... features (RCF), represented by the variance in photoelectric factor well log measurements (PEF) within sliding windows. To capture depth-by-depth variability in rock fabric by a unique value, we employ principal component analysis (PCA) sampling required for laboratory measurements. A representative...

... enkf spwla-2024-0127 assimilation wellbore integrity th annual logging symposium eccentricity inspection artificial intelligence machine learning koopman operator spwla 65 variance SPWLA 65th Annual Logging Symposium, May 18 22, 2024 DOI: 10.30632/SPWLA-2024-0127 THROUGH-TUBING CASING...

... relationships between the API gravity and SPWLA 65th Annual Logging Symposium, May 18-22, 2024 different ratios of selected time sections across the spectra. Fig. 9 Principal component analysis to capture the total data variance in the GPC-UV/vis dataset. Fig. 8 Pearson correlation coefficient matrix where...

... rock type allocation biogeochemistry geological subdiscipline spwla-2023-0083 geologist asia government sedimentary geology ems jurassic variance algorithm applicability doi accuracy reservoir surveillance reservoir characterization th annual logging symposium alkylbenzene scenario...

... producibility are devised. machine learning Upstream Oil & Gas correlation well logging basis signal Artificial Intelligence petrophysical evaluation porosity log analysis Pore System variance gas well contribution bitumen evaluation basis map Vaca Muerta Symposium spwla 58 Oil...

.... Graphically, PCA rotates the original axis of the data to the direction having maximum variance. New attributes are created as a result which are linear combination of existing variables. These new attributes are orthogonal and unrelated to each SPWLA 58th Annual Logging Symposium, June 17-21, 2017 8 other...

... & Gas Freedman signal model workflow Artificial Intelligence variance amplitude vector magnetization regularization parameter algorithm multidimensional inversion machine learning Bayesian Inference NMR measurement permeability sparse Bayesian vector Symposium matrix venkataramanan...

... on calibration and verification of depth associated measurements and more rigorous application of basic correction methodologies, quantification of the uncertainty in wireline depth measurements can be significantly improved. data quality calibration spwla 56 well logging variance coefficient...

... of the Allan variance (AV) to characterize heterogeneity field-wide from open hole or cased hole logs. A key advantage of the AV over other available indices is that the AV is presented as a function of reservoir thickness and converges for a number of signal distributions, including random walk, flicker...

... uncertainty. These tests utilize our a priori expectations of the statistical distribution of the pressure data to aid in finding outliers. Reservoir Characterization Artificial Intelligence Upstream Oil & Gas machine learning structural geology midpoint variance calculation linear fit...

... well logging uncertainty range log analysis petrophysical uncertainty evaluation Upstream Oil & Gas Thickness regression Simulation contribution Symposium variance dependency statistical analysis density log variation range uncertainty factor determination petrophysicist...

.... log analysis Upstream Oil & Gas variance spectral component well logging resolution noise ratio data quality frequency variation Artificial Intelligence detector noise grid impulse response response function optimally resolution length Symposium data density Drilling...

... . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7) The variance of this measurement is the square of the standard deviation and is written as U2.When performing weighted least-squares fitting, the fit is weighted by the variance of the data being fit. For solving Eq. 4, the weight matrix is a diagonal matrix W where the diagonal terms have...

..., and hydrocarbon density as the unknowns. Analysis of this interval by ULTRA with a conventional shaly-sand model yielded apparently reasonable answers, but theoretical and actual logs showed gross variance. The variance indicates that the apparently reasonable results are not correct. The premise of ULTRA...