Geoscientist Artificial Intelligence

Geoscientist Artificial IntelligenceGeoscientist Artificial IntelligenceGeoscientist Artificial Intelligence

Geoscientist Artificial Intelligence

Geoscientist Artificial IntelligenceGeoscientist Artificial IntelligenceGeoscientist Artificial Intelligence
  • Home
  • AI Signal Processing
    • Deconvolution
    • Inverse Q Filtering
    • Noise Attenuation
    • Multiple Attenuation
  • AI Imaging
    • Velocity & NMO Analysis
    • Anisotropy Analysis
    • Time to Depth Convrsion
    • Residual Moveout
    • Tomographic Inversion
    • Stacking
    • Migration
    • Wave Equation Datuming
  • AI Inversion
    • Deterministic
    • Stochastic
    • Elastic
    • Petrophysical
    • Time-Lapse (4D)
    • Machine Learning
  • AI AVO Analysis
    • AVO Classification
    • AVO Inversion
    • Rock Physics Modeling
    • AVO Attributes
    • Multi-Component Analysis
    • Calibration & Validation
  • AI Depth Conversion
    • Time-Depth Relationships
    • Well Log Integration
    • Seismic Interpretation
    • Uncertainty Analysis
    • Advanced Computaion Tech
  • AI Data Integration
    • Gravity and Magnetic Data
    • Electromagnetic (EM)
    • Advaned Data Fusion
  • AI FWI
    • Modeling and Simulation
    • Regularized & Constraints
    • Model Parameterization
    • Other Data Integration
    • Anisotropy & Attenuation
  • More
    • Home
    • AI Signal Processing
      • Deconvolution
      • Inverse Q Filtering
      • Noise Attenuation
      • Multiple Attenuation
    • AI Imaging
      • Velocity & NMO Analysis
      • Anisotropy Analysis
      • Time to Depth Convrsion
      • Residual Moveout
      • Tomographic Inversion
      • Stacking
      • Migration
      • Wave Equation Datuming
    • AI Inversion
      • Deterministic
      • Stochastic
      • Elastic
      • Petrophysical
      • Time-Lapse (4D)
      • Machine Learning
    • AI AVO Analysis
      • AVO Classification
      • AVO Inversion
      • Rock Physics Modeling
      • AVO Attributes
      • Multi-Component Analysis
      • Calibration & Validation
    • AI Depth Conversion
      • Time-Depth Relationships
      • Well Log Integration
      • Seismic Interpretation
      • Uncertainty Analysis
      • Advanced Computaion Tech
    • AI Data Integration
      • Gravity and Magnetic Data
      • Electromagnetic (EM)
      • Advaned Data Fusion
    • AI FWI
      • Modeling and Simulation
      • Regularized & Constraints
      • Model Parameterization
      • Other Data Integration
      • Anisotropy & Attenuation
  • Home
  • AI Signal Processing
    • Deconvolution
    • Inverse Q Filtering
    • Noise Attenuation
    • Multiple Attenuation
  • AI Imaging
    • Velocity & NMO Analysis
    • Anisotropy Analysis
    • Time to Depth Convrsion
    • Residual Moveout
    • Tomographic Inversion
    • Stacking
    • Migration
    • Wave Equation Datuming
  • AI Inversion
    • Deterministic
    • Stochastic
    • Elastic
    • Petrophysical
    • Time-Lapse (4D)
    • Machine Learning
  • AI AVO Analysis
    • AVO Classification
    • AVO Inversion
    • Rock Physics Modeling
    • AVO Attributes
    • Multi-Component Analysis
    • Calibration & Validation
  • AI Depth Conversion
    • Time-Depth Relationships
    • Well Log Integration
    • Seismic Interpretation
    • Uncertainty Analysis
    • Advanced Computaion Tech
  • AI Data Integration
    • Gravity and Magnetic Data
    • Electromagnetic (EM)
    • Advaned Data Fusion
  • AI FWI
    • Modeling and Simulation
    • Regularized & Constraints
    • Model Parameterization
    • Other Data Integration
    • Anisotropy & Attenuation

Seismic wave-equation datuming

Seismic wave-equation datuming is a process used to simulate the propagation of seismic data from one surface to another using wave-equation-based methods. It’s commonly applied to correct for topography, irregular acquisition geometry, or to flatten data to a common datum(e.g., from rough terrain to a flat surface) before migration or further processing. 


 Datuming means shifting seismic data from the original recording surface (like rough ground) to a new, often simpler surface (like a flat plane) while correctly accounting for the effects of wave travel (not just shifting times up or down like in simple static corrections). 


In general, datuming is the process of extrapolating recorded seismic data to a different reference surface. This can be:

  • Upward datuming (to simulate moving receivers/sources higher)
  • Downward datuming (to simulate moving receivers/sources closer to the target)

Conventional datuming (like static corrections) uses ray theory and assumes vertical rays, which can be inaccurate in complex geology.
Wave-equation datuming, however:

  • Handles complex wave propagation effects,
  • Preserves amplitudes and wavefront shapes,
  • Works better in areas with lateral velocity variation or steep dips.

How It Works – Step by Step

  1. Input

  • Seismic data recorded at an irregular surface (e.g., topographic or rugged acquisition surface),
  • Velocity model (usually near-surface or average velocity),
  • Source and/or receiver coordinates,
  • Target datum surface (often flat).

2. Define the Datum Surface

Choose the reference surface to which you want to move your sources/receivers  typically a flat horizontal surface.

3. Extrapolate Using the Wave Equation

Use one-way wave equation operators to propagate the wavefield from the original surface to the datum or in time domain, apply phase-shift, FD (finite-difference), or PSPI (phase-shift plus interpolation)methods to propagate the data. For downward datuming, simulate how data would look if receivers were at the datum surface.

  • Perform downward continuation to the datum level.

For upward datuming, simulate data recorded at a higher surface.

  • Perform upward continuation (which includes wavefield decay and spreading)

4. Repeat for All Traces

Apply the wave-equation datuming operator to every shot or trace to complete the extrapolation across the section.

5. Output

The output is a seismic dataset referenced to the new datum surface, ready for improved imaging or migration.

Applications

  • Preprocessing for migration (especially depth migration),
  • Land data with variable topography,
  • Removing irregular acquisition effects,
  • Flattening seabed in marine data,
  • Improving imaging in areas with velocity anomalies.

Seismic wave-equation datuming (WED)

WED on shot gather on flat target datum above surface

WED on shot gather on flat target datum bellow surface

WED on shot gather on arbitrary target datum above surface

WED on shot gather on arbitrary target datum bellow surface

Copyright © 2025 Geoscientist Artificial Intelligent - All Rights Reserved.

Powered by

This website uses cookies.

We use cookies to analyze website traffic and optimize your website experience. By accepting our use of cookies, your data will be aggregated with all other user data.

Accept