Multi-Volume Attributes

Multi-Volume Attributes (MVA) is a module for quantitative interpretation teams and oil companies interested in unconventional and 4D applications. MVA ensures reliability of inversion outcomes to avoid inconsistent near and far partial stacks that may render the outcomes of AVO inversion unreliable.

Determine Consistency Between Data Volumes

Multi-Volume Attributes

MVA determines reliability of inputs to 2D and 4D inversions to establish if two sample data volumes are similar by:

  • Far and mid stacks for AVO inversions
  • Monitor and Base in 4D analyses

 Key features include two attribute measures that are sensitive to noise, amplitude, static and phase differences between the input volumes.

From a cross-plot of Correlation and NRMS, we have two attributes: Quality and Anomaly.

Quality Attribute

  • Sensitive to Noise

Anomaly Attribute

  • Sensitive to amplitude differences
  • Sensitive to static differences
  • Sensitive to phase differences
Quality and Anomaly attributes obtained from comparing migrated seismic to AVO synthetics. The comparison was done for three different migration methods. Quality and Anomaly are more independent parameters than correlation and NRMS.

Multi-Volume Attributes Applications

Multi-Volume Attributes enables key QC steps:

  • QC of partial offset or angle stacks being considered for AVO inversion. MVA helps determine if near and far stacks contain consistent information.
  • 4D QC: Compare Base and Monitors for consistency.

Coleou, T., et al., 2013, AVO QC During Processing, 75th EAGE Conference & Exhibition Abstracts

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