Automated prediction of sedimentary facies from wireline logs
Erik Bølviken, Geir Olve Storvik, Dag Erik Nilsen, Erling Siring, Dirk van der Wel · Geological Society London Special Publications · 1992
Abstract The problem addressed is whether a computer can be programmed to identify depositional facies from a set of wireline logs. The basic approach is to let the computer learn by itself the patterns to search for by feeding it log signatures that have already been assigned facies labels. Having gone through this training phase, it can make sedimentary predictions from new data. The underlying model is a mathematical formalization of the idea that sedimentary processes have deposited lithological sequences which influence the observed log traces. Stochastic descriptions are used for these relationships. Markov chains link the lithology to the underlying sedimentary facies. The upward transition probabilities of the Markov chain are the main features which discriminate sedimentary facies. An efficient reconstruction algorithm permits probabilistic restoration of both lithology and sedimentology. This allows the uncertainty of the conclusions to be quantified, and more than one interpretation can be put forward where appropriate. Results of the tests are promising.