DeepSeg-based noise reduction algorithm trained on a hybrid synthetic dataset for signals from acoustic logging-while-drilling
March 2026
Acoustic logging-while-drilling (ALWD) enables real-time acoustic measurements during drilling operations. However, challenging downhole conditions introduce considerable noise into ALWD signals. This...
Seismic facies characterization: Integrated subsurface-outcrop analysis for complex depositional systems in northeast India
March 2026
Seismic facies analysis involves the interpretation of reflection patterns from seismic data to provide insights into subsurface sedimentary environments, depositional processes, and lithological variations,...
A data-driven approach to earthquake early warning: Multicomponent site-spectra prediction using deep neural networks
March 2026
This paper presents a hybrid deep learning framework for earthquake early warning (EEW) that leverages front-site observations to predict target-site spectral characteristics—specifically Fourier amplitude...
Fast sparse representation impedance inversion method based on online adaptive reservoir characterization
March 2026
Seismic impedance inversion is a key technique for extracting reservoir information from seismic data. Traditional model-driven inversion methods often prove inadequate when dealing with complex reservoirs,...
Enhancing model parameterization with linearly constrained deep generative network for ensemble-based history matching
March 2026
Ensemble-based data assimilation methods have been widely used for history matching in subsurface reservoir modeling, but struggle to handle the complex nonlinear and non-Gaussian behaviors prevalent...
Spatial mapping and modelling of soil organic carbon using random forest and remote sensing variables in part of Kaduna, Northern Nigeria
March 2026
Reliable and up-to-date digital soil data is crucial for achieving Sustainable Development Goal 13 (Climate Action) by enabling improved monitoring of soil carbon and land degradation, thereby supporting...
A hybrid unsupervised-supervised deep learning framework for sandstone thickness prediction from seismic data
March 2026
Accurate sandstone thickness prediction from seismic data is vital for reservoir characterization and well placement optimization. However, conventional deep learning methods are often hindered by inefficient...
Thank you reviewers!
Available online 13 January 2026
Cellular automata models for simulation and prediction of urban land use change: Development and prospects
December 2025
Rapid urbanization and land-use changes are placing immense pressure on resources, infrastructure, and environmental sustainability. To address these, accurate urban simulation models are essential...
Machine learning assisted estimation of total solids content of drilling fluids
December 2025
Characterization and optimization of physical and chemical properties of drilling fluids are critical for the efficiency and success of drilling operations. In particular, maintaining the optimal levels...
Generating high-resolution climate data in the Andes using artificial intelligence: A lightweight alternative to the WRF model
December 2025
In weather forecasting, generating atmospheric variables for regions with complex topography, such as the Andean regions with peaks reaching 6500 m above sea level, poses significant challenges. Traditional...
Quantifying uncertainty in foraminifera classification: How deep learning methods compare to human experts
December 2025
Foraminifera are shell-bearing microorganisms that are commonly found in marine deposits on the seabed. They are important indicators in many analyses, are used in climate change research, monitoring...
Quantification of greenhouse gas emissions from livestock using remote sensing & artificial intelligence
December 2025
Greenhouse gases (GHGs) from agriculture in Africa are among the world's fastest-growing emissions, with the livestock sector as the primary contributor. However, the methods for quantifying these emissions...
Prediction of groundwater level in Indonesian tropical peatland forest plantations using machine learning
December 2025
Maintaining high groundwater level (GWL) is important for preventing fires in peatlands. This study proposes GWL prediction using machine learning methods for forest plantations in Indonesian tropical...
Machine learning applied to recognition of dinoflagellate cysts: Type study with the species Batioladiniumlongicornutum
December 2025
This study explores the application of YOLOv10, a cutting-edge object detection framework, to automate the identification and classification of Batioladinium longicornutum. Utilizing a dataset of 137...
Application research of SSA-RF model in predicting the height of water-conducting fracture zone in deep and thick coal seams
December 2025
The 91 measured values of the development height of the water-conducting fracture zone (WCFZ) in deep and thick coal seam mining faces under thick loose layer conditions were collected. Five key characteristic...
Machine-learning seismic damage assessment model for building structures
December 2025
Buildings in seismic-prone regions are highly vulnerable to structural damage, necessitating meticulous Seismic Damage Assessment (SDA) for accurate design and mitigation strategies. The intricate nature...
Unsupervised hierarchical sequence stratigraphy framework of carbonate successions
December 2025
Performing the high-resolution stratigraphic analysis may be challenging and time-consuming if one has to work with large datasets. Moreover, sedimentary records have signals of different frequencies...
Undrained uplift capacity prediction of open-caisson anchors in anisotropic clays using XGBoost integrated with mutation-based genetic algorithms
December 2025
This study evaluates the undrained uplift capacity of open-caisson anchors embedded in anisotropic clay using Finite Element Limit Analysis (FELA) and a hybrid machine learning framework. The FELA simulations...
AI-based approaches for wetland mapping and classification: A review of current practices and future perspectives
December 2025
Wetlands are critical ecosystems that provide essential ecological, hydrological, and socio-economic services, such as water purification, climate regulation, and biodiversity conservation. However,...
Unveiling climate-driven water surface dynamics in the largest tropical lake in Borneo: A machine learning approach using multi-source satellite imagery
December 2025
Tropical lakes such as Lake Sentarum in Kalimantan, Indonesia, represent ecologically rich ecosystems with high biodiversity and constitute the largest lake on the island of Kalimantan. This lake serves...
Intelligent identification of fractures and holes in ultrasonic logging images based on the improved YOLOv8 model
December 2025
Aiming to address the demand for intelligent recognition of geological features in whole-wellbore ultrasonic images, this paper integrates the YOLOv8 model with the Convolution Block Attention Module...
GeoNeXt: Efficient landslide mapping using a pre-trained ConvNeXt V2 encoder with a PSA-ASPP decoder
December 2025
Landslides constitute one of the most destructive geological hazards worldwide, causing thousands of casualties and billions in economic losses annually. To mitigate these risks, accurate and efficient...
Opportunities, epistemological assessment and potential risks of machine learning applications in volcano science
December 2025
This manuscript explores the opportunities and epistemological risks of using machine learning in the Earth sciences with a focus on igneous petrology and volcanology. It begins by highlighting the...
Quantifying uncertainty of mineral prediction using a novel Bayesian deep learning framework
December 2025
Mineral resource exploration increasingly demands not only accurate prospectivity maps but also reliable measures of confidence to guide high-stakes decisions. In this study, a novel Bayesian deep learning...