Capstone: Land vibroseis through a weathered layer

Part 10 turns the techniques of Parts 0 to 9 into projects. Each capstone runs one project archetype from raw data to deliverable, shows which stages are critical and which are routine, and links every stage to the section that teaches it. Here you run a land flow stage by stage on a synthetic line: watch the weathered layer scramble the CMP gather, then watch the stack come back into focus as each correction is applied.

Project setup

A 2D land survey over Mesozoic carbonate targets under a variable weathered layer, 30 to 50 m thick, with velocities from 300 to 1000 m/s from place to place. Vibroseis source, 12 s sweep, 10 to 80 Hz; a 240-channel spread with a 25 m group interval. The weathered layer introduces shot-to-shot static differences of up to ±15 ms, more than half a wavelet period ($T/2 = 12.5$ ms) at the 40 Hz target frequency. Without a good near-surface correction the stack is incoherent, and no migration will save it.

The pipeline

As recorded, the figure's strongest reflection stacks at only 27 % of the perfectly corrected stack: the traces sit 7.7 ms RMS from their stack, a 111° phase error at 40 Hz, so part of every reflection cancels. After the full flow the same reflection stacks at 96 %, with the traces within 0.3 ms RMS of their stack. Then leave out refraction statics, the first stage marked critical, and compare the stack in (d): residual statics measure lags by correlation, and a lag of more than half a period locks onto the wrong cycle.

Why refraction statics is the central step

In marine processing the near surface is the water column: it is uniform and predictable, and its statics are negligible. On land the near surface is whatever soil, regolith, weathered bedrock and water table lies under each shot and receiver. Static shifts of 10 to 30 ms are routine, and they destroy stack coherence because neighbouring traces arrive at different times. The solution is to pick first breaks (ML-assisted, Section 9.4), invert them with refraction tomography (Section 2.3) for a near-surface velocity model, and shift each trace by the static that replaces the weathered layer with a uniform replacement velocity: $\\Delta t = h\_w\\,(1/V\_w - 1/V\_r)$ for each leg through a layer of thickness $h\_w$ and velocity $V\_w$, with replacement velocity $V\_r$. Get this step right and the stack snaps into focus; get it wrong and nothing downstream works.

Surface-consistent deconvolution and amplitude balancing

The weathered layer distorts the wavelet differently at each shot and receiver position. Surface-consistent deconvolution (Sections 2.4 and 2.8) decomposes the log-spectra of the traces into shot, receiver, offset and CMP terms and removes the shot and receiver terms, which the near surface caused. The CMP term, which carries the geology, stays. Without this step, AVO and post-stack amplitudes reflect the weathering, not the structure.

What this project does not get

• Depth migration. Post-stack time migration is adequate: lateral velocity variation below the weathered layer is moderate, so PSDM would be overkill.
• FWI. The sweep starts at 10 Hz, so the low frequencies FWI needs to avoid cycle skipping are missing, and the elastic near surface (ground roll, mode conversions) defeats acoustic FWI. Tomography and post-stack migration are the production standard.
• Full QI. Post-stack structural imaging is the primary deliverable. AVO analysis is advisory only, because imperfect surface-consistent amplitude correction leaves residual amplitude biases.
• 4D. The weathered layer changes between repeat surveys; NRMS under the reservoir is typically 40 to 50 %, not 4D grade.

Where this goes next

Section 10.2 contrasts this with a deep-water OBN project. The near-surface problem goes away; the sub-salt imaging problem takes its place.

References

• Yilmaz, Ö. (2001). Seismic Data Analysis (2 vols.). SEG.
• Sheriff, R. E., Geldart, L. P. (1995). Exploration Seismology (2nd ed.). Cambridge UP.
• Robinson, E. A., Treitel, S. (2008). Digital Imaging and Deconvolution. SEG.
• Claerbout, J. F. (1976). Fundamentals of Geophysical Data Processing. McGraw-Hill.