in July 2017.Pearson correlation analysis was introduced to preselect spectral wavelengths from the preprocessed spectra that passed the 0.01 level significance test.The successive projection algorithm(SPA),competitive adaptive reweighted sampling(CARS),and Boruta algorithm were used to detect the optimal variables from the preselected wavelengths.Finally,partial least squares regression(PLSR)and random forest(RF)models combined with the optimal wavelengths were applied to develop a quantitative estimation model of the SOM content.The results demonstrate that the optimal variables selected were mainly located near the range of spectral absorption features(i.e.,1400.0,1900.0,and 2200.0 nm),and the CARS and Boruta algorithm also selected a few visible wavelengths located in the range of 480.0–510.0 nm.Both models can achieve a more satisfactory prediction of the SOM content,and the RF model had better accuracy than the PLSR model.The SOM content prediction model established by Boruta algorithm combined with the RF model performed best with 23 variables and the model achieved the coefficient of determination(R2)of 0.78 and the residual prediction deviation(RPD)of 2.38.The Boruta algorithm effectively removed redundant information and optimized the optimal wavelengths to improve the prediction accuracy of the estimated SOM content.Therefore,combining vis-NIR spectroscopy with machine learning to estimate SOM content is an important method to improve the accuracy of SOM prediction in arid land.
文摘The method of questionnaire is employed to investigate the impact of Chinese thinking in the writing processes of 80 college English majors.It reveals that the English writing process is a bilingual event(namely,English writers have both Chinese and English at their disposal when they are composing in English).And no matter whether the English proficiency of the learners is high or low,the learners have a great dependence on Chinese thinking in the process of English writing.In the categories of task reacting and content organizing,there is no great difference between the high and low English proficiency students.But in the category of linguistic form,the influence of Chinese thinking on the low level students is far greater than the high level students.
文摘The simulation of large-strain geotechnical laboratory tests with conventional Lagrangian finite element method(FEM)techniques is often problematic due to excessive mesh distortion.The multiple reversal direct shear(MRDS)test can be used to measure the residual shear strength of soils in a laboratory setting.However,modelling and simulation generally require advanced numerical methods to accommodate the large shear strains concentrated in the shear plane.In reality,when the standard direct shear(DS)apparatus is used,the MRDS method is prone to two major sources of measurement error:load cap tilting and specimen loss.These sources of error make it difficult or even impossible to correctly determine the residual shear strength.This paper presents a modified DS apparatus and multi-reversal multi-stage test method,simulated using the coupled Eulerian-Lagrangian(CEL)method in a finite element environment.The method was successful in evaluating equipment and preventing both load cap tilting and specimen loss,while modelling large-deformation behaviour that is not readily simulated with the conventional FEM or arbitrary Lagrangian-Eulerian(ALE)analysis.Thereafter,a modified DS apparatus was created for the purpose of analysing mixtures of organic materials found in an Australian clay.The results obtained from the modified DS CEL model in combination with laboratory tests show a great improvement in the measured residual shear strength profiles compared to those from the standard apparatus.The modified DS setup ensures that accurate material residual shear strengths are calculated,a factor that is vital to ensure appropriate soil behaviour is simulated for numerical analyses of large-scale geotechnical projects.
