Seismic Attribute Analysis

attribute analysis bannerThe goal of seismic attribute analysis is to improve the spatial prediction of structural and stratigraphic features, as well as petrophysical and geomechanical rock properties throughout the reservoir. Key to the analysis is discovering the linear, and often non-linear, relationships between the seismic trace and production indicators.

Determining the Production Drivers

Seismic traces are composite responses to geological factors such as lithology, fluid saturations and geomechanical properties. Unraveling the influence each rock property has on the seismic trace and identifying a seismic attribute or combination of attributes which is capable of predicting that property is a mainstay of the CGG GeoConsulting reservoir characterization workflow.

Petrophysical rock property analysis from well logs and core/cuttings gives us insights into what is driving production in the reservoir. Forward modeling is then employed to identify key seismic attributes that distinguish these primary controls on production.

inverted-curve-dataKey Attributes Used in Interpretation

Seismic attributes are sensitive to lateral changes in geology so are utilized to assist in mapping facies, reservoir properties and faults.

  • Complex trace attributes help to interpret lateral continuity of stratigraphic events, bedding geometry, and the presence of hydrocarbon
  • Geometric attributes are used to characterize stratigraphic features and for fault/fracture detection
  • Time-Frequency attributes of Spectral Decomposition increase the seismic resolution to highlight lateral variability of depositional features and faults

Multi-Attribute Analysis for Rock Property Prediction

attributesIndividual seismic attributes give us indications of many subtle properties, however the real enhancement in predictive accuracy and reliability of results comes from combining multiple seismic attributes and solving the non-linear relationship between the seismic attributes and reservoir properties.
Multi-linear regression and neural network techniques are employed to determine which seismic attributes should be combined to predict a particular reservoir property.  Ultimately, 3D volumes of rock properties or other production indicators are generated.

The improved geologic interpretation and prediction of production indicators assist in the identification of preferential drilling locations and completion practices.

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Post-stack attribute-based fracture character...

Geoffrey Dorn | Joseph Dominguez
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Integrating surface seismic, microseismic, ro...

Gabino Castillo | Simon Voisey | Kevin Chesser | Norbert Van...
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