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Although modern wave‐dominated shorelines exhibit complex geomorphologies, their ancient counterparts are typically described in terms of shoreface‐shelf parasequences with a simple internal architecture. This discrepancy can lead to poor discrimination between, and incorrect identification of, different types of wave‐dominated shoreline in the stratigraphic record. Documented in this paper are the variability in facies characteristics, high‐resolution stratigraphic architecture and interpreted palaeo‐geomorphology within a single parasequence that is interpreted to record the advance of an ancient asymmetrical wave‐dominated delta. The Standardville (Ab1) parasequence of the Aberdeen Member, Blackhawk Formation is exposed in the Book Cliffs of central Utah, USA. This parasequence, and four others in the Aberdeen Member, record the eastward progradation of north/south‐trending, wave‐dominated shorelines. Within the Standardville (Ab1) parasequence, distal wave‐dominated shoreface‐shelf deposits in the eastern part of the study area are overlain across a downlap surface by southward prograding fluvial‐dominated delta‐front deposits, which have previously been assigned to a separate ‘stranded lowstand parasequence’ formed by a significant, allogenic change in relative sea‐level. High‐resolution stratigraphic analysis of these deposits reveals that they are instead more likely to record a single episode of shoreline progradation characterized by alternating periods of normal regressive and forced regressive shoreline trajectory because of minor cyclical fluctuations in relative sea‐level. Interpreted normal regressive shoreline trajectories within the wave‐dominated shoreface‐shelf deposits are marked by aggradational stacking of bedsets bounded by non‐depositional discontinuity surfaces. Interpreted forced regressive shoreline trajectories in the same deposits are characterized by shallow incision of fluvial distributary channels and strongly progradational stacking of bedsets bounded by erosional discontinuity surfaces that record enhanced wave‐base scour. Fluvial‐dominated delta‐front deposits most probably record the regression of a lobate delta parallel to the regional shoreline into an embayment that was sheltered from wave influence. Wave‐dominated shoreface‐shelf and fluvial‐dominated delta‐front deposits occur within the same parasequence, and their interpretation as the respective updrift and downdrift flanks of a single asymmetrical wave‐dominated delta that periodically shifted its position provides the most straightforward explanation of the distribution and relative orientation of these two deposit types.

International audienceThe inference of ancient environmental conditions from their preserved response in the sedimentary record still remains an outstanding issue in stratigraphy. Since the 1970s, conceptual stratigraphic models (e.g. sequence stratigraphy) based on the underlying assumption that accommodation space is the critical control on stratigraphic architecture have been widely used. Although these methods considered more recently other possible parameters such as sediment supply and transport efficiency, they still lack in taking into account the full range of possible parameters, processes, and their complex interactions that control stratigraphic architecture. In this contribution, we present a new quantitative method for the inference of key environmental parameters (specifically sediment supply and relative sea level) that control stratigraphy. The approach combines a fully non-linear inversion scheme with a 'process­response' forward model of stratigraphy. We formulate the inverse problem using a Bayesian framework in order to sample the full range of possible solutions and explicitly build in prior geological knowledge. Our methodology combines Reversible Jump Markov chain Monte Carlo and Simulated Tempering algorithms which are able to deal with variable-dimensional inverse problems and multi-modal posterior probability distributions, respectively. The inverse scheme has been linked to a forward stratigraphic model, BARSIM (developed by Joep Storms, University of Delft), which simulates shallow-marine wave/storm-dominated systems over geological timescales. This link requires the construction of a likelihood function to quantify the agreement between simulated and observed data of different types (e.g. sediment age and thickness, grain size distributions). The technique has been tested and validated with synthetic data, in which all the parameters are specified to produce a 'perfect' simulation, although we add noise to these synthetic data for subsequent testing of the inverse modelling approach. These tests addressed convergence and computational-overhead issues, and highlight the robustness of the inverse scheme, which is able to assess the full range of uncertainties on the inferred environmental parameters and facies distributions

Hydrocarbon recovery in clastic reservoirs depends essentially on how well we understand the precise architecture of sand bodies and intercalated shaly baffl es and barriers. Various methods have been developed for enriching the fundamental data collection from outcrop analogs; these include Terrestrial Laser Scanning (groundbased lidar), digital photogrammetry, highprecision GPS survey, etc. The three-dimensional outcrop data sets collected using these methods are critical for understanding the link between seismic-scale and well-scale data in the subsurface. This study illustrates a methodology for integrating three-dimensional outcrop data, interpreting that data, and integrating the resulting interpretations with data from traditional outcrop measurements. A reservoir model of a fl uvial sequence from the Escanilla Formation in the Ainsa Basin of northern Spain was produced using this methodology. Three-dimensional aerial photographs and laser scanner outcrop capture techniques provide a robust and fl exible data set that can spatially constrain the modeling of observed features. The three-dimensional outcrop reconstruction, coupled with sequence stratigraphy concepts, enables the morphology, size, and distribution of key architectural elements to be modeled in subsurface reservoirs. The reservoir model constructed from these data allows geologists and reservoir engineers to evaluate the critical differences between real and modeled heterogeneities and provides a mechanism for an improved understanding of modeling subsurface reservoirs.

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