US 12,242,013 B2
Stratigraphic forward modeling platform and methods of use
Peter Tilke, Watertown, MA (US); Marie Etchebes, Clamart (FR); Marie Emeline Cecile LeFranc, Lysaker (NO); Lingchen Zhu, Medford, MA (US); Michael Lis, Houston, TX (US); and Remy Sabathier, Orgeval (FR)
Assigned to SCHLUMBERGER TECHNOLOGY CORPORATION, Sugar Land, TX (US)
Filed by Schlumberger Technology Corporation, Sugar Land, TX (US)
Filed on Sep. 14, 2023, as Appl. No. 18/467,046.
Claims priority of provisional application 63/375,576, filed on Sep. 14, 2022.
Prior Publication US 2024/0111071 A1, Apr. 4, 2024
Int. Cl. G06F 30/27 (2020.01); G01V 20/00 (2024.01)
CPC G01V 20/00 (2024.01) [G06F 30/27 (2020.01)] 15 Claims
OG exemplary drawing
 
1. A method of using a stratigraphic forward modeling platform, comprising:
generating at least one synthetic stratigraphic models at the reservoir scale using at least one process mimicking algorithms by generating multiple different depositional facies using a time stepping approach;
defining an initial topography and an initial rates of subsidence and an initial rate of uplift over an area region of interest;
computing deposition of depofacies during each time step over a predefined map area, the predefined map area comprising at least a portion of the areal region of interest;
generating petrophysical and rock physics properties of the depofacies over the predefined map area;
generating multiple realizations of each stratigraphic model based on random seed and different hyperparameters;
storing each of the multiple model realizations and indexing the multiple model realizations in geological time; and
utilizing the stored multiple model realization data sets from the model to train an artificial intelligence and machine learning (AIML) application.