Feasibility of Reservoir Heating by Electromagnetic Irradiation

Fanchi, John R.

doi:10.2118/20483-ms

Cited by 42 publications

(10 citation statements)

References 9 publications

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“…Vertical heat loss is introduced through a heat flux continuity condition set at the boundaries of the reservoir with the adjacent formations as in Carrizales and Lake (2009). The expression for the EM heating source tern for a radial system was first introduced by Abernethy (1976), and later validated by Fanchi (1990). This expression depends primarily on the EM absorption coefficient derived from Maxwell's equations, which depends on the frequency, the electrical properties of the medium, and the water saturation.…”

Section: Governing Equationsmentioning

confidence: 99%

“…Several authors have dealt with the possibility of using EM heating to enhance recovery from heavy oil reservoirs (Abernethy, 1976;McPherson et al, 1985, Kim, 1987Fanchi, 1990;, however, there are no comprehensive models or commercial tools yet available that couples EM heating to multiphase fluid reservoir simulation. Bridges et al (1985) developed a single-well EM heating model, and used the resulting spatial heat distribution as an input to a finite difference reservoir simulator.…”

Section: Introductionmentioning

confidence: 99%

“…Sumbar et al, (1992) developed a numerical model; MEGAERA 4.0, to simulate single-phase EM heating that was used to evaluate schemes for EM heating of heavy oil reservoirs to enhance production. Fanchi (1990) presented a model for determining the temperature increase associated with EM heating. Although multiple phases are accounted for in calculating the total energy gained by a reservoir undergoing EM heating, his model neglects any phase changes (no heat of vaporization).…”

Section: Introductionmentioning

confidence: 99%

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Multiphase Fluid Flow Simulation of Heavy Oil Recovery by Electromagnetic Heating

Carrizales

Lake

Johns

2010

Proceedings of SPE Improved Oil Recovery Symposium

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Electromagnetic (EM) heating, also called high-frequency heating, generates EM waves through an antenna located inside a wellbore and parallel to the reservoir sand-face. The EM energy heats the reservoir from within, causing oil viscosity to lower and oil production to increase. Recent studies (Carrizales et al. 2008) showed that oil rate can be increased with the application of EM heating for single-phase radial flow. No simulations results or detailed modeling studies have yet been published that completely model the complex interactions of EM energy and multiphase flow.This paper presents a multiphase, two-dimensional radial model that describes the three-phase flow of water, oil, and steam and heat flow in a reservoir within confining formations. The model accounts for the appearance and/or disappearance of a phase, and uses the variation in temperature and water saturation to continuously update the EM heating rate. A single well is used to locate the EM source, and also to produce oil. Gravity effects and vertical heat loss into the confining layers are included. This model allows determining the temperature distribution and the productivity improvement from EM heating when multiple phases are present. This model will be useful to predict the recovery of heavy oil by EM heating where conventional steam injection is not attractive.To solve the model we used Lagrange-quadratic finite elements in the environment provided by COMSOL Multiphysics and its partial differential equations (PDE) application. Several simulations were made for hypothetical reservoirs with different fluid and rock properties. Special attention is on reservoirs with characteristics for which steam injection does not look attractive or feasible. Results show the feasibility of conducting EM heating based on the power source and frequency used to maintain an optimum absorption coefficient and to obtain higher production rates avoiding excessive power consumption. Also, a comparison shows that cumulative oil production and recovery factor obtained by EM heating is better than what is achieved by cyclic steam stimulation (CSS), especially for thin payzones.

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Section: Governing Equationsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Multiphase Fluid Flow Simulation of Heavy Oil Recovery by Electromagnetic Heating

Carrizales

Lake

Johns

2010

Proceedings of SPE Improved Oil Recovery Symposium

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“…Recently, electrical resistive heating was proposed, in which the energy is carried by the electric field that can be disaffected when two electrodes connected to the AC source are positioned within the reservoir at a certain distance [9,10]. There are some challenges for this approach also, because the electrodes need to be drilled into the reservoir to communicate with hydrocarbons and therefore the installation of the antenna in the reservoir well is very difficult [11,12]. Hence, a different approach that is very effective, significant, less expensive, and environmentally feasible is highly needed, which will be better prepared if nanofluids flooding is going to be improved.…”

