The development of mature waterflooded reservoirs to maintain long term and steady production while maximizing ultimate recovery has enormous challenges. The primary challenge to optimally develop waterflooded reservoirs is to enhance production per well while preventing the water-cut from rising too fast after adjusting the reservoir scheme and well operation parameters. Fulfilling this challenge requires the capability of integrating data associated to formation, wellbore and surface/facility sub-systems in order to comprehensively evaluate reservoir potential and optimize production while processing and analyzing large amounts of data.

This paper presents a methodology to address this challenge with a streamlined workflow by: (1) Characterizing reservoir properties and baseline existing well and surface/facility designs; (2) Correlating reservoir characteristics with production and injection history; (3) Identifying underperforming wells; (4) Assessing production enhancement possibilities; (5) Redesigning optimum operation parameters for candidates; (6) Then, proposing adjustment measures for injectors based upon injectivity analysis; and (7) Adjusting surface/facility designs with the enhancements.

A case study is presented to illustrate the effectiveness and benefits of this methodology. This study is based on gathering, validating and integrating sub-system data into a database-based application to systematically construct an integrated reservoir and production model. A combination of graphical, statistical, theoretical and simulation analysis tools were employed to identify: abnormalities, enhancement candidates and infill drilling opportunities. Analyzing the integrated subsystems ensured both: the reasonableness of the optimization design and the feasibility of adjustment recommendations. To validate the approach, a field pilot application was implemented on a waterflooded oilfield in western China, which resulted in a 15 percent increase in production of 3200 barrels per day. The study fully demonstrates that the methodology is suitable and practical to optimize production from such complex reservoirs.

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