PESA WA: July Technical Evening Presentation: Boyan Vakarelov

Many critical subsurface decisions depend on predicting fluid flow through stratigraphic architectures that occur below typical seismic resolution, or in areas with sparse well control. This sub-seismic uncertainty can be meaningfully reduced through following a geology-first approach, where depositional variability is constrained by process understanding and calibrated against natural analogues. Such an approach should embrace multiple geologically valid solutions and focus on the architectural scale most relevant to the decision at hand.

This presentation draws on insights from an extensive depositional analogue database compiled over the past two decades, highlighting how process regime and system type control the architecture of shallow marine and fluvial successions. We will then demonstrate how forward stratigraphic and object-based modeling workflows can generate geologically realistic scenarios in data-limited settings. These models not only improve uncertainty quantification and ultimately flow prediction but also provide physics-informed synthetic datasets for training AI neural network models.