Fractures play a major role in many tight reservoirs such as shale, carbonate, and low permeability sand by providing fluid flow conduits, for this reason knowledge of fracture orientation and intensity is of great importance for exploring hydrocarbon and designing drilling direction. Since fractures directly modify the effective impedance of rocks, seismic waves are sensitive to subsurface fractures. Nevertheless, the study of seismic expression of fractures still remains challenging for several reasons.

My study will apply Perez’s new binning method to converted wave prestack Kirchhoff migration to enhance the imaging resolution of fault and fracture discontinuities. My new imaging method uses a scanning approach to automatically perform the converted wave velocity analysis and provides convincing imaging quality. The migrated volumes from different azimuths are further evaluated by seismic attributes using Devon energy’s Fairview 3d dataset.

Shear wave birefringence is an addition to the subsurface fracture analysis. In my study, I propose to analyze not only the velocity azimuthal variation, but also polarization of radial and transverse converted waves data to predict the fracture orientation and intensity.

IntroductionIntroduction

0.8

1.3

Fracture prospecting using new seismic imaging approach, converted wave analysis, and seismic attributes

Kui Zhang* and Kurt J. Marfurt

ConocoPhillips School of Geology & Geophysics, University of Oklahoma

The Barnett Shale is a very important unconventional shale gas system in Fort Worth Basin (FWB), Texas where it serves as a source rock, seal, and trap (Perez, 2009). Since it has a very low permeability for production, Devon energy launched a program that fractured the rocks in the field in recent years by injecting high pressure fluid with 10 wells per square mile, thereby significantly improving the production rate. My objective is to differentiate damaged reservoir from potential undamaged (bypassed pay) reservoir by the integration of multiple geophysical techniques. If possible, mapping of fracture patterns could have a significant value in evaluation the effectiveness of alternative fracture programs used.

Geological ContextGeological Context

Figure 2. Map of seismic surveys in which Fairview is the one under study.

Figure 4. An inline seismic section (a) and crossline section (b) with the interpreted igneous body.

Figure 8. New way of azimuth binning. Figure 9. Comparison of image quality between nature binning and new azimuthal binning (Perez, 2008).

Figure 10. Converted wave azimuthal velocity analysis approach.

AcknowledgementAcknowledgementWe thank all the industry sponsors of the University of Oklahoma Attributes-Assisted Processing and Interpretation (AASPI) Consortium.

Figure 1. Formation interpretation based on gamma ray (Perez, 2009).

Data availabilityData availability

Anticipated resultsAnticipated resultsRework on P-wave migrated stacks from different azimuth using new binning imaging,Converted wave migrated stacks from different azimuth using new binning imaging,Attribute illumination of fractures based on the partial stacks from different azimuth for both P and C data,Interval velocity factor volume and fast velocity azimuth volume (Figure 13) ,Fracture prediction based upon converted wave analysis,Delineation of damaged zone and bypassed pay.

ReferencesReferencesMattocks B., J. Li, and S. L. Roche, Converted-wave azimuthal anisotropy in a carbonate foreland basin: 65th International Meeting, SEG, Expanded Abstracts, 897-900.Perez, G. and K. J. Mafurt, 2008, New azimuthal binning for improved delineation of faults and fractures: Geophysics, 73, S7-S15.Perez, R., Quantitative petrophysical characterization of the Barnett shale in Newark east field, Fort Worth Basin : M. S. thesis, University of Oklahoma, 2009.Treadgold, G., C. Sicking, V. Sublette, and G. Hoover, 2008, Azimuthal processing for fracture prediction and image improvement: CSEG recorder, 34, no. 4, 38-41.

Figure 3. Seismic data and interpreted horizons.

Figure 4. Attribute time slices at 1400ms.

energy ratio similarity

Most negative curvature

Most postive curvature

Figure 5. Horizon slices from Upper Barnett Shale.

Figure 6. Horizon slices from Lower Barnett Shale.

Figure 7. Horizon slices from Viola unconformity.

New imaging approachNew imaging approach

Converted wave analysisConverted wave analysis

Figure 11. Schematic illustration of shear wave birefringence (a) and layer stripping is taken to analyze the shear wave birefringence (b).

Figure 12 Schematic illustration of shear wave birefringence using a P-SV source with fractures oriented NE45(Mattocks, 2005).

Figure 13. Anticipated results from converted wave analysis (Treadgold, 2008).