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Characterizing Deep-Marine Sedimentary Architecture: A Database-Driven Meta-Analysis Approach

Abstract

The wide range of facies and architectural models currently invoked in deep-marine clastic studies are underpinned by the assumption that recognizable patterns of self-organization necessarily arise from the way system boundary conditions influence basic flow processes. A test of this assumption is best carried out through a meta-analysis of deep-marine depositional systems. Here we describe such an approach. A relational database – the Deep-Marine Architectural Knowledge Store (DMAKS) – has been developed as a repository of deep-marine siliciclastic sedimentary architectural data. The database stores data on the nature, geometry, internal facies character, and spatial and hierarchical relationships of deep-marine depositional units of classified depositional systems. The codification of architectural data in a standardized manner in DMAKS enables different deep-marine systems to be rigorously compared, and thus facilitates meta-analysis. Establishment of the DMAKS' standardized data-entry method allows the database to function both as a research tool, and as a means to facilitate the application of geologic analogs. Hierarchical relationships between units can now be assessed to reveal patterns in deep-marine architectural arrangement, e.g., by analyzing whether the organization of bounding surfaces seen within channelized environments is a result of specific basin controls, and whether such organization is replicated within other type of environments. As well as revealing common patterns within deep-marine environments, the reliability of interpretations of individual systems can also be tested; for example, the likelihood of an end-member architectural model or the diagnostic value of a facies sequence can be assessed by comparison with a much wider data pool. In addition, models of deep-marine reservoirs can be tested or constrained on the basis of quantitative database output, as the DMAKS' data can be filtered based upon specific basin controls (e.g., tectonic type, basin size or grain size) or architectural style (e.g. channel sinuosity or geometry). A final application of the approach lies in the prediction of the likely sedimentary architecture of a system type. For example, relationships between lobe sizes and the character of spatially associated channels can be used to inform and develop architectural models where only partial data are available.