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...
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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....
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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)...
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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...
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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...
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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...
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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...
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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...
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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...
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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...
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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...
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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...
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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...
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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...
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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...
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Understanding hydrological responses through LULC analysis and predictive modelling (MLPNN-MC Model): A study of Bandu Sub-watershed (India) over three decades
December 2025
•Bandu sub-watershed in Purulia district was categorized into eight distinct LULC classes using Google Earth Engine.•Thirty years of decadal transformations (1992–2022) predicts future LULC scenarios...
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Machine learning assisted enhancement of petrophysical property dataset of fractured Variscan granites of the Cornubian Batholith, SW UK
Available online 22 August 2025
Outcrop analogue studies play an important role in advancing our comprehension of reservoir architectures, offering insights into hidden reservoir rocks prior to drilling, in a cost-effective manner....
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Convolutional sparse coding network for sparse seismic time-frequency representation
June 2025
Seismic time-frequency (TF) transforms are essential tools in reservoir interpretation and signal processing, particularly for characterizing frequency variations in non-stationary seismic data. Recently,...
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Loosening rocks detection at Draa Sfar deep underground mine in Morocco using infrared thermal imaging and image segmentation models
June 2025
Rockfalls are among the frequent hazards in underground mines worldwide, requiring effective methods for detecting unstable rock blocks to ensure miners' and equipment's safety. This study proposes...
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Optimizing zero-shot text-based segmentation of remote sensing imagery using SAM and Grounding DINO
June 2025
The use of AI technologies in remote sensing (RS) tasks has been the focus of many individuals in both the professional and academic domains. Having more accessible interfaces and tools that allow people...
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Applying deep learning to teleseismic phase detection and picking: PcP and PKiKP cases
June 2025
The availability of a tremendous amount of seismic data demands seismological researchers to analyze seismic phases efficiently. Recently, deep learning algorithms exhibit a powerful capability of detecting...
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Innovative cone resistance and sleeve friction prediction from geophysics based on a coupled geo-statistical and machine learning process
June 2025
Geotechnical parameters derived from an intrusive cone penetration test (CPT) are used to asses mechanical properties to inform the design phase of infrastructure projects. However, local, in situ 1D...
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Robust low frequency seismic bandwidth extension with a U-net and synthetic training data
June 2025
This work focuses on enhancing low frequency seismic data using a convolutional neural network trained on synthetic data. Traditional seismic data often lack both high and low frequencies, which are...
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Microseismic moment tensor inversion based on ResNet model
June 2025
This paper proposed a moment tensor regression prediction technology based on ResNet for microseismic events. Taking the great advantages of deep networks in classification and regression tasks, it...
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Enhancing understanding of 3D rectangular tunnel heading stability in c-φ soils with surcharge loading: A comprehensive FELA analysis using three stability factors and machine learning
June 2025
This study examines the stability of three-dimensional rectangular tunnel headings in drained c-ϕ soils, incorporating surcharge effects using 3D Finite Element Limit Analysis (FELA). It focuses on...
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