The Upper Shihezi sedimentary rocks in the Linxing region has been estimated with a significant volume of tight sandstone gas.However,lateral distribution of the present-day stress magnitude is poorly understood,which...The Upper Shihezi sedimentary rocks in the Linxing region has been estimated with a significant volume of tight sandstone gas.However,lateral distribution of the present-day stress magnitude is poorly understood,which limits further gas production.Hence,a one-dimensional mechanical earth model and a three-dimensional heterogeneous geomechanical model are built to address this issue.The results indicate that the strike-slip stress regime is dominant in the Upper Shihezi Formation.Relatively low stresses are mainly located around wells L-60,L-22,L-40,L-90,etc,and stress distributions exhibit the similarity in the Members H2 and H4.The differential stresses are relatively low in the Upper Shihezi Formation,suggesting that complex hydraulic fracture networks may be produced.Natural fractures in the Upper Shihezi Formation contribute little to the overall gas production in the Linxing region.In addition,the minimum principal stress gradient increases with Young's modulus,suggesting that the stiffer rocks commonly convey higher stress magnitudes.There is a strong interplay between stress distribution and heterogeneity in rock mechanics.Overall,the relative error between the predicted and measured results is less than 10%,implying that the predicted stress distribution is reliable and can be used for subsequent analysis in the Linxing region.展开更多
China Oilfield Chemical Company(COCC)is a subsidiary company of China National Petroleum Corporation(CNPC),approved by the former Production Office of the State Couneil for its establishment.It is an enterprise with s...China Oilfield Chemical Company(COCC)is a subsidiary company of China National Petroleum Corporation(CNPC),approved by the former Production Office of the State Couneil for its establishment.It is an enterprise with state owner-ship and having qualifcation of legol Person regis-tered in the State Industry and Commerce Adminis-tration.The Company's headguarters is located in Beijing.展开更多
本试验旨在基于康奈尔净碳水化合物与蛋白质体系(CNCPS)建立大麦秸秆营养组分数据库,并利用近红外光谱分析技术(NIRS)建立其营养价值预测模型。试验采集甘肃省13个县市96份大麦秸秆样品,测定其干物质(DM)、粗灰分(Ash)、粗蛋白质(CP)、...本试验旨在基于康奈尔净碳水化合物与蛋白质体系(CNCPS)建立大麦秸秆营养组分数据库,并利用近红外光谱分析技术(NIRS)建立其营养价值预测模型。试验采集甘肃省13个县市96份大麦秸秆样品,测定其干物质(DM)、粗灰分(Ash)、粗蛋白质(CP)、粗脂肪(EE)、中性洗涤纤维(NDF)、酸性洗涤纤维(ADF)、酸性洗涤木质素(ADL)、中性洗涤不溶蛋白质(NDIP)、酸性洗涤不溶蛋白质(ADIP)、可溶性粗蛋白质(SP)、钙(Ca)和磷(P)含量,利用CNCPS 6.5计算各样品碳水化合物(CHO)和蛋白质营养组分。分别用76份和20份大麦秸秆样品作为定标集和验证集评价NIRS预测模型。结果显示:1)大麦秸秆DM、Ash、CP、EE、NDF、ADF、ADL、NDIP、ADIP、SP、Ca和P含量分别为95.21%、7.38%、3.51%、5.68%、70.95%、45.16%、5.17%、1.02%、0.57%、1.65%、0.71%和0.09%。2)大麦秸秆CNCPS CHO各组分CHO、非纤维性碳水化合物(NFC)、可溶性纤维(CB2)、可消化纤维(CB3)和不消化纤维(CC)含量分别为83.42%、12.47%、12.47%、58.55%和12.40%。大麦秸秆CNCPS蛋白质各组分可溶性真蛋白质(PA2)、难溶性真蛋白质(PB1)、纤维结合蛋白质(PB2)和非降解蛋白质(PC)含量分别为1.65%、1.23%、0.45%和0.57%。3)有机物(OM)、CP、NDF、ADF、CHO、NFC和CB2的交互验证决定系数(1-VR)>0.8,验证决定系数(RSQv)≥0.84,这些模型可用于日常分析。OM、CP、NDF、ADF、CHO、NFC和CB2的模型参数分别为标准正常化和去散射二阶导数处理(SNV and detrend 2,4,4,1)、SNV and detrend 2,4,4,1;标准正常化和去散射一阶导数处理(SNV and detrend 1,4,4,1);无散射一阶导数处理(None 1,4,4,1);SNV and detrend 2,4,4,1;无散射二阶导数处理(None 2,4,4,1);None 2,4,4,1。而其余成分所建模型未达到实用水平,模型须进一步完善。总之,本研究为大麦秸秆在反刍动物饲粮中的应用提供基础的化学分析数据,并通过NIRS方法建立了主要营养成分的快速预测模型。展开更多
基金The authors would like to thank the financial support from the National Natural Science Foundation of China(41702130,41872171 and 41672146)National Science and Technology Major Project(2016ZX05066)Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD).
