To understand the natural gas characteristics of multi-thin coal seam,this study selected the desorbed gas of coal seams in different layers of Well A in the Wujiu depression,Hailar Basin in northeast Inner Mongolia.T...To understand the natural gas characteristics of multi-thin coal seam,this study selected the desorbed gas of coal seams in different layers of Well A in the Wujiu depression,Hailar Basin in northeast Inner Mongolia.The results show that the heavy hydrocarbon content of desorbed gas increases significantly with the increasing depth.Methane carbon(δ13C_(1))and ethane carbon(δ13C_(2))isotope values are vertically become heavier downwards,while the δ13 values did not change significantly.The kerogen is close to the III–II mixed type with the source rocks mainly deposited in a shore/shallow lake or braided-river delta front,and the gas produced has certain characteristics of oil associated gas.However,the characteristics of oil associated gas produced by the organic formed in the shallow-water environment(braided-river delta plain)are not obvious.The sandstone pore and fracture systems interbedded with multi-thin coal seam are well developed.And it is conducive to the migration of methanogenic micro-organisms to coal seams via groundwater,making it easier to produce biogenic gas under this geological condition.During the burial evolution of coal-bearing strata in the study area,when the burial depth reaches the maximum,there are significant differences in the paleotemperature experienced by different vertical coal seams,caused by a high-paleogeothermal gradient,increasing the δ13C_(2) of desorbed gas with increasing depth.The above research indicates that there is less biogenic gas in the multi-thin coal seams with relatively developed mudstone,and the multi-thin coal seams with relatively developed sandstones have obvious biogenic gas characteristics.Therefore,for the exploration and development of biogenic gas in low-rank multi-thin coal seams,it is necessary to give priority to the layer with high sandstone content.展开更多
针对岩石薄片图像超分辨率重建过程中因纹理复杂导致现有重建方法效果不理想的问题,提出面向岩石薄片图像的超分辨率网络模型(super-resolution denoising diffusion probability model of rock slice,rsDDPMSR).针对传统上采样方法往...针对岩石薄片图像超分辨率重建过程中因纹理复杂导致现有重建方法效果不理想的问题,提出面向岩石薄片图像的超分辨率网络模型(super-resolution denoising diffusion probability model of rock slice,rsDDPMSR).针对传统上采样方法往往会导致伪影和低分辨率图像先验信息利用不充分的问题提出分层特征增强网络(layered feature enhancement network,LFE-Net),利用双通路网络对平稳小波变换分解后的高频与低频分量进行分层特征增强.为引导扩散模型的生成方向并提供丰富先验信息,将经过LFE-Net增强后的低分辨率特征与目标高分辨率加噪图像特征通道拼接作为扩散模型的条件输入.在U-Net的基础上设计了双编码器多尺度噪声预测网络(ACA-U-Net)有效处理岩石薄片多尺度信息并在跳跃连接中引入时间感知的自适应交叉注意力机制适配扩散模型不同去噪阶段的特征分布变化增强模型对关键区域的关注程度,有效提升图像重建细节.实验结果表明,rsDDPMSR在2×、4×、8×放大倍数下,峰值信噪比(PSNR)和结构相似度(SSIM)相比于CAMixerSR、SDFlow、IDM和SR3等主流重建方法具有更优的重建效果.展开更多
目的建立积雪草提取物的薄层色谱法(thin-layer chromatography,TLC)鉴别方法和高效液相色谱定量方法,并结合一测多评法(quantitative analysis of multi-components by single marker,QAMS)实现积雪草苷、积雪草苷B和羟基积雪草苷的定...目的建立积雪草提取物的薄层色谱法(thin-layer chromatography,TLC)鉴别方法和高效液相色谱定量方法,并结合一测多评法(quantitative analysis of multi-components by single marker,QAMS)实现积雪草苷、积雪草苷B和羟基积雪草苷的定量测定。方法首先采用TLC对积雪草提取物进行定性鉴别,确保样品的真实性;其次采用高效液相色谱法进行含量测定,流动相分别为2 mmol/Lβ-环糊精溶液和乙腈,检测波长为205 nm。以羟基积雪草苷为参照物,计算其他两种物质的相对校正因子,并将测定含量与外标法测定结果进行比较。结果3种成分在10~500 mg/L范围内线性关系良好,不同浓度水平的加标回收率范围为87.0%~108.2%,相对标准偏差为3.1%~5.2%,方法具有良好的精密度、重复性和稳定性。QAMS与外标法测定积雪草提取物中3种特征性成分的含量一致性良好。结论TLC鉴别方法结合QAMS方法实现定性定量检测,能够对积雪草提取物的质量控制提供技术支持。展开更多
基金We would like to thank the National Natural Science Foundation of China(Grant Nos.42130802,42002193,and 42002186)researchers Yanqiu Zhang,Wutao Hu,Haitao Lin,and Fengchun Li from Inner Mongolia Coal Geology Bureau for their help in sample acquisition.
