Deep learning-based intelligent characterization of sedimentary microfacies using logging curve images: Model comparison and application
December 2026
Intelligent identification and characterization of sedimentary microfacies is the core content of oil and gas reservoir geological research, which has important guiding significance for the analysis...
C2S-net: A confidence-guided multi-stage network for seismic data consecutively missing trace interpolation
December 2026
Consecutively missing traces pose a major challenge for seismic data reconstruction. Although multistage neural networks are a promising approach, each stage often inherits reconstruction errors from...
Multi-agent collaborative knowledge question answering for mineralogy
December 2026
When large language models are applied to professional geological fields such as mineralogy, they frequently suffer from knowledge obsolescence, factual hallucinations, and invalid complex logical reasoning....
From μCT images to micro scale parameters: A deep learning workflow for three-phase segmentation and 3D quantitative analysis of submarine landslide sediment
December 2026
Submarine landslides are a major geohazard, often preconditioned by micro-structural heterogeneity within sensitive weak layers. While X-ray micro-computed tomography (μCT) offers high-resolution insights...
Mask-Net: A U-Net architecture with spatial and channel attention mechanisms for improved cloud detection in sea surface temperature imagery
December 2026
Sea surface temperature (SST) is an essential climate variable, yet its estimation by infrared remote sensing remains fundamentally limited by cloud cover. Existing cloud masking approaches rely heavily...
An interpretable framework based on RS-MetaCost for lithology classification from imbalanced well logging data
December 2026
Lithology classification from well-logging data is critical for energy resource exploration but is severely challenged by class imbalance. This study proposes a framework based on the RS-MetaCost strategy,...
Reservoir identification via MSTG-Net: A multi-scale temporal-graph modeling method for well-logging curves
December 2026
To address the problems of evident multi-scale variations in logging responses, strong interwell correlations, and severe confusion among engineering-sensitive transitional reservoir types, this paper...
Machine learning assisted risk assessment of building exposure to landslides
December 2026
Landslides can enormously impact social, economic and infrastructural development. Landslide susceptibility maps (LSMs) are crucial for the identification of probable landslide areas, but often overlook...
A deep learning model for two types of ENSO predictions based on GRU-TSFE and interdecadal changes in predictability
December 2026
ENSO drives global climate variability and extremes, motivating skillful mid-range forecasts of ENSO indices. Here, we propose a three-branch deep-learning framework, the Seasonal Gated Recurrent Unit...
Modelling geometric geoid of Taiwan island integrating GNSS leveling and gravity data with multi-layer perceptron
December 2026
This study develops multi-layer perceptron (MLP)-based geoid prediction models for Taiwan using 1′×1′ gravity-anomaly grids, EGM2008 to degree and order 2159, and GNSS/levelling control information....
A physics-informed and transferable machine learning workflow for basin-scale heat flow prediction
December 2026
Accurate prediction of heat flow is critical for geothermal resource assessment yet remains challenging in structurally complex basins because of sparse measurements and the coupled effects of multiple...
Physics-constrained symbolic regression of Archie-extended relationships for reservoir saturation evaluation
December 2026
The Archie equation is a fundamental model for describing the relationships between formation resistivity, porosity and water saturation, and plays an important role in log-based saturation evaluation....
SeisDiff-FNO: Seismic data enhancement using Fourier Neural Operators within a conditional diffusion framework
December 2026
Seismic data processing is fundamental to subsurface exploration and reservoir characterization, providing critical information for hydrocarbon exploration, geological hazard assessment, and carbon...
A reproducible evaluation protocol for self-supervised three-component blind-spot seismic denoising
December 2026
Self-supervised blind-spot learning is attractive for seismic denoising because clean field targets are rarely available, but common evaluation practice can be misleading. Masked-validation loss need...
Autoencoder-assisted variational Gaussian process mineral prospectivity mapping for the Okiep Copper District, South Africa
Available online 13 October 2026
The Okiep Copper District in Namaqualand, South Africa, is a historically important copper province in which mineralisation is hosted mainly by small, irregular Koperberg Suite intrusions and associated...
Optimizing the potential of iterative bilateral proposed U-Net for advanced forest segmentation techniques
September 2026
Globally, advanced forest segmentation methods are essential for optimal environmental monitoring, managing resources and ecological studies. As, these techniques uses high-resolution satellite and...
Vision-language models for automated carbonate petrography and depositional environment interpretation
September 2026
Carbonate petrographic analysis provides essential qualitative and semi-quantitative constraints on depositional environments and diagenetic evolution at microscale. However, conventional thin-section...
Estimation of interval P-wave velocities from Dix slowness using implicit neural representation
September 2026
Mapping time-migration velocities to depth-domain interval velocities in the presence of lateral variation is important in seismic exploration. The first step of this process, computing Dix velocities...
Spatial intersection of soil texture classes and landscape features: An XGBoost-enhanced digital soil mapping approach
September 2026
Soil texture classes (STCs) can be digitally mapped by first estimating particle-size fractions (PSFs). This study focuses on developing an extreme gradient boosting (XGBoost) model to estimate the...
Joint time–space–depth feature learning for multimodal velocity estimation from array acoustic logging waveforms
September 2026
Accurate velocity estimation from array acoustic logging in unconventional hydrocarbon reservoirs is frequently hindered by complex wavefield interference, limited vertical resolution in thinly interbedded...
Simultaneous estimation of hyperparameters and basement depth in gravity data inversion using the JAYA algorithm
September 2026
Basement relief depth estimation is an important component in characterizing sedimentary basins, which serve as essential reservoir for geothermal energy, groundwater, and hydrocarbons. While residual...
Source-independent transfer learning for intelligent post-stack seismic inversion
September 2026
Post-stack seismic inversion plays a crucial role in the quantitative interpretation of reservoirs. Intelligent inversion approaches employ neural networks to characterize the relationship between observed...
Explainable AI for microseismic event detection
September 2026
Deep neural networks like PhaseNet show high accuracy in detecting microseismic events, but their black-box nature is a concern in critical applications. We apply Explainable Artificial Intelligence...
HCEC: An effective hybrid CNN-ensemble classifier for hyperspectral image classification
September 2026
Hyperspectral image classification (HSI) is extensively utilized to analyze remotely sensed images for different real-world applications. Recently, convolutional neural network(CNN) have been applied...
A hybrid Prophet–LSTM–BPNN framework for seasonal drought prediction
September 2026
Drought is among the most destructive hydroclimatic hazards, particularly in arid and semi-arid regions, where water scarcity directly threatens agricultural production and socioeconomic stability....
