Seismic Data Processing

Seismic Series
By OgbonLab

Raw shot gathers in, migrated image out. The path in between, finally explained.

From raw shot gathers to migrated image: signal processing, imaging, FWI, QI, and 4D, with a full math primer in Part 0.

13 parts 82 sections Free, browser-native
Start reading → First up: What math do we need?

Table of contents

Every section is a working session: text, math, code, interactive widgets. Click any title to jump in.

Part 1: Part 0: Processing Prerequisites

  1. What math do we need?
  2. Complex numbers & phasors
  3. Convolution from scratch
  4. The Fourier transform, slowly
  5. Sampling & aliasing
  6. Z-transform & filter theory
  7. Linear algebra primer
  8. Random variables & noise
  9. Optimization basics
  10. Wave equation in 30 minutes

Part 2: Part 1: Acquisition & the data we process

Part 3: Part 2: Pre-Processing Foundations

  1. Reformatting & geometry QC
  2. Trace editing & amplitude recovery
  3. Refraction & tomographic statics
  4. Residual statics & surface-consistent decomposition
  5. Noise attenuation suite
  6. Spiking deconvolution (Wiener filtering)
  7. Predictive deconvolution
  8. Surface-consistent deconvolution
  9. Bandwidth & spectral QC

Part 4: Part 3: Velocity Analysis & NMO

Part 5: Part 4: Multiple Attenuation

  1. Multiple classification
  2. Surface-related multiple elimination (SRME)
  3. Radon demultiple
  4. Adaptive subtraction
  5. Inter-bed multiples & model-based prediction

Part 6: Part 5: Imaging (migration)

Part 7: Part 6: Full-Waveform Inversion

  1. The inverse problem, mathematically
  2. FWI in practice: low-frequency strategies
  3. Encoded FWI & computational strategies
  4. Elastic and anisotropic FWI
  5. FWI QC: synthetic-vs-recorded matching

Part 8: Part 7: Processing for QI

  1. AVO-preserving processing
  2. True-amplitude migration
  3. Q-compensated imaging
  4. Near-offset conditioning for inversion
  5. Pre-stack gathers for simultaneous inversion

Part 9: Part 8: Time-Lapse (4D) Processing

Part 10: Part 9: Machine Learning in Processing

  1. ML in processing: where it fits
  2. Denoising with CNNs
  3. Interpolation / reconstruction
  4. ML-assisted first-break picking
  5. ML for FWI gradient acceleration

Part 11: Part 10: Processing Capstones

  1. Capstone: Land vibroseis through a weathered layer
  2. Capstone: OBN deep-water imaging in salt
  3. Capstone: Marine WAZ FWI project
  4. Capstone: CO₂ sequestration, Sleipner revisited
  5. Capstone: Ultra-high-frequency near-surface imaging
  6. Capstone: 4D repeatability challenge

Part 12: Part 11: Self-Assessment Quizzes

  1. Quiz: Part 0: Math prerequisites
  2. Quiz: Part 1: Acquisition
  3. Quiz: Part 2: Pre-processing
  4. Quiz: Part 3: Velocity & NMO
  5. Quiz: Part 4: Multiples
  6. Quiz: Part 5: Imaging
  7. Quiz: Part 6: FWI
  8. Quiz: Part 7: Processing for QI
  9. Quiz: Part 8: 4D
  10. Quiz: Part 9: ML
  11. Quiz: Part 10: Capstones
  12. Final Exam, 50-question integrated assessment

Part 13: Part 12: Processing Workflow Reference Card

  1. Master workflow: click a step, jump to its chapter

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