--> Heterogeneity in Unconfined Deep-Water Fans: Insights From a Quantitative Evaluation of Outcrop, Subsurface, and Computational Stratigraphy

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Heterogeneity in Unconfined Deep-Water Fans: Insights From a Quantitative Evaluation of Outcrop, Subsurface, and Computational Stratigraphy

Abstract

Deep-water fans are amongst the largest sediment accumulations on Earth and can host significant hydrocarbon reservoirs. These systems are regularly characterized as homogeneous and laterally extensive, characteristics derived from qualitative analyses of sparse outcrop and subsurface data. Yet, recent process-based studies have demonstrated that heterogeneity is spatially complex across multiple orders of depositional hierarchy (beds, elements, complexes), implying a need to better link stratigraphic heterogeneity with the processes that formed it. Here, we investigate key outcrop and subsurface data in the context of physics-based (process) numerical models that simulate the stratigraphic evolution of turbidite systems. Through the modeling of sediment transport, erosion, and deposition, we create 3D digital analogs that allow us to test hypotheses related to stratigraphic heterogeneity; our digital analogs also allow us to develop a framework to better predict the expected range of spatial heterogeneity in deep-water fans. Through an integrated approach (3D digital analogs, subsurface, and outcrop), we conclude that stratigraphic heterogeneity in deep-water fans is inherently non-stationary. We reach our conclusions by evaluating quantitatively the relationship between depositional hierarchy and variations in the degree, style, and length-scales of heterogeneity (e.g., NtG, amalgamation, facies trends). We find that our analysis also leads to better recognition of the channelized, transitional, and sheet-like zones, and a more robust linkage between stratigraphic architecture and patterns in 1D and spatial heterogeneity in 3D. We show that the characterization and prediction of heterogeneities, used for drainage area or production forecasting is dependent on the concept of hierarchical heterogeneity: the 3D extent of heterogeneities observed in 1D are dependent on their associated hierarchy. Critically, these heterogeneities such as internal facies trends, shale drapes, and stacking patterns compound across hierarchy and may result in a non-linear decrease in reservoir property consistency, uniform drainage area, and connectivity. We conclude that deep-water fans should be considered, characterized, and modeled as complex, not internally homogenous or with stationary properties, but with predicable heterogeneities that vary across multiple levels of depositional hierarchy and that can impact development-strategy optimization and performance forecasting.