Data Driven Interpreter Guided Geobody Interpretation.
Nicholas McArdle and James Lowell
ASEG Extended Abstracts
2013(1) 1 - 4
Published: 12 August 2013
Abstract
Fully volumetric interpretation needs to encompass 3D delineation of geological features beyond the extraction of top and base horizons. To address this issue 3D geobody delineation techniques based on thresholding and voxel connectivity have been developed. Such techniques have limited applicability as there is often insufficient information to enable the discrimination of the constituent components of a geological system based on the seismic data alone. Understanding how we perceive objects in images is central to the development of better interpretation tools. What we perceive in data is strongly influenced by geological knowledge, previous experience and analogues. These are subjective factors but to produce geologically realistic results we need to find a way of incorporating them within 3D geobody interpretation. A large step in this direction has been taken with a technology known as â??adaptive geobody delineationâ??. The adaptive geobodies technique combines an adaptive, classification based region growing method, with interactive 3D surface manipulation techniques. This enables delineation of 3D geobodies that are a best fit to the data whilst matching the interpreterâ??s view of what is geologically realistic. This paper will discuss how we perceive objects in images and, in the context of 3D geobody definition, how we can improve data analysis techniques for objectively delineating what we understand the image to represent. We present the potential utility of these techniques applied to the delineation of a variety of geological elements from seismic data acquired from the North Carnarvon Basin, North-Western Australia. These include fluvial and deltaic systems, submarine canyons and fans, carbonate reefs and clinoform complexes through to sub-reservoir scale lithofacies variation. The wide range of features of varying scale, morphology and depositional origin that have been successfully extracted within the sample sets demonstrates the broad applicability of the tool.https://doi.org/10.1071/ASEG2013ab339
© ASEG 2013