地震随机反演方法由于井间数据缺失,反演结果的横向连续性较差。且反演效率低、反演结果随机性强。为此,我们提出基于地震波形约束的地质统计学反演方法。用地震数据的相关系数来衡量地震波形的相似程度,代替传统的变差函数进行序贯高...地震随机反演方法由于井间数据缺失,反演结果的横向连续性较差。且反演效率低、反演结果随机性强。为此,我们提出基于地震波形约束的地质统计学反演方法。用地震数据的相关系数来衡量地震波形的相似程度,代替传统的变差函数进行序贯高斯模拟。在贝叶斯框架下,结合地震数据的约束,利用马尔科夫链-蒙特卡洛(Markov Chain Monte Carlo,MCMC)算法对模拟结果进行随机扰动和全局寻优,获得优化的参数反演结果。模型测试结果表明,基于地震波形约束的初始模型较为精确地刻画了地下储层的空间结构。对其进行迭代优化可以加快马尔科夫链的收敛速度,有效提高反演结果的精度。本文将提出的地质统计学反演方法用于某油田实际地震数据,在随机模拟过程和目标函数的约束中,充分挖掘了地震波形蕴含的地质信息,并为实现多数据联合约束地震反演提供了理论依据。展开更多
目的三结构域家族33(Trim33)在调控成骨细胞分化的过程中起到了非常重要的作用,而在脂肪细胞分化过程中的作用却鲜有报道。文中以Trim33为对象探讨其对脂肪细胞分化的影响。方法以转染Trim33-pcDNA3.1过表达质粒的骨髓基质细胞ST2细胞...目的三结构域家族33(Trim33)在调控成骨细胞分化的过程中起到了非常重要的作用,而在脂肪细胞分化过程中的作用却鲜有报道。文中以Trim33为对象探讨其对脂肪细胞分化的影响。方法以转染Trim33-pcDNA3.1过表达质粒的骨髓基质细胞ST2细胞作为实验组,以转染pc DNA3.1质粒的骨髓基质细胞ST2细胞作为对照组,将2组细胞进行成脂诱导分化后,利用油红O染色、qRT-PCR及Western blot技术分析2组细胞CCAAT增强子结合蛋白(C/EBP)α、成脂相关因子过氧化物酶体增殖物激活受体(PPAR)γ、脂肪细胞表征因子FABP4、脂肪因子adipsin等脂肪特异性基因表达的变化。结果与对照组相比,实验组Trim33表达水平显著上升(1.00±0.31 vs 88.51±14.31,P<0.01)。成脂诱导5 d后,经油红O染色,转染Trim33-pcDNA3.1过表达质粒,实验组较对照组细胞脂滴数量明显增多。A520结果与染色一致,实验组的A值明显高于对照组(0.69±0.03 vs 0.34±0.03,P<0.01)。与对照组比较,实验组PPARγ、C/EBPα、FABP4、adipsin mRNA相对表达[(1.00±0.19) vs (1.79±0.21)、(1.00±0.12) vs (2.28±0.24)、(1.00±0.01) vs (10.30±1.38)、(1.00±0.16) vs (12.50±1.96)]均明显增加(P<0.05)。实验组较对照组成脂特异性基因Trim33、PPARγ、C/EBPα、FABP4的蛋白表达上调。结论 Trim33能促进骨髓基质细胞脂堆积并增强脂肪特异性基因的表达。展开更多
目的:分析鉴定大鼠口服五子衍宗丸后的血中移行成分,并初步探讨其治疗少弱精子症的网络药理机制。方法:建立UPLC-ESI-LTQ-Orbitrap方法,分析五子衍宗丸的体内成分,鉴定其血中移行成分。随后利用Stitch、DrugBank、OMIM数据库分别获得药...目的:分析鉴定大鼠口服五子衍宗丸后的血中移行成分,并初步探讨其治疗少弱精子症的网络药理机制。方法:建立UPLC-ESI-LTQ-Orbitrap方法,分析五子衍宗丸的体内成分,鉴定其血中移行成分。随后利用Stitch、DrugBank、OMIM数据库分别获得药物入血成分靶标及与少弱精子症相关的靶标信息。采用String数据库和Cytoscape软件构建五子衍宗丸入血成分-入血成分靶标-少弱精子症靶标网络,再根据网络拓扑结构特征值筛选核心靶标并明确其对应的入血成分并通过Systems Dock Web Site对预测结果进行分子对接验证。最后借助DAVID数据库对核心靶标进行生物学功能和KEGG通路富集分析。结果:鉴定了五子衍宗丸大鼠血中移行成分42个,网络药理分析共筛选到五子衍宗丸入血成分20个,核心靶标78个。其治疗少弱精子症可能主要涉及信号转导、分子功能、催化活性、内环境稳态、生物合成及代谢等生物学过程和神经活性配体-受体相互作用、钙信号、甾体激素生物合成、甘氨酸、丝氨酸及苏氨酸代谢等信号通路。结论:本研究初步阐明了五子衍宗丸的潜在药效物质基础,探讨了五子衍宗丸治疗少弱精子症的作用机制,为更进一步深入研究其药效物质及其药理机制提供了有益参考。展开更多
In the conventional stochastic inversion method,the spatial structure information of underground strata is usually characterized by variograms.However,effectively characterizing the heterogeneity of complex strata is ...In the conventional stochastic inversion method,the spatial structure information of underground strata is usually characterized by variograms.However,effectively characterizing the heterogeneity of complex strata is difficult.In this paper,multiple parameters are used to fully explore the underground formation information in the known seismic reflection and well log data.The spatial structure characteristics of complex underground reservoirs are described more comprehensively using multiple statistical characteristic parameters.We propose a prestack seismic stochastic inversion method based on prior information on statistical characteristic parameters.According to the random medium theory,this method obtains several statistical characteristic parameters from known seismic and logging data,constructs a prior information model that meets the spatial structure characteristics of the underground strata,and integrates multiparameter constraints into the likelihood function to construct the objective function.The very fast quantum annealing algorithm is used to optimize and update the objective function to obtain the fi nal inversion result.The model test shows that compared with the traditional prior information model construction method,the prior information model based on multiple parameters in this paper contains more detailed stratigraphic information,which can better describe complex underground reservoirs.A real data analysis shows that the stochastic inversion method proposed in this paper can effectively predict the geophysical characteristics of complex underground reservoirs and has a high resolution.展开更多
