Speaker(s): Paul Baville

Date: Thursday 15th of October 2020, 1:00 pm.

Abstract:

Assisted well correlation aims at complementing sedimentological expertise with computational rigor to increase automation, improve reproducibility and assess uncertainties during stratigraphic correlation. We propose a computer-assisted method which automatically generates possible well correlations based on facies interpretation, dipmeter data and knowledge about depositional environments.

This method uses facies interpretations and progading or backstepping trends deduced from the vertical stacking of depositional environments. These data are translated into a paleo-geographic variable inferred from depositional environments, e.g. the position along a proximal-to-distal transect. Assuming that wells have a global distality due to their position with respect to the overall basin geometry within the considered stratigraphic interval, we can interpolate a three-dimensional surface constrained by well-markers and dipmeter data acquired along wells. These surfaces represent chronostratigraphic surfaces. In a first approximation, the depositional dip direction is assumed to parallel sediment transport direction and the depositional strike direction being at a right angle to the former.

Well correlations are computed using correlation costs between all possible marker combinations aggregated by the Dynamic Time Warping algorithm. These correlation costs are based on the shape of the relative paleo-topography. Additionally, proximal facies interpreted in a distal well cannot be associated with distal facies interpreted in a proximal well, and conversely distal facies interpreted in a distal well may be likely associated with a proximal facies interpreted in a proximal well. Along the depositional strike, the method tries to associate identical or close facies with respect to distality.