Abstract
The McKee Field was discovered onshore New Zealand in 1979 and brought to commercial production during 1984. Beginning with the early stages of development planning, each stage of the field's life has been actively guided by reservoir simulation. An early pre-development model was built in 1983, and full field simulation has been carried out, and routinely updated since 1986.
A review of the effectiveness of reservoir simulation as an ongoing planning and management tool for the McKee Field has been conducted. It is shown that reservoir simulation, even at the earliest stages, can act as an accurate model for determining optimum recovery processes and development strategies. Models must be continuously updated and refined to reflect the current best knowledge of the reservoir in order to remain effective at locating infill or re-completion candidate wells and at addressing the changing reservoir management objectives of the day. The ability of the model to accurately predict future field performance, is shown to be directly related to how well the simulation model represents reservoir geology, and structure, and the consequent relative ease with which a history match has been obtained.
The simulation technology applied has evolved, in order to accurately represent the improving state of reservoir knowledge with time, from conventional cartesian gridding with vertical faults used in 1983 and 1986, through corner-point geometry applied in 1988, simple polygonal gridding first applied to full-field modeling in 1991, to the complex polygonal full field model with explicit over-thrust and multiple back-thrust fault matching in use today.
The current simulation model is both a dynamic fluid-flow model and a detailed 3-D geological model of the reservoir. It includes a comprehensive representation of stratigraphy, permeability anisotropy, and all mapped faults with as-mapped dips and strikes. This model is currently used to plan infill drilling, water-flood, for appraising tertiary gas flood and WAG, and for managing aspects of production optimization.
