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About this Training Course

There are various kinds of geophysical data available, broadly divided into seismic and non-seismic or multi-physics data. While multi-physics methods such as gravity, magnetics, electrical, electromagnetic and spectral methods provide valuable complementary information, seismic remains the principal geophysical method used in the energy industry. Non-seismic methods are also important in shallow subsurface applications including engineering, pollution mapping, archaeology, geothermal energy and CO₂ storage.

This 5-day course covers the fundamentals of seismic acquisition, processing and interpretation. Participants will learn how seismic waves are generated, recorded and processed, and how the resulting data relates to subsurface rock and pore-fluid properties and supports the interpretation of subsurface structure and pore-space content. The programme covers both fundamental principles and advanced seismic methods that support increasingly accurate subsurface interpretation.

The course also introduces participants to modern AI and Machine Learning applications in geophysics. Machine Learning is increasingly important across seismic acquisition, processing and interpretation. Participants do not need to understand the algorithms in detail; instead, the focus is on recognising how these technologies can be used correctly within geoscience workflows. Most exercises use Python, allowing participants to compare alternative methods through practical application.

A key theme of the course is collaboration between disciplines. By developing a shared understanding of seismic terminology, approaches and workflows, geologists, petrophysicists, geophysicists and reservoir engineers can communicate more effectively, formulate appropriate technical requirements and contribute to better prospect ranking and improved production and infill-well decisions.