
%0 Journal Article
%A Sherlock, D.H. 
%A Evans, B.J. 
%A Ford, C.C. 
%T THE SEISMIC EXPRESSION OF THREE-DIMENSIONAL SANDBOX MODELS
%J The APPEA Journal
%D 1996/06/30
%V 36
%N 1
%P 490-499
%K 
%R https://doi.org/10.1071/AJ95027
%U https://www.publish.csiro.au/paper/AJ95027 
%X Analogue sandbox models provide cheap, concise data and allow the evolution of geological structures to be observed under controlled conditions in a laboratory. Seismic physical modelling is used to study the effects of seismic wave propagation in isotropic and anisotropic media and to improve methods of data acquisition, processing and interpretation. These two independent geological modelling techniques have been linked for the first time, to combine and expand the existing benefits of each method.Seismic physical modelling to date has employed solid models, constructed with pre-determined structures built into the model. Previous attempts to adapt this technology to unconsolidated materials failed due to the severe energy attenuation of seismic waves in cohesionless grain matrices, and excessive signal scatter due to scaling limitations of the geological feature size to wavelength ratio. This paper presents our research to overcome these problems and thereby allow the successful seismic imaging of sandbox models.A number of techniques have been developed to combine these two independent modelling methods and results show that it is possible to image several layers within the models, demonstrating the potential to interpret complex geological structures within such models. For seismic modelling, the main advantages are that the seismic data collected from these models contain natural variation that cannot be built into solid models, which results in a more realistic image, and the cost and construction time of the models are also dramatically reduced. For sandbox modelling, the recording of seismic data over them allows far more detailed interpretation of the structures than previously possible and also allows direct comparison with field data for the first time, to substantiate or negate an existing interpretation. 
