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Hoek van Holland, Netherlands

Van Der Zwan S.,Deltares | Toussaint M.,Deift University of Technology | Alidai A.,Deltares | Alidai A.,Technical University of Delft | And 3 more authors.
BHR Group - 12th International Conference on Pressure Surges | Year: 2016

A surge vessel is a common surge protection device in pipeline systems. The size of surge vessels is determined in mos cases through a hydraulic study in which water hammer software is utilized to simulate the hydraulic behaviour of the system The software models the behaviour of a surge vessel according to the ideal gas law and polyiropic expansion and compression of the air pocket. For a proper design, the two extremes, adiabatic and isothermal expansion of the air, are laken into account This is needed since the actual behaviour is not known and depends on the insulation of the vessels, variation in ambient temperature and many more heat transfer processes inside the surge vessel. This may lead to an additional required surge vessel compared to the case where the actual behaviour would be known To better predict the behaviour of surge vessels, a detailed thermodynamic model of a surge vessel has been developed In addition to the expansion and compression of air, this model also includes different sources of heat transfer inside the surge vessel and with the environment Field measurements in a large water transmission scheme in United Arab Emirates are used to make a tentative comparison between the model and the real world system, The results show a good agreement between the measurements and thc model Furthermore, it is shown that the new approach results in a smaller surge vessel capacity (up to 25%) needed for a safe system compared to the classical modelling approach based on the wide range of polytropic air pocket behaviour. © BHR Group 2015. Source

Zanganeh M.N.,Deift University of Technology | Kam S.I.,Louisiana State University | LaForce T.C.,Imperial College London | Rossen W.R.,Deift University of Technology
SPE Journal | Year: 2011

Solutions obtained by the method of characteristics (MOC) provide key insights into complex foam enhanced-oil-recovery (EOR) displacements and the simulators that represent them. Most applications of the MOC to foam have excluded oil. We extend the MOC to foam flow with oil, where foam is weakened or destroyed by oil saturations above a critical oil saturation and/or weakened or destroyed at low water saturations, as seen in experiments and represented in foam simulators. Simulators account for the effects of oil and capillary pressure on foam using algorithms that bring foam strength to zero as a function of oil or water saturation, respectively. Different simulators use different algorithms to accomplish this. We examine SAG (surfactant-alternating-gas) and continuous foam-flood (coinjection of gas and surfactant solution) processes in one dimension, using both the MOC and numerical simulation. We find that the way simulators express the negative effect of oil or water saturation on foam can have a large effect on the calculated nature of the displacement. For instance, for gas injection in a SAG process, if foam collapses at the injection point because of infinite capillary pressure, foam has almost no effect on the displacement in the cases examined here. On the other hand, if foam maintains finite strength at the injection point in the gas-injection cycle of a SAG process, displacement leads to implied success in several cases. However, successful mobility control is always possible with continuous foam flood if the initial oil saturation in the reservoir is below the critical oil saturation above which foam collapses. The resulting displacements can be complex. One may observe, for instance, foam propagation predicted at residual water saturation, with zero flow of water. In other cases, the displacement jumps in a shock past the entire range of conditions in which foam forms. We examine the sensitivity of the displacement to initial oil and water saturations in the reservoir, the foam quality, the functional forms used to express foam sensitivity to oil and water saturations, and linear and nonlinear relative permeability models. Copyright © 2011 Society of Petroleum Engineers. Source

Kil R.A.,Deift University of Technology | Nguyen Q.P.,University of Texas at Austin | Rossen W.R.,Deift University of Technology
SPE Journal | Year: 2011

Gas trapping by foam is a key mechanism of foam mobility and foam effectiveness in applications such as acid diversion in well stimulation, enhanced oil recovery (EOR), and aquifer remediation. Previous studies have attempted to quantify the extent of gas trapping by injecting a tracer gas within the foam and then fitting the effluent profile to a ID capacitance model. In this model, at any given axial position along the core, all flowing gas and all trapped gas are each characterized by a single tracer concentration. Computed-tomography (CT) images of experiments using xenon (Xe) tracer show that this characterization is not accurate: Trapped gas near flowing gas comes rapidly to equilibrium with flowing gas long before tracer diffuses into trapped gas farther away. We introduce a method that uses the CT images directly to estimate flowing-gas fraction. In the CT images, tracer advances many small channels and diffuses outward into surrounding regions of trapped gas a few millimeters in diameter. The difference between the higher tracer concentration at the center of these channels and the lower concentration at the edge can be related to the diffusion coefficient of the tracer and the flowing-gas fraction within the channel. For the CT images of Xe tracer in one experiment, this method gives flowing-gas fractions one or two orders of magnitude smaller than what is estimated using the ID capacitance model. The model can be used to estimate flowing-gas fraction in different regions of a core in spite of different average gas velocities in the different regions. Copyright © 2011 Society of Petroleum Engineers. Source

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