Estimation of Variable Fluid-Mixture Density With 4D-NMR Logging

2008 ◽  
Vol 60 (08) ◽  
pp. 59-62
Author(s):  
Dennis Denney
2007 ◽  
Author(s):  
Chanh Cao Minh ◽  
Emmanuel Caroli ◽  
Padmanabhan Sundararaman
Keyword(s):  

2000 ◽  
Vol 122 (2) ◽  
pp. 71-77 ◽  
Author(s):  
Mamdouh M. Salama

The current practice for eliminating erosional problems in piping systems is to limit the flow velocity Ve to that established by the recommended practice API RP 14E based on an empirical constant (C-factor) and the fluid mixture density ρm as follows: Ve=C/ρm. The API criterion is specified for clean service (noncorrosive and sand-free), and it is noted that the C-factor should be reduced if sand or corrosive conditions are present. The validity of the equation has been challenged on the basis that the API RP 14E limits on the C-factor can be very conservative for clean service and is not applicable for conditions when corrosion or sand are present. Extensive effort has been devoted to develop an alternative approach for establishing erosional velocity limits for sand-laden fluids. Unfortunately, none of these proposals have been adopted as a standard practice because of their complexity. This paper will review the results of these studies and proposes an alternative equation that is as simple as the API 14E equation. This alternative equation has the following form: Ve=SDρm/W. The value of the S-factor depends on the pipe geometry, i.e., bend, tee, contraction, expansion, etc. Using the units for mixture flow velocity Ve in m/s, fluid mixture density ρm in kg/m3, pipe diameter (D) in mm and sand production W in kg/day, the value of the S-factor is 0.05 for pipe bends. The accuracy of the proposed equation for predicting erosion in pipe bends for fluids containing sand is demonstrated by a comparison with several multi-phase flow loop tests that cover a broad range of liquid-gas ratios and sand concentrations. [S0195-0738(00)00202-8]


2021 ◽  
Author(s):  
Mohamed Eid Kandil

Abstract The mechanical properties of hydrocarbon reservoirs significantly depend on the elastic properties of the fluids occupying the pore space in the rock frame. Accurate data and models for the mechanical properties of fluid mixtures in a petroleum reservoir containing supercritical CO2 should be available at the same reservoir conditions for reliable design of well-completion, maximizing reservoir productivity, and minimizing risk in drilling operations. This work investigates the change in the bulk modulus of the higher hydrocarbon fluid (decane C10H22) after the injection with supercritical CO2 at reservoir conditions. The isothermal bulk modulus βT of liquids under pressure, simply defined as the first-order derivative of pressure with respect to volume, is determined in this study from the derivative of pressure with respect to density. The density data were obtained from experimental measurements of mixtures of supercritical CO2 + C10H22 for a range of CO2 mole fractions from 0 to 0.73, at temperatures from 40 to 137 °C and pressures up to 12000 psi. The isothermal derivative coefficients of the pressure as a function of density are reported for each CO2 concentration measured in this work. Common fluid-substitution models, including the Gassmann model, which is only valid for the isothermal regime, have limited predictive power because most fluids are treated as simple fluids, with their mechanical properties only characterized by their densities. However, under different environments, such as when supercritical CO2 is injected into the geological formation, the fluid phase and its mechanical properties can vary dramatically. At high pressure, the density of CO2 can equal to that of the hydrocarbon phase ρ(CO2)/ρ(C10H22) ≈ 1, while the bulk modulus of CO2 remains as low as only βT(CO2)/βT(C10H22) ≈ 7 %. Excessive decrease in the bulk modulus can easily cause subsidence, although the pore pressure and the fluid mixture density remain unchanged, even at pressures up to 4000 psi.


Author(s):  
Pedro Romero Rojas ◽  
◽  
Alexandrina Cristea ◽  
Paul Pavlakos ◽  
Okan Ergündüz ◽  
...  

1995 ◽  
Vol 60 (8) ◽  
pp. 1274-1280 ◽  
Author(s):  
Kamil Wichterle

Analysis of extended data on turbine impeller power input in geometrically similar agitated baffled tanks shows that the power number Po is a function of Reynolds number Po = Po*(Re) until the emergence of surface aeration. Though it is usually anticipated that Po* = const in high Reynolds number region, some, whatever weak, function should be taken into consideration in more detailed analysis of the power data even here. In practice, disturbances of level and gas captured in the impeller region play also a significant role, namely in smaller tanks at higher impeller speeds. Decrease of power input can be explained by decrease of gas-liquid mixture density, or in other words by increase of efficient gas holdup eE just in the impeller region. The value eE defined by the relation Po = Po*(Re)/(1 + eE) was determined from the available data. Like other effects of the surface aeration it depends mainly on the dimensionless number Nc = (We Fr)1/4. A simple correlation eE (Nc) is suggested as a correction factor for prediction of impeller power in presence of gas capture.


2010 ◽  
Vol 75 (3) ◽  
pp. 359-369 ◽  
Author(s):  
Mariano López De Haro ◽  
Anatol Malijevský ◽  
Stanislav Labík

Various truncations for the virial series of a binary fluid mixture of additive hard spheres are used to analyze the location of the critical consolute point of this system for different size asymmetries. The effect of uncertainties in the values of the eighth virial coefficients on the resulting critical constants is assessed. It is also shown that a replacement of the exact virial coefficients in lieu of the corresponding coefficients in the virial expansion of the analytical Boublík–Mansoori–Carnahan–Starling–Leland equation of state, which still leads to an analytical equation of state, may lead to a critical consolute point in the system.


Aerospace ◽  
2021 ◽  
Vol 8 (6) ◽  
pp. 152
Author(s):  
Micha Zoutendijk ◽  
Mihaela Mitici

The problem of flight delay prediction is approached most often by predicting a delay class or value. However, the aviation industry can benefit greatly from probabilistic delay predictions on an individual flight basis, as these give insight into the uncertainty of the delay predictions. Therefore, in this study, two probabilistic forecasting algorithms, Mixture Density Networks and Random Forest regression, are applied to predict flight delays at a European airport. The algorithms estimate well the distribution of arrival and departure flight delays with a Mean Absolute Error of less than 15 min. To illustrate the utility of the estimated delay distributions, we integrate these probabilistic predictions into a probabilistic flight-to-gate assignment problem. The objective of this problem is to increase the robustness of flight-to-gate assignments. Considering probabilistic delay predictions, our proposed flight-to-gate assignment model reduces the number of conflicted aircraft by up to 74% when compared to a deterministic flight-to-gate assignment model. In general, the results illustrate the utility of considering probabilistic forecasting for robust airport operations’ optimization.


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