From Data to Discovery: Turning Subsurface Data into Exploration Advantage

Exploration starts with data: acquiring seismic, well and geological data, processing it into a usable subsurface picture, and holding it where it can be found and reused. Few countries have this data consolidated into a single repository, and those that do hold an asset most operators cannot replicate. The quality of the picture depends as much on how data is collected and processed as on what is done with it afterwards. AI is now being added on top of this foundation. It can sharpen seismic interpretation, reprocess legacy surveys and stitch inconsistent datasets together, improving prospect identification. But the obstacle is not only the algorithm. Much of the value depends on the data itself: making decades of legacy records machine-readable, interoperable and easy to analyse at scale. Without that, AI has little to work with. Global technology partnerships can help on both fronts, from reprocessing old data to applying new tools. The discussion will focus on how exploration data is collected, processed and stored to build the right subsurface picture, how AI is then used to get more from it, and how operators and technology partners share both the data and the upside.