--> Abstract: Introducing A Priori Information in Non-Linear Slope Tomography: An Application to Minagish Seismic Survey, by Patrice Guillaume, Diego Carotti, Abdul Latif Al-Kandari, Nicolas Deladerriere, Adel H. El-Emam, Gilles Lambaré, Pierre Mitouard, Jean-Philippe Montel, Antony Prescott, Jean-Paul Touré, and Xiaoming Zhang; #90105 (2010)
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AAPG GEO 2010 Middle East
Geoscience Conference & Exhibition
Innovative Geoscience Solutions – Meeting Hydrocarbon Demand in Changing Times
March 7-10, 2010 – Manama, Bahrain

Introducing A Priori Information in Non-Linear Slope Tomography: An Application to Minagish Seismic Survey

Patrice Guillaume1; Diego Carotti2; Abdul Latif Al-Kandari3; Nicolas Deladerriere1; Adel H. El-Emam4; Previous HitGillesNext Hit Previous HitLambaréTop1; Pierre Mitouard2; Jean-Philippe Montel1; Antony Prescott1; Jean-Paul Touré1; Xiaoming Zhang1

(1) Imaging and Processing R&D, CGGVeritas, Massy, France.

(2) Imaging & Processing, CGGVeritas, Massy, France.

(3) Research & Technology Subsurface, Kuwait Oil Company, Kuwait, Kuwait.

(4) Exploration Group, Kuwait Oil Company, Kuwait, Kuwait.

Slope tomography allows velocity model estimation from locally coherent events. These events can be picked in the migrated prestack depth or time domains, and then de-migrated into the observation space-time domain, providing us with kinematic invariant data. When locally coherent events are picked directly in the observation space-time domain, the kinematic invariants carry the exact acquisition geometry.

Kinematic invariants describe locally coherent events by their position and slopes in the un-migrated prestack time domain. Non-linear 3D slope tomography based on the concept of kinematic invariants provides a powerful tool for velocity model building. Several iterations of residual move-out (RMO) picking, prestack depth migration and velocity updates are avoided, unlike conventional approaches based on a linear update where residual depth errors have to be re-picked several times.

Because kinematic invariants do not relate to a particular depth velocity model, a priori information can be easily inserted into the initial tomography velocity model to assess different geological assumptions.

This capability is illustrated on land Minagish dataset in Kuwait for which RMO has been picked from prestack time migrated gathers. Tomography and imaging results have been produced for two different a priori velocity models. A first model was built by 1D Dix inversion of time migration velocities while the second model was built using velocity information from wells. The updated “wells” model successfully combines two velocity components: the a priori high vertical resolution component that cannot be resolved by tomography and a lower vertical resolution component that maximizes the stack power of the depth migrated seismic data.