"Enhancing Confidence in Fracture Prediction Using Advanced Seismic Data Analysis. A case study from Russia"

Konstantin Smirnov

Information on the areas of high fracture can play a key role in the successful development of the majority of carbonate and unconventional reservoir types. Seismic data are one of the sources of such information and with modern acquisition methods optimally designed to obtain the field data of the highest quality, the possibilities now exist to extract maximum information and knowledge related directly to fracture characterization. 

Conventional surface seismic methods for fracture detection rely on the measurement of azimuthal anisotropy, coherency analysis other attributes. Diffraction imaging has gained interest to fracture detection and it is based on the fact that diffraction is the direct seismic wavefield response to small scale subsurface discontinuities. Seismic diffraction can help to detect and map systems of subsurface discontinuities that could be related to faults or fracture corridors. Increasing the confidence in fracture prediction can also be enhanced further by combining (fusion imaging) of the diffraction energy volume, the azimuthal anisotropy intensity volume and the geometry (coherence or dips or curvature) volume together using RGB blending in the 3-dimensional space. The integration with well log data can be used to quantify the probability of the areas of high fracture.

These techniques are presented in an integrated fracture zones detection case study for the oil and gas province of Russia.