GLOCAL: A global-local optimization template for multiple history-matched reservoir parameters

This work presents a global-local optimization template (GLOCAL) that produces multiple estimates of the parameter field by history-matching production data. More fundamentally, the technique produces realizations of the parameter field at different scales of resolution. Two sample history-matching problems are presented to illustrate the effectiveness of the method. Results from these examples show that the method can produce several estimates that show some pattern of heterogeneity found in the true field. However, the resemblance to the true field varies across different scales of resolution of the parameter field in the global template.