Conventional multivariate statistical methods for process monitoring may not be suitable for dynamic processes since they usually rely on assumptions such as time invariance or uncorrelation. We are therefore motivate...Conventional multivariate statistical methods for process monitoring may not be suitable for dynamic processes since they usually rely on assumptions such as time invariance or uncorrelation. We are therefore motivated to propose a new monitoring method by compensating the principal component analysis with a weight approach.The proposed monitor consists of two tiers. The first tier uses the principal component analysis method to extract cross-correlation structure among process data, expressed by independent components. The second tier estimates auto-correlation structure among the extracted components as auto-regressive models. It is therefore named a dynamic weighted principal component analysis with hybrid correlation structure. The essential of the proposed method is to incorporate a weight approach into principal component analysis to construct two new subspaces, namely the important component subspace and the residual subspace, and two new statistics are defined to monitor them respectively. Through computing the weight values upon a new observation, the proposed method increases the weights along directions of components that have large estimation errors while reduces the influences of other directions. The rationale behind comes from the observations that the fault information is associated with online estimation errors of auto-regressive models. The proposed monitoring method is exemplified by the Tennessee Eastman process. The monitoring results show that the proposed method outperforms conventional principal component analysis, dynamic principal component analysis and dynamic latent variable.展开更多
In this study, compositional characteristics of crude oil, including the variation of aliphatic, aromatic and pyrrolic nitrogen compounds, were systematically monitored and investigated in a high water-cut oil reservo...In this study, compositional characteristics of crude oil, including the variation of aliphatic, aromatic and pyrrolic nitrogen compounds, were systematically monitored and investigated in a high water-cut oil reservoir over a short time.The results showed that among the widely used parameters indicative of oil maturity and migration, tetramethyl/monomethyl DBT and tricyclic terpane/(tricyclic terpane+C30 hopanoid) varied remarkably, and a positive correlation was observed between these two parameters.The variation of each of these parameters during waterflooding development was correlated with the flow effect of crude promoted by the water drive in oil reservoirs.A solid consistency was observed among the results of numerical simulation and development; the direction and pathway of waterflooding crude was indicated by Tetramethyl/monomethyl DBT, and the distribution region prediction of remaining oil hereby obtained.Therefore, these two parameters could be used as molecular tracers for the oil during waterflooding.This study would be of practical significance for geochemical dynamic monitoring and reservoir development.展开更多
基金Supported by the National Natural Science Foundation of China(61174114)the Research Fund for the Doctoral Program of Higher Education in China(20120101130016)+1 种基金the Natural Science Foundation of Zhejiang Province(LQ15F030006)and the Science and Technology Program Project of Zhejiang Province(2015C33033)
文摘Conventional multivariate statistical methods for process monitoring may not be suitable for dynamic processes since they usually rely on assumptions such as time invariance or uncorrelation. We are therefore motivated to propose a new monitoring method by compensating the principal component analysis with a weight approach.The proposed monitor consists of two tiers. The first tier uses the principal component analysis method to extract cross-correlation structure among process data, expressed by independent components. The second tier estimates auto-correlation structure among the extracted components as auto-regressive models. It is therefore named a dynamic weighted principal component analysis with hybrid correlation structure. The essential of the proposed method is to incorporate a weight approach into principal component analysis to construct two new subspaces, namely the important component subspace and the residual subspace, and two new statistics are defined to monitor them respectively. Through computing the weight values upon a new observation, the proposed method increases the weights along directions of components that have large estimation errors while reduces the influences of other directions. The rationale behind comes from the observations that the fault information is associated with online estimation errors of auto-regressive models. The proposed monitoring method is exemplified by the Tennessee Eastman process. The monitoring results show that the proposed method outperforms conventional principal component analysis, dynamic principal component analysis and dynamic latent variable.
基金supported by Jidong Oilfield Branch Com-pany of CNPC
文摘In this study, compositional characteristics of crude oil, including the variation of aliphatic, aromatic and pyrrolic nitrogen compounds, were systematically monitored and investigated in a high water-cut oil reservoir over a short time.The results showed that among the widely used parameters indicative of oil maturity and migration, tetramethyl/monomethyl DBT and tricyclic terpane/(tricyclic terpane+C30 hopanoid) varied remarkably, and a positive correlation was observed between these two parameters.The variation of each of these parameters during waterflooding development was correlated with the flow effect of crude promoted by the water drive in oil reservoirs.A solid consistency was observed among the results of numerical simulation and development; the direction and pathway of waterflooding crude was indicated by Tetramethyl/monomethyl DBT, and the distribution region prediction of remaining oil hereby obtained.Therefore, these two parameters could be used as molecular tracers for the oil during waterflooding.This study would be of practical significance for geochemical dynamic monitoring and reservoir development.
