Hidden Markov Chains for Identifying Geological Features from Seismic Data

Abstract

In this paper we propose a hierarchical model for accomodating,geologic prior knowledge together with velocity and density observations. The goal is to characterize underlying geologic patterns in clastic depositional systems, patterns such as blocky sand, shales, and fining or coarsening upward sequences. We use Gibbs sampling to explore the statistical distributions. The method is tested on synthetic data and well data from a fluvial environment.