An, Cheng (2014-12). Modeling of Magnetic Nanoparticles Transport in Shale Reservoirs. Master's Thesis. Thesis uri icon

abstract

  • Currently, the application of nanoparticles has attracted much attention due to the potential of nanotechnology to lead to evolutionary changes in the petroleum industry. The literature contains numerous references to the possible use of this technology for enhanced oil recovery, nano-scale sensors and subsurface mapping. Little work has been conducted to establish numerical models to investigate nanoparticle transport in reservoirs, and particularly much less for shale reservoirs. Unlike conventional reservoirs, shale formations are usually made up of four pores systems: inorganic matter, organic matter dominated by hydrocarbon wettability, natural fractures and hydraulic fractures. Concurrently, hydraulic fractures and the associated stimulated reservoir volume (SRV) from induced fractures play a critical role in significantly increasing well productivity. In this project, a mathematical model for simulating nanoparticle transport in shale reservoirs was developed. The simulator includes contributions from Darcy flow, Brownian diffusion, gas diffusion and desorption, slippage flow, and capillary effects based on the extremely low permeability and micro- to nano-scale of the pores. Moreover, these diverse mechanisms are separately applied to different portions of the reservoir due to the variation in media properties. Applications of the model include numerical examples from two-dimensional micro models to macro models, both with organic matter randomly distributed within the inorganic matrix. The effects of varying water saturation, grid pressure, and mass concentration of nanoparticles are shown graphically in these numerical examples. The main conclusion from these models is that, as expected, nanoparticles can only easily flow along with the aqueous phase into the fractures, but their transport into the shale matrix is quite limited, with little transport shown into the organic matter. In addition, based on the magnetic properties of synthesized magnetic carbon-coated iron-oxide nanoparticles, the distribution of the volumetric magnetic susceptibility and the magnetization of reservoir including SRV are simulated and displayed in the numerical cases with and without magnetic nanoparticles. The numerical results demonstrate that magnetic nanoparticles can effectively increase the magnetic susceptibility and the magnetization of reservoir thus producing enhanced signals from well logging devices such as NMR and leading to improved reservoir and fracture characterization. This simulator can provide the benefits of both numerically simulating the transport and distribution of nanoparticles in hydraulically fractured shale formations and supplying helpful guidelines of nanoparticles injection plans to enhance well logging signals. Furthermore, this model can also allow us to mimic the tracer transport flow in unconventional reservoirs.
  • Currently, the application of nanoparticles has attracted much attention due to the potential of nanotechnology to lead to evolutionary changes in the petroleum industry. The literature contains numerous references to the possible use of this technology for enhanced oil recovery, nano-scale sensors and subsurface mapping. Little work has been conducted to establish numerical models to investigate nanoparticle transport in reservoirs, and particularly much less for shale reservoirs. Unlike conventional reservoirs, shale formations are usually made up of four pores systems: inorganic matter, organic matter dominated by hydrocarbon wettability, natural fractures and hydraulic fractures. Concurrently, hydraulic fractures and the associated stimulated reservoir volume (SRV) from induced fractures play a critical role in significantly increasing well productivity.

    In this project, a mathematical model for simulating nanoparticle transport in shale reservoirs was developed. The simulator includes contributions from Darcy flow, Brownian diffusion, gas diffusion and desorption, slippage flow, and capillary effects based on the extremely low permeability and micro- to nano-scale of the pores. Moreover, these diverse mechanisms are separately applied to different portions of the reservoir due to the variation in media properties. Applications of the model include numerical examples from two-dimensional micro models to macro models, both with organic matter randomly distributed within the inorganic matrix. The effects of varying water saturation, grid pressure, and mass concentration of nanoparticles are shown graphically in these numerical examples. The main conclusion from these models is that, as expected, nanoparticles can only easily flow along with the aqueous phase into the fractures, but their transport into the shale matrix is quite limited, with little transport shown into the organic matter. In addition, based on the magnetic properties of synthesized magnetic carbon-coated iron-oxide nanoparticles, the distribution of the volumetric magnetic susceptibility and the magnetization of reservoir including SRV are simulated and displayed in the numerical cases with and without magnetic nanoparticles. The numerical results demonstrate that magnetic nanoparticles can effectively increase the magnetic susceptibility and the magnetization of reservoir thus producing enhanced signals from well logging devices such as NMR and leading to improved reservoir and fracture characterization. This simulator can provide the benefits of both numerically simulating the transport and distribution of nanoparticles in hydraulically fractured shale formations and supplying helpful guidelines of nanoparticles injection plans to enhance well logging signals. Furthermore, this model can also allow us to mimic the tracer transport flow in unconventional reservoirs.

publication date

  • December 2014