Fit-for-Purpose Reference Card
Learning objectives
- Consult a task-to-engine decision table
- Recall the verdict and reason for each task
- Weigh engine cost against the physics required
- Carry the course distilled to one decision
The Course in One Table
If you remember one thing from this course, make it this: given the question, which engine? Every part and every capstone was, underneath, an instance of that single decision. This section collects them all into a reference card. Pick a task and the recommended engine, the reason, and the relative cost appear; the full matrix sits below for scanning.
One Rule, Down Every Row
The card looks like a lookup table, but it is really a single principle applied nine times: use the cheapest engine that carries the physics your question depends on, and no more. Convolution for geometry, the wave equation for edge and multiple physics, elastic modelling for fluids, azimuthal anisotropy for fractures, a velocity model for time-to-depth. When two engines both answer the question, take the cheaper one; reach up the ladder only when the answer lives in physics the simpler engine drops.
That is what separates a modeller from someone who merely runs software. Anyone can launch the most complete engine and wait; the skill is knowing when you do not need it, and when the simple answer is quietly wrong. Keep this card. The next section takes the heavier engines off the browser entirely, handing the model you built in the Lab to a Python runtime that can run the full wave equation for real.