South LouisianaTSL-FWI™
Highlander · Duck Lake merge · onshore Gulf CoastThe depth at the next well, before the next well
A follow-on exploration problem: one penetration at Highlander 1, a salt canopy, and an Austin Chalk target at 29,000 ft the legacy image could not resolve. Merging three surveys and inverting the minimally-processed field data, to see how far TSL-FWI™ could correct a conventionally-derived existing model with no additional well information.
- Austin Chalk target
- 30,000 ft
- Distance between wells
- 2 miles
- mistie correction
- 650 ft
- Well investment
- $300M
- 01
Data
Three datasets merged, minimally pre-processed.
- 02
Model
Macro then high-resolution TSL-FWI™ to 30,000 ft.
- 03
Imaging
FWI derived reflectivity
- 04
Blind tie
Over 600 ft correction in opposite directions at two wells
- 05
Prospect
The target surface, remapped.
Data-fitting for near surface refractions and deepest reflections
Three datasets shot years apart on different geometries, merged and inverted with almost nothing done to them in between. On land the weathering layer distorts every arrival under it, so the near surface is solved first — get it wrong and nothing deeper is worth updating.
- Minimally processed shots, filtered at 10 Hz
- TSL-FWI fitting refractions and reflections simultaneously, from the near surface down to 30 kft
Near surface · shot 803, field against prediction
The field record first, then the same shot predicted through the starting model and again after the near-surface update. The starting model reproduces little beyond the first arrivals; after the update the wavetrain behind them and the later events come through where the field has them.
The recorded shot — first arrivals, the wavetrain behind them and the later events the prediction has to reproduce.
Correcting an overshoot in the conventional model
TSL-FWI in macro mode corrects the overshoot, then TSL-FWI in targeted mode introduces high-resolution layering.
Vp in section · inline 177 & crossline 323



The same model in plan view


What the new model does to the image
Same data, same migration — only the velocity changed.


The image the prospect was carried on. Broken reflectors below the shallow section; both depth slices closer to noise than structure.
The inversion’s own reflectivity · inline 263 & crossline 216
The migration above is not the only image on offer. TSL-FWI solves for density as well as velocity, so it hands back a reflectivity of its own — no migration, no picked velocities, nothing after the inversion. Here it is at 10 Hz and again at 20 Hz: the structure is settled by the first frame and the second fills in the detail.


The density contrast the inversion resolved on its own at 10 Hz, displayed as reflectivity. The salt, the decollement and the Austin Chalk are all already there.
The model predicts the recorded shots
Field gathers against the wavefield modelled through the final model. Not a blind test — the well tie below is that — but it is where the model has to explain the recording event by event.
Shot 1044 · one shot, its receiver lines side by side





The recording. Eight receiver lines, zero to eight seconds.
TSL-FWI shifted the target 650 ft
Highlander 2 was drilled 3.3 km away and TSL-FWI corrected the pull up.
At Highlander 1 the pick falls in the gap between two events, and at Highlander 2 the chalk sits 650 ft above where the well found it. Between the wells the reflectors wobble and break up.
A purely data-driven velocity correction — free from human bias — that reliably predicts deep structure.
Four products off one inversion
Everything on this page comes out of one inversion of the merged field data.
Anisotropic TSL-FWI™ velocity
Vp to 9.5 km from the field shots, through the salt to the Austin Chalk. No picked horizons.
RTM on the final model
The operator's own migration, with only the velocity changed.
Like-for-like imaging comparison
Legacy PSDM against the new RTM, on identical displays.
Target surfaces
Austin Chalk and Tuscaloosa remapped on the final volume, before and after.
The prospect, mapped
Everything above lands here: the Tuscaloosa sand, remapped on the TSL-FWI volume.

We can do this on your data
Legacy datasets, minimal pre-processing, no picking — TSL-FWI™ on the field data, back to you in weeks.
South Louisiana. Three legacy onshore datasets merged and inverted together with X-Wave TSL-FWI™ from the field data. Depths are TVDSS; horizon names and picks are the operator's interpretation.