Technical Content

This article discusses the importance of performing rock physics diagnostics in the context of rock texture and geological processes that lead to rock formation. This makes it possible to select the right physical rock physics model to perform the modeling and set the parameters ...

Part of the GeoSoftware Synthetic Catalog Workflow, WellGen links petrophysics, rock physics and supervised machine learning for better seismic reservoir characterization.

The Central North Sea is a mature petroleum exploration province, with over 50 years of exploration to date. With increased maturity, recent exploration efforts have focused on the deeper targets below the Base Cretaceous Unconformity (BCU), where there is increased risk and often high-pressure ...

While the subsurface geoscience skills required for geothermal exploration and development differ from those required for oil and gas, there are existing skills and technologies that are highly transferable. Moreover, as the shift for geothermal resources moves away from high-enthalpy areas and towards sedimentary ...

GeoVerse is CGG’s flagship geological multi-client database. Through a combination of advanced data organization and machine-learning processes, GeoVerse enables a step-change in data analytics and data interrogation.

GepoSpec Cameroon Terms of Reference for Proposals on free blocks

Seismic imaging using full-wavefield data that includes primary reflections, transmitted waves, and their multiples, has been the holy grail for generations of geophysicists. To be able to use the full-wavefield data effectively requires a forward modeling process to generate full-wavefield data, an inversion scheme ...

Data from all sources, at all scales, has helped to assess petroleum potential offshore Mozambique beyond the relatively small play fairway proven to date. New insights into proven and potential reservoirs, plus improved predictions of the presence, type and maturity of source rocks, have ...

A machine learning workflow can quickly, and accurately, predict mineralogy, porosity and saturation in multiple wells to better understand productive layers in unconventional oil reservoirs.