Building confidence in geological models
Published:January 01, 2004
Geological models are required because we do not have complete knowledge, in time or space, of the system of interest. Models are constructed in an attempt to represent the system and its behaviour based on interpretation of observations and measurements (samples) of the system, combined with informed judgement (expert opinion) and, generally, constrained for convenience by the limitations of the modelling medium. Geological models are inherently uncertain; broadly those uncertainties can be classified as epistemic (knowledge based) or aleatory (reflecting the variability of the system). Traditional, quantitative methods of uncertainty analysis address the aleatory uncertainties but do not recognize incompleteness and ignorance. Evidence-based uncertainty analysis provides a framework within which both types of uncertainty can be represented explicitly and the dependability of models tested through rigorous examination, not just of data and data quality, but also of the modelling process and the quality of that process. The inclusion of human judgement in the interpretation and modelling process means that there will be frequent differences of opinion and the possibility of alternative, inconsistent and/or conflicting interpretations. The analysis presented here uses evidence-based uncertainty analysis to formulate a complete expression of the geological model, including presentation of the supporting and the conflicting or refuting evidences, representation of the remaining uncertainties and an audit trail to the observations and measurements that underpin the currently preferred and the possible alternative hypotheses.
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Geological Prior Information: Informing Science and Engineering
Geological prior information represents a new and emerging field within the geosciences. Prior information is the term used to describe previously existing knowledge that can be brought to bear on a new problem. This volume describes a range of methods that can be used to find solutions to practical and theoretical problems using geological prior information, and the nature of geological information that can be so employed. As such, this volume defines how geology can be influential far beyond the confines of its own definition.