Quantification of the bed‐scale architecture of submarine depositional environments

Abstract

AbstractSubmarine channel and fan deposits form the largest sediment accumulations on Earth and host significant reservoirs for hydrocarbons. While many studies of ancient fan deposits describe architectural variability along 2D transects (e.g. axis‐to‐fringe, proximal‐to‐distal), these relationships are often qualitative and are rarely quantified at the event‐bed scale. In order to enable quantitative comparison of the fine‐scale architecture of submarine depositional environments, 56 bed‐scale outcrop correlation panels from five broadly categorized environments (channel, levee, lobe, channel‐lobe transition zone, CLTZ and basin plain) were digitized. Measured architectural parameters (bed thickness, bed thinning rates, lateral correlation distance, net‐to‐gross) provide a large (n = 28,525) and statistically robust framework to compare event‐bed architectures within and between environments. “Thinning rate” data (i.e. the lateral rate of change of bed thickness) clearly differentiate deposits from different submarine depositional environments, helping to quantify generally accepted models for proximal‐to‐distal evolution of stratigraphic architecture. The thinning rates of sandstone beds and mudstone‐dominated intervals vary predictably between environments. For example, the highest sandstone thinning rates occur in channel deposits (0.2–6 cm/m; P10 and P90 values here and below) and decrease to lobe (0.1–1.6 cm/m), CLTZ (0.2–0.9 cm/m), levee (0.0024–0.078 cm/m) and basin‐plain deposits (0.000017–0.0054 cm/m). These quantitative relationships provide valuable insights for downslope flow evolution and the construction of stratigraphic architecture in submarine settings. Due to intra‐environment variability, net‐to‐gross is highly variable and thus (when considered alone) is not a diagnostic indicator of depositional environment. Submarine lobe deposits show the most variability in event bed thickness, thinning rate and net‐to‐gross, likely due to the inherent facies variability and differing boundary conditions. To explore this variability, lobe deposits were sub‐classified based on position (proximal, distal) and effective confinement (unconfined, semiconfined, confined) to provide a more detailed sub‐environment analysis. Unconfined lobe deposits show a proximal‐to‐distal increase in sandstone thickness and decrease in mudstone thickness, supporting conceptual models. Confined lobe deposits have thicker sandstone and mudstone beds and lower net‐to‐gross values as compared to unconfined and semiconfined lobes, supporting a sediment trapping mechanism by confinement. These quantified bed‐scale parameter comparisons enable the recognition of architectural similarities and differences within and between environments, demonstrating the need for more quantitative studies of bed‐scale heterogeneity. The results from this study are immediately applicable to parameterizing forward stratigraphic models, constraining property distribution in reservoir models, and probabilistic determination of depositional environment from outcrop and core descriptions of submarine depositional environments.