Seismic facies classification

B.P. West, S.R. May, J.E. Eastwood, and C. Rossen (2002) Interactive seismic facies classification using textural attributes and neural networks. The Leading Edge 10, 1042-1049. 

Automated Grid and Fault Extraction, Seismic Facies Classification. The first requirement for building a reservoir model is to determine its extents and characteristics. 

In this case study, well data are used to calibrate seismic facies with the main reservoir facies (oil saturated sand, water saturated sand, sand injections, shales and shales streaks). The results of the 3D seismic facies classification are shown in Figure 13 along a horizon-based slice just above the bottom of the reservoir sands. 

Prather, B. E., Booth, J. R., Steffens, G. S. Craig, P. A. 1998. Classification, lithologic calibration, and stratigraphic succession of seismic facies of intraslope basins, deep-water Gulf of Mexico. American Association of Petroleum Geologists Bulletin, 82, 701-728. 

Fig. 3. [Reproduced in colour in Plate 16 on page 433.] Workflow for seismic facies mapping using texture attributes and 3D classification based on neural network algorithm.

Fig. 6. [Reproduced in colonr in Plate 19 on page 434.] Classification of seismic facies based on texture attributes defines a geological/structural model. Using iterative and hierarchical classification capability, seismic facies can be calibrated and assigned to Uthology and fluids using well data or another set of attributes such as amplitude-based, or AVO data.

Fig. 13. [Reproduced in colour in Plate 23 on page 437.) Map views of seismic facies 3D classification 8 ms above the base reservoir from (A) PP data (acoustic mode), and (B) PS data (converted shear wave mode) viewed in PP time domain. The dotted lines represent linear deformation features. The white outlines highlight a potential flat spot on PP data (A) and a tuning effect or diagenesis effect on PS data (B).

A three-dimensional seismic facies model could be built from supervised classification of seismic textures that captures the detailed structural framework of the reservoir and its complex architecture. 

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