Water Complex Permittivity Model for Dielectric Logging

Donadille, Jean-Marc; Faivre, Ollivier

doi:10.2118/172566-ms

Cited by 11 publications

(7 citation statements)

References 9 publications

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“…With the addition of sodium chloride, the dielectric constant of simulated formation water (salinity of 10 000 ppm) slightly decreases, but the loss factor soars over the low frequencies, and then decreases with an increasing frequency. The added ions reduce the effective water concentration and restrain the water molecules’ orientation, leading to a decreased dielectric constant of water. As for the loss factor of the simulated formation water, the introduced extra ions can enhance the ion conduction, which increases the loss factor at low frequencies.…”

Section: Resultsmentioning

confidence: 99%

Determination of the permittivity of n‐hexane/oil sands mixtures over the frequency range of 200 MHz to 10 GHz

Ahmadloo

2018

Can J Chem Eng

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Combined electromagnetic (EM) heating and solvent injection has been recently proposed to recover bitumen from oil sands due to its great environmental friendliness. The permittivity of oil sands with the presence of solvent is a crucial property for the design, evaluation, and optimization of this process. In this study, we use the open-ended coaxial probe method to measure the permittivity of oil sands over the frequency range of 200 MHz to 10 GHz. Results of the permittivity of the constituents of oil sands reveal that water is a major dielectric contributor; no relaxation phenomenon has been found for bitumen, sand, and n-hexane over the tested frequency range. Also, the results for the oil sands mixtures show that water content is crucial for the permittivity of oil sands; both the dielectric constant and loss factor are enhanced with an increasing water content. With the addition of n-hexane, the permittivity of bitumen slightly changes and fluctuates between the dielectric values of pure bitumen and n-hexane. As for the n-hexane/oil sands mixtures, the added n-hexane induces the asphaltene aggregation/flocculation, affecting the interaction between water and asphaltene and leading to an enhanced free water content in the oil sands. Consequently, the permittivity of oil sands significantly increases after n-hexane addition. Based on the experimental data, we evaluate the prediction accuracy of commonly used mixing models. A modified Lichtenecker-Rother model considering effective water saturation is proposed to accurately characterize the permittivity of n-hexane/oil sands mixtures. The obtained data and correlations can be useful when experimental data are missing.

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Section: Resultsmentioning

confidence: 99%

Determination of the permittivity of n‐hexane/oil sands mixtures over the frequency range of 200 MHz to 10 GHz

Ahmadloo

2018

Can J Chem Eng

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“…The permittivity is conversed through the complex refractive index model (CRIM), a widely used dielectric mixed formula in the geological materials [16]. In a deep reservoir, high temperature and high salinity have significant impacts on water permittivity, while pressure effects can be neglected [17]. We included the salinity and temperature effects in our CRIM model by polynomially fitting the laboratory data presented by [17].…”

Section: B Borehole Radar Modelingmentioning

confidence: 99%

“…In a deep reservoir, high temperature and high salinity have significant impacts on water permittivity, while pressure effects can be neglected [17]. We included the salinity and temperature effects in our CRIM model by polynomially fitting the laboratory data presented by [17]. For this consideration, an obvious change is that water permittivity drops into approximately 58 at the temperature of 100°C or so, while it is normally deemed 88 in the surface GPR measurement.…”

Section: B Borehole Radar Modelingmentioning

confidence: 99%

“…For this consideration, an obvious change is that water permittivity drops into approximately 58 at the temperature of 100°C or so, while it is normally deemed 88 in the surface GPR measurement. The other change is that water permittivity becomes frequency independent in our applied radar frequency range when the reservoir temperature is above°C 100 [17]. The effective electrical conductivity is calculated by Archie's law under the assumption of a sandstone-type reservoir [18].…”

Section: B Borehole Radar Modelingmentioning

confidence: 99%

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Associating borehole radar logging data with petrophysical properties in a mud-contaminated reservoir: Can we converse disadvantage to advantage?

