Influence of permeability anisotropy and layering on geothermal battery energy storage

Panja, Palash; McLennan, John; Green, Sídney

doi:10.1016/j.geothermics.2020.101998

Cited by 21 publications

(11 citation statements)

References 10 publications

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“…However, none of these publications considered a single well injection/production scheme in porous formation for a geothermal energy storage system. In our previous study (Panja et al, 2021), it is shown that the heat recovery for a given cycle is not affected significantly by permeability anisotropy and layering of the storage medium. In this study, we investigate the effects of permeability heterogeneity on geothermal battery functionality.…”

Section: Parametersmentioning

confidence: 88%

Impact of permeability heterogeneity on geothermal battery energy storage

Panja

McLennan

Green

2021

Adv. Geo-Energy Res.

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In the emergence of new technologies to harness renewable energy, industrial-scale storage of heated water in a geothermal system is a promising technique. A porous, permeable medium, bounded by a poorly thermally conductive/convective overburden and underburden, can be used for transient subsurface thermal storage. The reservoir in this concept forms a geothermal battery. As a very simplified scenario, consider a single well injecting and producing hot water diurnally or seasonally. The source of the hot water could be solar-heated water, for example, or possibly even water heated from the excess regional electricity supply. For that situation, this study investigates the influence of spatial permeability heterogeneity on heat recovery, and the distributions of temperature and pressure inside the reservoir. Four heterogeneous models are created from lognormal distributions of permeability by varying the standard deviations while keeping the mean absolute permeability at 100 mD. The injection pressure experienced while pumping into a candidate formation is affected by heterogeneity; higher bottom hole pressure is required to inject water into a more heterogeneous reservoir. The spatial distribution of temperature is less affected by permeability heterogeneity. In the simulations carried out, 91% of the heat is recovered after the 30 th cycle of injection/production operation in all cases proving less impact of heterogeneity on heat recovery for fixed injection and production rates.

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Section: Parametersmentioning

confidence: 88%

Impact of permeability heterogeneity on geothermal battery energy storage

Panja

McLennan

Green

2021

Adv. Geo-Energy Res.

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“…Directional properties of pore space, including the preferred shape, alignment and connectivity of pores, control preferred flow directions in porous media. This pore fabric is thus an important input parameter for aquifer and reservoir modelling, to understand sub-surface flow patterns, and to predict fluid paths (Ayan et al, 1994;Bear, 2013;Bear, Braester, & Menier, 1987;Huang, Tao, Li, Lyu, & Guo, 2017;Ijeje, Gan, & Cai, 2019;Panja, McLennan, & Green, 2021;Rasolofosaon & Zinszner, 2002;Sinan, Glover, & Lorinczi, 2020;Storesletten, 1998;Wang, Huang, Lu, Tang, & Li, 2019;Willems, Nick, Donselaar, Weltje, & Bruhn, 2017).…”

Section: Introductionmentioning

confidence: 99%

Magnetic Properties of Ferrofluid Change Over Time: Implications for Magnetic Pore Fabric Studies

Biedermann

Parés

2022

JGR Solid Earth

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“…They are defined as the anisotropy of magnetic susceptibility (AMS) of ferrofluid-impregnated samples, and may reflect depositional or tectonic fabrics (Pfleiderer and Kissel, 1994, Hailwood and Ding, 2000, Parés et al, 2016. As pore fabrics control fluid flow in porous media, their accurate description is important in many areas of geophysics and geology, including convective flow models, aquifer and reservoir characterization, geothermal energy and CO2 storage applications (Ayan et al, 1994, Huang et al, 2017, Ijeje et al, 2019, Panja et al, 2021, Sinan et al, 2020, Wang et al, 2014, Wang et al, 2019, Willems et al, 2017, Storesletten, 1998. Traditional pore characterization methods such as X-ray tomography face trade-offs between sample size and resolution, and generate large amounts of data that need to be processed (Cnudde andBoone, 2013, Landis andKeane, 2010).…”

Section: Introductionmentioning

confidence: 99%

Explaining the large variability in empirical relationships between magnetic pore fabrics and pore space properties

Biedermann

Pugnetti

Zhou

2021

Geophysical Journal International

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Summary The magnetic anisotropy exhibited by ferrofluid-impregnated samples serves as a proxy for their pore fabrics, and is therefore known as magnetic pore fabric. Empirically, the orientation of the maximum susceptibility indicates the average pore elongation direction, and predicts the preferred flow direction. Further, correlations exist between the degree and shape of magnetic anisotropy and the pores’ axial ratio and shape, and between the degrees of magnetic and permeability anisotropies. Despite its potential, the method has been rarely used, likely because the large variability in reported empirical relationships compromises interpretation. Recent work identified an additional contribution of distribution anisotropy, related to the arrangement of the pores, and a strong dependence of anisotropy parameters on the ferrofluid type and concentration, partly explaining the variability. Here, an additional effect is shown; the effective susceptibility of the ferrofluid depends on the measurement frequency, so that the resulting anisotropy depends on measurement conditions. Using synthetic samples with known void geometry and ferrofluids with known susceptibility (4.04 SI and 1.38 SI for EMG705 and EMG909, respectively), magnetic measurements at frequencies from 500 Hz to 512 kHz are compared to numerical predictions. Measurements show a strong frequency-dependence, especially for EMG705, leading to large discrepancies between measured and calculated anisotropy degrees. We also observe artefacts related to the interaction of ferrofluid with its seal, and the aggregation of particles over time. The results presented here provide the basis for a robust and quantitative interpretation of magnetic pore fabrics in future studies, and allow for re-interpretation of previous results provided that the ferrofluid properties and measurement conditions are known. We recommend that experimental settings are selected to ensure a high intrinsic susceptibility of the fluid, and that the effective susceptibility of the fluid at measurement conditions is reported in future studies.

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Influence of permeability anisotropy and layering on geothermal battery energy storage

Cited by 21 publications

References 10 publications

Impact of permeability heterogeneity on geothermal battery energy storage

Impact of permeability heterogeneity on geothermal battery energy storage

Magnetic Properties of Ferrofluid Change Over Time: Implications for Magnetic Pore Fabric Studies

Explaining the large variability in empirical relationships between magnetic pore fabrics and pore space properties

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