Viscosity of aqueous NaCl solutions in the temperature range 25?200 �C and in the pressure range 0.1?30 MPa

Kestin, J.; Shankland, I. R.

doi:10.1007/bf00507835

Cited by 63 publications

(54 citation statements)

References 20 publications

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“…The oscillating-disc viscometer used by Kestin et al (1977Kestin et al ( , 1981a; Grimes et al (1979) and Kestin and Shankland (1984b), and to measure the viscosity for aqueous electrolyte solutions at high temperatures and high pressures, is schematically shown in Figure 6.3.…”

Section: Methodsmentioning

confidence: 99%

“…Such a viscometer has been used by several researchers as an instrument for viscosity measurements (see, for example, DiPippo et al, 1966;Kestin et al, 1977Kestin et al, , 1978aKestin et al, ,b, 1980Correia et al, 1979;Correia and Kestin, 1980;Kestin and Shankland, 1981b, 1984band Krall et al, 1987, 1992. The theoretical and experimental problems of this technique have been discussed in detail elsewhere (Verschaffelt, 1915;Kestin et al, 1957aKestin et al, , 1958Kestin et al, , 1959Kestin et al, , 1981aNewell, 1959;Khalifa, 1976 andShankland, 1981b).…”

Section: Oscillating-disk Techniquementioning

confidence: 99%

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Viscosity

Abdulagatov

Assael

2008

Hydrothermal Experimental Data

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Section: Methodsmentioning

confidence: 99%

Section: Oscillating-disk Techniquementioning

confidence: 99%

Viscosity

Abdulagatov

Assael

2008

Hydrothermal Experimental Data

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“…Adams and Bachu (2002) compared the algorithms of Kestin et al (1981) and Phillips et al (1981), the pressure-corrected algorithm presented by McCain (1991) and the algorithm of Palliser and McKibbin (1998). In his study, Bachu (2002) mentions that only Kestin et al (1981) and Palliser and McKibbin (1998) algorithms accurately take the temperature, salinity and pressure dependencies into account over the range of reservoir conditions. This study also notes that Kestin et al (1981) algorithm seems to be the most versatile for the calculation of water viscosity.…”

Section: Viscositymentioning

confidence: 99%

“…In his study, Bachu (2002) mentions that only Kestin et al (1981) and Palliser and McKibbin (1998) algorithms accurately take the temperature, salinity and pressure dependencies into account over the range of reservoir conditions. This study also notes that Kestin et al (1981) algorithm seems to be the most versatile for the calculation of water viscosity. Another study by Spivey (2004) also states that the Kestin viscosity correlation agrees extremely well with the IAPWS correlation for the pure water viscosity.…”

Section: Viscositymentioning

confidence: 99%

“…This correlation has an estimated uncertainty of 0.5% for temperatures between 25 and 150° C and pressures up to 30 MPa and for a sodium chloride concentration between 0 and 5.4 moles/kg water. This validity range encompasses the required range of reservoir conditions, therefore the correlation given by Kestin et al (1981) is used for the estimation of the aquifer water viscosity in this thesis.…”

Section: Viscositymentioning

confidence: 99%

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Optimization of Geothermal-Well-Doublet Placement

Smit¹,

Salimi

Wolf

2014

Proceedings

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The lifetime of geothermal projects mainly depends on the thermal breakthrough (thermal breakthrough occurs when a cold water front reaches the producer). Currently, geothermal-energy production is marginally economical because of its uncertainties and risks associated with the subsurface such as lifetime, flow rate, temperature. Lifetime of a geothermal reservoir plays the most important role in the use of geothermal energy because it mainly determines whether or not geothermal-energy production is economically viable.Through optimization of the well positions from one or more geothermal doublets in a homogeneous or heterogeneous reservoir, the profitability of the project, which is largely dependent on the time of compositional breakthrough, temperature breakthrough and the rate of temperature decline, can be improved. This thesis studies optimization of the well positions such that the Net Present Value (NPV) of a project is maximized in a 2D geothermal reservoir for the selected heterogeneity structure. For this purpose an automated, gradient-based optimization method is used. The approach is based on the concept to surround the wells, whose locations have to be optimized, by so-called pseudo-wells. The reservoir simulations are performed using the Finite Element Method in the program COMSOL Multiphysics 4.2a. The major features of the simulation results are discussed in detail.The compositional front moves faster than the thermal front (the ratio of these two is the thermal retardation factor). Breakthrough of water with altered composition will therefore occur at an early stage in the doublet lifetime. Reservoir heterogeneities influence the time at which thermal and compositional breakthrough occur and also determine the rate at which temperature and composition decline after breakthrough. The temperature and compositional decline curves after breakthrough are generally steeper in a homogeneous reservoir than in a heterogeneous reservoir. Therefore, the thermal breakthrough does not necessarily mean the end of the lifetime of a doublet. It is also shown that the effect of heterogeneities on the thermal retardation factor is small.Three successful optimization sequences in two different reservoirs are described in this thesis. It is shown that, from an economical standpoint, is makes little sense to assume a doublet lifetime of more than 30 years. Furthermore, the effectiveness at which a geothermal doublet is able to deplete a reservoir (recovery factor) and profitability of a geothermal doublet are closely interlinked. However, a higher recovery factor does not necessarily mean that the doublet is more profitable and vice versa. There exists an optimum well spacing for doublets positioned in homogeneous reservoirs, such that additional gain of later breakthrough (when placing the production well further away from the injector) is negated by the loss in pressure support of the injection well. This optimum well spacing is found to be an important factor, influencing the profitability in homogeneous...

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High‐Performance MXene Hydrogel for Self‐Propelled Marangoni Swimmers and Water‐Enabled Electricity Generator

Zhou,

Zhang,

Zhang

et al. 2024

Advanced Science

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Developing multifunctional materials that integrate self‐propulsion and self‐power generation is a significant challenge. This study introduces a high‐performance MXene‐chitosan composite hydrogel (CM) that successfully combines these functionalities. Utilizing Schiff base bond and hydrogen bond interactions, the CM hydrogel, composed of chitosan, vanillin, and MXene, achieves exceptional self‐propulsion on water driven by Marangoni forces. The hydrogel demonstrates rapid movement, extended operation, and controllable trajectories. Notably, the CM hydrogel also exhibits superior degradability, recyclability, and repeatability. Furthermore, the nano‐confined channels within the hydrogel play a crucial role in enhancing its water‐enabled electricity generation (WEG) performance. By efficiently adsorbing water molecules and selectively transporting cations through these channels, the hydrogel can generate electricity from water molecules and cations more efficiently. As a result, the CM‐WEG achieves a stable open‐circuit voltage of up to 0.83 V and a short‐circuit current of 0.107 mA on seawater, with further improvements in K2CO3‐containing water, reaching 1.26 V and 0.922 mA. Leveraging its unique combination of self‐propulsion and WEG functionalities, the CM hydrogel is successfully used for cargo delivery while simultaneously powering electronic devices. This research represents a significant step toward the development of self‐powered, autonomous soft robotics, opening new research directions in the field.

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Viscosity of aqueous NaCl solutions in the temperature range 25?200 �C and in the pressure range 0.1?30 MPa

Cited by 63 publications

References 20 publications

Viscosity

Viscosity

Optimization of Geothermal-Well-Doublet Placement

High‐Performance MXene Hydrogel for Self‐Propelled Marangoni Swimmers and Water‐Enabled Electricity Generator

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