Interwell connectivities are fundamental parameters required to manage waterfloods in oil reservoirs. Data-driven models, such as the capacitance-resistance model （CRM）, are fast tools to estimate these parameters f...Interwell connectivities are fundamental parameters required to manage waterfloods in oil reservoirs. Data-driven models, such as the capacitance-resistance model （CRM）, are fast tools to estimate these parameters from time-correlations of input （injection rates） and output （production rates） signals. Noise and structure of the input time-series impose limits on the information that can be extracted from a given data-set. This work uses the CRM to study general prescriptions for the design of input signals that enhance the information content of injection/production data in the estimation of well-to-well interactions. Numerical schemes and general features of the optimal input signal strategy are derived for this problem.展开更多
We apply a proper orthogonal decomposition(POD)to data stemming from numerical simulations of a fingering instability in a multiphase flow passing through obstacles in a porous medium,to study water injection processe...We apply a proper orthogonal decomposition(POD)to data stemming from numerical simulations of a fingering instability in a multiphase flow passing through obstacles in a porous medium,to study water injection processes in the production of hydrocarbon reservoirs.We show that the time evolution of a properly defined flow correlation length can be used to identify the onset of the fingering instability.Computation of characteristic lengths for each of the modes resulting from the POD provides further information on the dynamics of the system.Finally,using numerical simulations with different viscosity ratios,we show that the convergence of the POD depends non-trivially on whether the fingering instability develops or not.This result has implications on proposed methods to decrease the dimensionality of the problem by deriving reduced dynamical systems after truncating the system’s governing equations to a few POD modes.展开更多
基金financial support and to the Center for Petroleum Asset Risk Management of the University of Texas at Austin for hospitality and an exciting research environment
文摘Interwell connectivities are fundamental parameters required to manage waterfloods in oil reservoirs. Data-driven models, such as the capacitance-resistance model （CRM）, are fast tools to estimate these parameters from time-correlations of input （injection rates） and output （production rates） signals. Noise and structure of the input time-series impose limits on the information that can be extracted from a given data-set. This work uses the CRM to study general prescriptions for the design of input signals that enhance the information content of injection/production data in the estimation of well-to-well interactions. Numerical schemes and general features of the optimal input signal strategy are derived for this problem.
基金support from YPF-Tecnología(YTEC)support from PICT Grant No.2015-3530.
文摘We apply a proper orthogonal decomposition(POD)to data stemming from numerical simulations of a fingering instability in a multiphase flow passing through obstacles in a porous medium,to study water injection processes in the production of hydrocarbon reservoirs.We show that the time evolution of a properly defined flow correlation length can be used to identify the onset of the fingering instability.Computation of characteristic lengths for each of the modes resulting from the POD provides further information on the dynamics of the system.Finally,using numerical simulations with different viscosity ratios,we show that the convergence of the POD depends non-trivially on whether the fingering instability develops or not.This result has implications on proposed methods to decrease the dimensionality of the problem by deriving reduced dynamical systems after truncating the system’s governing equations to a few POD modes.
