A new study of magnetic nanoparticle transport and quantifying magnetization analysis in fractured shale reservoir using numerical modeling

Cheng An, Masoud Alfi, Bicheng Yan, John E. Killough

Research output: Contribution to journalArticlepeer-review

36 Scopus citations

Abstract

The application of nanoparticles has successfully attracted much attention due to the potential advantages of nanotechnology to lead to revolutionary changes in the oil and gas industry, such as nano-scale sensors, enhanced oil recovery and subsurface mapping. This paper will study the potential application of magnetic nanoparticles as contrast agents to enhance signals from well logging as well as improve reservoir and fracture characterization. Little work has been conducted to establish numerical models for investigating nanoparticle transport in reservoirs, and even less for unconventional reservoirs. Unlike conventional reservoirs, shale formations could contain four different pore systems: inorganic matter, organic matter dominated by hydrocarbon wettability, natural fractures and hydraulic fractures. These various pore media increase the difficulty to exactly describe the transport of nanoparticles along with aqueous phase. Concurrently, hydraulic fractures and the associated stimulated reservoir volume (SRV) from induced fractures need to be considered in hydraulically fractured reservoirs because of its significant assistance to well productivity.We have developed a mathematical model for simulating nanoparticle transport in shale reservoirs. The simulator includes various flow mechanisms from Darcy flow, Brownian diffusion of nanoparticles, 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 mechanisms are separately applied to the sub-media of the reservoir due to the variation of media properties. Firstly, numerical applications including both two-dimensional micro model and macro model are presented, both models with organic matter randomly distributed within the matrix. Based on the integral finite difference and Newton-Raphson method, the distribution of water saturation and nanoparticle mass are calculated and graphically shown in different time steps. The main conclusion from these models is, as expected, nanoparticles can easily flow along with the aqueous phase into the fractures, but their transport into the shale matrix is quite limited, with even less transport shown into the organic matter of matrix. Secondly, a large reservoir model containing SRV is built to investigate the effect of magnetic nanoparticles on the volumetric magnetic susceptibility (VMS) of the reservoir. Based on the measured properties of synthesized magnetic carbon-coated iron-oxide nanoparticles, the distribution of the VMS is simulated and displayed in the numerical cases with and without magnetic nanoparticles. Besides, several different grids are chosen to display the varying trend of VMS along with time. The numerical results demonstrate that magnetic nanoparticles can effectively enlarge the VMS and the magnetization of reservoir, thus producing enhanced signals from well logging devices such as Nuclear Magnetic Resonance (NMR). This simulator can provide the benefits of both numerically simulating the transport and distribution of nanoparticles in hydraulically fractured shale formations and supplying helpful guidance for nanoparticles injection plans to enhance well logging signals and improve petrophysical evaluation. Furthermore, this model could also allow us to simulate the tracer transport flow in unconventional reservoirs.
Original languageEnglish (US)
Pages (from-to)502-521
Number of pages20
JournalJournal of Natural Gas Science and Engineering
Volume28
DOIs
StatePublished - Jan 1 2016
Externally publishedYes

ASJC Scopus subject areas

  • Energy Engineering and Power Technology

Fingerprint

Dive into the research topics of 'A new study of magnetic nanoparticle transport and quantifying magnetization analysis in fractured shale reservoir using numerical modeling'. Together they form a unique fingerprint.

Cite this