Section: Introductionmentioning

confidence: 99%

Application of Magnetic and Dielectric Nanofluids for Electromagnetic-Assistance Enhanced Oil Recovery: A Review

et al. 2021

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Crude oil has been one of the most important natural resources since 1856, which was the first time a world refinery was constructed. However, the problem associated with trapped oil in the reservoir is a global concern. Consequently, Enhanced Oil Recovery (EOR) is a modern technique used to improve oil productivity that is being intensively studied. Nanoparticles (NPs) exhibited exceptional outcomes when applied in various sectors including oil and gas industries. The harshness of the reservoir situations disturbs the effective transformations of the NPs in which the particles tend to agglomerate and consequently leads to the discrimination of the NPs and their being trapped in the rock pores of the reservoir. Hence, Electromagnetic-Assisted nanofluids are very consequential in supporting the effective performance of the nanoflooding process. Several studies have shown considerable incremental oil recovery factors by employing magnetic and dielectric NPs assisted by electromagnetic radiation. This is attributed to the fact that the injected nanofluids absorb energy disaffected from the EM source, which changes the fluid mobility by creating disruptions within the fluid’s interface and allowing trapped oil to be released. This paper attempts to review the experimental work conducted via electromagnetic activation of magnetic and dielectric nanofluids for EOR and to analyze the effect of EM-assisted nanofluids on parameters such as sweeping efficiency, Interfacial tension, and wettability alteration. The current study is very significant in providing a comprehensive analysis and review of the role played by EM-assisted nanofluids to improve laboratory experiments as one of the substantial prerequisites in optimizing the process of the field application for EOR in the future.

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“…The injection pressure is calculated from the Peaceman equation (1978), assuming a cylindrical geometry for a rectangular shaped grid block and uniform properties in the grid block. Second, we use the Method of Characteristics (MOC) to examine saturation and mobility near the well and overall injectivity in the same Others have examined the effects of non-uniform saturations around the well on injectivity in gas-flooding (McMillan et al, 2008;Mathias et al, 2009;Pickup et al, 2012), non-uniform temperature near the well in schemes to heat the near-wellbore region (Baylor et al, 1990;Fanchi, 1990;Pizarro and Trevisan, 1990;Amit Chakma and Jha, 1992) and precipitation/dissolution waves in CO 2 injection into aquifers (Noh et al, 2007). This is the first study of the effects of saturation variation and foam rheology near the wellbore on foam injectivity.…”

Section: Introductionmentioning

confidence: 99%

Injectivity Errors in Simulation of Foam EOR

2013

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a b s t r a c tInjectivity is a key factor in the economics of foam enhanced oil recovery (EOR) processes. Poor injectivity of low-mobility foam slows the production of oil and allows more time for gravity segregation of injected gas. The conventional Peaceman equation (1978), when applied in a large grid block, makes two substantial errors in estimating foam injectivity: it ignores the rapidly changing saturations around the wellbore and the effect of non-Newtonian mobility of foam. When foam is injected in alternating slugs of gas and liquid ("SAG" injection), the rapid increase in injectivity from changing saturation near the well is an important and unique advantage of foam injection. Foam is also shear-thinning in many cases. This paper considers the two problems in turn: non-Newtonian effects and foam dry-out.In studying non-Newtonian effects we use the method-of-characteristics approach of Rossen et al. (2011), which resolves both changing saturations and non-Newtonian rheology with great precision near the wellbore, and compare to conventionally computed injectivity using the Peaceman equation in a grid block. By itself, the strongly non-Newtonian rheology of the "low-quality" foam regime makes a significant difference to injectivity of foam. However, one could estimate this effect using the equation for injectivity of power-law fluids, i.e. without accounting for changing water saturation near the well, without much error.In SAG processes, however, non-Newtonian rheology is less important than accounting for foam collapse in the immediate near-wellbore region. Averaging water saturation in a large grid block misses this dry-out very near the well and the Peaceman equation grossly underestimates the injectivity of gas. This error is similar in kind to, but much greater than, that in conventional gas-injection EOR. The magnitude of the effect on the overall simulation decreases as the simulation grid is refined around the well; this grid refinement is especially important for simulating foam SAG processes. We illustrate with examples using foam parameters fit to laboratory data.

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Feasibility of Reservoir Heating by Electromagnetic Irradiation

Cited by 42 publications

References 9 publications

Multiphase Fluid Flow Simulation of Heavy Oil Recovery by Electromagnetic Heating

Multiphase Fluid Flow Simulation of Heavy Oil Recovery by Electromagnetic Heating

Application of Magnetic and Dielectric Nanofluids for Electromagnetic-Assistance Enhanced Oil Recovery: A Review

Injectivity Errors in Simulation of Foam EOR

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