This paper presents a case history of defining the field development plan for a complex; heavily faulted layered; undersaturated oil reservoir, with significant degrees of structural and production uncertainties. In such case, good reservoir management practices and reservoir monitoring are the main keys to understanding the reservoir behavior.The reservoir has numerous challenges, which complicate reservoir management; like complex geology, pressure support for different layers, water injection optimization, scale depositions, and commingled production which introduces uncertainties regarding the production and injection contribution. This leads to difficulties to identify bypassed oil in the reservoir. Therefore frequent production logging, monitoring the producing water salinity, and key data from wells and RFT/MDT of the new infill wells were used for managing such uncertainties'. This served as primary keys to identify different vertical and lateral flow barriers, and was used as a basis for water injection optimization in such challenging conditions. The reservoirs were studied by means of analytical methods and integration approach of wells' and reservoir surveillance data for understanding the structural configuration, investigate various production problems, optimize water injection strategy, and identify bypassed oil and poorly swept areas. The methods defined an extensive portfolio of infill drilling and other cost saving rigless activities to restore production potential of the field. This approach added about 22 MMSTB of oil reserves which represent 8 % increase in the ultimate oil recovery, and flattened the oil production for more than 5 years.New infill wells were confidently identified to achieve all of the following objectives a) access bypassed reserves b) access attic oil reserves c) adding another drainage point to the existing producers. The presented reservoir management practices has proven its ability to timely support the operational decisions, pinpoint infill wells, and prolong the life of a mature asset. It is not moving away from detailed dynamic model, but these practices are required in similar uncertainties conditions to develop right sense of understanding of reservoir behavior, and provide invaluable input data which adds credibility to the dynamic model. 2 IPTC 17538

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Water flooding is an established method to increase oil production. In this research, we present a novel approach that uses data mining techniques on the operations data on a complex mature oil field located in the Gulf of Suez, currently being water flooded. We show how such methods help improve reservoir characterization for this specific field is particularly challenging because of its geological complexity and field performance. The continuous recording of production and injection data presents a new opportunity to apply analytical approaches to reservoir management. Such approaches provide an alternative to the traditional history-match model update and prediction that is not only time-consuming but also carry forwards all subsurface uncertainties. A combination of qualitative (cross-correlation analysis) and quantitative analysis (capacitance resistance model) is used to obtain an overall waterflood injection strategy for this Gulf of Suez field. In this manuscript, we focus on the analysis obtained from cross-correlation analysis. The presented analysis helps identify connectivity between wells in the reservoir during waterflood. The method presented is also adapted to specific characteristics of this field - water drive production in this model. We present evidence of how salinity data can be used to further justify the linkages between the different wells obtained from the cross-correlation analysis. We also show comparison between results from this analytical technique and the streamline approach. This comparison with salinity and streamlines helps benchmark the model results especially in cases where such secondary data (salinity/streamlines) are not available. The results presented in this research can be adapted to any waterflooded field to optimize recovery at frequent intervals, where injection and production data is continuously available.

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