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Keywords: machine learning
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Proceedings Papers

Paper presented at the SPWLA 66th Annual Logging Symposium, May 17–21, 2025
Paper Number: SPWLA-2025-0015
.... Based on measurements of these sensors, the machine learning method is then utilized to obtain fluid compositions, gas-oil ratio (GOR) and phase fractions. Furthermore, application of artificial intelligence to real-time fluid identification is presented in detail based on downhole optical data measured...
Proceedings Papers

Paper presented at the SPWLA 66th Annual Logging Symposium, May 17–21, 2025
Paper Number: SPWLA-2025-0017
... rock variation rock texture rock class plane investigation pixel annual logging symposium spwla-2025-0017 geological subdiscipline textural feature spatial variation heterogeneity tensor well logging feature contrast machine learning rock slice square window assessment rock image...
Proceedings Papers

Paper presented at the SPWLA 66th Annual Logging Symposium, May 17–21, 2025
Paper Number: SPWLA-2025-0018
... their diagnostic capabilities. geology geologist fluid dynamics flow in porous media well logging artificial intelligence formation testing log analysis model machine learning stabilization spwla 66 efficiency decision-making real time system spwla-2025-0018 buildup stabilization time...
Proceedings Papers

Paper presented at the SPWLA 66th Annual Logging Symposium, May 17–21, 2025
Paper Number: SPWLA-2025-0020
.... The predictive accuracy of the model will increase through feedback iteration because the discriminator assesses the authenticity of the generated data. The results of the study show that well logs generated by the GAN have high accuracy compared to traditional machine learning methods, even in complex...
Proceedings Papers

Paper presented at the SPWLA 66th Annual Logging Symposium, May 17–21, 2025
Paper Number: SPWLA-2025-0039
... logging log analysis sedimentary rock salt tectonics porosity machine learning total porosity geological subdiscipline spwla-2025-0039 resolution equation structural geology artificial intelligence reservoir geomechanics amplitude permeability carbonate impedance reservoir...
Proceedings Papers

Paper presented at the SPWLA 66th Annual Logging Symposium, May 17–21, 2025
Paper Number: SPWLA-2025-0041
... carbonate reservoir complex reservoir dolomite machine learning spwla 66th dissolution pore structure artificial intelligence geological subdiscipline porosity micp data permeability prediction sedimentary geology core analysis reservoir characterization annual logging symposium spwla-2025...
Proceedings Papers

Paper presented at the SPWLA 66th Annual Logging Symposium, May 17–21, 2025
Paper Number: SPWLA-2025-0048
... (Torres Caceres et al., 2022). While machine learning offers alternatives, supervised approaches demand large labeled datasets, and unsupervised clustering requires extensive post-processing, introducing potential errors (Acharya and Fabian, 2024b; Acharya et al., 2025). This study proposes a Siamese...
Proceedings Papers

Paper presented at the SPWLA 66th Annual Logging Symposium, May 17–21, 2025
Paper Number: SPWLA-2025-0049
... extreme-value (GEV) CDF-PDF. Optimized fitting parameters from GEV, including location ( μ ), scale ( σ gev ), and weighting constraints, served as inputs for machine-learning methods to estimate permeability. Ridge regression, random forests, and artificial neural networks (ANNs) were applied...
Proceedings Papers

Paper presented at the SPWLA 66th Annual Logging Symposium, May 17–21, 2025
Paper Number: SPWLA-2025-0051
...-consuming and rely heavily on the expertise of analysts, which can lead to variability in results. Recent advances in AI have enabled deep learning models to automate corrosion detection. Al-Khalidi and Abdulsadda (2024) examine efficient machine learning techniques that lower operational costs. However...

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