GEOSCAN, résultats de la recherche


TitreCombined inverse and forward numerical modelling for reconstruction of channel evolution and facies distributions in fluvial meander-belt deposits
AuteurParquer, M; Yan, N; Colombera, L; Mountney, N P; Collon, P; Caumon, G
SourceMarine and Petroleum Geology vol. 117, 104409, 2020 p. 1-15,
Séries alt.Ressources naturelles Canada, Contribution externe 20200058
Documentpublication en série
Mediapapier; en ligne; numérique
Formatspdf; html
Sujetssystèmes fluviaux; dépôts fluviaux; gîtes en forme de traînée; méandres; simulations par ordinateur; modèles de faciès; établissement de modèles; interpretations sismiques; données sismiques; méthodologie; sédimentologie; stratigraphie; géophysique; Nature et environnement; Sciences et technologie
Illustrationstables; geophysical images; geoscientific sketch maps; plots; seismic images; models; flow diagrams
Diffusé2020 04 27
Résumé(disponible en anglais seulement)
The sedimentary record of meandering rivers contains a diverse and complex set of lithological heterogeneities, which impact natural resource management. Different methods exist to model such accumulated successions present in the subsurface by integrating knowledge of system evolutionary behaviour and geometries visible on seismic time or stratal slices. With reference to case-study examples, we review, discuss and employ two of these methods: (i) ChaRMigS generates possible scenarios for channel evolution and meander cut-offs by a reverse migration process; (ii) PB-SAND is a forward stratigraphic model which simulates fluvial point-bar geometry and facies distributions from known palaeo-channel geometries. We introduce a workflow to demonstrate how these two methods can be applied in combination to predict fluvial meander-belt facies distributions, using a subsurface dataset on a Pleistocene succession from the Gulf of Thailand where abandoned channels are visible on seismic time slices, but for which bar-accretion geometries and the exact timing of channel abandonment are unclear. Results show the value of a combined modelling approach to automate the stochastic generation of facies distributions constrained by seismic interpretations.