US 11,913,865 B2
In-situ prediction and dynamic visualization of relative permeability and capillary pressure in porous medium
Ali M. Alsumaiti, Abu Dhabi (AE); Abdul Ravoof Shaik, Abu Dhabi (AE); Waleed Alameri, Abu Dhabi (AE); and Saikrishna Kanukollu, Abu Dhabi (AE)
Assigned to KHALIFA UNIVERSITY OF SCIENCE AND TECHNOLOGY, Abu Dhabi (AE)
Filed by Khalifa University of Science and Technology, Abu Dhabi (AE)
Filed on Jan. 8, 2020, as Appl. No. 16/737,520.
Prior Publication US 2021/0208050 A1, Jul. 8, 2021
Int. Cl. G01N 15/08 (2006.01); G01N 33/24 (2006.01); G06F 30/27 (2020.01); G06N 20/00 (2019.01); G06N 5/04 (2023.01)
CPC G01N 15/082 (2013.01) [G01N 33/24 (2013.01); G06F 30/27 (2020.01); G06N 5/04 (2013.01); G06N 20/00 (2019.01)] 13 Claims
OG exemplary drawing
 
7. An apparatus for in-situ estimation and dynamic visualization of a plurality of characteristics of a porous medium, the apparatus comprising:
an input source for inputting data from computer-aided simulations and real-time core flooding experiments;
an embedded hardware unit comprising of a processor running a prediction model with inferences of porous medium samples, and
a human-machine interface comprising a display unit for displaying the estimated plurality of characteristics of the porous medium and an input unit for accepting commands from a user;
wherein the input source is in real-time communication with the embedded hardware unit and the display unit and the apparatus reduces a total analysis time taken for characterizing the porous medium, and accelerates characterizing two-phase flow analysis of the porous medium; and
wherein the estimated plurality of characteristics of the porous medium is based on a Machine Learning (ML) inferences trained based on real-time offline simulations running on the embedded hardware unit.