The multi-factor recombination and processes superimposition model for hydrocarbon accumulation is put forward in view of the hydrocarbon geological characteristics of multiple episodes of structural evolution, multip...The multi-factor recombination and processes superimposition model for hydrocarbon accumulation is put forward in view of the hydrocarbon geological characteristics of multiple episodes of structural evolution, multiple sets of source-reservoir-seal assemblage, multiple cycles of hydrocarbon accumulation and multiple episodes of readjustment and reconstruction in the complex superimposed basins in China. It is a system including theories and methods that can help to predict favorable exploration regions. According to this model, the basic discipline for hydrocarbon generation, evolution and distribution in the superimposed basins can be summarized in multi-factor recombination, processes superimposition, multiple stages of oil filling and latest stage preservation. With the Silurian of the Tarim basin as an example, based on the reconstruction of the evolution history of the four factors （paleo-anticline, source rock, regional cap rock and kinematic equilibrium belt） controlling hydrocarbon accumulation, this model was adopted to predict favorable hydrocarbon accumulation areas and favorable exploration regions following structural destruction in three stages of oil filling, to provide guidance for further exploration ofoil and gas in the Silurian of the Tarim basin.展开更多
Deepwater oil and gas projects embody high risks from geology and engineering aspects, which exert substantial influence on project valuation. But the uncer- tainties may be converted to additional value to the projec...Deepwater oil and gas projects embody high risks from geology and engineering aspects, which exert substantial influence on project valuation. But the uncer- tainties may be converted to additional value to the projects in the case of flexible management. Given the flexibility of project management, this paper extends the classical real options model to a multi-factor model which contains oil price, geology, and engineering uncertainties. It then gives an application example of the new model to evaluate deepwater oil and gas projects with a numerical analytical method. Compared with other methods and models, this multi-factor real options model contains more project information. It reflects the potential value deriving not only from oil price variation but also from geology and engi- neering uncertainties, which provides more accurate and reliable valuation information for decision makers.展开更多
Infrared image recognition plays an important role in the inspection of power equipment.Existing technologies dedicated to this purpose often require manually selected features,which are not transferable and interpret...Infrared image recognition plays an important role in the inspection of power equipment.Existing technologies dedicated to this purpose often require manually selected features,which are not transferable and interpretable,and have limited training data.To address these limitations,this paper proposes an automatic infrared image recognition framework,which includes an object recognition module based on a deep self-attention network and a temperature distribution identification module based on a multi-factor similarity calculation.First,the features of an input image are extracted and embedded using a multi-head attention encoding-decoding mechanism.Thereafter,the embedded features are used to predict the equipment component category and location.In the located area,preliminary segmentation is performed.Finally,similar areas are gradually merged,and the temperature distribution of the equipment is obtained to identify a fault.Our experiments indicate that the proposed method demonstrates significantly improved accuracy compared with other related methods and,hence,provides a good reference for the automation of power equipment inspection.展开更多
When I read the paper“Electrolytes enriched by potassium perfluorinated sulfonates for lithium metal batteries”from Prof.Jianmin Ma’s group,which was published in Science Bulletin(doi.org/10.1016/j.scib.2020.09.018...When I read the paper“Electrolytes enriched by potassium perfluorinated sulfonates for lithium metal batteries”from Prof.Jianmin Ma’s group,which was published in Science Bulletin(doi.org/10.1016/j.scib.2020.09.018),I felt excited as presented a multi-factor principle for applying potassium perfluorinated sulfonates to suppress the dendrite growth and protect the cathode from the viewpoint of electrolyte additives.The effects of these additives are revealed through experimental results,molecular dynamics simulations and first-principle calculations.Specifically,it involves the influence of additives on Li^(+)solvation structure,solid electrolyte interphase(SEI),Li growth and nucleation.Following the guidance of the multi-factor principle,every part of the additive molecule should be utilized to regulate electrolytes.This multifactor principle for electrolyte additive molecule design(EAMD)offers a unique insight on understanding the electrochemical behavior of iontype electrolyte additives on both the Li metal anode and high-voltage cathode.In these regards,I would be delighted to write a highlight for this innovative work and,hopefully,it may raise more interest in the areas of electrolyte additives.展开更多
科学评估地下空间开发需求潜力是缓解城市化问题和合理拓展有限区域的重要基础工作。目前地下空间评价中的社会经济数据多来自于传统官方文件,其全面完整性和时空精度并不理想;此外主客观赋权方法的使用,一定程度上存在主观性强和受数...科学评估地下空间开发需求潜力是缓解城市化问题和合理拓展有限区域的重要基础工作。目前地下空间评价中的社会经济数据多来自于传统官方文件,其全面完整性和时空精度并不理想;此外主客观赋权方法的使用,一定程度上存在主观性强和受数据干扰等不足。文章以多源大数据支持的指标体系为基础,构建熵权-随机森林耦合的地下空间需求评价模型。该模型基于熵权法确定负样本,将总样本和指标因子导入随机森林算法中,挖掘社会经济指标与现有地下设施间的复杂非线性关系。研究表明,经过网格搜索调优后的模型AUC(area under curve)精度达到0.979,其中77.45%的现有设施落入评价的高需求区内,证明所采用模型有较强的准确性和可靠性,其精细化评价结果可为今后地下建设选址提供更符合实际的借鉴。展开更多
文摘The multi-factor recombination and processes superimposition model for hydrocarbon accumulation is put forward in view of the hydrocarbon geological characteristics of multiple episodes of structural evolution, multiple sets of source-reservoir-seal assemblage, multiple cycles of hydrocarbon accumulation and multiple episodes of readjustment and reconstruction in the complex superimposed basins in China. It is a system including theories and methods that can help to predict favorable exploration regions. According to this model, the basic discipline for hydrocarbon generation, evolution and distribution in the superimposed basins can be summarized in multi-factor recombination, processes superimposition, multiple stages of oil filling and latest stage preservation. With the Silurian of the Tarim basin as an example, based on the reconstruction of the evolution history of the four factors （paleo-anticline, source rock, regional cap rock and kinematic equilibrium belt） controlling hydrocarbon accumulation, this model was adopted to predict favorable hydrocarbon accumulation areas and favorable exploration regions following structural destruction in three stages of oil filling, to provide guidance for further exploration ofoil and gas in the Silurian of the Tarim basin.
