Refined lithological classification through structured multivariate analysis
|Location||International Geological Congress,oslo 2008|
|Author||Brandsegg, Kristian Bjarnّe; Hammer, Erik; Sinding-Larsen, Richard|
|Holding Date||27 September 2008|
Estimation of reservoir heterogeneity from well logs is an important yet difficult task encountered in geophysical formation evaluation and reservoir engineering. This paper presents a methodology for mapping petro-variability through a structured multivariate analysis of a well from the Upper Triassic to Lower Jurassic fluviodeltaic Åre fm., offshore mid-Norway. Traditionally, principal component analysis (PCA) is run by analyzing the entire wireline log and using PCA scores to characterize variability within and between lithologies. In this paper we propose a technique to quantify reservoir heterogeneity due to second order rock property contrasts, in addition to more standard approaches for lithological segmentation. In this study, lithology characterization has been addressed through the use of three separate PCAs. PC loadings and scores are calculated from: (1) a total analysis of all lithologies and all log variables (2) a subset analysis including only sandstone intervals, (3) subsets of specific sandstone dominated sequences and finally (4) a refined reservoir heterogeneity analysis portraying the effects of secondary sources of petro-variability is quantified through the use of the Eckart-Young theorem. This reconstruction of the wireline log variables into petro-normalized logs can then be used to enhance the within-lithology heterogeneities and refine the more standard characterization of reservoir heterogeneity. This paper demonstrates first, that the structured PCA analyzing specific lithofacies sequences is superior to the unstructured PCA when within-lithofacies variations are in focus. Secondly is it shown that the petro-normalization using the Eckart-Young theorem can decompose the initial wireline responses into specific litho-variation signatures indicating different rock property contrasts that can be used to enhance our ability to characterize reservoir heterogeneity. The structured PCA method and the inverse method using the Eckart-Young theorem on sandstone sequences allows for a fine-tuning of the interpretation of the initial wireline log data sets and can easily be tuned to other deposition patterns. The method should be particularly valuable in studies involving heterolithic deposits. The use of PCA permits the removal of variability due to gross lithological effects in the wireline responses and allows for a more distinct evaluation of the variability due to secondary or higher lithological heterogeneity. The method allows for a precise positioning of the core versus the wireline log. The application of this procedure provided additional insight into the complex fluviodeltaic characteristics of a heterolithic sequence that poses great challenges to development.