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Fracture Orientation from P Wave Seismic Data Using Volumetric Curvature, Silo Field, Wyoming*

By

Charles H. Blumentritt¹, Kurtt J. Marfurt², and Michael Murphy²

Search and Discovery Article #40250 (2007)

Posted August 6, 2007

*Adapted from oral presentation at AAPG Annual Convention, Long Beach, California, April 1-4, 2007

¹Geo-Texture Technologies, Houston, TX ([email protected])

²University of Houston, Houston, TX

Abstract 

Silo Field is a fractured reservoir over which 3-D P wave and S wave data have been acquired for the purpose of determining fracture orientation. The S wave data have been analyzed for the usual slow wave and fast wave orientations to yield a fracture orientation of 258 degrees. We apply volumetric curvature to the P wave data and observed a similar result. Our technique is a simple, cost effective method of using the lower cost P wave data to answer a question usually reserved for the more expensive S wave data.  

We determine curvature values for every point in a conventional stacked and migrated 3-D seismic data volume using a small (3 traces by 3 traces by 9 samples) subvolume. We then observe the lineaments appearing in the curvature data at the target level and analyze their orientations with rose diagrams. We propose that those lineaments represent subtle anticlines, synclines, and flexures caused by the stresses controlling and resulting from the anisotropy determined from the S wave data.

Selected Figures 

	Location map (from Lewis et al., 1991).
	Fracture orientation from shear wave data (from Lewis et al., 1991).
	Time structure map, top Niobrara, and seismic lineA-A’.
	Interpretation (Niobrara horizon slice): Most negative curvature (with inferred fractures).
	Rose diagram of fracture orientation (Niobrara horizon) from most negative curvature (left) compared to fracture orientation from shear-wave.

Conclusion 

P wave curvature provides identification of fracture orientation as well as 9-C shear wave data.

References 

Lewis, C., T.L. Davis, and C. Vuillermoz, 1991, Three-dimensional multicomponent imaging of reservoir heterogeneity, Silo Field, Wyoming: Geophysics, v. 56, p. 2048-2056.

Roberts, A., 2001, Curvature attributes and their application to 3D interpreted horizons: First Break, v. 19, p. 85-100.

Wynn, T.J., and S.A. Stewart, 2003, The role of spectral curvature mapping in characterizing subsurface strain distributions, in Fracture and in-situ stress characterization of hydrocarbon reservoirs: Geological Society of London Special Publications 209, p. 127-143.