4. Spectral Decomposition AASPI 2016 AASPI Workplan Kurt J. Marfurt Marcilio Matos Bo Zhang Brad Wallet OU AASPI Team Attribute-Assisted Seismic Processing and Interpretation

4. Spectral Decomposition AASPI 2015 Workplan Software Development Continued construction of “workflows” that link common steps for Preconditioned least-squares migration Thang Ha Migration-driven 5D interpolation Thang Ha Poststack or common angle Q estimation Fangyu Li Diffraction imaging Yuji Kim Multispectral fault delineation followed by fault enhancement Fault skeletonization Computation of volumetric aberrancy Dania Shaib Level set object and surface detection Tao Zhao An AASPI artificial neural network algorithm Yin Zhang

4. Spectral Decomposition AASPI 2016 Workplan Diffraction imaging Time-processed shot gathers Migration velocities Diffraction image? Demigrated shot gathers CLSM with cosθ obliquity factor CLSM with (1-cosθ) obliquity factor Migrated gathers Workflow for diffraction imaging which holds promise in mapping natural and induced fractures in resource plays. One approach is to migrate the data using 1.0 minus the obliquity factor. Early migration algorithms (e.g. Schneider, 1978) set the obliquity factor to be centered about the vertical where in principal it should be normal to structural dip. The obliquity factor cosθ favors specular reflections while 1-cosθ favors diffractions. Dip and azimuth cosθ stack dip3d Yuji Kim

Level Sets and Deformable Models (the mathematics of shrink-wrapping) 12. Image Enhancement and Object Extraction Level Sets and Deformable Models (the mathematics of shrink-wrapping) Shrink-wrapped boat Shrink-wrapped beer Papers on level sets (sometimes called deformable models) can be highly mathematical, with many of the mathematical constructs somewhat ‘ad hoc’. I think of level sets as ‘shrink wrapping’. My boat and boat cover are OU crimson and cream, but this image gives you the idea. I usually drink canned beer in the boat to protect future generations of swimmers, but the image of a shrink-wrapped six-pack gives you the idea of a level set. Physically, we wish to shrink-wrap a feature such as an irregular salt dome (imaged say by low coherence and low energy) within an elastic surface such that almost all voxels with the desired features fall inside the surface while voxels not having such desired properties fall outside the surface. The elastic surface has nice properties such as smooth derivatives in 2 dimensions. Objective: Enclose (almost) all the voxels of the volume of interest Constrain the surface to have constraints on curvature (strain) Tao Zhao

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”)

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

AASPI 2016 Workplan 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, Tengfei Lin, Yin Zhang 19

4. Spectral Decomposition AASPI 2015 Workplan Software Development Velocity vs. Azimuth (VVAz) via correlation Jie Qi Frequency vs. Azimuth (FVAz) Fangyu Lin Wave equation least-squares migration for land surveys Bin Lyu Q-compensation internal to migration Bin Lyu Wavelet based Radon transforms Tengfei Lin

4. Spectral Decomposition AASPI 2016 Workplan Correlation of attributes to “specialty logs” Finalized license with Pioneer on Permian Basin data (microseismic, image logs,…?) Megan Gunther? Saurab Sinha? Chesapeake Miss Lime data (image logs, ROP, …?) Joseph Snyder, Xuan Qi, Stephanie Cook, Mohsen Alali Correlate prestack inversion, MWD, image logs to natural and induced fractures in RedFork Energy Miss Lime survey – Trey Stearns and Mohsen Alali Will continue work on TOC prediction (Devon data) Correlation of attributes to production Obtained license from Devon Energy to perf locations in two Barnett Shale and one Granite Wash survey Have requested access to perf locations from Chesapeake Miss Lime survey Correlation of attributes to hydraulic fracturing May have lost champion at Chevron (John Best) for “time lapse survey”

TOC estimation from well logs Gamma Ray Low High Density Resistivity Neutron Porosity WTOC Discretized WTOC Estimated WTOC MD (ft) 8100 8200 8300 8400 Well A Discretized WTOC Low MD (ft) 8100 8200 8300 Estimated WTOC High Well A 8400 6500 6600 6700 Well B WTOC Regression WTOC 12

4. Spectral Decomposition AASPI 2016 Workplan Seismic geomorphology Have license to large 3D data volumes from New Zealand and Australia – contains volcanic intrusives, turbidites, FLTs – Lennon Infante and multiple geology students Will acquire licenses to large 3D volumes from Australia – carbonate banks, buildups, dewatering, … Brad Wallet and multiple geology students Salt segmentation Finalizing license with PGS to 3600 mi2 from GOM shelf – Jie Qi and multiple geology students Attributes from 2D vs. 3D surveys 2D and 3D data from New Zealand - Bryce Hutchinson

4. Spectral Decomposition AASPI 2016 Workplan Seismic data processing Legacy data from Central Basin Platform (CP) – Thang Ha and Gabriel Machado Perpendicular 3D surveys from Jeju Basin (KIGAM) – Yuji Kim Ground roll suppression and prestack inversion of Granite Wash (Devon) – Tobi Olorunsola Ground roll suppression and prestack inversion of Mississippi Lime (Chesapeake) – Mohsen Alali

4. Spectral Decomposition AASPI 2016 Workplan Suggestions from the floor?