Increasing Petrophysical Image Log Resolution using Deep Learning Techniques
AssigneeSaudi Arabian Oil Company
InventorAbdullah A. Alakeely
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Abstract
A computer-implemented method for increasing petrophysical image log resolution using deep learning is described. In examples, a group of images is prepared for training a machine learning model. The machine learning model is trained using the prepared group of images, wherein the machine learning model learns a function that increases a resolution of the prepared group of images. Unseen images are input to the trained machine learning model, wherein the trained machine learning model outputs respective high-resolution images.
Claims20
A computer-implemented method for increasing petrophysical image log resolution, the method comprising:
- preparing, using at least one hardware processor, a group of images for training a machine learning model, wherein a respective image of the group of images comprises random image data;
- training, using the at least one hardware processor, the machine learning model using the prepared group of images, wherein the machine learning model learns a function that increases a resolution of the prepared group of images;
- and
- inputting, using the at least one hardware processor, unseen images to the trained machine learning model, wherein the trained machine learning model outputs respective high-resolution images.
An apparatus comprising a non-transitory, computer readable, storage medium that stores instructions that, when executed by at least one processor, cause the at least one processor to perform operations comprising:
- preparing a group of images for training a machine learning model, wherein a respective image of the group of images comprises random image data;
- training the machine learning model using the prepared group of images, wherein the machine learning model learns a function that increases a resolution of the prepared group of images;
- and
- inputting unseen images to the trained machine learning model, wherein the trained machine learning model outputs respective high-resolution images.
A system, comprising:
- one or more memory modules;
- one or more hardware processors communicably coupled to the one or more memory modules, the one or more hardware processors configured to execute instructions stored on the one or more memory models to perform operations comprising:
- preparing a group of images for training a machine learning model, wherein a respective image of the group of images comprises random image data;
- training the machine learning model using the prepared group of images, wherein the machine learning model learns a function that increases a resolution of the prepared group of images;
- and
- inputting unseen images to the trained machine learning model, wherein the trained machine learning model outputs respective high-resolution images.
Dependencies are inferred from the claim text.