Title : Seismic data conditioning is an essential step for facies prediction.
Abstract:
To take full advantage of AVO (amplitude versus offset) inversion techniques seismic data needs to be carefully conditioned so that any variation in amplitude is solely the result of reflection-coefficient changes and not seismic processing artefacts (Chopra and Castagna 2014). AVO gradient in particular is highly influenced by far offset amplitudes, yet provides a key control on the output of Vp/Vs and thereby significantly influences fluid and lithology prediction. Data conditioning routines are therefore focused on the preservation of the AVO gradient, with each seismic dataset and each specific reservoir interval typically requiring a unique optimisation approach. Over-corrected and under-corrected seismic velocities, incorrect multiple removal parameters, improper migration and poor angle stack range selection can all cause significant distortion of AVO signatures on pre-stack seismic gathers. However, with a targeted seismic data conditioning (SDC) workflow these undesirable effects can be minimised and corrected allowing noise to be subtracted without impacting primary AVO signals. Post-stack noise that has not been removed by pre-stack SDC techniques must also be subtracted by routines that do not damage AVO signatures. In this paper, we summarise the specific SDC steps required for marine seismic data and demonstrate them on a regional, multisurvey, North Sea, seismic dataset via the application of facies based inversion (Kemper and Gunning 2014). Method and/or Theory.
Audience Takeaway Notes:
- Detailed workflow explains how to extract additional value from the seismic data.
- Highlight importance of seismic dada quality in relation to prediction of petrophysical properties.
- Audience can learn the importance of careful conditioning of seismic data, particularly for amplitude versus offset (AVO) inversion techniques
- The introduction outlines specific steps involved in seismic data conditioning (SDC) workflows, emphasizing the significance of preserving AVO gradients for accurate fluid and lithology prediction. Additionally, it highlights common challenges such as improper migration and poor angle stack range selection that can distort AVO signatures, stressing the need for targeted SDC techniques to minimize undesirable effects. Overall, readers gain insights into the critical role of SDC in enhancing the quality and reliability of seismic data for interpretation and exploration purposes.
