Desarrollo de un modelo probabilístico de flujo de materia y transporte de escalares en yacimientos de hidrocarburos sometidos a inyección de nanofluidos
During the last decade, the injection of nanofluids in hydrocarbon fields has been of increasing interest, as an enhanced oil recovery (EOR) technique. Specifically, when applying this technique, search among others, i.) improve the mobility of the hydrocarbon, change the matrix wettability from oil...
- Autores:
-
López Patiño, Eduin Alexander
- Tipo de recurso:
- Work document
- Fecha de publicación:
- 2020
- Institución:
- Universidad Nacional de Colombia
- Repositorio:
- Universidad Nacional de Colombia
- Idioma:
- spa
- OAI Identifier:
- oai:repositorio.unal.edu.co:unal/78554
- Acceso en línea:
- https://repositorio.unal.edu.co/handle/unal/78554
- Palabra clave:
- 660 - Ingeniería química
Thermal recovery
Multiphysics models
Porous media
Fluid flow
Retention and mobilization of nanoparticles
Modelos multifísicos
Medios porosos
Flujo de fluidos
Retención y movilización de nanopartículas
- Rights
- openAccess
- License
- Atribución-NoComercial 4.0 Internacional
Summary: | During the last decade, the injection of nanofluids in hydrocarbon fields has been of increasing interest, as an enhanced oil recovery (EOR) technique. Specifically, when applying this technique, search among others, i.) improve the mobility of the hydrocarbon, change the matrix wettability from oil to water, ii.) increase the amount of saturates and aromatics at the expense of the asphaltenes found in the improved hydrocarbon (The -Diasty & Aly, 2015). In general, it has been found that the injection of nanofluids has improved recovery by up to 10%. Therefore, it becomes relevant to generate a phenomenological model that allows the description of the system and the obtaining of relevant information on the process. The novelty of the study of the nanofluid injection problem is that it proposes a deterministic / probabilistic hybrid model, which presents two reference frameworks in its development. First, an Eulerian framework, where the transport of mass of the fluid phases present in the porous medium and energy is considered deterministically and second, a Lagrangian framework, which considers a probability density function that evolves to through the Fokker-Planck equation, giving to the probabilistic component model. Here, the Lagrangian part emerges from the solution of the probability equation obtained by finding the marginal PDFs. For example, if the marginal PDF is found in the position space, the Fokker equation - Planck converts to the probabilistic advection-diffusion equation. Now, to solve this advection-diffusion equation, a Lagrangian method is used. In the particular case of the study the stochastic particle method (SPM) will be used. Some of the results obtained with this work are: first, the extension of the SPM to the description of components such as tracers and nanoparticles is achieved. For this, it is necessary consider non-equilibrium phenomena, such as retention / mobilization. Furthermore, the probabilistic transport model is validated using a commercial simulator and experimental data (Li, et al., 2015). Also, the model is applicable under multiphasic, multidimensional and non-isothermal flow conditions. Among the conclusions obtained from this study are: first, the equivalence between the hybrid and deterministic methods, second, the additional information provided by the hybrid model associated with statistical moments such as standard deviation and the evaluation of PDF's, third, the representation without the use of mesh of the phenomenology associated with the system, e.g, positioning of concentration fronts. All this opens a branch of possibilities to the use of the SPM to the description of other components such as surfactants, polymers or mixtures of these. Finally, the SPM can be expanded to the description of other fields such as temperature, among others. |
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