Technical Content

The near surface in the Middle East is characterized by the presence of very shallow fast carbonates and anhydrites interleaved by slow-velocity clastic layers, resulting in sharp velocity inversions. We present here examples from two case studies in the Sultanate of Oman using Multi-Wave ...

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 ...

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 ...

A new OBN survey was acquired over the Shenzi field in the deep water GOM. The primary goal was to leverage recent advances in FWI to improve the velocity model with an expectation that the image would benefit from the full-azimuth, long offset OBN ...

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.

A new, proprietary technique that improves production forecasts has been demonstrated on an Asian gas field. Multi-scale ensemble-based history matching (MS-EnOpt) improves production forecasting and reserve estimation, and provides engineers with an understanding of key reservoir uncertainties.