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Shape information is of great importance in many applications. For example,the oil-bearing capacity of sand bodies, the subterranean remnants of ancientrivers, is related to their cross-sectional shapes. The analysis of theseshapes is therefore of some interest, but current classifications aresimplistic and ad hoc. In this paper, we describe the first steps towards acoherent statistical analysis of these shapes by deriving the integratedlikelihood for data shapes given class parameters. The result is of interestbeyond this particular application.

Bayesian shape modelling of cross-sectional geological data