AASPI 2016 AASPI Workplan Kurt J Marfurt Marcilio

AASPI 2016 AASPI Workplan Kurt J. Marfurt Marcilio Matos Bo Zhang Brad Wallet OU AASPI Team Attribute-Assisted Seismic Processing and Interpretation 1

AASPI 2015 Workplan Software Development Continued construction of “workflows” that link common steps for • Preconditioned least-squares migration Thang Ha • Migration-driven 5 D interpolation Thang Ha • Poststack or common angle Q estimation Fangyu Li • Diffraction imaging Yuji Kim • Multispectral fault delineation followed by fault enhancement • Fault skeletonization 2 Computation of volumetric aberrancy Dania Shaib Level set object and surface detection Tao Zhao An AASPI artificial neural network algorithm Yin Zhang

AASPI 2016 Workplan Diffraction imaging Timeprocessed shot gathers Migration velocities CLSM with cosθ obliquity factor Diffraction image? Demigrated shot gathers CLSM with (1 -cosθ) obliquity factor Migrated gathers stack 3 dip 3 d Dip and azimuth cosθ Yuji Kim

Level Sets and Deformable Models (the mathematics of shrink-wrapping) Shrink-wrapped boat Shrink-wrapped beer Objective: • Enclose (almost) all the voxels of the volume of interest • Constrain the surface to have constraints on curvature (strain) 11 -4 Tao Zhao

Aberrancy and the 3 rd 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”) 5

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

AASPI 2016 Workplan Continued graphical data interaction and display 19 Tao Zhao, Tengfei Lin, Yin Zhang

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 8 Q-compensation internal to migration Bin Lyu Wavelet based Radon transforms Tengfei Lin

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 Red. Fork 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 9 • May have lost champion at Chevron (John Best) for “time lapse survey”

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

AASPI 2016 Workplan Seismic geomorphology • Have license to large 3 D data volumes from New Zealand Australia – contains volcanic intrusives, turbidites, FLTs – Lennon Infante and multiple geology students • Will acquire licenses to large 3 D volumes from Australia – carbonate banks, buildups, dewatering, … Brad Wallet and multiple geology students Salt segmentation • Finalizing license with PGS to 3600 mi 2 from GOM shelf – Jie Qi and multiple geology students Attributes from 2 D vs. 3 D surveys • 11 2 D and 3 D data from New Zealand - Bryce Hutchinson

AASPI 2016 Workplan Seismic data processing • Legacy data from Central Basin Platform (CP) – Thang Ha and Gabriel Machado • Perpendicular 3 D 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 12

AASPI 2016 Workplan Suggestions from the floor? 13