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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.
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.