InterWell
Result of decades of R&D from IFPen, InterWellTM core technology relies on model-based grid-based multi-channel inversion with the same Bayesian formalism and joint inversion approach for all algorithms.
From the most standard inversions (post or pre-stack simultaneous inversion) to the most advanced technologies (4D, multi-component, inter-bed multiple modeling), InterWellTM inversion capabilities make it one of the most complete inversion software of the market.
Based on an industrial partnership with CERENA (Lisbon), the post-/pre-stack geostatistical inversion (GSI) provide high resolution simulations to capture the uncertainties on the sub-surface elastic model and on the final reservoir properties.
Pioneer in matrix and fracture characterization, Beicip-Franlab gathers in InterWellTM all its know-how to provide you a complete and reliable characterization offer. To evaluate either rock properties, lithology or fluid distributions, a large range of applications for matrix characterization is included, powered by machine learning.
The multi-attribute fracture characterization workflow, as used in Beicip-Franlab integrated fracture studies, is available, with more than 20 attributes, to be conditioned and combined to provide a synthesis of your fault/fracture network from your raw or previously enhanced seismic dataset.
Explore and combine different velocity data sources, from well data (time-depth laws, markers, DT logs) and seismic velocity, to build the most informed velocity model. Either using maps, log extrapolation or formulas, InterWellTM is flexible in order to design the velocity model adapted to your data and your geological context. The efficient and semi-automatic calibration workflow allows the model to perfectly fit with the well data, to provide the more robust time-depth conversion.
- Seismic data conditioning, including the NMO, the stacking of gathers, and the residual NMO correction
- Multi-well wavelet estimation and multi-cube well calibration with a hybrid deterministic-statistical procedure
- Robust prior model building guided by the dip of seismic events
- HPC performance from optimized algorithms
- Trace classification (supervised and unsupervised)
- Continuous property volume estimation
- Highly customizable Bayesian lithology prediction
- Geobody extraction and its analysis
- Semi-automatic velocity model calibration workflow to fit the well data