... Abstract Lithofacies represent stratigraphic structure information with high resolution, but the accuracy of lithofacies analysis is often largely affected by the complexity of geological environment. In recent years, machine learning has received increasing attention due to its feasibility...

... us government accuracy drilling measurement lwd calculation well trajectory boundary logging while drilling azimuthal resistivity lwd data spwla 63 rd annual logging symposium algorithm stochastic inversion drilling data acquisition upstream oil & gas well target vendor...

... network structure of LSTM and CNN can fully examine the internal relationships and sequence characteristics of log curves. The weighted cross-entropy loss function significantly improves the fluid identification accuracy of oil-bearing reservoirs. Moreover, the multi-level reservoir identification method...

... facies schlumberger pca accuracy spwla 63 limestone final classification tsne matrixe interpretation rd annual logging symposium artificial intelligence classification variation workflow original classification spwla-2022-0129 SPWLA 63rd Annual Logging Symposium, June 10-15, 2022 DOI...

... drilling fluid management & disposal real time system well logging equation of state pvt measurement log analysis drilling fluids and materials pvt sample threshold mud gas spwla-2022-0007 composition castberg field accuracy prediction spwla 63 machine learning artificial...

... upstream oil & gas annual logging symposium pixel machine learning accuracy spwla 63 artificial intelligence classifier workflow lithofacies predictor feature ct-scan image rock classification algorithm core photo permeability spwla-2022-0018 vertical resolution rd annual...

... well logging log analysis machine learning artificial intelligence reservoir characterization neural network spwla-2022-0082 statistical fluctuation formation condition structural geology annual logging symposium spwla 63 interpretation spectrum east china deep learning accuracy...

... by direct 4 SPWLA-2021-0051 SPWLA 62nd Annual Logging Symposium, May 17-20, 2021 from the two training wells. The preprocessing of the Figure 4: - Cross validation plot indicating minimal training data set included standard scaling of each number of features required for maximum accuracy. input variable...

... techniques in the subsurface domain, it is essential that the quality of the input data is carefully considered when working with these tools. If the input data is of poor quality, the impact on precision and accuracy of the prediction can be significant. Consequently, this can impact key decisions about...

... of fast pressure structures. Petrophysicists are utilizing core data to decay matrix permeability from intact rock. calibrate their log interpretations for predictive models. As a result, the accuracy of core data, including The workflow starts with acquisition of NMR T2 and assessment of total porosity...

..., and etc. We employed 5 various machine learning algorithms for comparison, among which BiLSTM showed the best performance with an R-squared of more than 90% and an RMSE of less than 10. The predicted results can be directly used to calculate geomechanical properties, of which accuracy is also improved...

... to identify the geological concept near the horizontal well section using multiscale data. The accuracy of modeling depends on the details of the accepted geological model based on the data of borehole images, logs, geosteering inversion, and seismic data. 3D modeling can be applied to improve the accuracy...

... analysis spwla 62 annual logging symposium cement thickness artificial intelligence accuracy mayir mamtimin machine learning upstream oil & gas layer-1 density detector count rate layer-2 density algorithm spwla-2021-0067 well logging layer density compton nd annual logging symposium...

... ring accuracy spwla-2021-0066 artificial intelligence count rate cement ring thickness forward model casing thickness thickness formation density cement ring density SPWLA 62nd Annual Logging Symposium, May 17-20, 2021 DOI: 10.30632/SPWLA-2021-0066 THEORETICAL METHOD AND EXPERIMENTAL...

... log analysis drilling measurement machine learning well logging lwd artificial intelligence upstream oil & gas drilling operation accuracy reservoir navigation spwla 62 drilling data acquisition logging while drilling geosteering nd annual logging symposium tool response...

... its high accuracy of ±5% or less for resistivity below 10 ohm.m at a resolution of 0.001 ohm.m. The design eliminates any dead volume and all flowline fluid passes through the sensor. The sensor tube is smoothly flushable for fast dynamic response in multiphase slug flow. This paper also discusses...

... element and mineral fraction measurements on core, for a mineralogically complex formation in the Norwegian North Sea. The goals were to: (1) Assess the accuracy of dry-weight element and mineral fractions measured on core, which typically are assumed to be the ground-truth against which to validate logs...

... ABSTRACT Depth is the most fundamental subsurface measurement made in our business. Logging while drilling depths are based on driller's depths. Driller's depths have been plagued with accuracy issues, with numerous articles highlighting this. Driller's depth measurement is based...

... and accuracy of a Fourier transform infrared spectrometer using a partial least squares regression. MOC performs an analogue dot product regression in the optical domain, which uniquely suits MOC to enable high resolution mid-infrared spectroscopy at high temperature. This is particularly important...

... high values of coefficient of determination. The small error and high values of coefficient of determination denote the SVR models good performances. The prediction accuracy improves as more data are included to train the algorithm. From the comparison of SVR-kernel-function-based models, we observe...