Using direct S-wave seismic modes for reservoir characterization in Wellington Field, Kansas
Creators: name: Gupta, Menal
name: 0000-0003-2687-7962
Publisher: name: The University of Texas at Austin
Year: 2017
Subjects: S-waves
Converted-waves
Fracture characterization
Reservoir characterization
Seismic anisotropy
Multicomponent seismic data

description: S-waves exhibit birefringence, provide independent measurements of subsurface elastic properties and play a vital role in reservoir characterization. Despite obvious advantages, direct S-wave data (S-S and SV-P) remain under-utilized for characterization of fractured reservoirs, partly due to limited understanding of seismic attributes quantitatively estimate fracture properties, and because of the high-cost associated with direct S-wave data acquisition. This dissertation offers solutions to these challenges by creating S-S AVO attributes that can estimate fracture properties, and demonstrating use of low-cost, mode-converted P-wave data (SV-P) generated by conventional P-wave sources, for reservoir characterization. Multicomponent seismic data and well data from Wellington Field, Kansas are analyzed to understand reservoir facies and fractures characteristics in the Arbuckle Group, which is being considered for CO₂ injection. Results from multicomponent seismic interpretation suggest a mechanically stratified Arbuckle interval with varying lithofacies, and presence of seismic anisotropy caused by fractures. Rock physics modeling and S-wave AVO analysis demonstrate that the Intercept Anisotropy (IA) attribute and Gradient Anisotropy (GA) attribute proposed in this dissertation can be used to estimate fracture-density and fluid-fill in fractures, respectively. Results show that amplitude-based anisotropy analysis, in conjunction with travel-time-based analysis for seismic anisotropy, helps reduce ambiguity and provides high-resolution fracture characterization. Finally, a series of comparisons between the inversion results of P-P, P-SV and SV-P seismic data show that vertical-vibrator SV-P data from vertical geophones work as good as P-SV seismic data from horizontal geophones to estimate reservoir properties, and provide better subsurface resolution than do SV-P data generated by a horizontal vibrator. These results validate that direct S-wave data generated by conventional P-wave sources are a low-cost, yet highly-effective, alternative to data generated by more expensive S-wave sources. Overall, this dissertation advances our understanding of S-wave AVO attributes, and offers novel workflows to characterize naturally fractured reservoirs using direct S-wave data that do not require expensive seismic data acquisition. Multicomponent seismic data and well data from Wellington Field, Kansas are analyzed to understand reservoir facies and fractures characteristics in the Arbuckle Group, which is being considered for CO2 injection. Results from multicomponent seismic interpretation suggest a mechanically stratified Arbuckle interval with varying lithofacies, and presence of seismic anisotropy caused by fractures. Rock physics modeling and S-wave AVO analysis demonstrate that the Intercept Anisotropy (IA) attribute and Gradient Anisotropy (GA) attribute proposed in this dissertation can be used to estimate fracture-density and fluid-fill in fractures, respectively. Results show that amplitude-based anisotropy analysis, in conjunction with travel-time-based analysis for seismic anisotropy, helps reduce ambiguity and provides high-resolution fracture characterization. Finally, a series of comparisons between the inversion results of P-P, P-SV and SV-P seismic data show that vertical-vibrator SV-P data from vertical geophones work as good as P-SV seismic data from horizontal geophones to estimate reservoir properties, and provide better subsurface resolution than do SV-P data generated by a horizontal vibrator. These results validate that direct S-wave data generated by conventional P-wave sources are a low-cost, yet highly-effective, alternative to data generated by more expensive S-wave sources. Overall, this dissertation advances our understanding of S-wave AVO attributes, and offers novel workflows to characterize naturally fractured reservoirs using direct S-wave data that do not require expensive seismic data acquisition.