Joint elastic‐electrical effective medium models of reservoir sandstones

Han, Tongcheng; Best, Angus I.; MacGregor, Lucy; Sothcott, J.; Minshull, T. A.

doi:10.1111/j.1365-2478.2011.00956.x

Cited by 41 publications

(48 citation statements)

References 39 publications

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“…In the example, the calculations at each iteration number are made using 6 different mixing orders of the 3 inclusions, as shown in the legend where 0, 30, and 90 stand for the quartz oriented 0 ∘ , 30 ∘ , and 90 ∘ to the bedding, respectively, and their orders in the legend represent the mixing order of the corresponding ingredients. The big separation between the simulated relative permittivity and conductivity when is set to be 1 confirms that the conventional DEM model is dependent on the mixing order of the multiple components (e.g., [15,32,33]). With an increase in the iteration number, the ordering effect decreases, and the calculated relative permittivity and conductivity at each direction start to converge and become identical when the iteration number is sufficiently high (i.e., when n = 1000), demonstrating that the developed multiphase anisotropic dielectric model is independent of mixing order at high iteration numbers.…”

Section: Anisotropic Dielectric Modelmentioning

confidence: 69%

“…The multiphase anisotropic dielectric model was developed based on the incremental algorithm [21,28], in which a small amount of each component is required to be added in every increment, making the model independent of the mixing order, a problem usually encountered by multiphase DEM models [15,32,33]. This excludes the difference in the results caused by the order of mixing the different mineral phases and ensures that the results are unique for the determined shale dielectric properties based on the dielectric responses and volume fractions of the constituents and their specific microstructure described by the simplified orientation distribution function of the clay particles, which determines the anisotropy of the bulk dielectric properties through the orientational alignments of the clay minerals.…”

Section: Discussionmentioning

confidence: 99%

“…To describe the dielectric behaviors of a heterogeneous system caused by the Maxwell-Wagner polarization, various models have been developed (e.g., [11][12][13][14][15][16][17][18][19][20]) and a comprehensive review of the models can be found in Cai et al [19]. Among these models, the differential effective medium (DEM) models are the kind of models that have had the most success in simulating the dielectric behavior of clay-free sedimentary rocks [21] and in modeling the high-frequency dielectric properties of both clay-free soils and clay soils [22].…”

Section: Introductionmentioning

confidence: 99%

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Theoretical Modeling of Dielectric Properties of Artificial Shales

et al. 2018

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Accurately modeling the anisotropic dielectric properties of shales is important for the interpretation of dielectric data acquired from shales as source rocks and unconventional reservoirs. We have developed a multiphase incremental model for the frequency dependent anisotropic dielectric properties of sedimentary rocks and presented an approach based on the developed model to simulate the measured anisotropic dielectric behaviors of artificial shales. The new model was built based on the theoretical basis of differential effective medium models for any number of mineral grain components aligned in any direction and was shown to be independent of the mixing order. The model incorporates the measured orientation distribution function of the clay particles to determine the shale dielectric anisotropy, and the frequency dependent dielectric behaviors of the wet clay minerals are obtained by inverting the dielectric properties of the artificial sample composed of clay and the same brine as in other artificial shales. The modeling technique combined important polarization mechanisms in the intermediate frequency range and was shown to give satisfactory fit to the measured frequency dependent anisotropic relative permittivity and conductivity of the artificial shales with varying silt contents by using a reasonable aspect ratio and constant dielectric parameters for the silt grains.

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Section: Anisotropic Dielectric Modelmentioning

confidence: 69%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Theoretical Modeling of Dielectric Properties of Artificial Shales

et al. 2018

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“…Han et al [27]. The logarithm of  shows an approximate linear increase with increasing V p , satisfying log()= 0.0019V p 3.0201 with squared correlation coefficient R 2 = 0.7841, where V p is in m/s and  in Ωm.…”

Section: Joint Elastic-electrical Propertiesmentioning

confidence: 96%

Joint elastic-electrical properties of sediments in the Yellow Sea

Han

Liu

Kan

et al. 2011

Sci. China Earth Sci.

