--> Predictive Models for Basin Scale Alluvial Architecture: Paleocene-Eocene Bighorn Basin, Wyoming

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Predictive Models for Basin Scale Alluvial Architecture: Paleocene-Eocene Bighorn Basin, Wyoming

Abstract

As sedimentary deposits host important petroleum reserves, being able to predict key characteristics such as facies distribution and sandbody architecture variations will greatly increase the changes of successful identification, prediction and exploitation of oil and gas. This study aims to analyse facies and sandstone body distribution across a near entire depositional basin to assess applicability of conceptual fluvial models in understanding how predictable key properties such as sandstone percentage, channel body percentage and sandstone geometry (five of which are defined and described in detail) are. This field based study was conducted over 28 locations in the Bighorn Basin, Wyoming, where extensive exposure has allowed over 4000 m of combined vertical succession to be analysed over 8,700 km2. To date the basin has only been analysed from a lithostratigraphic approach, which this study aims to refine by detailing different depositional systems (distributive fluvial system, alluvial fan and axial system) to help better constrain the paleogeography and predictability of reservoir characteristics. Analyses of statistical data of the channel facies demonstrates how highly variable the architecture and nature of the basin fill deposits are. Basin margin to basin centre trends are not as evident as may have been expected. Broad generalised trends are present when analysing channel percentage, grain size, average channel thickness and storey thickness, with highest values residing near the basin margin and lowest in the basin centre. However, many anomalies are present resulting in complicated trends. However, by applying conceptual models derived from the study of modern continental sedimentary basins, four key sediment source areas were identified along with an important axial system component. Predictable downstream trends were then able to be identified, allowing better prediction of facies distribution and deposit architecture to be made. This study highlights the importance of having conceptual models to understand sedimentary basins and their fluvial deposits, and provides one of a limited quantified basin scale datasets of key reservoir characteristics.