Turbidite bed thickness statistics of architectural elements in a deep-marine confined mini-basin setting: Examples from the Grès d'Annot Formation, SE France

G. Pantopoulos*, B. C. Kneller, A. D. McArthur, S. Courivaud, A. E. Grings, J. Kuchle

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)

Abstract

Statistical analysis of bed thickness was performed for sampled turbidite successions from well-documented architectural elements of the Grès d' Annot Formation to characterize confined deep-water mini-basins of the Tertiary foreland basin of SE France. The purpose was to use advanced statistical processing techniques in order to evaluate whether a discrimination of different architectural elements is feasible through observed statistical signatures of bed thickness. Statistical methods were focused on: i) fitting of widely used non-normal theoretical distribution models using robust non-parametric goodness-of-fit statistical tests, and ii) detecting the possible presence of non-random bed thickness clustering using existing and new clustering estimation methods. Results indicate that the bed thickness data are best characterized by a multi-modal lognormal distribution model which probably reflects a background sedimentological process. Several datasets exhibit power law as well as exponential thick-bedded tails. The data also exhibit non-random clustering of bed thickness. Discrimination of architectural elements in this confined turbidite succession seems to be feasible based on the characteristics of the observed composite lognormal distributions such as number and variability of the detected components. The estimation of the degree of facies clustering has potential for the discrimination of architectural elements in confined basin settings if used in conjunction with alternative estimation methods (such as periodogram estimation). This methodology may now be applied to other confined turbidite successions, be they outcrops with less certain architecture, or subsurface datasets with borehole imaging.

Original languageEnglish
Pages (from-to)16-29
Number of pages14
JournalMarine and Petroleum Geology
Volume95
Early online date22 Apr 2018
DOIs
Publication statusPublished - 31 Aug 2018

Bibliographical note

This study was part of the DMS Tools Project, executed at Universidade Federal do Rio Grande do Sul (UFRGS), to which the first author is grateful for a post-doctorate scholarship grant. We also thank Shell and former BG Brasil for financial support and permission to publish results. The Agência Nacional do Petróleo (ANP) also supported this project under the Brazilian Petroleum Law for research commitment clauses. Sven Egenhoff is thanked for editorial handling. Constructive comments and criticisms by Carl Drummond and an anonymous reviewer improved an initial version of this manuscript.

Keywords

  • Bed thickness distribution
  • Deep-water
  • Eocene
  • Facies clustering
  • Grès d'Annot
  • Lognormal
  • Power law

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