Zhou¹,

Giannakis

Giannopoulos

et al. 2019

10th International Workshop on Advanced Ground Penetrating Radar

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Logging engineers deem mud invasion a harm and attempt to eliminate its impact on logging data. However, from our point of view, the mud-contaminated parts of the formation do also carry some valuable information, notably with regard to the key hydraulic properties. Therefore, if adequately characterized, the invasion effects, in turn, could be utilized for reservoir estimation. Typically, the invasion depth critically depends of the formation porosity and permeability. To achieve this objective, we propose to use borehole radar to determine the mud invasion depth considering a high spatial resolution of ground-penetrating radar (GPR) compared with the conventional logging tools. We implement numerical investigations on the feasibility of this approach. The simulations imply that a timelapse radar logging is able to extract EM reflection signals from mud invasion front, and the invasion depth and EM velocity can be estimated by the downhole measurement of one source and two receivers. We find that there exists a positive correlation between the estimated invasion depth and permeability curves, and a negative correlation between the estimated velocity and porosity curves. We suggest that borehole radar has potential to estimate permeability and porosity of oil reservoirs, wherein the mud invasion effect is positively utilized.

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“…Such a reservoir condition is readily satisfied in realistic oil fields, and thus it is a natural regime for a true radar measurement. In the meantime, the radar frequency is not suggested to exceed a few GHz to avoid dielectric relaxation caused by water molecular polarization (Donadille and Faivre, 2015). In the limited frequency bands, the lower operation frequency tends to achieve a larger detection range.…”

Section: Radar Modelingmentioning

confidence: 99%

Reservoir monitoring using borehole radars to improve oil recovery: Suggestions from 3D electromagnetic and fluid modeling

et al. 2018

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The recently developed smart well technology allows for sectionalized production control by means of downhole inflow control valves and monitoring devices. We consider borehole radars as permanently installed downhole sensors to monitor fluid evolution in reservoirs, and it provides the possibility to support a proactive control for smart well production. To investigate the potential of borehole radar on monitoring reservoirs, we establish a 3D numerical model by coupling electromagnetic propagation and multiphase flow modeling in a bottom-water drive reservoir environment. Simulation results indicate that time-lapse downhole radar measurements can capture the evolution of water and oil distributions in the proximity (order of meters) of a production well, and reservoir imaging with an array of downhole radars successfully reconstructs the profile of a flowing water front. With the information of reservoir dynamics, a proactive control procedure with smart well production is conducted. This method observably delays the water breakthrough and extends the water-free recovery period. To assess the potential benefits that borehole radar brings to hydrocarbon recovery, three production strategies are simulated in a thin oil rim reservoir scenario, i.e., a conventional well production, a reactive production, and a combined production supported by borehole radar monitoring. Relative to the reactive strategy, the combined strategy further reduces cumulative water production by 66.89%, 1.75%, and 0.45% whereas it increases cumulative oil production by 4.76%, 0.57%, and 0.31%, in the production periods of 1 year, 5 years, and 10 years, respectively. The quantitative comparisons reflect that the combined production strategy has the capability of accelerating oil production and suppressing water production, especially in the early stage of production. We suggest that borehole radar is a promising reservoir monitoring technology, and it has the potential to improve oil recovery efficiency.

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Water Complex Permittivity Model for Dielectric Logging

Cited by 11 publications

References 9 publications

Determination of the permittivity of n‐hexane/oil sands mixtures over the frequency range of 200 MHz to 10 GHz

Determination of the permittivity of n‐hexane/oil sands mixtures over the frequency range of 200 MHz to 10 GHz

Associating borehole radar logging data with petrophysical properties in a mud-contaminated reservoir: Can we converse disadvantage to advantage?

Reservoir monitoring using borehole radars to improve oil recovery: Suggestions from 3D electromagnetic and fluid modeling

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