Recent advances and challenges of cement bond evaluation based on ultrasonic measurements in cased holes
March 2026
Cement bond quality evaluations are essential for assessing zonal isolation between formation strata, providing crucial information for ensuring environmental and ecological safety in oil and gas exploitation,...
Enhancing fault detection using CHRRA-Unet and focal loss functions for imbalanced data: A case study in Luoping county, Yunnan, China
March 2026
Recent advancements in remote sensing technology have made it easier to detect surface faults. Deep learning, especially convolutional models, offers new potential for automatic fault detection from...
Prediction of the soil–water retention curve of compacted clays using PSO–GA XGBoost
March 2026
Soil–water retention (SWR) is fundamental for understanding the hydro-mechanical behavior of unsaturated clay soils. The soil–water retention curve is typically obtained through extensive and costly...
Hierarchical machine learning for the automatic classification of surface deformation from SAR observations
March 2026
Ground deformation processes, such as landslides and subsidence, cause significant social, economic, and environmental impacts. This study aims to automatically classify ground deformation processes...
Application of machine learning for permeability prediction in heterogeneous carbonate reservoirs
March 2026
Accurate prediction of reservoir permeability based on geostatistical modeling and history matching is often limited by spatial resolution and computational efficiency. To address this limitation, we...
The Fossil Frontier: An answer to the 3-billion fossil question
March 2026
Microfossil analysis is important in subsurface mapping, for example to match strata between wells. This analysis is currently conducted by specialist geoscientists who manually investigate large numbers...
An adaptable hybrid method for lossless airborne lidar data compression
March 2026
Light Detection and Ranging (LIDAR) point clouds provide high precision spatial data but impose significant storage and transmission challenges, often exceeding one gigabyte per square kilometer. This...
DTPP:An efficient depthwise separable TCN for seismic phase picking
March 2026
With the rapid development of artificial intelligence in seismology, various deep learning-based seismic phase picking models have emerged in recent years. However, existing models face challenges in...
An FCM-based microseismic phase arrival picking method and application
March 2026
Artificial intelligence-based methods for picking microseismic phase arrivals have been widely adopted. However, these methods are frequently challenged by complex and dynamic monitoring scenarios,...
Remote sensing estimation of rice chlorophyll content based on UAV image feature selection and PSO-optimized ensemble learning
March 2026
Chlorophyll content is one crucial indicator of evaluating crop growth and physiological status. Rapid, accurate, and large-scale monitoring of chlorophyll content is vital for the precise diagnosis...
Explainable flood damage assessment using multi-atrous self-attention and vision-language integration
March 2026
Flood disasters triggered by excessive rainfall cause severe damage to infrastructure and pose significant risks to human life. Within the context of disaster management, accurately identifying affected...
Application of YOLOv11 deep learning model for classification and counting ice-rafted debris (IRD) in core sediments in the Arctic Ocean
March 2026
The classification and quantification of ice-rafted debris (IRD) in marine sediments are key to reconstructing glacial-interglacial dynamics and sediment provenance. However, traditional IRD analysis,...
Machine learning-driven permeability prediction in carbonates and sandstones using NMR relaxation data
March 2026
Nuclear Magnetic Resonance (NMR) has proven to be a powerful tool for in-situ permeability quantification however, it typically requires laboratory calibration, and its accuracy is strongly influenced...
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...
Unlocking the potential of legacy data for future geoenergy and storage applications: Porosity and permeability prediction based on machine learning applied to petrographic data
Available online 10 March 2026
Machine learning techniques are increasingly applied in geological research and widely adopted in industry. However, one commonly available dataset remains underutilized: petrographic data from classical...
Deep learning enhanced crack identification on rocks
Available online 3 March 2026
This study focuses on enhancing crack identification in rock surfaces using deep learning techniques. The research proposes a novel convolutional architecture to achieve pixel-level classification for...
Thank you reviewers!
Available online 13 January 2026
On the application of machine learning algorithms in predicting the permeability of oil reservoirs
December 2025
Permeability is one of the main oil reservoir characteristics. It affects potential oil production, well-completion technologies, the choice of enhanced oil recovery methods, and more. The methods used...
Interpretable machine learning models for evaluating strength of ternary geopolymers
December 2025
Ternary geopolymers incorporating multiple solid wastes such as steel slag (SS), fly ash (FA), and granulated blast furnace slag (GBFS) are considered environmentally friendly and exhibit enhanced performance....