Offset-Dependent Picking

When Common Image Gathers (CIGs) display moveout which coincides with low order polynomial terms, polynomial-based RMO picking may effectively describe the smooth curvature

In situations where the curvature is complex, the polynomial assumption may often be inaccurate.

Complicated areas, such as those with high anisotropy, or showing heavy faulting, will often yield events with multiple turning points, which may actually be made worse by polynomial-based flattening.

In TGS offset-dependent picking method, the RMO is represented as continuous displacement field rather than as a series of discrete events. A multiscale, constrained solver is used to estimate the displacement field for each CIG. The principle constrain is that the gradient if the displacement field (g) is less than some tolerance (T), where T is less than 1 (Hale, 2013)

The constraint prevents crossing events, and also waveform distortion caused by excessive stretching and squeezing. The events with maximum coherency are then computed from the derived displacement field. Th advantage of this approach is that the computed events will be more consistent than the if each event is estimated independently.

Source: TaejongKim*, FrancisSherrill, GuyHilburn, YangHe, and CristinaReta-Tang (2014) A case study: Improved imaging beneath the Cotton Valley formation through offset-dependent RMO picking and high-resolution tomography in the Lloyd Ridge area in the Gulf of Mexico. SEG Technical Program Expanded Abstracts 2014: pp. 4723-4727.

Red curves: single-parameter picks
Green curves: offset-dependent picks
 

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offset dependent
Orion Stack Image – After offset-dependent picking Update
offset
Orion Stack Image – after Hyperbolic-picking Update


Gulf of Mexico data highlighting the Cotton Valley Formation

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offset after
Orion Stack Image – After offset-dependent picking Update
hyperbolic picking
Orion Stack Image – after Hyperbolic-picking Update
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