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.
Highlights
List of Symbols R2 the correlation coefficient determination Фe, % Effective porosity mD Milli Darcy Permeability Фc Porosity cut-off Kc Permeability cut-offThe request for oil products has placed massive pressure on the search for hydrocarbons with the development of technologies to reduce the risks of hydrocarbon exploration
The seismic data recorded in Structural reservoir modeling is the first step in static reservoir modeling that includes seismic interpretation of the geological horizons, faults, and goecellular network are vital in static reservoir modeling (Rahimi and Riahi 2020)
This study has integrated and evaluated seismic, well log, and core data to generate information that would assist in the delineation of petrophysical properties and hydrocarbon prospect locations within the Gamtoos Basin, offshore South Africa
Summary
List of Symbols R2 the correlation coefficient determination Фe, % Effective porosity mD Milli Darcy Permeability Фc Porosity cut-off Kc Permeability cut-offThe request for oil products has placed massive pressure on the search for hydrocarbons with the development of technologies to reduce the risks of hydrocarbon exploration. It is essential to build up a reservoir model as accurately as possible to calculate the reserves and determine the most up-to-date way of recovering as much petroleum as possible in an economical way. Geophysical, petrophysical, geostatistics, and reservoir engineering is essential for reservoir characterization (Zee Ma and La Pointe 2011). A static reservoir model applies geological theory to understand the architecture of varieties. Journal of Petroleum Exploration and Production Technology (2021) 11:4185–4200 of fluid flow and obstacles within the reservoir. It demonstrates the reservoir network based on information from different sources such as seismic, core, and well logs data (Viste 2008; Cannon 2018). The proper integration of seismic data with a well log will enhance the lateral description of reservoirs
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