1887
Volume 16, Issue 4
  • ISSN: 1354-0793
  • E-ISSN:

Abstract

ABSTRACT

Turbidite sequences within confined basins constitute important hydrocarbon reservoirs world-wide and, for this reason, the discrimination of sedimentary sub-environments based on an objective statistical method is of interest for pure and applied science. We investigated the potential use of the Hurst test as a statistical tool to discriminate sub-environments within geologically complex turbiditic units that fill a confined basin with well-exposed facies transitions and onlaps, at the scale of several stacked reservoirs (Cengio and Bric la Croce–Castelnuovo Turbidite Systems in the Tertiary Piedmont Basin, Oligocene, northern Italy). In vertical stratigraphic sections, the Hurst test determines the degree of clustering of low and high values of sedimentological variables, such as bed thickness, grain size and sand/mud ratio, which are dependent on sub-environments of deposition. We applied the Hurst test to depocentral and marginal sub-areas across the basin (parallel and perpendicular to the main palaeocurrent direction), documenting a different clustering of thick and thin beds, and of high and low values of the sand/mud ratio, in the depocentre–distal sector with respect to the onlap areas.

A new field (onlap sub-environment) could thus be added to the classification diagram of turbidite settings based on the Hurst index. The Hurst phenomenon (clustering of high and low values of the selected variables) was also able to distinguish between proximal and distal (depocentral) lobe settings, and to recognize the fingerprint of the different depositional lobes (fully confined aggrading, prograding, backstepping). The map of turbidite sub-environments obtained by interpolation of the Hurst index is quite comparable to the field-observed facies map, providing impressive robust validation of the Hurst statistics. This method seems to represent a very promising predictive tool for subsurface studies of turbiditic oil fields based on core and log analyses.

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/content/journals/10.1144/1354-079309-005
2010-11-01
2022-11-28
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