Subtle Stratigraphic Trap
Learning objectives
- Model a pinch-out trap and image it two ways
- See convolution fade the edge without locating it
- See the edge diffraction localise the pinch-out tip
- Justify the wave equation when the edge carries the trap
The Brief
The second capstone flips the first. A prospect hinges on a thin reservoir sand that pinches out updip against a seal. The trap is precisely the pinch-out edge, and the only question that matters is where the sand ends. Model it and image it.
The Build
The model is a wedge that thins to zero at the tip. Convolution renders it instantly: the top and base reflections tune together as the bed thins, then fade where it vanishes. The result is clean, and quietly misleading. The fade tells you the bed is thinning but not exactly where it ends, and the trap is exactly there.
The full-physics panel adds what convolution structurally cannot: an edge diffraction radiating from the pinch-out tip. It is not noise. Its apex sits directly over the tip, so it localises the edge the convolutional fade left vague. A migration would collapse that hyperbola back to a point and pin the pinch-out exactly.
The Debrief
Which engine? The wave equation. Here convolution does not merely cost less; it is wrong by omission, dropping the one feature, the tip diffraction, that carries the trap. A subtle stratigraphic trap lives in exactly the edge physics convolution cannot produce, so a diffraction-aware, wave-equation workflow is not optional.
Set beside the fault capstone, this is the whole thesis in two panels. Identical course, identical tools, opposite verdict, and the difference is only whether your question lives in the geometry convolution keeps or the physics it drops. The next capstone leaves acoustic imaging entirely and takes on a fractured carbonate, where the rock-physics chain of Part 8 is the right tool.