A novel approach named aligned mixture probabilistic principal component analysis(AMPPCA) is proposed in this study for fault detection of multimode chemical processes. In order to exploit within-mode correlations,the...A novel approach named aligned mixture probabilistic principal component analysis(AMPPCA) is proposed in this study for fault detection of multimode chemical processes. In order to exploit within-mode correlations,the AMPPCA algorithm first estimates a statistical description for each operating mode by applying mixture probabilistic principal component analysis(MPPCA). As a comparison, the combined MPPCA is employed where monitoring results are softly integrated according to posterior probabilities of the test sample in each local model. For exploiting the cross-mode correlations, which may be useful but are inadvertently neglected due to separately held monitoring approaches, a global monitoring model is constructed by aligning all local models together. In this way, both within-mode and cross-mode correlations are preserved in this integrated space. Finally, the utility and feasibility of AMPPCA are demonstrated through a non-isothermal continuous stirred tank reactor and the TE benchmark process.展开更多
Seismic Rock physics plays a bridge role between the rock moduli and physical properties of the hydrocarbon reservoirs.Prestack seismic inversion is an important method for the quantitative characterization of elastic...Seismic Rock physics plays a bridge role between the rock moduli and physical properties of the hydrocarbon reservoirs.Prestack seismic inversion is an important method for the quantitative characterization of elasticity,physical properties,lithology and fluid properties of subsurface reservoirs.In this paper,a high order approximation of rock physics model for clastic rocks is established and one seismic AVO reflection equation characterized by the high order approximation(Jacobian and Hessian matrix)of rock moduli is derived.Besides,the contribution of porosity,shale content and fluid saturation to AVO reflectivity is analyzed.The feasibility of the proposed AVO equation is discussed in the direct estimation of rock physical properties.On the basis of this,one probabilistic AVO inversion based on differential evolution-Markov chain Monte Carlo stochastic model is proposed on the premise that the model parameters obey Gaussian mixture probability prior model.The stochastic model has both the global optimization characteristics of the differential evolution algorithm and the uncertainty analysis ability of Markov chain Monte Carlo model.Through the cross parallel of multiple Markov chains,multiple stochastic solutions of the model parameters can be obtained simultaneously,and the posterior probability density distribution of the model parameters can be simulated effectively.The posterior mean is treated as the optimal solution of the model to be inverted.Besides,the variance and confidence interval are utilized to evaluate the uncertainties of the estimated results,so as to realize the simultaneous estimation of reservoir elasticity,physical properties,discrete lithofacies and dry rock skeleton.The validity of the proposed approach is verified by theoretical tests and one real application case in eastern China.展开更多
基金Supported by the National Natural Science Foundation of China(61374140)Shanghai Pujiang Program(12PJ1402200)
文摘A novel approach named aligned mixture probabilistic principal component analysis(AMPPCA) is proposed in this study for fault detection of multimode chemical processes. In order to exploit within-mode correlations,the AMPPCA algorithm first estimates a statistical description for each operating mode by applying mixture probabilistic principal component analysis(MPPCA). As a comparison, the combined MPPCA is employed where monitoring results are softly integrated according to posterior probabilities of the test sample in each local model. For exploiting the cross-mode correlations, which may be useful but are inadvertently neglected due to separately held monitoring approaches, a global monitoring model is constructed by aligning all local models together. In this way, both within-mode and cross-mode correlations are preserved in this integrated space. Finally, the utility and feasibility of AMPPCA are demonstrated through a non-isothermal continuous stirred tank reactor and the TE benchmark process.
基金supported by the National Grand Project for Science and Technology(Grant Nos.2016ZX05024-004,2017ZX05009-001,2017ZX05036-005)the Science Foundation from SINOPEC Key Laboratory of Geophysics(Grant No.WTYJY-WX2019-0104)。
文摘Seismic Rock physics plays a bridge role between the rock moduli and physical properties of the hydrocarbon reservoirs.Prestack seismic inversion is an important method for the quantitative characterization of elasticity,physical properties,lithology and fluid properties of subsurface reservoirs.In this paper,a high order approximation of rock physics model for clastic rocks is established and one seismic AVO reflection equation characterized by the high order approximation(Jacobian and Hessian matrix)of rock moduli is derived.Besides,the contribution of porosity,shale content and fluid saturation to AVO reflectivity is analyzed.The feasibility of the proposed AVO equation is discussed in the direct estimation of rock physical properties.On the basis of this,one probabilistic AVO inversion based on differential evolution-Markov chain Monte Carlo stochastic model is proposed on the premise that the model parameters obey Gaussian mixture probability prior model.The stochastic model has both the global optimization characteristics of the differential evolution algorithm and the uncertainty analysis ability of Markov chain Monte Carlo model.Through the cross parallel of multiple Markov chains,multiple stochastic solutions of the model parameters can be obtained simultaneously,and the posterior probability density distribution of the model parameters can be simulated effectively.The posterior mean is treated as the optimal solution of the model to be inverted.Besides,the variance and confidence interval are utilized to evaluate the uncertainties of the estimated results,so as to realize the simultaneous estimation of reservoir elasticity,physical properties,discrete lithofacies and dry rock skeleton.The validity of the proposed approach is verified by theoretical tests and one real application case in eastern China.
