4. Spectral Decomposition AASPI 2017 AASPI Workplan Kurt J. Marfurt Marcilio Matos Bo Zhang Brad Wallet OU AASPI Team Attribute-Assisted Seismic Processing and Interpretation

Continued graphical data interaction and display To better build the link from seismic attributes to different facies, we now see the attribute responses of four key facies. All attribute are normalized using z-score. As expected, similar facies (colors) on the SOM map have similar attribute responses. We see the sample vector from the sand-filled channel deposits, has a similar response to that of facies 3, which is the sandy overbank complexes. The inter-channel overbank complex and the mud-filled sinuous channel complex are in similar facies (blue to purple colors). We can also see the difference in seismic amplitudes of the multistoried channel (more chaotic) and older sand filled channel (more flat and higher amplitude). Tao Zhao, Thang Ha, Yin Zhang 19

Aberrancy and the 3rd derivatives of surfaces The objective Delineate flexures But what are the other three roots? (in kinematics, we have location, velocity, acceleration, and “jolt” or “jerk”)

Spectral decomposition and anisotropy analysis Software development and comparison of VVAz vs. AVAz Azimuth analysis – Jie Qi Frequency vs. incident angle to better estimate thickness – Fangyu Li Frequency vs. Azimuth to estimate fractures and stress anisotropy – Fangyu Li 3D near-offset volumetric Q estimation (soft sediments) – Fangyu Li Variational mode decomposition (difficulty – how to interpret the results!) – Fangyu Li

Data condition and texture analysis Compare poststack kx-ky vs. space-wavenumber CWT footprint suppression workflows – Mohsen Alali Use space-wavenumber CWT algorithm to quantify periodic geologic features (syneresis, polygonal faulting, dunes and sand bars,… – Mohsen Alali

Facies analysis and clustering Design workflows to help choose the best attributes to discriminate undefined facies – Tao Zhao Apply weighted attribute workflow to discriminate facies in both conventional and unconventional reservoirs – Tao Zhao Define software and workflow to allow identification of small facies populations within the seismic data – Tao Zhao An AASPI artificial neural network algorithm - David Lubo An AASPI Gaussian mixture model algorithm – Bob Hardesty Correlation of image logs to seismic facies – Tao Zhao and Stephanie Cook

Development of an AASPI neural network algorithm to compare to PSVM 15

Diffraction imaging, least-squares migration and data interpolation Separate specular from non specular reflections using 3D estimates of volumetric dip – Mohsen Alali Compare 5D interpolation computed in unmigrated common midpoints to migration-driven interpolation – Thang Ha Merge orthogonal narrow azimuth surveys using least-squares migration – Yuji Kim Quantify the value of least-squares migration on prestack impedance inversion – Thang Ha Quantify the value of least-squares migration on AVAz analysis – Thang Ha

Fault and Horizon Analysis Correlate water injection wells to fault proximity – Gabriel Machado Evaluate Wu and Hale fault slip estimation algorithm – Thang Ha Implement a geochronostratigraphy algorithm – Bo Zhang

4. Spectral Decomposition AASPI 2017 Workplan Suggestions from the floor?