公开(公告)号：US10997705B2

公开(公告)日：2021-05-04

申请号：US16601818

申请日：2019-10-15

Applicant: Chevron U.S.A. Inc.

Inventor： Bo Gong ,  Dustin J. Keele ,  Emmanuel Toumelin ,  Simon Clinch

IPC: G06T7/00 ,  G06N20/00 ,  G06N3/08

Abstract: A method is described for ways to generate a Fraction of Sand (Fsand) estimate and net-to-gross (NTG) estimate of sand in a formation using a machine-learning algorithm such as a neural network based on borehole image logs. The method may use the Fsand and other information to estimate hydrocarbons in place in a subsurface formation. The method may be executed by a computer system.

公开(公告)号：US11320357B2

公开(公告)日：2022-05-03

申请号：US16724830

申请日：2019-12-23

Applicant: Chevron U.S.A. Inc.

Inventor： Paul Duke ,  Bo Gong ,  Paul Hart

IPC: G01N15/08 ,  G06T7/30 ,  G06T3/40

Abstract: A method is described for training a model that refines estimated parameter values within core images is disclosed. The method includes receiving multiple training image pairs wherein each training image pair includes: (i) an unrefined core image of a rock sample to be used for estimating rock properties, and (ii) a refined core image of the same rock sample; generating a training dataset from the multiple training image pairs; receiving an initial core model; generating a conditioned core model by training, using the multiple training image pairs, the initial core model; and storing the conditioned core model in electronic storage. The conditioned core model may be applied to an initial target core image data set to generate a refined target sore image dataset. The method may be executed by a computer system.