Tease out More - Advanced Porosity Analysis in Fractured Reservoirs Combining Statistical Method with Outcrop Data

Summary Statistical analysis are presented for the description of a porosity-permeability system in order to transfer tectonic facies classification to log data and to improve flow unit determination. Two working hypothesis are investigated: a) Porosities at each measured section point represent an accumulation of distinct porosity classes and b) Significant periods can be identified in oscillating porosities. The four major workflow steps of the statistical analysis are described. Decomposition, non-linear regression, and periodograms delivered encouraging results to understand the porosity composition of the multi-fractured dolomite. Five porosity components of high statistical significance are identified and related to tectonic influence factors. Furthermore, results of sinusoidal regression show significant trends, which might be related to deformation history and complexes. Decomposition of oscillating functions resulted in classes of significant periods, where sinusoidal oscillations with specific period lengths are represented. Finally, statistical analysis reveal different porosity distributions depending on the logging tool generation, which can have a considerable impact on the reserve estimation. Statistical analysis of log data -if applicable - are a fast and cost-effective approach to support reservoir characterisation. The study show that the use of statistical analysis of log data can provide significant information to develop or validate static and dynamic reservoir models