Since the mechanisms of methane-mudstone interactions are important for estimating shale gas reserves,methane adsorption under supercritical conditions of 30 MPa pressure and 303.15,333.15,363.15 K temperatures was st...Since the mechanisms of methane-mudstone interactions are important for estimating shale gas reserves,methane adsorption under supercritical conditions of 30 MPa pressure and 303.15,333.15,363.15 K temperatures was studied to measure the excess methane adsorption in two mudstone samples from Yanchang Formation,Ordos Basin.Excess adsorption features inflection points where the amount of adsorbed gas changes from increasing to decreasing concentrations.Three methods(fixed,slope,and freely fitted density)were applied to calculate the adsorbed-phase density(rad),which was then used to fit the measured excess adsorption.Two criteria,the goodness-of-fit and whether the fitting can obtain reasonable absolute adsorption,were applied to determine the most accurate model.Results indicated that the supercritical Dubinin-Radushkevich(SDR)model with freely fitted rad was the most reasonable model.The volume of adsorbed methane at 363.15 K is close to the micropore(d<2 nm)volume of the corresponding mudstone.Considering the actual geological conditions,the adsorbed gas should be predominantly stored in micropores.Thermodynamic parameters reveal that the methane adsorption on mudstone is a physisorption process that is jointly controlled by the heterogeneity of,and interaction forces between the methane molecule and,the rock surface.展开更多
For the complex batch process with characteristics of unequal batch data length,a novel data-driven batch process monitoring method is proposed based on mixed data features analysis and multi-way kernel entropy compon...For the complex batch process with characteristics of unequal batch data length,a novel data-driven batch process monitoring method is proposed based on mixed data features analysis and multi-way kernel entropy component analysis(MDFA-MKECA)in this paper.Combining the mechanistic knowledge,different mixed data features of each batch including statistical and thermodynamics entropy features,are extracted to finish data pre-processing.After that,MKECA is applied to reduce data dimensionality and finally establish a monitoring model.The proposed method is applied to a reheating furnace industry process,and the experimental results demonstrate that the MDFA-MKECA method can reduce the calculated amount and effectively provide on-line monitoring of the batch process.展开更多
基金This work was supported by the Natural Science Basic Research Program of Shaanxi[No.2022JQ-2912021JQ-234]+1 种基金the China Postdoctoral Science Foundation[No.2021M692735]the Fundamental Research Funds for the Central Universities,Chang'an University[No.300102271305].
文摘Since the mechanisms of methane-mudstone interactions are important for estimating shale gas reserves,methane adsorption under supercritical conditions of 30 MPa pressure and 303.15,333.15,363.15 K temperatures was studied to measure the excess methane adsorption in two mudstone samples from Yanchang Formation,Ordos Basin.Excess adsorption features inflection points where the amount of adsorbed gas changes from increasing to decreasing concentrations.Three methods(fixed,slope,and freely fitted density)were applied to calculate the adsorbed-phase density(rad),which was then used to fit the measured excess adsorption.Two criteria,the goodness-of-fit and whether the fitting can obtain reasonable absolute adsorption,were applied to determine the most accurate model.Results indicated that the supercritical Dubinin-Radushkevich(SDR)model with freely fitted rad was the most reasonable model.The volume of adsorbed methane at 363.15 K is close to the micropore(d<2 nm)volume of the corresponding mudstone.Considering the actual geological conditions,the adsorbed gas should be predominantly stored in micropores.Thermodynamic parameters reveal that the methane adsorption on mudstone is a physisorption process that is jointly controlled by the heterogeneity of,and interaction forces between the methane molecule and,the rock surface.
基金supported by National Key R&D Program of China(Smart process control technology for aluminum&copper strip based on industrial big data)(2017YFB0306405)。
文摘For the complex batch process with characteristics of unequal batch data length,a novel data-driven batch process monitoring method is proposed based on mixed data features analysis and multi-way kernel entropy component analysis(MDFA-MKECA)in this paper.Combining the mechanistic knowledge,different mixed data features of each batch including statistical and thermodynamics entropy features,are extracted to finish data pre-processing.After that,MKECA is applied to reduce data dimensionality and finally establish a monitoring model.The proposed method is applied to a reheating furnace industry process,and the experimental results demonstrate that the MDFA-MKECA method can reduce the calculated amount and effectively provide on-line monitoring of the batch process.
