Day 2 of the SEG Annual Meeting brought another 93 talks in the morning, and 103 in the afternoon, leaving us bewildered again: how to choose ten or so talks to see? (We have some ideas on this, more of which another day). Matt tried just sitting through a single session (well, almost), whereas Evan adopted the migrant approach again. These are our picks, just for you.
Stewart Trickett, Kelman
There has never been a dull or difficult talk from Stewart, one of Calgary's smartest and most thoughtful programmer–processors. He has recently addressed the hot-topic of 5D interpolation, a powerful process for making the dream of cheap, dense sampling a reality. Today, he explained why we need to now think about optimizing acquisition not for imaging, but for interpolation. And interpolation really likes pseudorandom sampling, because it helps negotiate the terms & conditions of Nyquist and avoid spatial aliasing. He went on to show a 3D subsampled then imaged three ways: remove every other shot line, remove every other shot, or remove a random shot from every pair of shots. All reduce the fold to 12% of the full data. The result: pseudorandom sampling wins every time. But don't panic, the difference in the migrated images was much smaller than in the structure stacks.
Gaynor Payton, ffA
In what could have been a product-focused marketing talk, Gaynor did a good job of outlining five easy-to-follow, practical workflows for interpreters working on thin beds. She showed frequency- and phase-based methods that exploit near-tuning, unresolved doublets in the waveform. A nice-looking bandwidth enhancement result was followed up with ffA's new high-resolution spectral decomposition we covered recently. Then she showed how negative spikes in instantaneous frequency can reveal subtle doublets in the waveform. This was extended with a skeletonized image, a sort of band-limited reflectivity display. Finally, she showed an interesting display of signed trace slope, which seemed to reveal the extent of just-resolved doublets quite nicely.
Scott Mackay, consultant
Scott MacKay shared some of his deep experience with depth imaging, but specially translated for interpreters. And this is only right: depth imaging is first and foremost an interpretive, iterative process, not a product. He gave some basic heuristics, guiding principles for interpreters. The first velocity model should be smooth—really smooth. Iterations should be only incrementally less smooth, 'creeping up' on the solution. Structure should get less, not more, complex with each step. Gathers should be flattish, not flat. Be patient, and let the data speak. And above all, Don't Panic. Always good advice.