... , is given by Eq. (10) . Once the phase behavior is determined and physical properties are obtained from PR-VT EOS, the dynamic viscosities of phases are predicted via LBC viscosity correlation. We adopt the standard format to calculate the viscosity of mixture, μ , as Eq. (6) . LBC viscosity...

... values. The results showed that all rock samples achieved initial water saturation (S wi ) in the range of 18-32% with no correlation between S wi and rock permeability. In addition, spontaneous imbibition tests showed slight oil production which reflect the oil-wetness of these cores used...

... distribution. Correlations between model parameters and rock properties (i.e., porosity, permeability, and texture) were derived, which could be used to predict capillary pressure curves from porosity and permeability in relatively less heterogeneous RRTs. Rock types were successfully classified within...

... Regression models (GPR) correlate features and permeability well. For the tested heterogeneous core plugs, the exponential Gaussian Process model performs the best. The R-Squared values of the three sets of training data are 0.88, 0.87 and 0.91 respectively. Afterwards, the selected ML model was tested...

... resonance (NMR), which involves applying a magnetic field to the formation and detecting signals emitted from pore spaces. The main objective of this study is to develop an empirical correlation for porosity, permeability, and irreducible water saturation by comparing NMR and laboratory measurements...

... studies. The current correlations are restricted by the use of sample from a particular field. As the physical properties and the composition of the crude oil varies the results becomes erroneous after a specific range. This correlation will give results only over a specific range of properties like...

..., and geologicalwise. Ultimately, an equation to correlate between the results was developed graphically and using logistic regression techniques. permeability flow in porous media equation probe permeameter upstream oil & gas machine learning darcy asia government permeameter spe formation...

... management reservoir simulation reservoir characterization netherlands government injection chemical flooding methods tubing correlation diameter permeability realization subsurface storage artificial intelligence machine learning workflow co2 injection experiment united states government...

... As part of this study, different ML algorithms were used for outlier detection, core data clustering and analytical saturation function coefficients correlation to the petrophysical properties. These algorithms are briefly described hereunder. Outlier Detection Abstract Capillary...

... paraffin remediation abu dhabi international petroleum exhibition conference asphaltene precipitation experiment reproduce correlation asphaltene envelope Overall Workflow Introduction Many crudes in the Middle East are naturally unstable with respect to asphaltenes, and asphaltene...

... characterization exhibition huban eage conference complex reservoir inversion acquisition interpretation correlation late jurassic carbonate reservoir non-repeated obc geometry seismic acquisition brechet simulation seismic monitoring lafram repeatability noise phase-1 sequence Abstract...

... this novel approach. Real-time density/neutron does not have good correlation with modelled density /neutron due to gas effect. Such poor correlation can be attributed to proximity to a Gas Oil Contact (GOC) and dynamic invasion, complicating the real-time geo-steering. However, real-time total porosity from...

... aiming to obtain unbiased parameters which are blind to well control. Finally, using elastic properties constrained at the well locations, the joint geostatistical inversion was run to obtain multiple realizations of P-impedance, S-impedance, density and lithofacies. The cross-correlation between seismic...

... Intelligence (AI) supporting operations geologist during drilling phases. Two different tools have been created: litho-fluid interpretations, a set of AI algorithms used to identify in real-time the lithology and to interpret the formation fluids; well-to-well log correlation and look ahead, models used...

.... Reservoir Characterization Artificial Intelligence Fluid Dynamics water saturation flow in porous media Leverett porosity capillary pressure curve interfacial tension Engineer saturation-height function permeability Upstream Oil & Gas correlation transition zone saturation equation...

... and Soave-Redlich-Kwong EOS. Third, statistical analysis is performed to determine the level of confidence of the different methods. Fourth, a correlation to determine the optimal number of pseudo-components is defined. These steps include: Characterization of fluid and heavy components Tuning...

... and Production logging information. This approach has allowed to obtain a Karst/No Karst Supervised dataset for about 60 wells. In the second phase different seismic and geological attributes have been considered in order to investigate possible correlations with karst features. In fact there are some...

... Abstract This study examines which is the margin of usability for Artificial Intelligence (AI) algorithms related to the rock properties distribution in static modeling. This novel method shows a forward modeling approach using neural networks and genetic algorithms to optimize correlation...

... where multipliers W i are history matching parameters and PERMX is the permeability along X. Artificial Intelligence evolutionary algorithm flow in porous media Fluid Dynamics correlation Upstream Oil & Gas perm-poro relationship porosity reservoir simulation permeability value...

... in formation evaluation than horizontal wells and pose less problematic to the property assignment of the grid cells [ 2 ]. In this case study, the static model coverage is limited to one reservoir with 12 vertical/low deviated wells penetrating this reservoir. The first step is to correlate the 3D...