... region were deployed to construct the principal component space to reassess the previous system, and then all principal components were projected onto the T 2 and SPE equations to determine their control limits. Once this robust predictive model was built, any new input vector at any time step could...

... temperature to other temperatures is achieved using dimension reduction approach involving principal component analysis (PCA) technique. It is found that the T 2 distributions at any given temperature for both the high- and low-quality carbonate reservoirs can be predicted robustly from the T 2...

... and tightening, sand production and hole pack-off. machine learning artificial intelligence principal component complex reservoir upstream oil & gas shale gas strength shale gas reservoir evaluation compressive strength multivariate regression analysis assessment acoustic dataset wave...

... decision tree algorithm RPM Artificial Intelligence principal component ROP stick slip vibration drill string society of petroleum engineers Introduction Two kinds of vibration are of significant concern. First is Stick-Slip. In this case, the bit periodically stops rotating in a torque up...

... learning Artificial Intelligence principal component prediction performance size distribution well logging Fluid Dynamics NMR measurement geometric mean new core sample permeability model initial core sample log analysis Upstream Oil & Gas RBF mapping function porosity core data sample...

... costs, and optimize production. artificial lift system ESP operation time step real time data mining principal component contribution big data ESP performance operation Time Period Upstream Oil & Gas information t-square statistic corrective action decision variable impending...

... production profiles in the field. Principal component analysis can be applied to the functional data, termed (fPCA). Applying fPCA to declining rates from many wells, transforms time varying data into lower-dimensional score data. We found that in the real field data studied, 2-3 such functional principal...

... in the short term. Thus, the impact of the transport processes within the slower domain depends primarily on the transport rate within the faster domain; this is referred to as hierarchical dependence. The principal component analysis (PCA) method was applied to study the continuous movement of the pressure...

... such as principal component analysis (PCA) and cluster analysis. Finally, in the Ranking step, we apply a similarity function to the group of previously selected "analogous reservoirs", generating a similarity ranking of analogous reservoirs. To validate this new method we use the Casablanca oil field as a target...

... the problem we may need to reduce the number of features, using feature selection techniques or dimension reduction techniques, like principal component analysis or nonlinear techniques. The data would then be ready for pattern recognition techniques like clustering, classification and regression...

... in a petrophysical sense is also a better gas producer. upstream oil & gas toc lithofacies petrofacies 1 dataset petrofacies permeability principal component porosity perforated interval petrofacies 2 reservoir characterization barnett shale rock type hg rock type capillary pressure curve...

... is rotated to the principal coordinate system. This rotation is characterized by three angles: ?, ?, and ?; and three principal, diagonal magnetic field components Hxx, Hyy, and Hzz. After the three angles and three principal components are determined, we recover principal formation resistivities using...

...) were analyzed using several statistical methods: analysis of variance, multivariate correlations, cluster analysis, and principal component analysis. The analyses revealed a number of interesting trends. For example, the water drop and oil dryness parameters were found to be more independent of one...

... information instrumented oilfield frequency spectrum upstream oil & gas production control sensor prediction production monitoring frequency spectra variability frequency component configuration amplitude technical conference acoustic noise principal component choke valve completion...

... of the immiscible WAG process. Simulation studies have shown how three-phase flow description may influence the choice of drive mechanisms and also the design of a WAG process. Furthermore, a principal component analysis (PCA) is conducted on the simulation model that is consistent with the experimental data...

... but follows naturally based on the unique characteristics of well log measurements reflecting minerals and lithofacies within the logged interval. A combination of principal component analysis, model-based cluster analysis and discriminant analysis is used to characterize and identify electrofacies types...

... showing principal components. Figure 2 - Trip-out sequence showing relative positions of principal component as hoisting and rsmoval of drill pipe is accomplished. I 1 :, 1.1; 4J. , .. . r 0.! A M - 3!_w u? CWJCA Lo#SR JAdS KAAE UP CHUCK ToRL. ARM TA CLWP3 u-13-66 Figure 3...