Supercritical-flow Deposits and Their Distribution in a Submarine Channel System, Middle Eocene, Ainsa Basin, Spanish Pyrenees

Abstract

Studies of supercritical-flow deposits (SFDs) and their spatial distribution in ancient deep-water systems should provide an additional tool to improve the understanding of the flow dynamics during deposition and the architecture of sandbodies. Outcrop recognition of SFDs in ancient deep-marine environments remains poorly documented, although their study dates back to the 1970s. This paper focusses on the criteria for recognizing SFDs and their distribution in three selected depositional environments from an ancient mid-lower slope to a proximal-basin floor setting in the middle Eocene Ainsa Basin, Spanish Pyrenees. From field observations, six facies associations interpreted as related to supercritical flow are defined. These facies associations are grouped in two categories. The first group includes facies associations related to erosional coarse-grained supercritical-flow bedforms related to meter and centimeter-scale scours and backfilling structures interpreted as large-scale cyclic steps or small-scale cyclic steps, respectively. Erosional coarse-grained supercritical bedforms are observed mainly in relatively high-gradient slopes and relatively confined settings. The second group of facies associations are related to depositional fine-grained supercritical-flow bedforms associated with upflow-dipping sandstone lenses, upflow-stacked wavy bedforms, upflow-stacked sigmoidal bedforms, and plane beds, interpreted as unstable and stable antidunes and upper-flow-regime plane beds. Depositional fine-grained supercritical-flow bedforms are observed mainly in relatively unconfined settings such as lower-slope, break-of-slope and proximal basin-floor environments. Two main SFD trends were observed in the Ainsa Basin in: (i) an axial-lateral direction, showing a decrease in SFDs from channel axis to channel margin, and (ii) a longitudinal proximal–distal direction, showing an increase in SFDs from the Gerbe System (mid-slope environment), to the Banastón System (proximal basin-floor environment), to the Ainsa System (lower-slope environment). From this study, two parameters are recognized as likely playing an important role on whether a flow is under supercritical or subcritical conditions: (i) confinement of the sandbodies, and (ii) slope gradient.

Magnetostratigraphy and stable isotope stratigraphy of the middle-Eocene succession of the Ainsa basin (Spain): new age constraints and implications for sediment delivery to the deep waters

“…11). In this work, Banaston I was placed in the turbidite stack previously identified as Gerbe II by Our interpretation is in accordance with the map of Cornard and Pickering (2019) and set the correlation between both section in the lateral equivalents of Banaston I (Fig. 11).…”

“…Stratigraphic thicknesses of the sections were measured with a Jacob staff, and geometric calculations based on field dip and strike data when direct measurements were not possible. The identification of the different SGF systems is based on the geological maps of Pickering and Bayliss (2009) and Cornard and Pickering (2019).…”

Syndepositional tectonics and mass-transport deposits control channelized, bathymetrically complex deep-water systems (Aínsa depocenter, Spain)

“…The Arro system formed in an elongate corridor with high axial gradients bound by structures or canyon walls, similar to that of the younger Aínsa systems (Cornard and Pickering, 2019). The deposits therein can therefore be compared with those deposited in modern high-gradient confined systems such as large canyons (e.g., the Monterrey Canyon; Paull et al, 2018) or fjord-head delta slopes (e.g., the Bute Inlet, British Columbia; Hughes Clark, 2016).…”

“…However, nomenclatural inconsistency is common in the description of the deep-water Aínsa depocenter fill (cf. Mutti, 1985;Fernández et al, 2004;Pickering and Corregidor, 2005;Arbués et al, 2007a;Das Gupta and Pickering, 2008;Heard and Pickering, 2008;Pickering and Bayliss, 2009;Muñoz et al, 2013;Heard et al, 2014;Pickering and Cantalejo, 2015;Scotchman et al, 2015;Cornard and Pickering, 2019).…”

Towards adopting open and data‐driven science practices in bed form dynamics research, and some steps to this end

“…It is expected that stewarded bed form data would potentially encompass heterogenous, multi‐source, multi‐temporal, multi‐scale, high‐dimensional, highly complex, and unstructured geospatial datasets, which are typical characteristics of many geophysical signals datasets (Nativi et al ., 2015; Sharma et al ., 2015). For instance, due to their specific research interests, stratigraphists (Cornard and Pickering, 2019; West et al ., 2019) actively collect and analyse bed form data that may be at different resolution than that used by hydraulic engineers, and compile palaeocurrent trends (Brand et al ., 2015). They have also devised schemes to classify cross‐strata (Jopling and Walker, 1968; Cheel, 1990) and determine palaeoflows (DeCelles et al ., 1983; Dasgupta, 2002), whose products would represent one data entity.…”