Breathing New Life into Vintage Land Seismic Surveys with Next-Generation FWI

Acquired across multiple surveys in the 1990s, the data lacks low frequencies, long offsets, and is sparse. Further complications arise due to the topography and near surface effects. The input data for FWI was minimally preprocessed - denoising and wavelet consistency. S-Cube applied its proprietary Adaptive Waveform Inversion (AWI) and Reflection Waveform Inversion (RWI) workflow to refine the model to 20Hz. Unlike conventional FWI, AWI overcomes cycle skipping, is more sensitive to reflection moveout, and is less impacted by amplitude mismatches. RWI further strengthens the velocity update by focusing on reflection kinematics, working effectively even with multiples and ghosts.

Before/AfterPredicted seismic data generated from our final FWI model, showing a close match to the field data.

Proprietary AWI and RWI Workflow

S-Cube then applied its proprietary Adaptive Waveform Inversion (AWI) and Reflection Waveform Inversion (RWI) workflow to refine the model to 20Hz. Unlike conventional FWI, AWI overcomes cycle skipping, is more sensitive to reflection moveout, and is less impacted by amplitude mismatches. RWI further strengthened the velocity update by focusing on reflection kinematics, working effectively even with multiples and ghosts.

Before/AfterS-Cube's 20Hz XWI FWI Velocity Model

Unlocking New Potential in Old Surveys

The resulting 45Hz Reverse Time Migration (RTM) image is structurally simpler, sharper, and far superior to the legacy migration - reducing noise, improving focus, and enhancing subsurface clarity. Remarkably, these results were achieved on surveys acquired over 25 years ago, proving that S-Cube’s next-generation FWI workflow can breathe new life into vintage datasets once considered unsuitable for inversion.

Before/AfterThe final RTM image shows significant uplift in focus and structural clarity over the legacy PSDM.

Even with non-ideal acquisition, our workflow delivers high-resolution seismic images that increase confidence in interpretation and unlocks new exploration opportunities.