Introduction: 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. Methods: 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: 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. Conclusion: 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.

Pipelines are commonly used in the petroleum industry to extract and transport crude oil and natural gas from the petroleum reservoir to storage facilities. The flow kinematics of crude oil through pipelines is unsteady and is associated with a constant change in the viscosity of fluid. The effect of unsteady viscous flow is predominant at wall boundaries, where there exist relative motion between crude oil and pipe wall, acting in reverse direction. This fluidwall interaction induces viscous drag at the wall boundary due to friction. When friction occurs, stress and heat will be exerted at the contact interface. Solid particles sourced from the unconsolidated nature of sandstone lithology are transported alongside with crude oil. These particles impinges on the pipe wall and erodes the corrosion resistant layer, thereby exposing the pipe surface to the corrosive fluid. This study is aimed at evaluating the impact of unsteady viscous flow and presence of solid particles on pipeline surfaces during crude oil transport. Identified areas with high viscous stress is important and this was achieved using CFD. The two equation k-ω turbulent model and particle tracing were used as the flow physics, to achieve the aim of this paper. It was established that the properties of crude oil had an influence on the estimation of wall viscosity and erosion rate. The numeric value of the selected fluid properties such as dynamic viscosity, specific gravity, and velocity was in the range 0.08-0.20 Pas, 0.66-0.93 and 20-60 m/s respectively. Regions with maximum contact with the moving fluid had the maximum viscous drag and frictional velocity predictions. This region was identified as the potential hotspot and located at the pipe elbow.

Introduction: Building a large number of static models to analyze reservoir performance is vital in reservoir development planning. For the purpose of maximizing oil recovery, reservoir behavior must be modelled properly to predict its performance. This requires the study of the variation of the reservoir petrophysical properties as a function of spatial location. Methods: In recent times, the method used to analyze reservoir behavior is the use of reservoir simulation. Hence, this study seeks to analyze the spatial distribution pattern of reservoir petrophysical properties such as porosity, permeability, thickness, saturation and ascertain its effect on cumulative oil production. Geostatistical techniques were used to distribute the petrophysical properties in building a 2D static model of the reservoir and construction of dynamic model to analyze reservoir performance. Vertical to horizontal permeability anisotropy ratio affects horizontal wells drilled in the 2D static reservoir. The performance of the horizontal wells appeared to be increasing steadily as kv/kh increases. At kv/kh value of 0.55, a higher cumulative oil production was observed compared to a kv/kh ratio of 0.4, 0.2, and 0.1. In addition, horizontal well length significantly affects cumulative oil production of the petroleum reservoir studied. Results: At kv/kh of 0.55, the results of the analysis showed a rapid decrement in cumulative oil production as the horizontal well length decreases. Considering horizontal well length of 3000 ft, 2000 ft, and 1500 ft, a minimum cumulative oil production was obtained from a horizontal well length of 1500 ft. Conclusion: The geostatistical and reservoir simulation methods employed in this study will serve as an insight in analyzing horizontal well performance.

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