Predicting Facies Distribution Within a Fluvial System in the Subsurface: Triassic of the Central North Sea

Abstract

The understanding of fluvial systems in the subsurface relies heavily on the sedimentological interpretations of cored intervals, as well as outcrop studies of analogous strata and wireline logs from un-cored intervals. Integrating this sedimentological detail from core to un-cored intervals and wells is a key step towards maximising the available data-set. This study utilises varied classes of artificial neural network to complete this integration of core interpretation with wireline log expression. Wells from Quadrants 22, 29 & 30 of the Central North Sea UKCS form the focus of this study, with continued work to be extended east into the Norwegian North Sea, and north into the Northern North Sea. The Mid-Late Triassic Skagerrak Formation is composed of alternating fluvial sandstone dominated and lacustrine and playa mudstone dominated members, and is the focus strata of this study. This sandstone to mudstone alternation is thought to represent climate influenced expansion and contraction of terminal fluvial systems. This study shows that core interpreted facies associations within Skagerrak Formation sandstone dominated members can be recognised in un-cored intervals using wireline logs and artificial neural networks. This recognition allows for the quantification of the facies distribution between and within sandstone dominated Skagerrak Formation members, within the study area. This quantification allows for comparison with analogous outcrop studies from Southwest USA and Northern Spain to aid the understanding of the regional system. Further applications of this study could include the use of the presented workflow to interpret similar subsurface datasets, and possibly aiding the continued hydrocarbon exploration and exploitation of the Skagerrak Formation in the Central North Sea.

AAPG Datapages/Search and Discovery Article #90291 ©2017 AAPG Annual Convention and Exhibition, Houston, Texas, April 2-5, 2017