A step-change in velocity modelling and subsurface imaging results

An Enhanced Approach to Full Wave Inversion

Dynamic Matching Full Wave Inversion (DM FWI) is a technology that uses seismic reflection and refraction information to automatically update the velocity model. The Dynamic Matching feature is the TGS technique that overcomes many of the limitations of standard FWI like cycle skipping.

Dynamic Matching FWI allows for superior, geologically coherent velocity models, improved subsurface analysis and reduced uncertainty. It will enable reduced cycle times, cost reduction and significant de-risking in complex imaging areas.

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Greater Efficiency and Reliability

Dynamic Matching FWI achieves a step-change in velocity modelling where imaging in depth is clearer and more geologically consistent. This approach can be applied to a wide range of data sets and particularly excels in geologically complex areas like salt basins and in improving geological understanding in the deeper plays.

Our inversion-based algorithm significantly reduces human error and bias. Models are data-driven, enhancing existing interpretation. The method automatically updates current earth models enabling more accurate mapping beneath complex overburden (gas, salt, etc.).

DM FWI facilitates new survey designs while also applicable to existing survey designs such as the recent TGS Amendment ultra-long off-set FWI in the Gulf of Mexico. This allows E&P companies to build velocity models better than any other technique and potentially in a much shorter space of time, reducing overall cycle times and, in-turn, cutting costs.


But don't take our word for it. See the results for yourself...

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Seismic Example (with velocity overlay), showing seismic imaging using the legacy velocity model vs that created using the TGS Dynamic Matching FWI approach*

FWI can update not only for sediment velocity but also for salt geometry. It benefits from the longer offsets and better low frequency signal common in modern acquisition.


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Seismic Example (with velocity overlay), showing processing with and without DM FWI*


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Seismic Example (with velocity overlay), showing processing with and without DM FWI*


DM FWI takes a superior technical approach

HubSpot Video

Senior Researcher Jian Mao presents the advanced Dynamic Matching Full Waveform Inversion (DM FWI) algorithm and its applications on field datasets

In the FWI workflow below you can see how TGS performs forward modelling to create the synthetic data. If the model generates data close enough to the real data, then it is approved. If not, the residual between the data and the synthetic is back projected to update the model. The whole flow is designed to automatically construct a model that can generate the best match of the real data. In this way FWI is a form of machine learning. It learns from the misfit to iteratively derive a better model. As the synthetic becomes closer and closer to the real data, we get closer to the true model. The webinar link above presents a more in-depth explanation.




As you can see from the graphic below, the TGS approach, using local window normalization to minimize amplitude effect, has many advantages over other techniques. In the data domain we introduce a quality factor to weigh down low S/N contribution and in the image domain we have regularization to reduce artefacts in the FWI gradient. These constraints combine to improve robustness. In addition, the Dynamic Matching element minimizes amplitude impact and emphasizes kinematic differences. 




Recent Papers Published by TGS on FWI

Contact us using the form provided (top left) for details on further papers awaiting presentation at SEG 2020 and EAGE 2020 events



* All DM FWI data examples taken from the Amendment Phase 1 survey which was acquired in partnership with WesternGeco and processed by TGS.”

Media Release

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  • Gives clearer, more accurate velocity models

  • Cuts cycle times

  • De-risks prospects

  • Provides greater geological understanding

More about TGS Imaging

TGS' research and development professionals are continually developing new technology and workflows for seismic imaging, as well as enhancing existing ones.

Learn more at TGS.com

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Amendment Phase 1 3D Advert-2

Amendment Phase 1

Amendment is the first project to utilize DM-FWI. The application to the Amendment sparse node dataset with ultralong offsets in the Gulf of Mexico demonstrates the capability to resolve large velocity errors and give significant uplift on the sub-salt image.

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