Facies Modeling of Fluvial-Dominated Outcrop Using LiDAR Data and Multiple-Point Statistics

M.H. Sarraj¹

Abstract

Light Detection and Ranging (LiDAR) has revolutionized digital outcrop characterization methods by providing high resolution data (e.g., x, y, z; spatial coordinates) of 2D surface structural topology in the 3D spatial domain. The prediction of the 3D subsurface extension of 2D LiDAR erosional surface information remains as an outstanding problem in outcrop studies for reconstructing sedimentary facies of paleo-depositional environments. In this study, a 3D cellular model of the subsurface was constructed using training images that were drawn based on LiDAR outcrop measurements and integrating other geological descriptions. The training images are the prior constraint describing the geobody shapes and geological connectivity structure in Multiple-Point Statistics (MPS) facies models. Hence the interpretation of outcropping geo-bodies from LiDAR data aids to draw more realistic training images. The objective of this study is to generate facies conditioned to exhaustive LiDAR data in a large outcrop.

AAPG Search and Discovery Article #90188 ©GEO-2014, 11th Middle East Geosciences Conference and Exhibition, 10-12 March 2014, Manama, Bahrain