Research progress on intelligent identification of seismic facies

Abstract

Seismic facies are the reflection of sedimentary facies on the seismic profile, which can provide a favorable basis for the exploration and development of underground resources, especially for oil and gas.In recent years, with the rapid development of artificial intelligence and its vigorous advancement in oil and gas, researchers have proposed several methods for intelligent identification of seismic facies.This article summarizes the intelligent identification methods for seismic facies and classifies them into three categories: unsupervised, supervised, and semi-supervised learnings.Furthermore, it introduces the principles, application status, advantages, and disadvantages of these three categories in detail.Unsupervised learning uses unlabeled seismic data for learning clustering to realize automatic identification of seismic facies, which is simple and easy to operate.Supervised learning mainly adopts label data to feedback learning and continuously approaches labels through learning, so that it has high accuracy in seismic phase recognition.Semi-supervised learning applies synthetic pseudo-labels and other methods for learning when there are insufficient seismic data tags, but the errors in the pseudo-labels reduce its accuracy.Finally, an example of neural network seismic facies recognition is shown, and the intelligent seismic facies recognition technology is prospected.