The capacitance-resistance model （CRM） is an alternative to conventional reservoir simulation. CRM, a simplification of complex numerical models, uses production and injection rates to infer a reservoir description....The capacitance-resistance model （CRM） is an alternative to conventional reservoir simulation. CRM, a simplification of complex numerical models, uses production and injection rates to infer a reservoir description. There is no prior geologic model. The principal output of CRM fitting is the fraction of injected fluid （usually water） that is produced at a producer at steady-state. These fractions are interwell connectivities. Interwell connectivities are fundamental information needed to manage waterfloods in oil reservoirs. The data-driven CRM is a fast tool to estimate these parameters in mature fields and allows one to make full use of the dynamic data available. This paper considers the problem of setting an upper bound on the uncertainty of interwell connectivities for linear-constrained models. Using analytical bounds and numerical simulations, we derive a consistent upper limit on the uncertainty of interwell connections that can be used to quantify the information content of a given dataset.展开更多
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
基金YPF for 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The capacitance-resistance model （CRM） is an alternative to conventional reservoir simulation. CRM, a simplification of complex numerical models, uses production and injection rates to infer a reservoir description. There is no prior geologic model. The principal output of CRM fitting is the fraction of injected fluid （usually water） that is produced at a producer at steady-state. These fractions are interwell connectivities. Interwell connectivities are fundamental information needed to manage waterfloods in oil reservoirs. The data-driven CRM is a fast tool to estimate these parameters in mature fields and allows one to make full use of the dynamic data available. This paper considers the problem of setting an upper bound on the uncertainty of interwell connectivities for linear-constrained models. Using analytical bounds and numerical simulations, we derive a consistent upper limit on the uncertainty of interwell connections that can be used to quantify the information content of a given dataset.
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.
