DLP Webinar: AI Seismic Interpretation of vintage seismic data with implications for CCS site characterisation
| Instructor: | Dr Ryan Williams |
|---|---|
| Duration: | 30 min + Q&A |
| Discipline: | AI, Seismic Interpretation |
| Main topics: | AI, Seismic Interpretation |
| Language: | English |
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Carbon Capture Utilisation and Storage (CCUS) is seen as a potential solution to the World’s climate/carbon crisis. Around the world potential CCUS sites have been identified for CO2 storage, whether it be an abandoned hydrocarbon field or a subsurface aquifer. The Southern North Sea is thought to contain several highly prospective sites. Un-faulted, anticlinal mounds of Bunter Sandstone aquifer/ reservoir material formed from underlying salt pillowing is overlain by Triassic shales, forming a reliable trap and seal pairing. The presence of the Esmond gas field supports the ability of these formations to trap and store fluids within the subsurface.
Using AI networks, it has been possible to investigate and interpret a Southern North Sea Bunter mound, for identification of a CCUS site location. Revealing the presence of faults within the site’s location is of vital importance for, not only for sealing potential and trap definition, but also to identify any aquifer compartmentalisation which may reduce the ability to successfully fill the structure. The AI fault detection network can also be fine-tuned to the specific style of faulting observed within the seismic volume. Extracting horizons from seismic data can be a time-consuming process, especially with complex faulting. Therefore, having the ability to extract every horizon within a volume can free up a significant portion of an interpreter’s time, allowing them to concentrate in areas of complexity. Extracting all horizons will allow an interpreter to clearly visualise the structure and the lateral extents of aquifer/reservoir and seal pair with greater confidence.
Combining the structural and stratigraphic analysis generated using AI allows for a quicker/ time efficient interpretation without and loss of accuracy. The ability to create quick, reliable, and consistent interpretation is key for successful CCUS site investigation. It is vital that the interpreter is involved throughout the AI interpretation process, as they have all the necessary experience, knowledge and skills. AI allows the interpreter to complete the work, whilst saving time and improve the quality of results.
Participants' Profile
Geologists
Geophysicists
Reservoir Engineers
About the Lecturer
Ryan Williams is a senior geoscientist working for Geoteric based in Aberdeen, where he has worked on several projects based in the UK and Norwegian North Sea as well as Mainland Europe, offshore West Africa and onshore/offshore India. Prior to
Geoteric, Ryan worked at Senergy in their Edinburgh office as part of the Reservoir Seismic Characterisation team. He joined the industry having completed a Ph.D. at Edinburgh University where he focused on interpreting the East Shetland Basins’ structural
networks to understand the implications for hydrocarbon exploration in a multi-rift environment.