文摘The Upper Shihezi sedimentary rocks in the Linxing region has been estimated with a significant volume of tight sandstone gas.However,lateral distribution of the present-day stress magnitude is poorly understood,which limits further gas production.Hence,a one-dimensional mechanical earth model and a three-dimensional heterogeneous geomechanical model are built to address this issue.The results indicate that the strike-slip stress regime is dominant in the Upper Shihezi Formation.Relatively low stresses are mainly located around wells L-60,L-22,L-40,L-90,etc,and stress distributions exhibit the similarity in the Members H2 and H4.The differential stresses are relatively low in the Upper Shihezi Formation,suggesting that complex hydraulic fracture networks may be produced.Natural fractures in the Upper Shihezi Formation contribute little to the overall gas production in the Linxing region.In addition,the minimum principal stress gradient increases with Young's modulus,suggesting that the stiffer rocks commonly convey higher stress magnitudes.There is a strong interplay between stress distribution and heterogeneity in rock mechanics.Overall,the relative error between the predicted and measured results is less than 10%,implying that the predicted stress distribution is reliable and can be used for subsequent analysis in the Linxing region.
文摘China Oilfield Chemical Company(COCC)is a subsidiary company of China National Petroleum Corporation(CNPC),approved by the former Production Office of the State Couneil for its establishment.It is an enterprise with state owner-ship and having qualifcation of legol Person regis-tered in the State Industry and Commerce Adminis-tration.The Company's headguarters is located in Beijing.
文摘本试验旨在基于康奈尔净碳水化合物与蛋白质体系(CNCPS)建立大麦秸秆营养组分数据库,并利用近红外光谱分析技术(NIRS)建立其营养价值预测模型。试验采集甘肃省13个县市96份大麦秸秆样品,测定其干物质(DM)、粗灰分(Ash)、粗蛋白质(CP)、粗脂肪(EE)、中性洗涤纤维(NDF)、酸性洗涤纤维(ADF)、酸性洗涤木质素(ADL)、中性洗涤不溶蛋白质(NDIP)、酸性洗涤不溶蛋白质(ADIP)、可溶性粗蛋白质(SP)、钙(Ca)和磷(P)含量,利用CNCPS 6.5计算各样品碳水化合物(CHO)和蛋白质营养组分。分别用76份和20份大麦秸秆样品作为定标集和验证集评价NIRS预测模型。结果显示:1)大麦秸秆DM、Ash、CP、EE、NDF、ADF、ADL、NDIP、ADIP、SP、Ca和P含量分别为95.21%、7.38%、3.51%、5.68%、70.95%、45.16%、5.17%、1.02%、0.57%、1.65%、0.71%和0.09%。2)大麦秸秆CNCPS CHO各组分CHO、非纤维性碳水化合物(NFC)、可溶性纤维(CB2)、可消化纤维(CB3)和不消化纤维(CC)含量分别为83.42%、12.47%、12.47%、58.55%和12.40%。大麦秸秆CNCPS蛋白质各组分可溶性真蛋白质(PA2)、难溶性真蛋白质(PB1)、纤维结合蛋白质(PB2)和非降解蛋白质(PC)含量分别为1.65%、1.23%、0.45%和0.57%。3)有机物(OM)、CP、NDF、ADF、CHO、NFC和CB2的交互验证决定系数(1-VR)>0.8,验证决定系数(RSQv)≥0.84,这些模型可用于日常分析。OM、CP、NDF、ADF、CHO、NFC和CB2的模型参数分别为标准正常化和去散射二阶导数处理(SNV and detrend 2,4,4,1)、SNV and detrend 2,4,4,1;标准正常化和去散射一阶导数处理(SNV and detrend 1,4,4,1);无散射一阶导数处理(None 1,4,4,1);SNV and detrend 2,4,4,1;无散射二阶导数处理(None 2,4,4,1);None 2,4,4,1。而其余成分所建模型未达到实用水平,模型须进一步完善。总之,本研究为大麦秸秆在反刍动物饲粮中的应用提供基础的化学分析数据,并通过NIRS方法建立了主要营养成分的快速预测模型。
