Application of Physics-Informed Neural Networks for Estimation of Saturation Functions from Countercurrent Spontaneous Imbibition Tests
J Abbasi, PØ Andersen - SPE Journal, 2024 - onepetro.org
In this work, physics-informed neural networks (PINNs) are used for history matching data
from core-scale countercurrent spontaneous imbibition (COUCSI) tests. To our knowledge …
from core-scale countercurrent spontaneous imbibition (COUCSI) tests. To our knowledge …
Thermal modeling of patient-specific breast cancer with physics-based artificial intelligence
I Perez-Raya, SG Kandlikar - ASME Journal of …, 2023 - asmedigitalcollection.asme.org
Breast cancer is a prevalent form of cancer among women. It is associated with increased
heat generation due to higher metabolism in the tumor and increased blood vessels …
heat generation due to higher metabolism in the tumor and increased blood vessels …
Production Well Placement and History Matching by Hyperparametric Optimization and Machine Learning
A Donskoi, A Medvedev, T Shchudro… - Lobachevskii Journal of …, 2024 - Springer
This article explores methods for resolving two practical issues in reservoir engineering:
discovering an optimal position for the production well on a grid, and recovering unknown …
discovering an optimal position for the production well on a grid, and recovering unknown …
A Transformative Approach for Breast Cancer Detection Using Physics-Informed Neural Network and Surface Temperature Data
I Perez-Raya, C Gutierrez… - ASME Journal of …, 2024 - asmedigitalcollection.asme.org
Early detection is the most effective defense against breast cancer. Mammography is a well-
established X-ray-based technique that is used for annual or biennial screening of women …
established X-ray-based technique that is used for annual or biennial screening of women …
Application of Physics-Informed Neural Networks for Estimation of Saturation Functions from Countercurrent Spontaneous Imbibition Tests
J Abbasi, PØ Andersen - IOR+ 2023, 2023 - earthdoc.org
In this work, Physics-informed Neural Networks (PINNs) are employed for history-matching
data from core-scale countercurrent spontaneous imbibition (COUCSI) tests. To our …
data from core-scale countercurrent spontaneous imbibition (COUCSI) tests. To our …
Input Parameterized Physics Informed Neural Networks for Advanced Time Resolved Three-Dimensional Phase-Contrast Magnetic Resonance Imaging
R D'Souza, A Pashaei Kalajahi, Z Mamun… - Available at SSRN … - papers.ssrn.com
Time resolved three-dimensional phase-contrast magnetic resonance imaging (4D Flow
MRI) enables non-invasive in vivo quantification of blood flow velocities, yet it suffers from …
MRI) enables non-invasive in vivo quantification of blood flow velocities, yet it suffers from …