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    • Home
    • AI Signal Processing
      • Calibration & Validation
      • Deconvolution
      • Inverse Q Filtering
      • Noise Attenuation
      • Multiple Attenuation
      • Static Correction
    • AI Imaging
      • Velocity & NMO Analysis
      • Anisotropy Analysis
      • Time to Depth Convrsion
      • Stacking
      • Migration
      • Wave Equation Datuming
    • AI Q-Interpretation
      • AI INVERSION
      • AI AVO Analysis
      • Rock Physics Modeling
      • Seismic Attributes
      • Spectral Blending
    • AI Modeling
      • Ray Tracing
      • Waveform Modeling
    • AI Depth Conversion(Dvlp)
      • Multi-Component Analysis
      • Time-Depth Relationships
      • Well Log Integration
      • Uncertainty Analysis
      • Advanced Computaion Tech
    • AI Data Integration(Dvlp)
      • Gravity and Magnetic Data
      • Electromagnetic (EM)
      • Advaned Data Fusion
    • AI FWI(Dvlp)
      • Modeling and Simulation
      • Regularized & Constraints
      • Model Parameterization
      • Other Data Integration
      • Anisotropy & Attenuation
  • Home
  • AI Signal Processing
    • Calibration & Validation
    • Deconvolution
    • Inverse Q Filtering
    • Noise Attenuation
    • Multiple Attenuation
    • Static Correction
  • AI Imaging
    • Velocity & NMO Analysis
    • Anisotropy Analysis
    • Time to Depth Convrsion
    • Stacking
    • Migration
    • Wave Equation Datuming
  • AI Q-Interpretation
    • AI INVERSION
    • AI AVO Analysis
    • Rock Physics Modeling
    • Seismic Attributes
    • Spectral Blending
  • AI Modeling
    • Ray Tracing
    • Waveform Modeling
  • AI Depth Conversion(Dvlp)
    • Multi-Component Analysis
    • Time-Depth Relationships
    • Well Log Integration
    • Uncertainty Analysis
    • Advanced Computaion Tech
  • AI Data Integration(Dvlp)
    • Gravity and Magnetic Data
    • Electromagnetic (EM)
    • Advaned Data Fusion
  • AI FWI(Dvlp)
    • Modeling and Simulation
    • Regularized & Constraints
    • Model Parameterization
    • Other Data Integration
    • Anisotropy & Attenuation

Spectral blending

Spectral blending (often called RGB spectral decomposition) is a seismic visualization technique where different frequency components of the seismic signal are extracted (using spectral decomposition methods like Fourier, Wavelet, or S-transform) and then assigned to different color channels (Red, Green, Blue)in an image. This allows interpreters to see thin beds, channels, reefs, and stratigraphic details that are not visible in the broadband seismic data.

How It Works

Spectral blending specifically blends spectral decomposition results(e.g., 15 Hz, 30 Hz, 60 Hz) into a color composite.

⚙️ Detailed Workflow

       1. Spectral Decomposition 

  • Compute frequency-dependent amplitude volumes using methods like: 
    • Short-Time Fourier Transform (STFT)
    • Continuous Wavelet Transform (CWT)
    • Matching Pursuit Decomposition (MPD)
  • Result → amplitude cubes: A_15Hz, A_30Hz, A_60Hz

       2. Amplitude Normalization 

  • Normalize each frequency amplitude to a consistent dynamic range (e.g., 0–1 or percentile scaling).
  • Prevents one band from dominating visually.

       3. RGB Assignment 

  • R → Low frequency (e.g., 15 Hz)
  • G → Mid frequency (e.g., 30 Hz)
  • B → High frequency (e.g., 60 Hz)
  • RGB(x,z)=[A15​(x,z),A30​(x,z),A60​(x,z)]

        4. Blending 

  • Combine into a single color image.
  • Optionally overlay on amplitude or coherence section for context.

Implementation in Software

Most seismic interpretation platforms (e.g., Petrel, OpendTect, Kingdom, Geoteric) allow color blending via an RGB panel:

You can assign each attribute (or filtered frequency) to a color channel. Adjust the gain or stretch of each to balance intensity.

Optionally, use transparency or opacity blending to overlay on amplitude data.

Example setup:

RGB Channel   Attribute                    Description

========================================================= 

R                        Coherence                Faults and discontinuities

G                        Curvature                  Structural deformation

B                        Sweetness                (AVO) Lithologic variation or                   

                                                                  hydrocarbon indicator.

This composite allows simultaneous visualization of structure, stratigraphy, and lithology.

Geologic Meaning

Dominant Color   Frequency Band  Interpretation

=========================================================

Red                        Low (15 Hz)            Thick beds or broad features

Green                    Mid (30 Hz)            Intermediate bed thickness

Blue                       High (60 Hz)         Thin beds or sharp boundaries

Cyan/Magenta    Mixed                      Transition zones or                              

/Yellow/White                                        complex layering


🔹 Interpretation Uses

  • Channel delineation: channels often show strong color contrast due to frequency attenuation or tuning.
  • Thin-bed tuning detection: high-frequency dominance (blue) highlights tuned reflections.
  • Facies differentiation: lithologic changes alter dominant frequency response.
  • Hydrocarbon indicators: gas-charged sands often exhibit local spectral anomalies.

Spectral (RGB) blending

Frequency zone of Interest:

Low frequency zone: (6-25 Hz),    Mid frequency zone: (30-45 Hz),   High frequency zone:  (50-80 Hz)

Spectral (RGB) blending

Frequency zone of Interest:

Low frequency zone: (6-27 Hz),    Mid frequency zone: (30-48 Hz),   High frequency zone:  (50-80 Hz)

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