Static reservoir modeling using stochastic method: a case study of the cretaceous sequence of Gamtoos Basin, Offshore, South Africa

Abstract

Gamtoos Basin is an echelon sub-basin under the Outeniqua offshore Basin of South Africa. It is a complex rift-type basin with both onshore and offshore components and consists of relatively simple half-grabens bounded by a major fault to the northeast. This study is mainly focused on the evaluation of the reservoir heterogeneity of the Valanginian depositional sequence. The prime objective of this work is to generate a 3D static reservoir model for a better understanding of the spatial distribution of discrete and continuous reservoir properties (porosity, permeability, and water saturation). The methodology adopted in this work includes the integration of 2D seismic and well-log data. These data were used to construct 3D models of lithofacies, porosity, permeability, and water saturation through petrophysical analysis, upscaling, Sequential Indicator Simulation, and Sequential Gaussian Simulation algorithms, respectively. Results indicated that static reservoir modeling adequately captured reservoir geometry and spatial properties distribution. In this study, the static geocellular model delineates lithology into three facies: sandstone, silt, and shale. Petrophysical models were integrated with facies within the reservoir to identify the best location that has the potential to produce hydrocarbon. The statistical analysis model revealed sandstone is the best facies and that the porosity, permeability, and water saturation ranges between 8 and 22%, 0.1 mD (< 1.0 mD) to 1.0 mD, and 30–55%. Geocellular model results showed that the northwestern part of the Gamtoos Basin has the best petrophysical properties, followed by the central part of the Basin. Findings from this study have provided the information needed for further gas exploration, appraisal, and development programs in the Gamtoos Basin.

A Reservoir Modeling Study for the Evaluation of CO2 Storage Upscaling at the Decatur Site in the Eastern Illinois Basin

“…We upscaled the well logs to the layers in order to assign values to each cell that was penetrated by the wells used in the model. Facies logs were upscaled using the "most of" algorithm, as this honors the most representative value in the penetrated cells [18,19]. Porosity and permeability logs were upscaled using arithmetic and geometric methods, respectively [18,20,21].…”

“…Facies logs were upscaled using the "most of" algorithm, as this honors the most representative value in the penetrated cells [18,19]. Porosity and permeability logs were upscaled using arithmetic and geometric methods, respectively [18,20,21].…”

The Impact of Detrital Minerals on Reservoir Flow Zones in the Northeastern Bredasdorp Basin, South Africa, Using Core Data

“…Reservoir rock delineation in a heterogeneous formation is complicated and requires an accurate integration of petrophysical and petrography evaluation because each rock has its petrophysical, petrographical, mechanical and depositional characteristics [1][2][3][4][5][6][7]. Detailed reservoir characterization is possible by using petrophysical core data with a petrography study by dividing the reservoir into different zones based on similar hydraulic rock units or petrophysical rock types.…”