Spatial variation in paleocurrent velocities estimated from a turbidite bed of the Mio-Pliocene Kiyosumi Formation in Boso Peninsula, Japan.

雄介, 久保; 富士雄, 増田; 秀一, 徳橋; 哲弥, 酒井

doi:10.5575/geosoc.104.359

Cited by 7 publications

(20 citation statements)

References 14 publications

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“…The rare occurrence of AB divisions < 20 cm thick and the much greater thickness of AB divisions compared with CD divisions with the same grain‐size range suggest a relatively abrupt thinning of the entire bed near the downflow termination of the AB division. Such a geometry has been observed by Kubo et al . (1998) and Tokuhashi (1979) in the Boso Peninsula, Japan, and in the experiments of Hallworth & Huppert (1998).…”

Section: Discussionmentioning

confidence: 99%

On the frequency distribution of turbidite thickness

Talling¹

2001

Sedimentology

110

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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 workers is explained as the result of a change in the power‐law exponent. This analysis supports the view that A and B divisions were deposited from high‐concentration flow components and that distinct grain‐size modes undergo different depositional processes. Summation of log‐normal frequency distributions for thin‐ and thick‐bedded turbidites produces a cumulative frequency distribution of thickness with a segmented power‐law trend. Thus, the occurrence of both log‐normal and segmented power‐law frequency distributions can be explained in a holistic fashion. Power‐law frequency distributions of turbidite thickness have previously been linked to power‐law distributions of earthquake magnitude or volumes of submarine slope failure. The log‐normal distribution for a given grain‐size class observed in this study suggests an alternative view, that turbidite thickness is determined by the multiplicative addition of several randomly distributed parameters, in addition to the settling velocity of the grain‐sizes present.

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Section: Discussionmentioning

confidence: 99%

On the frequency distribution of turbidite thickness

Talling¹

2001

Sedimentology

110

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“…The shape of ancient turbidite beds has been documented in only two other sequences in sufficient detail to allow comparison with this study. The first location is on the Boso Peninsula in Japan (Hirayama & Nakajima, 1977;Tokuhashi, 1979Tokuhashi, , 1989Kubo, 1998). Turbidite shape is documented using transects orientated across a radial palaeoflow pattern.…”

Section: Comparison With Turbidite Bed Geometry In Other Locationsmentioning

confidence: 99%

“…, 1998). Few field data sets have constrained bed geometry in sufficient detail to allow meaningful comparison with numerical or experimental results (Dade & Huppert, 1994; Zeng & Lowe, 1997; Kubo, 1998; Bursik & Woods, 2000). This is an unsatisfactory situation.…”

Section: Introductionmentioning

confidence: 99%

“…The validity of numerical models for simulating large-scale submarine flows has often been assessed through comparisons with laboratory flows (Bonnecaze et al, 1993(Bonnecaze et al, , 1996Gladstone et al, 1998;Woods et al, 1998). Few field data sets have constrained bed geometry in sufficient detail to allow meaningful comparison with numerical or experimental results (Dade & Huppert, 1994;Zeng & Lowe, 1997;Kubo, 1998;Bursik & Woods, 2000). This is an unsatisfactory situation.…”

Section: Introductionmentioning

confidence: 99%

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New insight into the evolution of large‐volume turbidity currents: comparison of turbidite shape and previous modelling results

Talling¹,

Amy²,

Wynn

2007

Sedimentology

178

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The Marnoso Arenacea Formation provides the most extensive correlation of individual flow deposits (beds) yet documented in an ancient turbidite system. These correlations provide unusually detailed constraints on bed shape, which is used to deduce flow evolution and assess the validity of numerical and laboratory models. Bed volumes have an approximately log‐normal frequency distribution; a small number of flows dominated sediment supply to this non‐channelized basin plain. Turbidite sandstone within small‐volume (<0·7 km3) beds thins downflow in an approximately exponential fashion. This shape is a property of spatially depletive flows, and has been reproduced by previous mathematical models and laboratory experiments. Sandstone intervals in larger‐volume (0·7–7 km3) beds have a broad thickness maximum in their proximal part. Grain‐size trends within this broad thickness maximum indicate spatially near‐uniform flow for distances of ∼30 km, although the flow was temporally unsteady. Previous mathematical models and laboratory experiments have not reproduced this type of deposit shape. This may be because models fail to simulate the way in which near bed sediment concentration tends towards a constant value (saturates) in powerful flows. Alternatively, the discrepancy may be the result of relatively high ratios of flow thickness and sediment settling velocity in submarine flows, together with very gradual changes in sea‐floor gradient. Intra‐bed erosion, temporally varying discharge, and reworking of suspension fallout as bedload could also help to explain the discrepancy in deposit shape. Most large‐volume beds contain an internal erosion surface underlain by inversely graded sandstone, recording waxing and waning flow. It has been inferred previously that these characteristics are diagnostic of turbidites generated by hyperpycnal flood discharge. These turbidites are too voluminous to have been formed by hyperpycnal flows, unless such flows are capable of eroding cubic kilometres of sea‐floor sediment. It is more likely that these flows originated from submarine slope failure. Two beds comprise multiple sandstone intervals separated only by turbidite mudstone. These features suggest that the submarine slope failures occurred as either a waxing and waning event, or in a number of stages.

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“…In recent years, there have been several attempts to reconstruct the hydraulic conditions of ancient turbidity currents from geologic records [Stow and Bowen, 1980;van Tassell, 1981;Bowen et al, 1984;Komar, 1985;Hiscott, 1994;Allen, 1991;Kubo et al, 1995Kubo et al, , 1998Baas et al, 2000;Falcini et al, 2009;Lesshafft et al, 2011]. Initially, the critical velocities of particle motion inferred from turbidites were used for estimating the paleo-flow conditions of turbidity currents [Komar, 1985;Kubo et al, 1995Kubo et al, , 1998]. However, these methods based on critical velocity estimate only the minimum values of flow velocity, because deposition can occur even at velocities much higher than the critical velocity of particle motion when the capacity of sediment transport in a turbidity current is exceeded by the volume flux of sediment [Hiscott, 1994].…”

Section: Introductionmentioning

confidence: 99%

Inverse analysis to reconstruct hydraulic conditions of non-steady turbidity currents based on multiple grain-size classes

Nakao¹,

Naruse²

2017

Preprint

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This study proposes a new method of inverse analysis of ancient turbidites to represent non-steady turbidity currents and account for multiple grain-size classes. The forward model employed in this study is based on the shallow water equation, and the initial conditions of flows are assumed as a lock-exchange type. To obtain a solution to the inverse problem, a genetic algorithm is employed to determine the optimal initial conditions. The present method successfully estimated the true initial conditions of the turbidity currents from the artificial data sets of deposits created by the forward model. The method is also applied to a turbidite bed of the Kiyosumi Formation. The results of the inverse analysis yield solutions that fits well with the observed data of the individual turbidite, and provide estimates of the flow velocity, flow thickness and sediment concentration of the turbidity current. The flow thickness and velocity when the turbidity current reached the downstream end of the study area were reconstructed to be 334.6 m, 0.98 m/s, respectively.

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Spatial variation in paleocurrent velocities estimated from a turbidite bed of the Mio-Pliocene Kiyosumi Formation in Boso Peninsula, Japan.

Cited by 7 publications

References 14 publications

On the frequency distribution of turbidite thickness

On the frequency distribution of turbidite thickness

New insight into the evolution of large‐volume turbidity currents: comparison of turbidite shape and previous modelling results

Inverse analysis to reconstruct hydraulic conditions of non-steady turbidity currents based on multiple grain-size classes

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