Permeability estimating from complex resistivity measurement of shaly sand reservoir

Tong, Maosong; Tao, Honggen

doi:10.1111/j.1365-246x.2008.03730.x

Cited by 40 publications

(20 citation statements)

References 26 publications

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“…If some measurements of h are available or the h (θ) relationship is known for the soil horizons together with estimation of K sat and % Clay , combined use of ERT measurement, hydraulic measurements and the derived σ ‐ K relationship, based on the simplified approach () could lead to a direct estimation of the spatial variability with time of soil water fluxes. Recent results from induced polarization measurements show a power law relationship between Cole‐Cole relaxation time [ Binley et al , 2005] or slope of the log‐log variation of imaginary conductivity variation with frequency [ Tong and Tao , 2008] with saturated permeability, and possibly unsaturated hydraulic conductivity, of sandstones. Moreover, relaxation time may also be linked to van Genuchten parameters of the retention curve [ Binley et al , 2005].…”

Section: Resultsmentioning

confidence: 99%

Prediction of unsaturated soil hydraulic conductivity with electrical conductivity

Doussan

Ruy

2009

Water Resources Research

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Soil hydraulic conductivity (K) varies greatly with matric potential (h) and exhibits a high variability at the field scale. However, this key property for estimating water flux in soils is difficult to measure. In contrast, soil electrical conductivity (σ) is easier to measure and is influenced by the same parameters affecting K. We derive a simple relationship between σ and K(h) and test it against laboratory and literature data. Importantly, we show that parameters of this σ‐K(h) relationship can be completely determined with accessible measurements of saturated hydraulic conductivity, electrical conductivity of the soil solution, and clay content. This results in K(h) estimation with a RMSE ranging between 0.4 and 0.5 for log K, i.e., of the order of most experimental determinations of K. A further test of the σ‐K(h) relationship on the large UNSODA hydraulic database shows good agreement and the robustness of the relationship. Such a relation could be useful in the spatial monitoring of water fluxes at the field scale using electrical resistivity tomography if the σ(h) relationship can be obtained.

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Section: Resultsmentioning

confidence: 99%

Prediction of unsaturated soil hydraulic conductivity with electrical conductivity

Doussan

Ruy

2009

Water Resources Research

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“…Equation (1) may also therefore be expressed as [B€ orner et al, 1996] polarization processes occurring at grain/pore surfaces has led to the belief that such measurements may be a suitable candidate as a proxy for the hydraulic properties of a porous material. Consequently, there has been widespread interest in the search for relationships which allow permeability to be predicted from SIP data [e.g., B€ orner et al, 1996;Koch et al, 2012;Revil and Florsch, 2010;Revil et al, 2012b;Slater, 2007;Slater and Lesmes, 2002;Tong et al, 2006aTong et al, , 2006bTong and Tau, 2008;Zisser et al, 2010aZisser et al, , 2010b.…”

Section: Introductionmentioning

confidence: 99%

Spectral‐induced polarization measurements on sieved sands and the relationship to permeability

Joseph

Ingham

Gouws

2016

Water Resources Research

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Laboratory measurements of the permeability and spectral-induced polarization (SIP) response of samples consisting of unconsolidated sands typical of those found in New Zealand aquifers have been made. After correction of measured formation factors to allow for the fact that some were measured at only one fluid conductivity, predictions of permeability from the grain size (d) of the samples are found to agree well with measured values of permeability. The Cole-Cole time constant (derived from the SIP measurements) is found, as expected, to depend upon d 2 , but can be affected by the inclusion of smaller grains in the sample. Measurements made on samples comprising of mixtures of grain sizes show that inclusion in a sample of even 10% of smaller grains can significantly reduce both the Cole-Cole time constant (s CC ) and the permeability, and support theoretical derivation of how the permeability of a mixture of grain sizes varies with the content of the mixture. Proposed relationships for using s CC as a predictor for permeability are tested and found to be crucially dependent on the assumed relationship between the dynamic pore radius and grain size. The inclusion of a multiplicative constant to take account of numerical approximations results in good predictions for the permeability of the samples in this study. It seems unlikely, however, that there is a single global expression for predicting permeability from SIP data for all samples.

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“…The joint interpretation of resistivity and induced polarization (IP) data can improve the estimation of permeability (e.g., Lima and Niwas 2000;Tong et al 2006;Weller et al 2015). Tong and Tao (2008) predicted the permeability of shaly sand samples from Daqing oil field using the complex resistivity measurements. Weller et al (2010) estimated the permeability of sandstone samples of the Bahariya Formation, north Western Desert of Egypt, from nuclear magnetic resonance (NMR) and complex resistivity data.…”

Section: Introductionmentioning

confidence: 99%

Prediction of permeability anisotropy using Dar-Zarrouk parameters of deep resistivity logs: a case study in the northern Western Desert of Egypt

Attwa

Nabih

2015

Arab J Geosci

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This study is a trial to predict the relationship between the formation resistivity data and some petrophysical properties of rocks in Tut and Khalda oil fields at the northern Western Desert, Egypt. First, the deep resistivity (deep laterolog (LLD)) and gamma ray (GR) logs are smoothed by a linear combination of simple fitting functions that satisfy the smoothness criteria, and consequently the behavior of both logs can be simulated. Next, the smoothed log data are divided into branches, where high and frequent excursions in GR and LLD logs occur. In subsequent steps, the Dar-Zarrouk parameters are calculated and followed by a smoothing process for each branch. Based on a visual inspection of these parameters with effective porosity logs, the Dar-Zarrouk parameters are divided into zones and then interpreted in terms of shale content and the potentiality of the two oil fields. The permeability trend observed in core samples showed that the calculated parameters provide an adequate qualitative prediction for the petrophysical properties including the overall permeability trends. Despite the fact that the predicted permeability trends in Khalda oil field coincides with those measured from core samples, a weak correlation is observed, which can be attributed to the reservoir heterogeneity with dominance of laminated and dispersed shale and/or iron oxides. The potentiality of the proposed method lies in its simplicity, requiring only GR, LLD, and effective porosity logs. However, it would be more meaningful if the above method is tested in areas with diverse geological environment.

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Permeability estimating from complex resistivity measurement of shaly sand reservoir

Cited by 40 publications

References 26 publications

Prediction of unsaturated soil hydraulic conductivity with electrical conductivity

Prediction of unsaturated soil hydraulic conductivity with electrical conductivity

Spectral‐induced polarization measurements on sieved sands and the relationship to permeability

Prediction of permeability anisotropy using Dar-Zarrouk parameters of deep resistivity logs: a case study in the northern Western Desert of Egypt

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