Contributions to sequence stratigraphy from analogue and numerical experiments

Abstract

The sequence stratigraphic model, although no longer focused on eustasy and accommodation, has been until recently based largely on observation and interpretation of outcrop and subsurface data. This approach may be restrictive if the current model places limits on what is observed and how observations are interpreted. To make progress in our understanding of strata, the sequence stratigraphic model and method should be tested against and fully incorporate theoretical and experimental results that provide new knowledge of (1) autogenesis, (2) intrinsic stratigraphic responses, (3) alluvial grade, and (4) scales appropriate to single depositional systems evolving with relative sea-level changes. More extensive inclusion of analogue and numerical experimental results could lead to significant modification and refinement of existing sequence stratigraphic models.The emergence of the seismic and sequence stratigraphy method and model in the 1970s is often described as a revolution in the science of stratigraphy, and has been compared to the origination and establishment of plate tectonics theory (e.g. Miall 1995;Catuneanu 2006). Certainly, sequence stratigraphy, especially through the use of seismic data, has had a huge impact on the study and interpretation of strata in the late 20th century. It showed that sedimentary strata imaged by seismic data were commonly organized into discrete, repetitive unconformity bounded onlapping-to-downlapping depositional sequences. The early model used long-standing ideas that gave priority to eustasy as the best-known repetitive driving mechanism to create sequences. However, a simple eustasy-based interpretation of the repetitive stratal packages attracted criticism (e.g. Christie-Blick et al. 1988Miall & Miall 2001, and references therein) and the more recent sequence stratigraphic models (e.g. Wilgus et al.

Can sediment supply variations create sequences? Insights from stratigraphic forward modelling

“…However, future work could improve both precision and accuracy of these estimates and improve understanding of how they vary at shorter time scales (<1 My). Future work should also focus on understanding the probability of occurrence of accommodation‐dominated and supply‐dominated sequences (e.g. Heller et al, ; Burgess & Steel, ), particularly under different tectonic, climatic and eustatic conditions, and taking into account possible interactions between autogenic processes and allogenic controls (Hajek & Straub, ; Muto, Steel, & Burgess, ). Perhaps many existing interpretations of accommodation‐dominated sequences need to be revisited, assessed and possibly revised.…”

The grade index model as a rationale for autogenic nonequilibrium responses of deltaic clinoform to relative sea‐level rise

“…The simulations also verify another important notion, that the spatial changes to the topset part of the depositional system (delta/alluvial plain), expressed as increase in A t* , affect how the clinoform evolves as relative sea‐level rises. This case is fundamentally different from that of a stationary sea level (Muto, Steel, et al, ; Wang et al, ) in that when the relative sea‐level rises, the variations in A t* plays a critical role in determining stratigraphic responses. The combination of G index with A t* functions to regulate the effects of basin water depth upon the evolution of deltaic clinoforms as relative sea level rises.…”

Reply to Comment of O. Catuneanu and M. Zecchin on Non‐unique stratal geometries: implications for sequence stratigraphic interpretations, by: P. M. Burgess and G. D. Prince, Basin Research (2015) 27, 351–365

“…Neal et al, 2016), but this is perhaps more difficult than some suggest. We would therefore argue that the optimum approach is to combine outcrop, numerical and analogue modelling into an experimental approach to improve our understanding of how stratigraphic systems work (Muto et al, 2016). For example, using modern and Pleistocene deposystems and analogue and numerical experiments to provide more detailed understanding of how and why fluvial aggradation occurs would be useful, and would help ensure that when it is difficult to separate model and method, the models are more robust.…”