Using XWITM to define and quantify the target layer formation in a producing field.
XWITM on Amazon Web Services
S-Cube delivering breakthrough capability for waveform inversion of seismic data
Machine-driven earth-model optimisation. Industry's leading FWI algorithm. Uncover every detail.
XWI Parameter Learning
- Fully automated data-in model-out optimisation framework for deriving the most detailed and accurate best-fit velocity volume from recorded seismic data.
- The toolbox integrates CWI and RWI with the AWITM and FWI cost functions for adjusting model training weights to predict seismic field recordings.
- The result is more accuracy, more predictive power, more automation starting further away from the true answer.
Case Studies
A set of 3D field deployments comparing the velocity resolution achieved by waveform inversion relative to standard tomographic techniques.
Equinor OBC field data
Using XWITM to capture details of a gas accumulation filled with fluid escaped from an underlying reservoir.
Woodside NATS field data
Using XWITM in exploration to reveal a prospect and pre-drill define its geometry.
XWITM on AWS User Tullow Oil
Burst Compute Capacity
Industry's Leading Algorithm
Better. Faster. Deeper.
Four pillars:
Accuracy
Resolution
Predictive Power
Differentiated Capability
Cloud-native architecture:
Multiple XWITM initialisations
Travel through search space
Cloud-enabled hyper-tuning
Industry Awards and Measures of Esteem
Academic founders internationally recognized as leaders in the field
Distinguished Awards
Award for Adaptive Waveform Inversion
Award for advances in Full Waveform Inversion
Key Presentations
Woodside AWI deployment in Myanmar
Full-bandwidth adaptive waveform inversion at the reservoir (2017)
Statoil AWI deployment in the North Sea
Imaging Beneath a Gas Cloud in the North Sea without Conventional Tomography (2017)
Run XWI on the Cloud
Discover an unprecedented increase in the resolution of your velocity model.