We develop a new data-driven model for the assisted history matching of production data from a reservoir under waterflood. Although the model is developed from production data and requires no prior knowledge of rock property fields, it incorporates far more fundamental physics than that of the popular capacitance-resistance model (CRM). The new model also represents a substantial improvement on an interwell numerical simulation model (INSIM) which was presented previously in a paper co-authored by the last two authors of the current paper. The new model, which is referred to as INSIM-FT, eliminates the three deficiencies of the original INSIM data-driven model. (1) For some complex cases, e.g., when a producer is converted to an injector or when injected water from more than one injector passes through an intermediate well node, the INSIM procedure for calculation of water saturation degrades to an ad hoc calculation which introduces inaccuracies. Our new model uses an accurate front-tracking procedure to calculate water saturation, hence the name INSIM-FT. (2) The original INSIM formulation assumes relative permeabilities are known a priori which defeats the objective of finding a model without requiring knowledge of petrophysical properties; INSIM-FT estimates relative permeabilities by historymatching. (3) Unlike CRM, the original INSIM model does not provide a reasonable characterization of how water from an injector is allocated among producers and thus does not reliably identify large-scale geological features such as faults. INSIM-FT remedies this INSIM deficiency.

The reliability of INSIM-FT for history-matching, future reservoir performance prediction and reservoir characterization is validated with two synthetic models, and its performance is compared with that of CRM. Finally, INSIM-FT is applied to a field case.

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