Skip to Main Content
Book Chapter

Next Generation Three-Dimensional Geologic Modeling and Inversion

By
Mark Jessell
Mark Jessell
Centre for Exploration Targeting, University of Western Australia, 35 Stirling Highway, Crawley, Western Australia 6009, AustraliaSchool of Earth, Atmosphere and Environment, Monash University, P.O. Box 28E, Victoria 3800, AustraliaInstitut de Recherche pour le Développement, UR 234, GET, 14 Av. Edouard Belin, F-31400 Toulouse, France
Search for other works by this author on:
Laurent Aillères
Laurent Aillères
School of Earth, Atmosphere and Environment, Monash University, P.O. Box 28E, Victoria 3800, Australia
Search for other works by this author on:
Eric de Kemp
Eric de Kemp
Natural Resources Canada, 615 Booth St., Ottawa, Ontario K1A 0E9, Canada
Search for other works by this author on:
Mark Lindsay
Mark Lindsay
Centre for Exploration Targeting, University of Western Australia, 35 Stirling Highway, Crawley, Western Australia 6009, Australia
Search for other works by this author on:
Florian Wellmann
Florian Wellmann
Centre for Exploration Targeting, University of Western Australia, 35 Stirling Highway, Crawley, Western Australia 6009, Australia
Search for other works by this author on:
Michael Hillier
Michael Hillier
Natural Resources Canada, 615 Booth St., Ottawa, Ontario K1A 0E9, Canada
Search for other works by this author on:
Gautier Laurent
Gautier Laurent
School of Earth, Atmosphere and Environment, Monash University, P.O. Box 28E, Victoria 3800, Australia
Search for other works by this author on:
Thomas Carmichael
Thomas Carmichael
School of Earth, Atmosphere and Environment, Monash University, P.O. Box 28E, Victoria 3800, Australia
Search for other works by this author on:
Roland Martin
Roland Martin
Géosciences Environnement Toulouse, GET, CNRS, UMR 5563, 14 avenue Edouard Belin, F-31400 Toulouse, France
Search for other works by this author on:
Published:
January 01, 2014

Abstract

Existing three-dimensional (3-D) geologic systems are well adapted to high data-density environments, such as at the mine scale where abundant drill core exists, or in basins where 3-D seismic provides stratigraphie constraints but are poorly adapted to regional geologic problems. There are three areas where improvements in the 3-D workflow need to be made: (1) the handling of uncertainty, (2) the model-building algorithms themselves, and (3) the interface with geophysical inversion.

All 3-D models are underconstrained, and at the regional scale this is especially critical for choosing modeling strategies. The practice of only producing a single model ignores the huge uncertainties that underlie model-building processes, and underpins the difficulty in providing meaningful information to end-users about the inherent risk involved in applying the model to solve geologic problems. Future studies need to recognize this and focus on the characterization of model uncertainty, spatially and in terms of geologic features, and produce plausible model suites, rather than single models with unknown validity.

The most promising systems for understanding uncertainty use implicit algorithms because they allow the inclusion of some geologic knowledge, for example, age relationships of faults and onlap-offlap relationships. Unfortunately, existing implicit algorithms belie their origins as basin or mine modeling systems because they lack inclusion of normal structural criteria, such as cleavages, lineations, and recognition of polydeformation, all of which are primary tools for the field geologist that is making geologic maps in structurally complex areas. One area of future research will be to establish generalized structural geologic rules that can be built into the modeling process.

Finally, and this probably represents the biggest challenge, there is the need for geologic meaning to be maintained during the model-building processes. Current data flows consist of the construction of complex 3-D geologic models that incorporate geologic and geophysical data as well as the prior experience of the modeler, via their interpretation choices. These inputs are used to create a geometric model, which is then transformed into a petrophysical model prior to geophysical inversion. All of the underlying geologic rules are then ignored during the geophysical inversion process. Examples exist that demonstrate that the loss of geologic meaning between geologic and geophysical modeling can be at least partially overcome by increased use of uncertainty characteristics in the workflow.

You do not currently have access to this article.

Figures & Tables

Contents

Special Publications of the Society of Economic Geologists

Building Exploration Capability for the 21st Century

Karen D. Kelley
Karen D. Kelley
Search for other works by this author on:
Howard C. Golden
Howard C. Golden
Search for other works by this author on:
Society of Economic Geologists
Volume
18
ISBN electronic:
9781629499291
Publication date:
January 01, 2014

GeoRef

References

Related

Citing Books via

Close Modal
This Feature Is Available To Subscribers Only

Sign In or Create an Account

Close Modal
Close Modal