Hydrocarbon saturation in Bakken Petroleum System based on joint inversion of resistivity and dielectric dispersion logs

Tathed, Pratiksha; Ying, Han; Misra, Siddharth

doi:10.1016/j.fuel.2018.06.019

Cited by 23 publications

(6 citation statements)

References 15 publications

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“…In order to show the advantages of particle swarm optimization (PSO) algorithm, the Levenberg–Marquardt (LM) algorithm is used to inverse parameters for comparison. LM algorithm is a traditional inversion method and is widely used to inverse reservoir parameters (Han & Misra, 2018; Tathed et al., 2018a, 2018b). In this section, we synthesize four permittivity logs and four conductivity logs at four frequencies by assuming reservoir properties close to the Chang 8 member of the Triassic Yanchang Formation, Ordos Basin, China (Zhao et al., 2022).…”

Section: Resultsmentioning

confidence: 99%

“…In order to show the advantages of particle swarm optimization (PSO) algorithm, the Levenberg-Marquardt (LM) algorithm is used to inverse parameters for comparison. LM algorithm is a traditional inversion method and is widely used to inverse reservoir parameters (Han & Misra, 2018;Tathed et al, 2018aTathed et al, , 2018b. In this section, we synthesize four permit- Temperature (˚F) 160…”

Section: Application Of Revised Models To Synthetic Logs With Assumed...mentioning

confidence: 99%

“…Additionally, several researchers used various model to process dielectric dispersion logs (Han & Misra, 2018;Tathed et al, 2018aTathed et al, , 2018bZhao et al, 2020Zhao et al, , 2022. Han and Misra (2018) evaluated the hydrocarbon saturation in the Bakken Petroleum System using SMD model, Lichtenecker-Rother model and mechanistic electrochemical model based on Levenberg-Marquardt algorithm.…”

Section: Introductionmentioning

confidence: 99%

“…Han and Misra (2018) evaluated the hydrocarbon saturation in the Bakken Petroleum System using SMD model, Lichtenecker-Rother model and mechanistic electrochemical model based on Levenberg-Marquardt algorithm. Tathed et al, 2018aTathed et al, , 2018b applied SMD model, CRIM model and Waxman-Smith equation to interpret dielectric dispersion logs of the Bakken and the Wolfcamp shale formations. Water saturation, brine conductivity, cementation exponent and saturation exponent are obtained by joint inversion of resistivity and dielectric dispersion logs.…”

Section: Introductionmentioning

confidence: 99%

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Revised models for evaluating hydrocarbon saturation of tight sandstone formations based on dielectric dispersion logs

Wang,

Liao,

Zhao

et al. 2023

Geophysical Prospecting

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Accurate estimation of hydrocarbon saturation is significant for log interpreters to evaluate tight sandstone formations. It is difficult to use conventional wireline logs to calculate hydrocarbon saturation in complex reservoirs. Dielectric dispersion logs are processed using dielectric models to obtain accurate saturation assessment, especially in high salinity shaly sand formations. However, the dielectric models consist of complex refractive index method model and shaly sand model ignore the impact of clay effects on complex refractive index method model, and the dielectric dispersion logs generated by them appear several unphysical phenomena in the clay‐bearing formations, such as the permittivity data at the highest frequency are greater than those at the second highest frequency and the conductivity data at the highest frequency are lower than those at the second highest frequency. This paper modifies the dielectric models by introducing a combined conductive phase in complex refractive index method model to correct the unphysical behaviors. Revised models are combined with four permittivity and four conductivity logs acquired by Dielectric Scanner at 24, 102, 360, and 960MHz to inverse the water saturation, water salinity, textural index for water‐bearing pore, and fraction of clay‐related phase. The complex refractive index method model interprets the logs measured at 960MHz and shaly sand model interprets other dielectric dispersion logs. The particle swarm optimization algorithm is used to search inversion parameters. The results of forward simulation show that the revised models can correct unphysical behaviors of dielectric dispersion logs generated by the original models. Moreover, we apply original models and revised models to laboratory core data. The results of experiments show that the mean relative error values of the original models are 19.38% and 23.60% and of the revised models are 5.54% and 6.28% in two cases. It shows that the revised models are more accurate than the original models to interpret dielectric dispersion logs of tight sandstone reservoirs.This article is protected by copyright. All rights reserved

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Section: Resultsmentioning

confidence: 99%

Section: Application Of Revised Models To Synthetic Logs With Assumed...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Revised models for evaluating hydrocarbon saturation of tight sandstone formations based on dielectric dispersion logs

Wang,

Liao,

Zhao

et al. 2023

Geophysical Prospecting

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show abstract

“…However, inversion results may lack reliability, in particular, due to the small number of available data, the presence of noise in the measurements, and the lack of sensitivity of each data set to the water saturation profile. Therefore, a possible solution to improve the inversion of ND measurements relies upon combining the two types of data, the electrical resistivity, and the dielectric permittivity, taking advantage of their complementarity (Tathed, 2018).…”

Section: Introductionmentioning

confidence: 99%

A Joint Inversion Approach of Capacitive and Resistive Measurements for the Estimation of Water Saturation Profiles in Concrete Structures

Alhajj¹,

Villain²,

Bourguignon³

et al. 2020

XV International Conference on Durability of Building Materials and Components. eBook of Proceedings

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Concrete is a construction material that is well known for its durability. However, it is exposed to environmental attacks that lead to the penetration of aggressive agents such as water and chlorides, thus, threatening its durability and service life. Within this context and exploiting the sensitivity of the electromagnetic properties of concrete to its water content, the literature suggests determining water saturation profiles using non-destructive techniques. For instance, measuring the electrical resistivity at several points of the surface of the concrete structure can lead to an estimate of the resistivity depth profile. Then, after a calibration step, the water saturation depth profile can be obtained and the durability can be assessed. Similarly, the water depth profile can be assessed by dielectric permittivity measurements. In this paper, we propose a new inversion scheme based on the combination of both resistive and capacitive measurements: resistivity and permittivity measurements are inverted jointly to estimate the water saturation profile in concrete. Numerical experiments with simulated data show that information gathered from the two measurements enriches the inversion process, leading to the determination of more reliable water saturation profiles.

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Quantitative Estimation on Methane Storage Capacity of Organic-Rich Shales from the Lower Silurian Longmaxi Formation in the Eastern Sichuan Basin, China

Guo,

Luo,

Dong

et al. 2023

J. Earth Sci.

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Hydrocarbon saturation in Bakken Petroleum System based on joint inversion of resistivity and dielectric dispersion logs

Cited by 23 publications

References 15 publications

Revised models for evaluating hydrocarbon saturation of tight sandstone formations based on dielectric dispersion logs

Revised models for evaluating hydrocarbon saturation of tight sandstone formations based on dielectric dispersion logs

A Joint Inversion Approach of Capacitive and Resistive Measurements for the Estimation of Water Saturation Profiles in Concrete Structures

Quantitative Estimation on Methane Storage Capacity of Organic-Rich Shales from the Lower Silurian Longmaxi Formation in the Eastern Sichuan Basin, China

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