Integrated Reservoir Characterisation for Petrophysical Flow Units Evaluation and Performance Prediction
Annan Boah Evans1, *, Aidoo Borsah Abraham1, Brantson Eric Thompson2
1 Oil and Gas Engineering Department, School of Engineering, All Nations University College, Koforidua, Ghana
2 Petroleum Engineering Department, Faculty of Mineral Resources Technology, University of Mines and Technology, Tarkwa, Ghana
An improved understanding of complex clastic reservoirs has led to more detailed reservoir description using integrated approach. In this study, we implemented cluster analysis, geostatistical methods, reservoir quality indicator technique and reservoir simulation to characterize clastic system with complex pore architecture and heterogeneity.
Model based clustering technique from Ward’s analytical algorithm was utilised to transform relationship between core and calculated well logs for paraflow units (PFUs) classification in terms of porosity, permeability and pore throat radius of the reservoir. The architecture of the reservoir at pore scale is described using flow zone indicator (FZI) values and the significant flow units characterized adopting the reservoir quality index (RQI) method. The reservoir porosity, permeability, oil saturation and pressure for delineated flow units were distributed stochastically in 2D numerical models utilising geostatistical conditional simulation. In addition, production behaviour of the field is predicted using history matching. Dynamic models were built for field water cut (FWCT), total field water production (FWPT) and field gas-oil-ratio (FGOR) and history matched, considering a number of simulation runs.
Results obtained showed a satisfactory match between the proposed models and history data, describing the production behaviour of the field. The average FWCT peaked at 78.9% with FWPT of 10 MMSTB. Consequently, high FGOR of 6.8 MSCF/STB was obtained.
The integrated reservoir characterisation approach used in this study has provided the framework for defining productive zones and a better understanding of flow characteristics including spatial distribution of continuous and discrete reservoir properties for performance prediction of sandstone reservoir.
Keywords: Reservoir quality, Paraflow unit, Ward’s analytical algorithm, History matching, Reservoir simulation, Performance prediction.
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* Address correspondence to this author at the Oil and Gas Engineering Department, School of Engineering, All Nations University College, Koforidua, Ghana; Tel: +233242547703; E-mail: email@example.com