Application of production data-driven diagnostics workflow for water shut-off candidate selection in tight carbonate field

Abstract

The newly developed tight carbonates impose many challenges during the early production stage due to the reservoir rock and fluid heterogeneities which has limited the utilization of simulation model as the main way of data integration and performance prediction. Therefore, the surveillance data-driven analytics coupled with petrophysical and stress state properties become of interest to reduce uncertainties involved in selecting reliable improved oil recovery candidates in these reservoirs. This paper presents a workflow based on production data for water shut-off (WSO) candidate selection. The WSO candidates were recognized based on heterogeneity index, decline curve analysis, water oil ratio and the effect of excess water production on the well ultimate recovery. The mechanism and source of produced water was diagnosed based on Chan plot and Stiff diagram through the presented screening.