文摘To understand the natural gas characteristics of multi-thin coal seam,this study selected the desorbed gas of coal seams in different layers of Well A in the Wujiu depression,Hailar Basin in northeast Inner Mongolia.The results show that the heavy hydrocarbon content of desorbed gas increases significantly with the increasing depth.Methane carbon(δ13C_(1))and ethane carbon(δ13C_(2))isotope values are vertically become heavier downwards,while the δ13 values did not change significantly.The kerogen is close to the III–II mixed type with the source rocks mainly deposited in a shore/shallow lake or braided-river delta front,and the gas produced has certain characteristics of oil associated gas.However,the characteristics of oil associated gas produced by the organic formed in the shallow-water environment(braided-river delta plain)are not obvious.The sandstone pore and fracture systems interbedded with multi-thin coal seam are well developed.And it is conducive to the migration of methanogenic micro-organisms to coal seams via groundwater,making it easier to produce biogenic gas under this geological condition.During the burial evolution of coal-bearing strata in the study area,when the burial depth reaches the maximum,there are significant differences in the paleotemperature experienced by different vertical coal seams,caused by a high-paleogeothermal gradient,increasing the δ13C_(2) of desorbed gas with increasing depth.The above research indicates that there is less biogenic gas in the multi-thin coal seams with relatively developed mudstone,and the multi-thin coal seams with relatively developed sandstones have obvious biogenic gas characteristics.Therefore,for the exploration and development of biogenic gas in low-rank multi-thin coal seams,it is necessary to give priority to the layer with high sandstone content.
文摘针对岩石薄片图像超分辨率重建过程中因纹理复杂导致现有重建方法效果不理想的问题,提出面向岩石薄片图像的超分辨率网络模型(super-resolution denoising diffusion probability model of rock slice,rsDDPMSR).针对传统上采样方法往往会导致伪影和低分辨率图像先验信息利用不充分的问题提出分层特征增强网络(layered feature enhancement network,LFE-Net),利用双通路网络对平稳小波变换分解后的高频与低频分量进行分层特征增强.为引导扩散模型的生成方向并提供丰富先验信息,将经过LFE-Net增强后的低分辨率特征与目标高分辨率加噪图像特征通道拼接作为扩散模型的条件输入.在U-Net的基础上设计了双编码器多尺度噪声预测网络(ACA-U-Net)有效处理岩石薄片多尺度信息并在跳跃连接中引入时间感知的自适应交叉注意力机制适配扩散模型不同去噪阶段的特征分布变化增强模型对关键区域的关注程度,有效提升图像重建细节.实验结果表明,rsDDPMSR在2×、4×、8×放大倍数下,峰值信噪比(PSNR)和结构相似度(SSIM)相比于CAMixerSR、SDFlow、IDM和SR3等主流重建方法具有更优的重建效果.
文摘目的建立积雪草提取物的薄层色谱法(thin-layer chromatography,TLC)鉴别方法和高效液相色谱定量方法,并结合一测多评法(quantitative analysis of multi-components by single marker,QAMS)实现积雪草苷、积雪草苷B和羟基积雪草苷的定量测定。方法首先采用TLC对积雪草提取物进行定性鉴别,确保样品的真实性;其次采用高效液相色谱法进行含量测定,流动相分别为2 mmol/Lβ-环糊精溶液和乙腈,检测波长为205 nm。以羟基积雪草苷为参照物,计算其他两种物质的相对校正因子,并将测定含量与外标法测定结果进行比较。结果3种成分在10~500 mg/L范围内线性关系良好,不同浓度水平的加标回收率范围为87.0%~108.2%,相对标准偏差为3.1%~5.2%,方法具有良好的精密度、重复性和稳定性。QAMS与外标法测定积雪草提取物中3种特征性成分的含量一致性良好。结论TLC鉴别方法结合QAMS方法实现定性定量检测,能够对积雪草提取物的质量控制提供技术支持。
