The design of a gravity dump flood well for a depleted QG reservoir located offshore in M Field was significantly enhanced by the inclusion of an Electric Submersible Pump (ESP). This resulted in 1,500 barrels of oil per day production gain from producer wells in Area 2 of the reservoir that had become inactive due to low tubing head pressures with reservoir pressure depletion. The identification of an optimal water injector location to improve the low reservoir energy and sweep oil towards the existing producers was grossly challenged due to remote nature of existing wells from water injection facility. Significant cost implications exist for the construction of new pipelines to the Water Injection facility. In addition, the existing infrastructure is aged and degraded, creating a need for a cost-saving solution. The challenges were tackled by implementing a pilot ESP powered dumpflood in an ideally situated injector "Xi". With this technique, a single well acts as both the producer and injector, utilizing an ESP generated pressure differential to pump water from a deep aquifer to a shallow reservoir or boost natural gravity forces to reverse pump water from a shallow aquifer to a deeper reservoir (R. Quttainah 2001). The latter option proved ideal for this application given the shallower location of the water source relative to the target oil zone. By innovatively using Y-tool technology, the ESP reverse pumped 7,000 BWIPD at a discharge pressure of 772 psig from the upper "A" aquifer zone into the target oil QG reservoir within the same well at startup. The ESP motor was powered by a 4km electrical subsea cable to draw power from the field's Quarter Production Platform. Significant cost savings were achieved by eliminating the need for pipeline construction since water source and injection were combined in one well. Within 3-months of ESP startup, the target reservoir pressure boost resulted in the restoration of inactive wells and 1,500 BOPD incremental production gain from producers in Area 2 of the reservoir. Following the success of the ESP powered dumpflood pilot project with initial oil production gain of 1,500 bopd and significant cost savings, a study is ongoing for a field-wide deployment of the technique in field M and 2 neighbouring fields.

Unavailability of core data in most Niger delta wells makes pertinent the need for a reliable permeability distribution. This paper accounts for how permeability was modelled in a reservoir without core data in the Niger Delta by using five empirical approaches namely, Timur, Coates, Tixier, Udegbunam and also a correlation generated from core data of a nearby field. The five permeability results from the five approaches were used in building five different 3 D geological models. Flow simulation was carried out for all the models to analyse their flow peformance. The permeability distribution from the correlation generated from the nearby field core data yielded a higher oil recovery. Introduction The permeability of a rock is one of the most important parameters neccessary for effective reservoir characterization and management. Therefore accurate knowledge of its distribution in the reservoir is critical to accurate production performance prediction. During primary depletion, areal variation of permeability influences oil recovery. Permeability measurements from cores are direct measurement of these properties. But a reservoir without core data is often associated with uncertainties as these properties have to be log derived. Permeability of a formation is affected by factors such as porosity and pore space characteristics, types, amount and distribution of clay minerals, rock matrix composition and size of matrix grains. Several authors have proposed models for permeability determination in an uncored reservoir using well logs. These models are based on correlation between permeability, porosity and irreducible water saturation. Irreducible water saturation being a function of the rock characteristics. The workflow consists of petrophysical evaluation, permeability estimation, 3D geocellular modeling, upscaling of fine grid models for flow simulation and dynamic modeling.

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