Data Conditioning

For Optimized QI and Reservoir Characterization

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Seismic data pre-conditioning is an essential foundation for any quantitative seismic interpretation or reservoir characterization project that relies upon pre-stack seismic inversion technology.
  • Input data are optimized for the pre-stack seismic inversion: gathers are flat, denoised and match expected AVO behavior (when well logs are available)
  • Stack responses will be improved
  • More accurate AVO attribute analysis from common image-gathers
  • Seismic inversion results are more robust and reliable

PGS uses a tailored processing sequence called the reservoir-oriented processing (ResOP) workflow to remove noise, enhance amplitude and bandwidth, and optimize event alignment. Both pre-stack and post-stack data conditioning processes are possible. The pre-stack process tends to be more time-consuming but more advanced and accurate.

Flexible Workflows for Optimal Data Preconditioning

Workflows are highly customizable however, there are some common steps

  • Improved gather flattening
  • Enhanced demultiple
  • Angle-dependent resolution enhancement
  • Zero phasing
  • Angle stack generation
  • Post-stack data conditioning


The improved gather flattening step is used for dense velocity picking and trim statics. An optimized velocity model is computed to improve gather flatness and serve as the reference velocity for both building the low-frequency model and for performing the depth conversion step

Angle-dependent resolution enhancement, including wavelet destretch | This can be beneficial to compensate for energy loss due to the propagation of energy through the earth, especially where the wavelet shape is significantly changed due to the attenuation of the higher-frequency energy. Residual trim statics corrections are often required when the velocity-driven NMO corrections are unable to flatten CDP gathers completely. Hence, the need for an additional process post imaging and dense velocity picking. The wavelet-destretching workflow attempts to minimize the NMO-related stretch that strongly affects stack response and AVO / AVA analysis, particularly at large angles of incidence. Post-stack matching may be used as an alternative or supplement to wavelet destretch.

A multi-dimensional cross-equalization algorithm (PGS Simile) computes 3D or 4D matching operators. These operators are based on the estimation of the individual coherent seismic signal while disregarding any uncorrelated noise content. Multi-signal matching is a key technique in time-lapse / angle stacks processing for calibrating the different vintages/angles

In the zero phasing step, the well-to-seismic tie between the synthetic seismogram and the stacked seismic data will be used to extract the wavelet and to generate a filter to convert the data to zero-phase.

In angle stack generation, some angle stacks are generated after the preconditioning steps using the stacking velocity. Great care is taken at this time between the well modeling and the seismic response. Critical interactions between the imaging and QI teams ensure the optimization of the angle stacking process.

In post-stack data conditioning, post-stack alignment may be used as an alternative or in addition to the pre-stack trim statics application to correct residual misalignment between the angle stacks. Structurally oriented filtering (SOF) is used to remove noise in a manner that preserves geological information. Alternatively, structurally conformable filtering offers additional scope for frequency-dependent parameterization in the workflow.

Gradient before ResOP
Gradient after ResOP

A tailored and state-of-the-art seismic data conditioning workflow has been applied to this dataset revealing the anomaly of interest in the middle of the seismic section.

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