Confident decisions from exploration to production

DPI estimates subsurface properties and facies probabilities, even in complex settings where traditional methods struggle. It handles uncertainty in a mathematically robust way and resolves thin beds below standard seismic detection limits, giving you greater confidence in what lies beneath.

This method uses all the energy in the seismic gather, including multiples and converted waves, to build a more complete picture of subsurface properties. It works on both new and legacy data, and is particularly effective where conventional approaches leave signal on the table.

Our simultaneous AVO inversion transforms angle-dependent seismic data into elastic properties such as impedance and density. The result is reliable property volumes calibrated to your wells, providing a foundation for further interpretation and integration.

Using locally calibrated rock physics models, we convert elastic inversion results into petrophysical properties such as porosity, clay content, and water saturation. This bridges the gap between geophysics and reservoir characterisation, delivering outputs your team can work with directly.

We invert ultra-high resolution seismic data for geotechnical parameters such as bulk modulus, shear modulus, and density. From these, we derive synthetic CPTs and soil classifications, giving you spatial mapping of properties across your site to support foundation design and hazard assessment.

By analysing how seismic amplitudes vary with azimuth, we estimate fracture intensity and orientation as well as the effective stress field. This delivers calibrated fracture and stress characterisation to support reservoir assessment and completion planning, particularly in unconventional settings.

We apply the same filtering and processing effects that seismic data undergo to your reservoir simulation outputs. This enables a consistent, like-for-like comparison between what the model predicts and what the seismic shows, supporting history matching and model validation.