... machine learning chlorite template log analysis mudstone th annual logging symposium rock type spwla 64 well logging depositional environment geological subdiscipline calculation spwla-2023-0104 doi fandango field crossplot sandstone seismic model reservoir characterization porosity...

... logging / surface measurements risk management dataset log analysis information stratigraphy interpretation geochemical characterization machine learning spwla 64 spwla-2023-0107 workflow turkiye university norway government drilling fluid management & disposal biogeochemistry...

... with interpreter-defined polygons, and unsupervised machine learning algorithms, such as principal component analysis and cluster analysis. A significant shortcoming for all of these methods is that the calculated volumes for each fluid are simply the cumulative sum of the amplitudes that are contained within...

... of coordinates in a T 1 - T 2 map. sedimentary rock geologist united states government complex reservoir geology workflow artificial intelligence machine learning reservoir characterization interpretation annual logging symposium rock type log analysis fraction upstream oil & gas...

... machine learning gamma spectrum spwla 64 coefficient resolution elemental concentration inelastic gamma spectra annual logging symposium spwla-2023-0120 algorithm fraction th annual logging symposium inelastic gamma spectrum silicon SPWLA 64th Annual Logging Symposium, June 10-14, 2023 DOI...

... mineral neural network upstream oil & gas asia government rock type europe government well logging logging while drilling log analysis machine learning spwla-2023-0121 spwla 64 annual logging symposium porosity detector dry-weight fraction spectroscopy detector fraction artificial...

... shale automated vsh quantile machine learning spwla-2023-0123 spwla 64 algorithm gr ss equation lfi radioactivity SPWLA 64th Annual Logging Symposium, June 10 14, 2023 DOI: 10.30632/SPWLA-2023-0123 ROBUST AND AUTOMATIC SHALE VOLUME INTERPRETATION USING ADAPTIVE LITHOLOGICAL THRESHOLDS BUILT...

... of logging data. Manual log interpretation relies on geophysical mechanism and logging data, which are complex. The interpretation expert's subjectivity will determine the interpretation results, and the analysis of the data set using novel data analysis and processing tools, such as machine learning...

... government log analysis machine learning evaluation matrix spwla 64 concentration contribution robustness interpretation fraction compositional matrix SPWLA 64th Annual Logging Symposium, June 10-14, 2023 DOI: 10.30632/SPWLA-2023-0126 ACCURATE MINERALOGY WHEN LOGS ARE SCARCE OR OF LIMITED...

... artificial intelligence contamination absorbance baker hughe co asia government th annual logging symposium filtrate prediction sefer coskun spwla 64 cleanup junjie yang united states government machine learning cleanliness formation fluid sampling anup hunnur emiliano hall SPWLA 64th...

... on the accuracy of different rock typing methods. To achieve this objective, geological, petrographic, and petrophysical analysis was performed using well logs, core analysis, and thin sections. The analysis results were used to evaluate geological, petrophysical, and machine learning-based rock types...

... and closed fractures. Simple cutoff methods are widely used for lithofacies identification and facies classification, which can be a time-consuming task. However, this work presents an automated machine learning based electro-facies classification using a combination of resistivity and permittivity dominated...

... ABSTRACT Global equations for predicting GOR , API gravity and saturated viscosity from downhole testing and sampling measurements have been developed using a symbolic regression (SR) machine learning method. Nearly 700 fluid samples collected from more than 500 wells from many parts of world...

... applications in dynamic contamination level monitoring and corrosive chemicals detection. artificial intelligence spectral library upstream oil & gas well logging united states government log analysis absorbance spectra spectra machine learning th annual logging symposium spwla 64...

..., the color is treated as background and removed; fortunately, oil coloration obeys a simple functional relationship, the "Urbach tail" from solid state physics (Mullins, 2008). geologist united states government geology equation of state pvt measurement artificial intelligence machine learning...

... sampling programs over the years, but this application is not limited to exploration wells. A technique presented by Yang et al., 2019 has demonstrated the potential of machine learning predictions using EEC compositional data. More recently, results shared by Kopal et al., 2022 demonstrate...

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... intelligence spectra doi machine learning upstream oil & gas deep learning well logging neural network nmr application university log analysis th annual logging symposium dataset resonance regularization spwla 64 noise spectrum inversion spwla-2023-0026 journal snr SPWLA 64th...

... measurement dataset logging while drilling drilling data acquisition real time system upstream oil & gas lwd log analysis machine learning information application generator spwla 64 resistivity electrode augmentation gan lwd real time image spwla-2023-0037 fracture resolution...

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