Lithology Identification Method and Application Based on Generative Adversarial Neural Network
Cejing jishuLithology identification is the basis of reservoir evaluation and the key to reservoir parameter calculation and reservoir evaluation and development.
YIN Qiong
doaj +1 more source
Enhanced machine learning tree classifiers for lithology identification using Bayesian optimization
Applied Computing and Geosciences, 2022 Lithology identification is a fundamental activity in oil and gas exploration. The application of artificial intelligence (AI) is currently being adopted as a state-of-the-art means of automating lithology identification.
Solomon Asante-Okyere +2 more
doaj +1 more source
High‐elevation endemic plants predicted to lose habitat from changing climate in Washington State
American Journal of Botany, EarlyView.Abstract Premise High‐elevation plants face unique challenges from potential climate change impacts that will likely require upslope migration into increasingly smaller suitable habitat. This situation is particularly acute for endemic species that by definition occupy small geographic ranges.
Nicholas L. Gjording +4 more
wiley +1 more source
A lithology identification method while drilling based on KAN neural network
Meitan xuebaoLithology identification while drilling is an important geological guarantee means for transparent detection of coal mine geology. The traditional lithology identification method mainly relies on manual judgment, which relies on the accumulation of ...
Bo WANG +6 more
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Asia-Pacific Journal of Chemical Engineering, EarlyView.ABSTRACT Enhancing oil recovery (EOR) in mature reservoirs is hindered by high interfacial tension (IFT) and oil‐wet rock formations, especially under harsh, high‐salinity conditions. This study aims to overcome these limitations by synthesizing a novel carbon nanotube nanocomposite covalently grafted with polyethylenimine and non‐covalently ...
Mohamed Abu Shuheil +8 more
wiley +1 more source
Evaluation Techniques for Shale Oil Lithology and Mineral Composition Based on Principal Component Analysis Optimized Clustering Algorithm [PDF]
, 2023 Shale oil reservoirs are characterized by complex lithology, complex mineral composition and strong heterogeneity. This causes great difficulty in lithologic evaluation.
Wenyuan Cai +6 more
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A new occurrence of tetrapod footprints from the Late Triassic of the Candelária Sequence, Brazil
The Anatomical Record, EarlyView.Abstract The Hyperodapedon Assemblage Zone of the Candelária Sequence (Santa Maria Supersequence, Paraná Basin) preserves one of the most significant Late Triassic continental vertebrate assemblages in southern Brazil. Despite the relatively well‐documented body fossil record from this interval, ichnological records remain comparatively scarce.
Murilo Andrade‐Silva +1 more
wiley +1 more source
A machine learning lithologic identification method combined with vertical reservoir information
地质科技通报, 2023 Compared with coring data, well logging data contain much lithologic information with the advantages of strong continuity and low cost. The machine learning method is applied to explore the correlation between the log curves and the lithology of the ...
Chi Zhang +4 more
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Archaeological Prospection, EarlyView.ABSTRACT Rain‐induced erosion processes can severely damage Earthen archaeological sites. Huaca Chornancap (HCH; eighth–14th century ad) is a platform located in the Lambayeque region (Peru) exposed to seasonal rain due to El Niño Southern Oscillation (ENSO).
Luigi Magnini +5 more
wiley +1 more source
Well-Logging-Based Lithology Classification Using Machine Learning Methods for High-Quality Reservoir Identification: A Case Study of Baikouquan Formation in Mahu Area of Junggar Basin, NW China [PDF]
, 2022 The identification of underground formation lithology is fundamental in reservoir characterization during petroleum exploration. With the increasing availability and diversity of well-logging data, automated interpretation of well-logging data is in ...
Weifeng Li +4 more
core +1 more source