The tomography algorithm within TGS’ ImageZ™ depth imaging software suite implements a high-resolution grid-based approach to tomography.

The algorithm implements automatic reflection patch picking and residual moveout picking. The tomography system is solved on multiple nodes in parallel. The user may also supply information to mask out zones where the input dip fields and residual moveout curvatures will not be used or the velocity will not be updated. The velocity update in the masked-out zones can be interpolated or extrapolated using geological horizons as guides or using a statistical Kriging method. All the inputs to tomography are QC’d prior to the run. The algorithm supports single or multiazimuth ray tracing and may be used in either a full-azimuth or azimuth-sector mode.

High-resolution tomographic inversion with image-guided preconditioning and offset-dependent picking: 84th Annual International Meeting, SEG, Expanded Abstracts, 4768-4772, Hilburn, Guy, Yang He, Zengjia Yan and Francis Sherrill, 2014.

Concepts of Tomography – Moveout PickingConcepts of Tomography – Moveout Picking

  • Residual moveout (RMO) refers to the vertical displacement of an event in a migrated offset gather, relative to its depth at zero offset.
  • Perfectly flat events, with no RMO, suggest that the average velocity for that event is correct.
  • TGS generally uses two types of moveout picking:
  • Curvature-based (hyperbolic) picking uses a formula to describe a pick by one parameter, which is ideal for simple cases.
    • z2 – z02 = C*offset2
  • Offset-dependent picking is nonparabolic, so its picks may take any shape, allowing for complete generality.

Concepts of Tomography – Ray Tracing


  • Ray tracing is used to determine the paths taken by energy which forms a gather event.
  • Dip information is used to find the correct incident and reflected angles.
  • Each offset bin is considered for ray tracing, to build a fan of rays for each event.

Concepts of Tomography – Inversion

concepts of tomo

  • The ray tracing results are input to an inversion code.
  • The inversion calculates the total travel time for each ray, from its path through the model.
  • Then, based on the travel time error calculated from the RMO depth error, each ray’s required velocity update is projected along its path.
  • The ray paths will heavily overlap each other, effectively averaging out the update for all events.
  • Further smoothing or preconditioning is applied to the update, and then the process iterates until converged.

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