基金Supported by Shaanxi Provincial Innovation Capability Support Program(2019XY-03)Shaanxi Provincial Key R&D Program(2019ZDLNY01-05-02)+3 种基金Key R&D Project of Guangxi Zhuang Autonomous Region(GK AB19259016)Scientific and Technological Innovation Program of Shaanxi Academy of Forestry(SXLK2020-0218)Xi’an Science and Technology Program(20193051YF039N039)Xianyang Key R&D Program(2021DYF-GY-0008)。
文摘[Objectives]This study was conducted to improve the quality of straw returning to the field,enhance wheat disease resistance and ensure high and stable yield of wheat.[Methods]The effects of four returning modes on wheat stem rot and yield were studied by observation and experiments.[Results]The incidence rate and disease index of stem rot and white head rate of wheat were significantly reduced and the yield was significantly increased by adopting the method of straw returning to the field with the separation of"returning and seeding".The incidence rate and disease index of stem rot and white head rate of wheat were higher than those of the CK and the yield was significantly reduced when adopting the straw returning method of direct sowing.Treatment T_(1)(after maize was harvested,fertilizers,a nutrient-loaded microbial agent and a soil conditioner were evenly spread on the surface of straw,which was then returned to the field using a straw returning machine twice,and then ploughing,soil preparation and wheat sowing were carried out)showed an incidence rate of wheat crown rot 54.8%lower than that of the CK and a white head rate 87.5%lower than that of the CK,and the yield was 2305 kg/hm^(2) higher than that of the CK.[Conclusions]Straw returning can increase soil organic matter content,reduce soil bulk density,enhance soil respiration,and improve wheat disease resistance and yield.
基金Shaanxi Provincial Innovation Capability Support Program(2019XY-03)Key R&D Program of Shaanxi Province(2019ZDLN01-05-02)+2 种基金Guangxi Key R&D Program(GuiKe AB19259016)Project of Shaanxi Academy of Forestry Sciences(SXLK2020-0218)Xi'an Science and Technology Plan Project(20193051YF039NS039,20NYYF0026).
文摘[Objectives]To alleviate the influence of meteorological conditions on soil environment(temperature and water content)and maintain high and stable grain yield.[Methods]Taking Sunzhen Experimental Station of Weinan Academy of Agricultural Sciences as the experimental base,the effects of returning double-crop wheat and corn straw to field(Twm),returning single-crop corn straw to field(Tm),returning single-crop wheat straw to field(Tw)on soil temperature,water content,straw decomposition rate and nutrient release,soil organic matter and bulk density were studied systematically.[Results]Twm treatment could effectively alleviate the effects of meteorological conditions on soil temperature and water content.The decomposition rate of straw treated with Twm was 4.7%higher than that of Tm treatment,3.8%higher than that of Tw treatment,10.5%higher than that of Tm treatment,and the decomposition rate of straw showed a trend of"first fast,then slow and then fast".The release of nitrogen from straw was basically similar to that of straw decay,and the release of potassium and phosphorus increased at first and then remained basically unchanged.The release rate of potassium was the highest,followed by phosphorus and nitrogen.The content of soil organic matter in Twm treatment increased by 11.67%annually,an annual average of 0.998 g/kg.The soil bulk density of Twm treatment decreased by 0.058 g/cm^(3) annually,an annual average of 4.29%.The fundamental reason is that Twm treatment provides conditions(temperature,water content,nutrition)for microbial growth,reproduction,enzyme production and biochemical reaction,and increases the exchange capacity of soil and external water,heat,gas and fertilizer.[Conclusions]It is expected is to help people change their understanding of returning straw to field from"quick harvest"to"fertilizer transformation".
基金This work was funded by National Science and Technology Major Project of China(Grant No.2011ZX05009-002)。
文摘Shale oil refers to liquid hydrocarbons existing in free,dissolved or adsorbed states in the effective source rock of mudstones or shales,where some residual oil is retained after hydrocarbon generation and expulsion from the mudstones or shales.Basically shale oil experiences no migration or only undergoes some primary,short-distance migration within the source rocks.So far,there is no consensus on the exact definition of shale oil in China.Researches on the reservoir-controlling factors and evaluation elements are also far from sufficient.In this study,shale oil reservoirs are defined as mudstones or shales excluding the interbedded or adjacent layers of coarser siliciclastic or chemical-biogenic lithofacies(e.g.siltstone,carbonate,salt or chert layers)in the source rocks.According to different reservoiring mechanisms,shale oil reservoirs are classified into“fracture type”and“matrix type”.The general features of shale oil reservoirs include:rich in organic matters,dominated by Type I and II_(1) kerogen(with Ro=0.6%-1.2%and total organic content(TOC)>2.0%),complex mineral compositions and laminated structures,tight storage space,low porosity and ultra-low permeability,and as well as the requirement for reservoir fracturing.This paper emphasizes the critical role of organic matter in the formation and evaluation of shale oil reservoirs,and its critical control on the oil generation potential and storage capacity of shale,which eventually determine the oil content and productivity of shale oil reservoirs.Besides,a set of reservoir evaluation criteria is also put forward with a focus on the TOC content,in which the threshold values of TOC are set to be 2%and 4%,and a variety of indicators are taken into account including the type and maturity of organic matter,the thickness of organic-rich shale,mineral compositions and rock types,porosity and permeability,and fracturing ability.The evaluation criteria divide shale oil reservoirs into three grades,i.e.,target reservoir,favorable reservoir and invalid reservoir.
