Laterally discontinuous coal measures are common in alluvial settings due to interaction with fluvial systems. Under these conditions it is difficult to accurately represent coalbeds and interburden sandstone bodies in static and dynamic models at a regional scale. These challenges are compounded in the Walloon Coal Measures by non-uniform drill spacing, which varies from clustered to sparse and insufficient outcrop exposures available to constrain the correlations.
To address these issues, this study investigates a nested approach to facies modelling of the Upper Juandah Member of the Jurassic Walloon Coal Measures in the Surat Basin, Queensland, which contains some 3,600 wells, of which half were analysed for lithofacies distributions. This approach contrasts the application of truncated Gaussian simulation, object modelling and multiple-point geostatistical simulation.
First, a regional scale structural model was developed based on the correlation of sub units within the basin and the lithofacies were then interpreted from normalised wireline logs. Then geometries of individual facies were defined from two local scale models (~6 × 6 km2) where dense drilling, 3D seismic and paleocurrent analysis data were available to constrain the models. Three training images, generated by object modelling, an analogue of one part of the Ob River, and an interactive method were subsequently used to model primary channels, channels and crevasse splays, respectively. Truncated Gaussian simulation was used in modelling the distribution of marginal and coal swamp. The final model is a combination of the model with primary channels and channels, and the model with marginal and coal swamp.
This approach is the first trial in modelling swamp and channel distributions at a regional scale by integrating data from local models, depositional analogues and paleo-flow interpretation in the Surat Basin.
Assessing the effectiveness of ground truth data to capture landscape variability from an agricultural region using Gaussian simulation and geostatistical techniques
