Ditapis dengan
Enhanced permeability prediction in porous media using particle swarm optimiz…
Accurately and efficiently predicting the permeability of porous media is essential for addressing a wide range of hydrogeological issues. However, the complexity of porous media often limits the effectiveness of individual prediction methods. This study introduces a novel Particle Swarm Optimization-based Permeability Integrated Prediction model (PSO-PIP), which incorporates a particle swarm o…
- Edisi
- Vol.5, December 2024
- ISBN/ISSN
- 2666-5441
- Deskripsi Fisik
- 12 hlm PDF, 9.874 KB
- Judul Seri
- Artificial Intelligence in Geosciences
- No. Panggil
- 551
A 3D convolutional neural network model with multiple outputs for simultaneou…
Porosity, tortuosity, specific surface area (SSA), and permeability are four key parameters of reactive transport modeling in sandstone, which are important for understanding solute transport and geochemical reaction processes in sandstone aquifers. These four parameters reflect the characteristics of pore structure of sandstone from different perspectives, and the traditional empirical formula…
- Edisi
- Vol.5, December 2024
- ISBN/ISSN
- 2666-5441
- Deskripsi Fisik
- 10 hlm PDF, 54.556 KB
- Judul Seri
- Artificial Intelligence in Geosciences
- No. Panggil
- 551
Pore-to-Darcy scale permeability upscaling for media with dynamic pore struct…
Permeability is a key rock property important for scientific applications that require simulation of fluid flow. Although permeability is determined using core flooding experiments, recent advancements in micro-CT imaging and pore scale fluid flow simulations have made it possible to constrain permeability honoring pore scale rock structure. Previous studies have reported that complex associati…
- Edisi
- Vol.23, September 2024
- ISBN/ISSN
- 2590-1974
- Deskripsi Fisik
- 13 hlm PDF, 10.127 KB
- Judul Seri
- Applied Computing and Geoscience - Open Access
- No. Panggil
- 551.136
A competitive ensemble model for permeability prediction in heterogeneous oil…
One important property of oil and gas reservoirs is permeability, which has proven to be difficult to predict. Empirical and regression models are the current industrial practice for predicting permeability due to high cost and time consumption associated with laboratory measurement. In recent times, machine learning algorithms have been employed for the prediction of permeability due to their …
- Edisi
- Vol.1, October 2019
- ISBN/ISSN
- 2590-1974
- Deskripsi Fisik
- 13 hlm PDF, 3.657 KB
- Judul Seri
- Applied Computing and Geoscience - Open Access
- No. Panggil
- 551.136
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