Seismic Data Conditioning

To ensure a successful QI study we offer a full suite of seismic data conditioning tools to improve the quality of the input seismic data. These include various noise suppression techniques and other processes to get the data into a state that is suitable for inversion. Our seismic conditioning algorithms and our QC products are developed in-house specifically for AVO inversion applications. All of our techniques pay particular attention to amplitude and wavelet shape preservation during conditioning.

Seismic CDP gathers conditioning

  • Radon de-multiple
  • Residual moveout correction (RMO)
  • Offset gathers to angle stacks

Seismic angle stack conditioning

  • Q-compensation
  • Residual noise suppression
  • Zero-phase filter
  • Seismic alignment (including 3D alignment)
  • Spectral whitening
  • Spectral balancing
  • Other suggestions as deemed valuable

Qeye's Seismic Warping

Seismic warping or alignment is an essential tool within the seismic quantitative interpretation workflow.

Applications include:

  • angle stack warping suppresses seismic event misalignment originating from inaccurate velocity modeling or migration (Figure 1)
  • 4D warping estimates time shifts that arise from velocity changes due to production and/or compaction (Figures 2 to 5)
  • 4D warping suppresses lateral positioning errors associated with velocity changes and migration across structural features (Figure 4)
  • 4D warping is essential to estimate the geomechanical effects within and around the reservoir arising from hydrocarbon production

Our warping algorithm has the following key features:

  • 1D and 3D warping with optional geological dip constraints
  • displacement cube is optimized both locally and globally
  • amplitude preserving – making it suitable for AVO inversion
  • the computed displacement field can be used as a constraint in the 4D inversion
Figure 1: Angle stack alignment using QeyeWarp.
Figure 2: 4D warping to account for traveltime differences due to production.
Figure 3: Time displacement field computed for a compacting reservoir. Note the time displacement associated with the stretching of the overburden.
Figure 4: In-line displacement field computed for a compacting reservoir. The in-line displacement is the result of lateral positioning errors associated with velocity changes and migration across the structure.
Figure 5: X-line displacement field computed for a compacting reservoir.
Figure 7: Amplitude difference between vintages after warping.
Figure 6: Amplitude difference between vintages before warping.