US 12,449,557 B2
Prediction of permeability distribution of deep buried sandstones using machine learning
Ahmed Khidir, Dhahran (SA); Ahmed Alghamdi, Dammam (SA); and Ali Al-Masrahy, Al Khobar (SA)
Assigned to Saudi Arabian Oil Company, Dhahran (SA)
Filed by Saudi Arabian Oil Company, Dhahran (SA)
Filed on Nov. 8, 2022, as Appl. No. 17/983,068.
Prior Publication US 2024/0151868 A1, May 9, 2024
Int. Cl. G01V 1/50 (2006.01); G06N 20/00 (2019.01)
CPC G01V 1/50 (2013.01) [G06N 20/00 (2019.01); G01V 2210/64 (2013.01); G01V 2210/65 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A computer-implemented method, comprising:
receiving a plurality of wireline well log responses of a plurality of cored well sections of a subsurface sandstone reservoir;
receiving a respective authigenic clay type associated with each of the plurality of cored well sections of the subsurface sandstone reservoir, wherein the respective authigenic clay type comprises a respective type of authigenic clay of each of the plurality of cored well sections of the subsurface sandstone reservoir;
labeling, based on the respective authigenic clay type associated with each of the plurality of cored well sections of the subsurface sandstone reservoir, the plurality of wireline well log responses of the plurality of cored well sections;
training, based on the plurality of labeled wireline well log responses of the plurality of cored well sections, a machine learning (ML) model for predicting a permeability distribution of a plurality of uncored well sections of the subsurface sandstone reservoir;
receiving a plurality of wireline well log responses of the plurality of uncored well sections of the subsurface sandstone reservoir;
predicting, using the trained ML model and based on the plurality of wireline well log responses of the plurality of uncored well sections, the permeability distribution of the plurality of uncored well sections of the subsurface sandstone reservoir;
mapping the predicted permeability distribution to a 3D sweet spot map of the subsurface sandstone reservoir; and
identifying, using the 3D sweet spot map, one or more new wellbore locations within the subsurface sandstone reservoir.