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
Available online 14 January 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
Available online 14 January 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,...
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....
Comparison of processing speed of NRS-ANN hybrid and ANN models for oil production rate estimation of reservoir under waterflooding
December 2025
This study compared the predictive performance and processing speed of an artificial neural network (ANN) and a hybrid of a numerical reservoir simulation (NRS) and artificial neural network (NRS-ANN)...
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...
Deep learning approaches for estimating maximum wall deflection in excavations with inconsistent clay stratigraphy
December 2025
This paper presents a deep learning architecture combined with exploratory data analysis to estimate maximum wall deflection in deep excavations. Six major geotechnical parameters were studied. Statistical...
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...
Improved estimation of two-phase capillary pressure with nuclear magnetic resonance measurements via machine learning
December 2025
Capillary pressure plays a crucial role in determining the spatial distribution of oil and gas, particularly in medium-to-low permeability reservoirs, where it is closely linked to the rock's pore structure...
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...
Explaining machine learning models trained to predict Copernicus DEM errors in different land cover environments
December 2025
Machine learning models are increasingly used to correct the vertical biases (mainly due to vegetation and buildings) in global Digital Elevation Models (DEMs), for downstream applications which need...
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...
Online learning to accelerate nonlinear PDE solvers: Applied to multiphase porous media flow
December 2025
We propose a novel type of nonlinear solver acceleration for systems of nonlinear partial differential equations (PDEs) that is based on online/adaptive learning. It is applied in the context of multiphase...
Earthquake location and magnitude estimation using seismic arrival times pattern and gradient boosted decision trees
December 2025
We present a machine learning approach for earthquake location and magnitude estimation based on seismic arrival time patterns, using Histogram-Based Gradient Boosting for its high accuracy and computational...
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...