基金supported from the National Science and Technology Major Project under Grant No.2011ZX05030
文摘Deepwater oil and gas projects embody high risks from geology and engineering aspects, which exert substantial influence on project valuation. But the uncer- tainties may be converted to additional value to the projects in the case of flexible management. Given the flexibility of project management, this paper extends the classical real options model to a multi-factor model which contains oil price, geology, and engineering uncertainties. It then gives an application example of the new model to evaluate deepwater oil and gas projects with a numerical analytical method. Compared with other methods and models, this multi-factor real options model contains more project information. It reflects the potential value deriving not only from oil price variation but also from geology and engi- neering uncertainties, which provides more accurate and reliable valuation information for decision makers.
基金This work was supported by National Key R&D Program of China(2019YFE0102900).
文摘Infrared image recognition plays an important role in the inspection of power equipment.Existing technologies dedicated to this purpose often require manually selected features,which are not transferable and interpretable,and have limited training data.To address these limitations,this paper proposes an automatic infrared image recognition framework,which includes an object recognition module based on a deep self-attention network and a temperature distribution identification module based on a multi-factor similarity calculation.First,the features of an input image are extracted and embedded using a multi-head attention encoding-decoding mechanism.Thereafter,the embedded features are used to predict the equipment component category and location.In the located area,preliminary segmentation is performed.Finally,similar areas are gradually merged,and the temperature distribution of the equipment is obtained to identify a fault.Our experiments indicate that the proposed method demonstrates significantly improved accuracy compared with other related methods and,hence,provides a good reference for the automation of power equipment inspection.
基金financial support from the Natural Sciences and Engineering Research Council of Canada(NSERC)Institut National de la Recherche Scientifique(INRS)
文摘When I read the paper“Electrolytes enriched by potassium perfluorinated sulfonates for lithium metal batteries”from Prof.Jianmin Ma’s group,which was published in Science Bulletin(doi.org/10.1016/j.scib.2020.09.018),I felt excited as presented a multi-factor principle for applying potassium perfluorinated sulfonates to suppress the dendrite growth and protect the cathode from the viewpoint of electrolyte additives.The effects of these additives are revealed through experimental results,molecular dynamics simulations and first-principle calculations.Specifically,it involves the influence of additives on Li^(+)solvation structure,solid electrolyte interphase(SEI),Li growth and nucleation.Following the guidance of the multi-factor principle,every part of the additive molecule should be utilized to regulate electrolytes.This multifactor principle for electrolyte additive molecule design(EAMD)offers a unique insight on understanding the electrochemical behavior of iontype electrolyte additives on both the Li metal anode and high-voltage cathode.In these regards,I would be delighted to write a highlight for this innovative work and,hopefully,it may raise more interest in the areas of electrolyte additives.
文摘科学评估地下空间开发需求潜力是缓解城市化问题和合理拓展有限区域的重要基础工作。目前地下空间评价中的社会经济数据多来自于传统官方文件,其全面完整性和时空精度并不理想;此外主客观赋权方法的使用,一定程度上存在主观性强和受数据干扰等不足。文章以多源大数据支持的指标体系为基础,构建熵权-随机森林耦合的地下空间需求评价模型。该模型基于熵权法确定负样本,将总样本和指标因子导入随机森林算法中,挖掘社会经济指标与现有地下设施间的复杂非线性关系。研究表明,经过网格搜索调优后的模型AUC(area under curve)精度达到0.979,其中77.45%的现有设施落入评价的高需求区内,证明所采用模型有较强的准确性和可靠性,其精细化评价结果可为今后地下建设选址提供更符合实际的借鉴。
