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Stacking — How It Works

Stacking — How It Works

Introduction

Stacking is one of the most fundamental steps in seismic processing. It improves signal‑to‑noise ratio by summing traces recorded at different offsets. The result is a cleaner, more coherent seismic section that forms the basis for interpretation.

This article explains what stacking is, why it works, and how it fits into the seismic processing workflow.

1. What Is Stacking?

Stacking combines multiple seismic traces that reflect from the same subsurface point. Because noise is random but signal is coherent, stacking enhances true reflections while suppressing noise.

Mathematically:

Stacked trace = sum of NMO‑corrected traces / number of traces

This produces a single, high‑quality trace for each subsurface location.

2. Why Stacking Matters

✔ Improved signal‑to‑noise ratio

Noise cancels out; signal reinforces.

✔ Cleaner seismic images

Reflectors become more continuous and easier to interpret.

✔ Better attribute quality

Attributes computed on stacked data are more reliable.

✔ Foundation for interpretation

Most interpreters work primarily with stacked sections.

3. The Stacking Workflow

A. NMO Correction

Normal Moveout correction aligns reflections across offsets.

B. Muting

Removes noisy far offsets or stretched samples.

C. Trace Weighting

Offsets may be weighted to balance contributions.

D. Stack Summation

Aligned traces are summed and averaged.

E. QC

Interpreters check:

  • Continuity

  • Amplitude behavior

  • Residual moveout

4. Types of Stacking

A. CMP Stacking

Common Midpoint stacking — the industry standard.

B. CRP Stacking

Common Reflection Point stacking — used in depth imaging.

C. Angle Stacking

Used for AVO and inversion workflows.

5. Challenges

  • Incorrect velocities

  • Poor NMO correction

  • Noise contamination

  • Stretching artifacts

  • Sparse offset coverage

Conclusion

Stacking is a simple yet powerful technique that enhances seismic data quality. By reinforcing coherent energy and suppressing noise, it produces clean seismic sections that support accurate interpretation and reservoir characterization.

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