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We measured in the laboratory compressional wave velocity and electrical resistivity on 434 sediment samples collected from the Yellow Sea to study the joint elastic-electrical properties of marine sediments. Porosity was found to reduce both elastic velocity and electrical resistivity of the marine sediments in a non-linear fashion; velocity showed an approximate linear increase with increasing logarithm of resistivity. Various effective medium models either implemented or developed were compared with the new dataset. The model results showed that the combined self-consistent approximation and differential effective medium model using critical porosity of 0.6 and 0.5 for velocity and resistivity respectively gave a reasonable description of the joint elastic-electrical behaviors of the marine sediments. The joint elastic-electrical properties of the marine sediments established would be used to estimate resistivity from measured velocity and vice versa, and could also be suitable for detection of gas hydrate or other suitable targets from joint seismic-resistivity surveys. joint elastic-electrical properties, marine sediments, Yellow Sea, effective medium models Marine sediments on the shallow surface of seafloor are an important interface between sea water and the rocks beneath in terms of their transitional physical properties. The acoustic properties (mainly sound speed and attenuation) of marine sediments are key factors that affect sound spatial structure, underwater sound communication, underwater objection locating, and underwater sonar performance, and are therefore being significant research topics of military oceanography and military geophysics that play an important role in national coast defenses [1,2]. On the other hand, the measurements of electrical properties (e.g. electrical resistivity or its inverse electrical conductivity) of marine sediments provide valuable information for marine engineering [3] and resource [4,5] investigations and seafloor environmental monitoring [6].Recent development in in-situ seafloor sediments acoustic equipment [1,7] and the controlled source electromagnetic (CSEM) techniques [8] has made the accurate joint elastic-electrical measurements of marine sediments possible, which can give a better evaluation of the sedimentological properties (e.g. porosity and brine or gas content) provided that the inter-relationships among sediment engineering and the joint elastic-electrical properties of marine sediments are known. There has been joint elastic-electrical research on sedimentary rocks (e.g. reservoir sandstones) [9, 10], but unfortunately none relevant work on marine sediments can be found in the open literature.We aim in this paper to establish the relationship between compressional wave velocity (V p ) and electrical resistivity (  ) of marine sediments (referred to as the joint elastic-electrical properties) based on comprehensive laboratory

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“…(2011a) presented a rather comprehensive study of combined measurements at various differential stresses involving 63 brine saturated samples collected from various well and quarry locations around the world. In an accompanying paper, Han et al . (2011b) also presented results from a joint elastic‐electrical effective‐medium type of modelling.…”

Section: Introductionmentioning

confidence: 98%

Consistent joint elastic‐electrical differential effective‐medium modelling of compacting reservoir sandstones

Jensen

Gelius

Johansen

et al. 2012

Geophysical Prospecting

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Improved reservoir characterization and monitoring can be achieved by combining seismic and controlled‐source electromagnetic techniques. This requires developing coherent rock physics descriptions. In this paper we demonstrate consistent joint elastic‐electrical modelling according to the differential effective‐medium theory. We test our modelling against data from a compaction experiment on a set of 11 sandstone core samples from the same quarry location. The presented approach is analogous to calibrating a rock physics model to a particular reservoir based on data from possible well logs and core samples. For simplicity we choose to use multivariable non‐linear regression in the inversion. It shows that this technique is able to identify solutions that are physically sound. However, a more rigorous inversion method might be considered in future implementations. To identify the critical parameters we test the elastic‐electrical sensitivity of the various unknown variables involved. The most sensitive parameters identified are then perturbed during the modelling. The mineralogy consists mainly of quartz, which we assume to be spherical and kaolinite. We use the resistivity to calibrate the aspect ratio of the clay grains and estimate the porosity reduction due to compaction. These values are in turn used in inverse modelling of the bulk and shear moduli. The solid minerals make up the inclusion material in the differential effective‐ medium modelling for both the elastic and electrical properties. Hence, this formulation constitutes a consistent joint elastic‐electrical modelling scheme. We achieve good fits between the model results and the laboratory measurements for most of the samples. The reason for the less good fit with some of the samples might be due to measurement errors in the laboratory. This is supported by the observed abnormal stiffness compaction trends associated with those samples.

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Joint elastic‐electrical effective medium models of reservoir sandstones

Cited by 41 publications

References 39 publications

Theoretical Modeling of Dielectric Properties of Artificial Shales

Theoretical Modeling of Dielectric Properties of Artificial Shales

Joint elastic-electrical properties of sediments in the Yellow Sea

Consistent joint elastic‐electrical differential effective‐medium modelling of compacting reservoir sandstones

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