... , flow in porous media aperture dimensionless coefficient experiment Fluid Dynamics regime inertia regime hydraulic fracturing roughness correlation Upstream Oil & Gas flow rate pressure drop fracture non-darcy regime coefficient Zimmerman equation auriault fracture permeability...

... serve as a practical resource for drilling through the Hartha formation. well control machine learning Artificial Intelligence Upstream Oil & Gas Leverage plot Polymer Mud fcl mud drilling operation operational drilling parameter ROP model ECD model coefficient drilling fluids...

... field data measurements. ANN was able to predict the rheological properties on a real time with a high accuracy. Four new empirical correlations were developed to predict PV, AV, YP, and n. The accuracy of these correlations are very high (correlation coefficient (CC) greater than 90% and the average...

... into the correlation among the dimensionless starting time of quasi-radial flow, the dimensionless wellbore storage coefficient and skin factor. A formal formula of the dimensionless starting time of quasi-radial flow is determined. The on-site data show that the above formula has been successfully applied...

... The strength of ANN is its capability to find a correlation between input and output. This correlation consists of several connections called neurons that represent coefficients and weight factors. Developing such neurons requires a large number of internal iterations and data processing, which include a lot...

.... The model requires some experimental work to get the regression coefficients. The percentage of limestone and dolomite must be known to use this model. Furthermore, the optimum injection rate can be estimated using Eq. 3 : (3) q c r t = 2.155 k 1 14 ( μ ρ ) 2...

.... This failure criterion is mainly contributed from the cohesion and coefficient of internal friction parameters, which are determined by laboratory measurements. The laboratory measurements, although more reliable, are expensive and time-consuming. This paper discusses artificial intelligence models...

... empirical models based on average absolute error and coefficient of determination. The analysis of the outcome of this work shows that the new model predicts oil flow rate with an accuracy of 98%, interestingly, example of such accuracy is not found in the current literature. The results of this study show...

... empirical models. The result showed that FN methods outperformed all the fracture pressure equations by high margin (very high correlation coefficient (R) of 0.986 and a very low average absolute percentage error (AAPE) of 0.201). the developed technique will help the drilling engineers to design the cement...

... of the local permeabilities, calculated on each line of cells parallel to the given direction (lower bound). The idea is to take a value between these two bounds, and the weighting coefficient is the key for accurate results. We presented a fast algorithm to estimate the weighting coefficient in the sense...

... method estimated the formation pressure with a high accuracy (high correlation coefficient (R) of 0.998 and low average absolute percentage error (AAPE) of 0.234%). FL outperformed all previously published models. The advantage of the new technique is its simplicity, which represented from its estimation...

... model FNBEM, forward backward model FNFBM and backward forward model FNBFM. Then based on correlation coefficient R and average absolute percentage error AAPE, a comparison was made and the one which performed better was selected for prediction of sonic wave transit times. The novelty of this work...

... contributes towards the success of specialized studies, e.g. SCAL tests, Enhanced Oil Recovery and Acid Treatment. To examine the level of heterogeneity of rock samples on the basis of CT numbers, this study focuses on the application of statistical parameters, including Coefficient of Variation (CV...

... wells located in giant carbonate reservoir. A comparison between the predicted failure parameters by the proposed models with actual laboratory measured data reveals that new proposed model predicted with significantly less average absolute percentage error (AAPE) and high coefficient of determination...

... − α ( ∂ p ∂ x ) where 0 ≤ α ≤ 1 and k α is a phenomenological coefficient (pseudopermeability) with dimension L 2 T 1-α . Equation (1) indicates the volumetric flux is time-dependent, such flux relationship accounts for delays in fluid propagation through the porous...

..., 21 cases were run with different combination of input parameters. Good agreement was observed between the SVR-predicted UCS and the laboratory measurement. Two quantitative measures for estimation accuracy are calculated and examined including the coefficient of determination and the mean absolute...

... production monitoring Upstream Oil & Gas information diameter confidence level coverage factor equation discharge coefficient production logging Contributor sensitivity coefficient standard uncertainty field operation society of petroleum engineers independent variable uncertainty...

... of maturity (LOM), where these models assumed a linear relation between resistivity and porosity logs. The average absolute deviation (ADD) of the previous model was not less than 1.20wt% of TOC with a coefficient of determination (R 2 ) of less than 0.85. The objective of this research is to develop new...

... viscosity average absolute error actual value apparent viscosity artificial neural network flow behavior index coefficient machine learning drilling fluids and materials plastic viscosity mud density invert emulsion correlation coefficient fluid density society of petroleum engineers fluid...

... coefficient. The mass-transfer coefficient and the effective dispersion coefficients are defined as follows: (6) Sh = 2k c r p D m = Sh ∞ (7) D eR = α OS D m + 2λ R | U | r p ϵ (8) D eT = α OS D m...