Accurately detecting the arrival time of a channel wave in a coal seam is very important for in-seam seismic data processing. The arrival time greatly affects the accuracy of the channel wave inversion and the compute...Accurately detecting the arrival time of a channel wave in a coal seam is very important for in-seam seismic data processing. The arrival time greatly affects the accuracy of the channel wave inversion and the computed tomography （CT） result. However, because the signal-to-noise ratio of in-seam seismic data is reduced by the long wavelength and strong frequency dispersion, accurately timing the arrival of channel waves is extremely difficult. For this purpose, we propose a method that automatically picks up the arrival time of channel waves based on multi-channel constraints. We first estimate the Jaccard similarity coefficient of two ray paths, then apply it as a weight coefficient for stacking the multi- channel dispersion spectra. The reasonableness and effectiveness of the proposed method is verified in an actual data application. Most importantly, the method increases the degree of automation and the pickup precision of the channel-wave arrival time.展开更多
基金supported by special fund for research institutes supplied the National Key Research and Development Project(2018YFC0807804)the General Program of National Natural Science Foundation of China(42074175)the Project Supported by Natural Science Basic Research Plan in Shaanxi Province of China(2020JM-714,2020JQ-741,2021JQ-949).
基金supported by the National Natural Science Foundation of China[Grant Nos.42174146,42074136,42174144]Innovation Fund Project for Graduate Students of China University of Petroleum(East China)[Grant No.23CX04015A].
文摘地震随机反演方法由于井间数据缺失,反演结果的横向连续性较差。且反演效率低、反演结果随机性强。为此,我们提出基于地震波形约束的地质统计学反演方法。用地震数据的相关系数来衡量地震波形的相似程度,代替传统的变差函数进行序贯高斯模拟。在贝叶斯框架下,结合地震数据的约束,利用马尔科夫链-蒙特卡洛(Markov Chain Monte Carlo,MCMC)算法对模拟结果进行随机扰动和全局寻优,获得优化的参数反演结果。模型测试结果表明,基于地震波形约束的初始模型较为精确地刻画了地下储层的空间结构。对其进行迭代优化可以加快马尔科夫链的收敛速度,有效提高反演结果的精度。本文将提出的地质统计学反演方法用于某油田实际地震数据,在随机模拟过程和目标函数的约束中,充分挖掘了地震波形蕴含的地质信息,并为实现多数据联合约束地震反演提供了理论依据。
文摘目的三结构域家族33(Trim33)在调控成骨细胞分化的过程中起到了非常重要的作用,而在脂肪细胞分化过程中的作用却鲜有报道。文中以Trim33为对象探讨其对脂肪细胞分化的影响。方法以转染Trim33-pcDNA3.1过表达质粒的骨髓基质细胞ST2细胞作为实验组,以转染pc DNA3.1质粒的骨髓基质细胞ST2细胞作为对照组,将2组细胞进行成脂诱导分化后,利用油红O染色、qRT-PCR及Western blot技术分析2组细胞CCAAT增强子结合蛋白(C/EBP)α、成脂相关因子过氧化物酶体增殖物激活受体(PPAR)γ、脂肪细胞表征因子FABP4、脂肪因子adipsin等脂肪特异性基因表达的变化。结果与对照组相比,实验组Trim33表达水平显著上升(1.00±0.31 vs 88.51±14.31,P<0.01)。成脂诱导5 d后,经油红O染色,转染Trim33-pcDNA3.1过表达质粒,实验组较对照组细胞脂滴数量明显增多。A520结果与染色一致,实验组的A值明显高于对照组(0.69±0.03 vs 0.34±0.03,P<0.01)。与对照组比较,实验组PPARγ、C/EBPα、FABP4、adipsin mRNA相对表达[(1.00±0.19) vs (1.79±0.21)、(1.00±0.12) vs (2.28±0.24)、(1.00±0.01) vs (10.30±1.38)、(1.00±0.16) vs (12.50±1.96)]均明显增加(P<0.05)。实验组较对照组成脂特异性基因Trim33、PPARγ、C/EBPα、FABP4的蛋白表达上调。结论 Trim33能促进骨髓基质细胞脂堆积并增强脂肪特异性基因的表达。
