Cluster Assisted 3D And 2D Unsupervised Seismic Facies Analysis, an Example From the Barnett Shale Formation In the Fort Worth Basin, Texas. Available to Purchase

The most popular seismic attributes fall into broad categories — those that are sensitive to lateral changes in waveform and structure, such as coherence and curvature, and those that are sensitive to lithology and fluid properties — such as AVO and impedance inversion. Unfortunately neither of these two attribute families works well in differentiating the depositional packages characterized by subtle changes in the stratigraphic column or lateral changes in texture. Automatic seismic facies analysis aims to classify similar seismic traces based on amplitude, phase, frequency and other seismic attributes. This paper reviews Kohonen Self Organizing Maps as one of the clustering algorithms that can generate 3D seismic facies volumes and maps using multiple attributes as input. The present area of study is the Mississippian Barnett Shale of the Fort Worth Basin in Texas. The aim of the study is to visualize the variation in shale and possible relationship between these rock types and their seismic expression and try to delineate by passed play after hydraulic fracturing.