Unsupervised pre-stack seismic facies analysis constrained by spatial continuity

Abstract

Seismic facies analysis plays important roles in geological research, especially in sedimentary environment identification. Traditional method is mainly based on seismic waveform or attributes of a single seismic gather to classify the seismic facies. Ignoring the correlation between adjacent seismic gathers leads to poor lateral continuities in generated facies map, which cannot fit the sedimentary characteristics well. In fact, according to sedimentology theory, the horizontal continuities of the stratum can be utilized as priori information to provide more information for waveform classification. Therefore, we develop an unsupervised method for pre-stack seismic facies analysis, which is constrained by spatial continuity. The proposed method establishes a probabilistic model to characterize the correlation between neighboring reflection elements. Subsequently, this correlation is used as a regularization term to modify the objective function of the clustering algorithm, allowing the mode assignment of reflective elements to be influenced by the labels of their neighbors. Test on synthetic data confirms that, compared with traditional seismic facies analysis methods, the facies maps generated by the proposed method have more continuous and homogeneous textures, and less uncertainty on the boundary. The test on actual seismic data further confirms that the proposed method can describe more details of the distribution of lithological bodies of interest. The proposed method is an effective tool for pre-stack seismic facies analysis.