Case Studies
Features
Webinars
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High Resolution Seismic Conditioning
Mean Seismic Conditioning
Fault Interpretation
Horizon Interpretation
Structure-Oriented Seismic Conditioning
Paleo-Channels Detection
Salt Bodies Delineation
Resolving Sub-Salt Strata on Groningen Field
Improving Faults Imaging on Opunake 3D Data
Improving Seismic Data Quality on Waka Field
Delineation of Salt Bodies
Automatic Horizon Interpretation
Automatic Fault Tracking
Paleo Channels Discovery
Seismic Facies Identification
Problematics
Approach
Results
Tools
Business Effect

Identifying seismic facies is essential for transitioning from seismic images to field geology. This process enables the interpretation of depositional zones, sediment transport pathways, and the evolution of sedimentary basins—often long before drilling commences.


Qualitative seismostratigraphic analysis provides rapid identification of geobodies and seismic facies.

However, like any visual method, it has a number of limitations:

Problematics
Simplifications of the 3D complex
datasets the capabilities of human perception
Reduced reliability of interpretation results
due to strong human bias
Significant time investment
(up to months) for manual horizon picking
Our technology based on neural network algorithms provides automatic identification of seismic complexes across the entire data volume with minimal interpreter intervention, immediately forming ready-made seismic facies boundaries.

This approach integrates the interpreter's expert vision and regional expertise directly into the model.
Approach
Calculation speed
From several hours to 2-3 days
Required parameter setting
1 or 2 parameters only per procedure
Required input data
  • Stacked seismic data of any quality;
  • Manual seismic facies picks on 2-5 sections of the volume
Results
Results extraction
into standard data formats for further interpretation in different software
Extrapolation of forecast results
to adjacent territories with a similar geological structure
Semi-automatic classification
of seismic facies in 3D volume
Extracted geobodies boundaries as horizons
3D seismic facies volume
Tools
Model adaptation with expert control
Reproducing the result for processing check-up by interpretation team
Quick classification of seismic facies in 3D
Seismic facies identification requires original seismic data and manual picking of their borders on 2-5 sections. That will allow to extrapolate the approach to the whole dataset.
Manual picking of several sections instead of the whole volume
Go to Case Studies
Business Effect
Reducing drilling risks
Up to 90% using mapping areas of high fracturing and geological heterogeneity in advance
Increasing Oil Recovery Factor
by accurately accounting for the impact of faults on hydrodynamics in productive reservoirs
Improving Structural Model
by transitioning to objective and full mapping of faults
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