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Current knowledge of submarine fan deposits has historically relied heavily on qualitative field and subsurface observations and interpretations, but recent studies using statistical analyses have enhanced the understanding of submarine fan sub‐environments, including the degree of confinement, stratigraphic patterns and potential control factors. The purpose of this study is to improve the quantitative understanding of synorogenic submarine fan deposition at foreland basin settings with a statistical approach. A suite of statistical methods is integrated and developed (Hurst Statistics/rescaled range analysis, bed thickness frequency distribution analysis, Markov Chains and time‐series analysis), and applied to the well‐understood Pennsylvanian lower Atoka submarine fan system in the Ouachita Mountains, United States, for this purpose. The results of the Hurst Statistics and bed thickness analyses corroborate qualitative interpretations that: (i) the lower Atoka is lobe‐dominated; and (ii) the south‐eastern (wedge top) portion of the system is more strongly confined than the northern (foredeep) portion. The Markov Chains and time‐series analyses reveal the prevalence (56% of the measured sections) of stratigraphic orderliness and cyclicity; these results are used to discuss potential control signals, which are otherwise difficult to distinguish, on the turbidite sandstone recurrence cycles. The results of this study demonstrate that these integrated statistical methods can be utilized to quantify depositional interpretations and extract hidden information using outcrops with limited exposures. [ABSTRACT FROM AUTHOR]

The partitioning of different grain‐size classes in gravity flow deposits is one of the key characteristics used to infer depositional processes. Turbidites have relatively clean sandstones with most of their clay deposited as part of a mudstone cap or as a distal mudstone layer, whereas sand‐bearing debrites commonly comprise mixtures of sand grains and interstitial clay; hybrid event beds develop alternations of clean and dirty (clay‐rich) sandstones in varying proportions. Analysis of co‐genetic mudstone caps in terms of thickness and composition is a novel approach that can provide new insight into gravity flow depositional processes. Bed thickness data from the ponded Castagnola system show that turbidites contain more clay overall than do hybrid event beds. The Castagnola system is characterized by deposits of two very different petrographic types. Thanks to this duality, analyses of sandstone and mudstone composition allow inference of which proportion of the clay in each of the deposit types was acquired en route. In combination with standard sedimentological observations the new data allow insight into the likely characteristics of their parent flows. Clean turbidites were deposited by lower concentration, long duration, erosive, muddy turbidity currents which were more efficient at fractionating clay particles away from their basal layer. Hybrid event beds were deposited by shorter duration, higher‐concentration, less‐erosive sandier flows which were less efficient at clay fractionation. The results are consistent with data from other turbidite systems (for example, Marnoso‐arenacea). The approach represents a new method to infer the controls on the degree of clay partitioning in gravity flow deposits. [ABSTRACT FROM AUTHOR]

Turbidite bed thickness distributions are often interpreted in terms of power laws, even when there are significant departures from a single straight line on a log–log exceedence probability plot. Alternatively, these distributions have been described by a lognormal mixture model. Statistical methods used to analyse and distinguish the two models (power law and lognormal mixture) are presented here. In addition, the shortcomings of some frequently applied techniques are discussed, using a new data set from the Tarcău Sandstone of the East Carpathians, Romania, and published data from the Marnoso-Arenacea Formation of Italy. Log–log exceedence plots and least squares fitting by themselves are inappropriate tools for the analysis of bed thickness distributions; they must be accompanied by the assessment of other types of diagrams (cumulative probability, histogram of log-transformed values, q–q plots) and the use of a measure of goodness-of-fit other than R2, such as the chi-square or the Kolmogorov–Smirnov statistics. When interpreting data that do not follow a single straight line on a log–log exceedence plot, it is important to take into account that ‘segmented’ power laws are not simple mixtures of power law populations with arbitrary parameters. Although a simple model of flow confinement does result in segmented plots at the centre of a basin, the segmented shape of the exceedence curve breaks down as the sampling location moves away from the basin centre. The lognormal mixture model is a sedimentologically intuitive alternative to the power law distribution. The expectation–maximization algorithm can be used to estimate the parameters and thus to model lognormal bed thickness mixtures. Taking into account these observations, the bed thickness data from the Tarcău Sandstone are best described by a lognormal mixture model with two components. Compared with the Marnoso-Arenacea Formation, in which bed thicknesses of thin beds have a larger variability than thicknesses of the thicker beds, the thinner-bedded population of the Tarcău Sandstone has a lower variability than the thicker-bedded population. Such differences might reflect contrasting depositional settings, such as the difference between channel levées and basin plains. [ABSTRACT FROM AUTHOR]

A series of laboratory experiments on cohesive sediments under inorganic conditions was undertaken in order to evaluate the impact of fluid bed shear stress on the build-up of bed resistance to erosion with time. The importance of small pressures due to flowing water to increase bed strength is presented. It is also shown that the susceptibility of a cohesive bed to changes in its erodibility is related to deposited bed thickness due to sediment disturbance caused by dewatering from the consolidating bed. Laboratory experiments that use beds deposited from suspension should thus report the thickness of the bed prior to resuspension. [ABSTRACT FROM AUTHOR]

The frequency distribution of turbidite thickness records information on flow hydrodynamics, initial sediment volumes and source migration and is an important component of petroleum reservoir models. However, the nature of this thickness distribution is currently uncertain, with log-normal or negative-exponential frequency distributions and power-law cumulative frequency distributions having been proposed by different authors. A detailed analysis of the Miocene Marnoso Arenacea Formation of the Italian Apennines shows that turbidite bed thickness and sand-interval thickness within each bed have a frequency distribution comprising the sum of a series of log-normal frequency distributions. These strata were deposited predominantly in a basin-plain setting, and bed amalgamation is relatively rare. Beds or sand intervals truncated by erosion were excluded from this analysis. Each log-normal frequency distribution characterizes bed or sand-interval thickness for a given basal grain-size or basal Bouma division. Measurements from the Silurian Aberystwyth Grits in Wales, the Cretaceous Great Valley Sequence in California and the Permian Karoo Basin in South Africa show that this conclusion holds for sequences of disparate age and variable location. The median thickness of these log-normal distributions is positively correlated with basal grain-size. The power-law exponent relating the basal grain-size and median thickness is different for turbidites with a basal A or B division and those with only C, D and E divisions. These two types of turbidite have been termed ‘thin bedded’ and ‘thick bedded’ by previous workers. A change in the power-law exponent is proposed to be related to: (i) a transition from viscous to inertial settling of sediment grains; and (ii) hindered settling at high sediment concentrations. The bimodal thickness distribution of ‘thin-bedded’ and ‘thick-bedded’ turbidites noted by previous... [ABSTRACT FROM AUTHOR]

Recent studies of turbidite bed thickness distributions have demonstrated power-law as well as log-normal statistical distributions. The different distributions may reflect different fan processes and environments and, therefore, could be used as a quantitative method to help identify those environments, including those devoid of sequential patterns. The cumulative distributions of well-known turbidite deposits spanning a range of interpreted fan subenvironments are used to illustrate the potential correlation between cumulative distribution and environments. Assuming that power-law distributions may, for some systems, be the primary input signal, one-dimensional modelling allows semi-quantitative characterization of the effects of different fan processes such as erosion and bed amalgamation. Environments indicative of different fan processes may be characterized based on the degree to which processes have acted as a ‘filter’ to modify the assumed power-law distribution systematically. This model of the effect of fan processes on the power-law distribution is used to help to account for bed thickness distributions observed in several field sites. [ABSTRACT FROM AUTHOR]