Petrophysical characterization of sandstone reservoirs through boreholes E-S3, E-S5 and F-AH4 using multivariate statistical techniques and seismic facies in the Central Bredasdorp Basin

• Main Author: Mosavel, Haajierah
• Other Authors: Opuwari, Mimonitu
• Language: en
• Published: University of the Western Cape 2015
• Subjects: Porosity; Permeability; Multivariate analysis; Factor analysis; Discriminant analysis; Cluster analysis
• Online Access: http://hdl.handle.net/11394/3984

>Magister Scientiae - MSc === The thesis aims to determine the depositional environments, rock types and petrophysical characteristics of the reservoirs in Wells E-S3, E-S5 and F-AH4 of Area X in the Bredasdorp Basin, offshore South Africa. The three wells were studied using methods including core description, petrophysical analysis, seismic facies and multivariate statistics in order to evaluate their reservoir potential. The thesis includes digital wireline log signatures, 2D seismic data, well data and core analysis from selected depths. Based on core description, five lithofacies were identified as claystone (HM1), fine to coarse grained sandstone (HM2), very fine to medium grained sandstone (HM3), fine to medium grained sandstone (HM4) and conglomerate (HM5). Deltaic and shallow marine depositional environments were also interpreted from the core description based on the sedimentary structures and ichnofossils. The results obtained from the petrophysical analysis indicate that the sandstone reservoirs show a relatively fair to good porosity (range 13-20 %), water saturation (range 17-45 %) and a predicted permeability (range 4- 108 mD) for Wells E-S3, E-S5 andF-AH4. The seismic facies model of the study area shows five seismic facies described as parallel, variable amplitude variable continuity, semi-continuous high amplitude, divergent variable amplitude and chaotic seismic facies as well as a probable shallow marine, deltaic and submarine fan depositional system. Linking lithofacies to seismic facies maps helped to understand and predict the distribution and quality of reservoir packages in the studied wells. Multivariate statistical methods of factor, discriminant and cluster analysis were used. For Wells E-S3, E-S5 and F-AH4, two factors were derived from the wireline log data reflecting oil and non- oil bearing depths. Cluster analysis delineated oil and non-oil bearing groups with similar wireline properties. This thesis demonstrates that the approach taken is useful because petrophysical analysis, seismic facies and multivariate statistics has provided useful information on reservoir quality such as net to gross, depths of hydrocarbon saturation and depositional environment.