Reservoir connectivity analysis plays an important role in understanding and successful development of compartmentalized and stacked reservoirs. The field compartments are initially defined based on the geological boundaries such as faults, shale layers, and other geological barriers. Well penetrations, fluid contact measurements, and initial pressure distribution surveys will complete the static connectivity of the compartments prior to production data. Reservoir behavior in the production time scale may change the initial understanding of the compartments system. Dynamic connectivity can bring surprises which affect the development plan and may require more investment to manage them. For a brown field development with such a complex structure, it is vital to have a systematic analytical approach in place to integrate the available data which had highlighted the missing gaps for the future development plan and helped to locate the remaining oil in place. This paper demonstrates the above concept in Baram field; a highly compartmentalized and stacked reservoir located offshore Miri in Sarawak, Malaysia. Based on the available production data and by using reservoir engineering techniques like material balance, reservoir uncertainty analysis and history matching; dynamic reservoir connectivity was defined. Fault seal analysis was evaluated to understand the behavior of the faults during the depletion phase of the field. The estimation of fault’s transmissibility compliments the material balance outcome and was refined in dynamic modeling/ history matching. Geomechanics study of the field proved useful to evaluate the impact of stress change during the future pressure maintenance study as a part of the brown field development plan.

In today's fast paced and challenging oil industry, the need of faster evaluation studies for quick generation of field development plan (FDP) is becoming more crucial to remain competitive. Field's geological and structural complexity, uncertainty of production data adds to the challenges. Traditional approach of building dynamic mesh models carrying out numerical simulation to history match, then predict has always remained time consuming in large mature fields. The ‘B’ field in Peninsular Malaysia is a mature clastic with stacked reservoirs having a huge gas cap with moderate aquifer. Significant production over last 30+ years led to uneven movement of the gas cap and also of the edge aquifer leading to possibility of bypassed oil. The updated dynamic model could not match the preferential gas cap movement, thus failed to match the high GOR of downdip wells and also unable to match high watercut of certain updip wells. To identify the areas of bypassed oil thus is a significant challenge with the current dynamic model. New engineering tools of polygon balancing, material balance, normalized EUR bubbles were used with the 3D static model volume and the facies understanding. The uncertainties and risks were also identified and clear measurable methods were proposed to address the uncertainties and reduce the risks. Very detailed decision tree with clear data gathering plan to drill successive optimum wells have been planned during the campaign. This paper details the new engineering tools used to delineate and quantify the bypassed oil in these huge clastic reservoir with preferential gas and water movement, unable to be history matched by the dynamic model. It explains the engineering methods applied to identify and quantify the 10 infill wells proposed for the development campaign. To reduce risks, this paper would also explain the blind testing that was carried out on for this new reservoir engineering analysis tool by deriving the infill potentials of the previous campaign (4 years back) by the same method. The paper details how robust technical development plans were generated having infill well locations and reserve determination. This paper will also demonstrate the classic "Do-Learn-Adapt" strategy through its infill wells prioritization & ranking, subsurface de-risking analysis, data acquisition and mitigations plans.

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