Metadata Approaches and Their Effects on Deep-Marine System Analysis, Analogue Selection and Reservoir Characterisation

Abstract

A metadata approach is described that enhances the ability to characterise and model siliciclastic deep-marine hydrocarbon reservoirs. This is achieved through a relational database approach - the Deep-Marine Architectural Knowledge Store (DMAKS) – which entails a consistent method of data entry, ensuring data from ancient, modern and sub-surface investigations are stored to a common standard. The DMAKS stores information relating to the depositional systems’ setting and environmental controls, the architectural geometry and facies characteristics, along with hierarchical and spatial relationships. This deep-marine data repository thus enables quantitative meta-data analysis. The expansive range of data and parameters contained within the database improves the quality of predictive models, while the ability to produce statistical outputs enables deep-marine analogues to be more objectively selected. An initial investigation into a single case-study – the Golo system – helps to demonstrate the DMAKS research capabilities. Here, an original lobe-type architectural model is tested against a larger data-pool. The DMAKS quantitatively verifies the existence of distinct parent lobe-types (small, single-story versus larger, composite lobes associated with leveed-channels) through the analysis of geometrical, hierarchical and spatial relationships. It also provides new insights, as the hierarchical status of a lobe is seen to influence its resultant geometry.