基金the National Key Research and Development Program of China(No.2017YFD0800103)the Strategic Priority Research Program of Chinese Academy of Sciences(No.XDA23020401)。
文摘Oxamide is a potential slow-release nitrogen(N)fertilizer,especially under waterlogged conditions,due to its low solubility in water and the slow-release of ammonium by soil amidases.To investigate the effects of oxamide granules(2.00-2.38 mm in diameter)as a single basal fertilizer(180 or 144 kg N ha^(-1))on rice growth,soil properties,and N use efficiency in terms of N recovery efficiency(NRE),we conducted field experiments on two different types of paddy soils over two rice-growing seasons.Results showed that the fertilization effects of oxamide granules varied between the two types of paddy soils.In the red clayey paddy soil,the grain yields for both rice-growing seasons were high with a significantly higher NRE in the oxamide treatment than in the urea treatment.However,in the alluvial sandy paddy soil,the grain yields in the oxamide treatment were slightly lower than those in the urea treatment.Furthermore,oxamide produced little improvement in NRE in the alluvial sandy paddy soil.Soil incubation experiments over 98 d were also carried out to evaluate the factors affecting the N release behavior of oxamide granules in the two types of paddy soils.We found that the amidase activity was higher and,therefore,the oxamide hydrolysis rate was faster in the alluvial sandy paddy soil,which had a higher soil pH value and organic matter content,compared to the red clayey paddy soil.The faster N release and the longer growth period resulted in a mismatch between N supply by oxamide and rice demand,which,in turn,led to little improvement in NRE and a decreased grain yield in the alluvial sandy paddy soil,especially in the reduced oxamide treatment.These results could help select the appropriate size of oxamide granules for use as a slow-release N fertilizer depending on the soil properties and growth period of rice.
基金This project(FUEL,reference 2016-HW-MS-8)is funded under the EPA Research Programme 2014-2020The EPA Research Programme is a Government of Ireland initiative funded by the Department of Communications,Climate Action and Environment.
文摘A series of laboratory experiments were conducted to examine the leaching of decabromodiphenyl ether(BDE-209)and hexabromocyclododecane(HBCDD)from a mix of three fabrics.Consistent with previous reports that such leaching is governed by second order kinetics,concentrations in leachate were markedly higher in the first 24 h of leaching,and diminished by an order of magnitude after 1 week.The influence of the waste:leachate ratio was examined for the first time,with leaching of both BDE-209 and HBCDD significantly greater(p<0.05)at a waste:leachate ratio of 0.005 g/mL than at 0.05 g/mL.Using dissolved humic matter(DHM)solutions as proxy for simulating organic landfill leachates we found that leaching of both BDE-209 and HBCDD was also significantly greater at a DHM concentration of 1,000 mg/L in leachate compared to that observed at DHM values of 100 and 0 mg/L.Agitation of waste:leachate mixtures significantly enhanced leaching.While leaching of HBCDD decreased significantly as leachate pH increased from 5.8,through 6.5,to 8.5;no significant impact of pH on leaching of BDE-209 was detected.Concentrations in leachate of both BDE-209 and HBCDD decreased significantly on increasing leachate temperature from 20℃to 60℃and 80℃.This is considered most likely due to volatilisation of these contaminants into the headspace of the leaching vessel at higher temperatures.
