The pursuit of oil recovery enhancement is an important matter in petroleum industry. Besides explore and exploit new opportunities, the optimization of existing well through New-Zone-behind-Pipe (NZBP) is one of the main tools to optimize brown field production. North Area of Roger Block, in Central Sumatera, consists of several brown fields; still have opportunities for production enhancement through NZBP candidacy optimization. Abundant unperforated zones were still unproduced due to difficulty in evaluating and prioritizing remaining NZBP prospects. Recently, there is no standardized method to prioritized NZBP opportunities. Therefore, this study was conducted to improve understanding of reservoir for NZBP ranking, and also develop selection criteria with objective to increase success rate. Furthermore, enhancing field performance by executing NZBP will be achievable.

To develop screening process, this study is implementing Lean Sigma statistical tools such as CNX, Pareto, and scatter plot to define and improve NZBP selection process. This study also implemented Design of Experiment (DOE, related to statistics) methods to evaluate dependency between reservoir dynamic parameters and NZBP result. The result itself then came up with 4 major parameters which are most influential to NZBP historical oil gain result: water cut, sand thickness, resistivity, and permeability. In addition, a scientific cut off for each of those parameters were introduced for ranking the existing NZBP candidates empirically and statistically. After generating a screening process, the next step is to build reliable forecasting methods for future NZBP job. Therefore, we utilize the equation resulted from previous multi-variable linear regression and 2nd degree polynomial regression to estimate oil gain.

This process is currently in place and results enormous financial revenue up to 9.4 MMUSD within 1 year. It has successfully increased success ratio to 70% and increase average oil gain by 246%. Lesson learned from this study was the development of good screening process to improve the candidacy. There is a big opportunity to adopt and adapt this small yet significant effort to other field worldwide.

Keywords:
knowledge management, machine learning, Completion Installation and Operations, Prioritization, Thickness, Artificial Intelligence, water cut, Upstream Oil & Gas, nzbp program, nzbp job
Subjects:
Improved and Enhanced Recovery, Asset and Portfolio Management, Professionalism, Training, and Education, Information Management and Systems, Perforating, Field development optimization and planning, Communities of practice, Knowledge management, Completion Installation and Operations, Completion Operations
Copyright 2015, Society of Petroleum Engineers
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