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AN UPDATED NUMERICAL MODEL OF THE OHAAKI GEOTHERMAL FIELD

M.J. O’Sullivan, T. Renaud, M.J. Gravatt, J. Riffault, J. Popineau, J.P. O’Sullivan, N.C. Ruiz and M. Sophy

Key words
Reservoir modelling, Geothermal, Ohaaki, Broadlands, Leapfrog, conceptual modelling
Conference
New Zealand Geothermal Workshop
Year
2021
Session
Session 3.3 - Reservoir Modelling 2
Paper number
43

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Abstract

The first well was drilled at the Ohaaki geothermal field in 1965 and not long afterwards the University of Auckland began a long collaboration with Contact Energy and its predecessors in modelling the Ohaaki reservoir. The succession of models has been used to inform decision making and aid consent applications. The permeability distribution in the model has evolved over the years to match data, particularly pressure and temperature trends. As the conceptual understanding of the field changes new versions of the model must reflect these changes.
In recent years, we have been developing a modelling framework that can better capture the fault structures, the geology and the geophysics in a numerical reservoir model. This framework is based on mapping a geological model from Leapfrog Geothermal® into an AUTOUGH2 (or Waiwera) computer model. This paper shows how we imposed this framework on to a model of the Ohaaki geothermal field. We have employed techniques to maintain the state of calibration that has been developed over several years in the current numerical model but also allows new rock types to be added easily as our conceptual understanding of the field evolves. In this paper we discuss our techniques for maintaining the match to data while changing the underlying rock distribution. We also demonstrate how we can change the fault structure, geology, alteration model or model grid without too much effort. A new grid structure is used to allow the model to be run in either AUTOUGH2 or Waiwera, in the latter case benefitting from the improved computational speed.
The aim of this work is to increase the transparency of numerical modelling without compromising the complexity that is needed to match the behaviour of the reservoir. Having a numerical model that is closely linked to the languages used by geologists, geophysicists and reservoir engineers allows a complex model to be explained more easily.

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