Deep-learning-based workflow for boundary and small target segmentation in digital rock images using UNet++ and IK-EBM

Journal of Petroleum Science and Engineering, Год журнала: 2022, Номер 215, С. 110596 - 110596

Опубликована: Май 4, 2022

Язык: Английский

---

A method to interpret fracture aperture of rock slope using adaptive shape and unmanned aerial vehicle multi-angle nap-of-the-object photogrammetry

Journal of Rock Mechanics and Geotechnical Engineering, Год журнала: 2023, Номер 16(3), С. 924 - 941

Опубликована: Сен. 12, 2023

The aperture of natural rock fractures significantly affects the deformation and strength properties masses, as well hydrodynamic fractured masses. conventional measurement methods are inadequate for collecting data on high-steep slopes in complex mountainous regions. This study establishes a high-resolution three-dimensional model slope using unmanned aerial vehicle (UAV) multi-angle nap-of-the-object photogrammetry to obtain edge feature points fractures. Fracture opening morphology is characterized coordinate projection transformation. central axis determined vertical measuring lines, allowing interpretation adaptive fracture shape. feasibility reliability new method verified at construction site railway southeast Tibet, China. shows that has significant interval effect size effect. optimal sampling length approximately 0.5–1 m, results can be achieved when line spacing 1% length. Tensile area generally have larger apertures than shear fractures, their tendency increase with height also greater tensile positively correlated trace length, while correlation between appears weak. Fractures different orientations exhibit certain differences distribution aperture, but follow forms normal, log-normal, gamma distributions. provides essential support stability evaluation, which practical importance.

Язык: Английский

---

Machine Learning for Urban Land Use/ Cover Mapping: Comparison of Artificial Neural Network, Random Forest and Support Vector Machine, A Case Study of Dilla Town

Heliyon, Год журнала: 2024, Номер 10(20), С. e39146 - e39146

Опубликована: Окт. 1, 2024

Язык: Английский

---

Assessing the impact of rainfall, topography, and human disturbances on nutrient levels using integrated machine learning and GAMs models in the Choctawhatchee River Watershed

Journal of Environmental Management, Год журнала: 2025, Номер 375, С. 124361 - 124361

Опубликована: Янв. 31, 2025

Язык: Английский

---

Multi-Scale Pore Network Fusion and Upscaling of Microporosity Using Artificial Neural Network

Marine and Petroleum Geology, Год журнала: 2025, Номер unknown, С. 107349 - 107349

Опубликована: Фев. 1, 2025

Язык: Английский

---

PoreSeg: An unsupervised and interactive-based framework for automatic segmentation of X-ray tomography of porous materials

Advances in Water Resources, Год журнала: 2023, Номер 178, С. 104495 - 104495

Опубликована: Июнь 21, 2023

Язык: Английский

---

Minkowski functional evaluation of representative elementary volume of rock microtomography images at multiple resolutions

Advances in Water Resources, Год журнала: 2023, Номер 179, С. 104501 - 104501

Опубликована: Июль 13, 2023

Язык: Английский

---

Synthetic Graphic Well Log Generation Using an Enhanced Deep Learning Workflow: Imbalanced Multiclass Data, Sample Size, and Scalability Challenges

SPE Journal, Год журнала: 2023, Номер 29(01), С. 1 - 20

Опубликована: Сен. 7, 2023

Summary The present study introduces an enhanced deep learning (DL) workflow based on transfer (TL) for producing high-resolution synthetic graphic well logs (SGWLs). To examine the scalability of proposed workflow, a carbonate reservoir with high geological heterogeneity has been chosen as case study, and developed is evaluated unseen data (i.e., blind well). Data sources include conventional graphical (GWLs) from neighboring wells. During drilling operations, GWLs are standard practice collecting data. GWL provides rapid visual representation subsurface lithofacies to establish correlations. This investigation examines five wells in southwest Iranian oil field. Due heterogeneities, primary challenge this research lies addressing imbalanced facies distribution. traditional artificial intelligence strategies that manage [e.g., modified minority oversampling technique (M-SMOTE) Tomek link (TKL)] mainly designed solve binary problems. However, adapt these methods upcoming multiclass situation, one-vs.-one (OVO) one-vs.-all (OVA) decomposition ad-hoc techniques used. Well-known VGG16-1D ResNet18-1D used adaptive very-deep algorithms. Additionally, highlight robustness efficiency algorithms, shallow approaches support vector machine (SVM) random forest (RF) classification also other main need enough points train very resolved through TL. After identifying well, four wells’ entered model training. average kappa statistic F-measure, appropriate imbalance evaluation metrics, implemented assess workflows’ performance. numerical comparison analysis shows TL performs better set when combined OVA scheme TKL combat tactic. An 86.33% mean F-measure 92.09% demonstrate superiority. Considering prevalence different distributions, scalable can be efficient productive generating SGWL.

Язык: Английский

---

Intelligent detection of dynamic cracking along an interface of brittle material using high-speed photography assisted by data augmentation and machine learning

International Journal of Rock Mechanics and Mining Sciences, Год журнала: 2024, Номер 179, С. 105784 - 105784

Опубликована: Июнь 3, 2024

Язык: Английский

---

Application of unsupervised deep learning to image segmentation and in-situ contact angle measurements in a CO2-water-rock system

Advances in Water Resources, Год журнала: 2023, Номер 173, С. 104385 - 104385

Опубликована: Янв. 18, 2023

Язык: Английский

---