文摘目的:分析鉴定大鼠口服五子衍宗丸后的血中移行成分,并初步探讨其治疗少弱精子症的网络药理机制。方法:建立UPLC-ESI-LTQ-Orbitrap方法,分析五子衍宗丸的体内成分,鉴定其血中移行成分。随后利用Stitch、DrugBank、OMIM数据库分别获得药物入血成分靶标及与少弱精子症相关的靶标信息。采用String数据库和Cytoscape软件构建五子衍宗丸入血成分-入血成分靶标-少弱精子症靶标网络,再根据网络拓扑结构特征值筛选核心靶标并明确其对应的入血成分并通过Systems Dock Web Site对预测结果进行分子对接验证。最后借助DAVID数据库对核心靶标进行生物学功能和KEGG通路富集分析。结果:鉴定了五子衍宗丸大鼠血中移行成分42个,网络药理分析共筛选到五子衍宗丸入血成分20个,核心靶标78个。其治疗少弱精子症可能主要涉及信号转导、分子功能、催化活性、内环境稳态、生物合成及代谢等生物学过程和神经活性配体-受体相互作用、钙信号、甾体激素生物合成、甘氨酸、丝氨酸及苏氨酸代谢等信号通路。结论:本研究初步阐明了五子衍宗丸的潜在药效物质基础,探讨了五子衍宗丸治疗少弱精子症的作用机制,为更进一步深入研究其药效物质及其药理机制提供了有益参考。
基金the National Science Foundation of China(No.42074136 and U19B2008)the Major National Science and Technology Projects(No.2016ZX05027004-001 and 2016ZX05002-005-009)+1 种基金the Fundamental Research Funds for the Central Universities(No.19CX02007A)China Postdoctoral Science Foundation(No.2020M672170).
文摘In the conventional stochastic inversion method,the spatial structure information of underground strata is usually characterized by variograms.However,effectively characterizing the heterogeneity of complex strata is difficult.In this paper,multiple parameters are used to fully explore the underground formation information in the known seismic reflection and well log data.The spatial structure characteristics of complex underground reservoirs are described more comprehensively using multiple statistical characteristic parameters.We propose a prestack seismic stochastic inversion method based on prior information on statistical characteristic parameters.According to the random medium theory,this method obtains several statistical characteristic parameters from known seismic and logging data,constructs a prior information model that meets the spatial structure characteristics of the underground strata,and integrates multiparameter constraints into the likelihood function to construct the objective function.The very fast quantum annealing algorithm is used to optimize and update the objective function to obtain the fi nal inversion result.The model test shows that compared with the traditional prior information model construction method,the prior information model based on multiple parameters in this paper contains more detailed stratigraphic information,which can better describe complex underground reservoirs.A real data analysis shows that the stochastic inversion method proposed in this paper can effectively predict the geophysical characteristics of complex underground reservoirs and has a high resolution.
基金supported by the National Major Scientific and Technological Special Project during the 13th Five-year Plan Period(No.2016ZX05045003-005)
文摘Accurately detecting the arrival time of a channel wave in a coal seam is very important for in-seam seismic data processing. The arrival time greatly affects the accuracy of the channel wave inversion and the computed tomography （CT） result. However, because the signal-to-noise ratio of in-seam seismic data is reduced by the long wavelength and strong frequency dispersion, accurately timing the arrival of channel waves is extremely difficult. For this purpose, we propose a method that automatically picks up the arrival time of channel waves based on multi-channel constraints. We first estimate the Jaccard similarity coefficient of two ray paths, then apply it as a weight coefficient for stacking the multi- channel dispersion spectra. The reasonableness and effectiveness of the proposed method is verified in an actual data application. Most importantly, the method increases the degree of automation and the pickup precision of the channel-wave arrival time.
