Macroscopic Electrical Anisotropy of Laminated Reservoirs: A Tensor Resistivity Saturation Model

Schoen, J.; Mollison, R.A.; Georgi, Daniel T.

doi:10.2118/56509-ms

Cited by 30 publications

(3 citation statements)

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“…Empirical evidence suggests that electrical conductivity of Earth materials is anisotropic as a rule, rather than an exception, and anisotropy is observed on the cm scale [8], the m scale [9] and the km scale [10]. Causes of electrical anisotropy are varied, ranging from preferential direction of rock fractures and layering of rock-strata to the alignment of crystals in the rock matrix.…”

Section: Introductionmentioning

confidence: 99%

Anisotropic resistivity inversion

et al. 2003

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We present an inversion method for 3D electrical imaging in media with an inhomogeneous and anisotropic conductivity distribution. The conductivity distribution is discretized via finite elements and is described by a second-order tensor at each finite element node. The inversion method is formulated as a functional optimization with an error functional containing terms measuring data misfit and model covariance by means of smoothness, anisotropy and deviation from a starting model. Including the model covariance information overcomes the problem of ill-posedness at the expense of limiting the allowed models to the class of models which are compatible with the provided model covariance information. The discretized form of the error functional is minimized by a Levenberg–Marquardt type method using an iterative preconditioned conjugate gradient solver. The use of an iterative solver allows one to bypass the actual computation of the Jacobian or an inverse system matrix. The use of a memory efficient iterative solver together with the implementation on parallel computers allows large-scale inverse problems, comprising several hundred thousand nodes with hundreds of sources and receivers, to be solved. The new method is tested using computer-generated data from two- and three-dimensional synthetic models. For each inversion a choice of penalty parameters, gauging the level of model covariance information imposed, has to be made and the level of regularization required is hard to estimate. We find that running a suite of inversions with varying penalty parameters and subsequent examination of the results (including inspection of residual maps) offers a viable method for choosing appropriate numerical values for the penalty levels. In the applications we found the inversion process to be highly non-linear. Inversion models from intermediate steps of the iterative inversion show structure in places that do not exhibit structure in the true model and only at later iterations do anomalies move to the correct location in the modelling domain. This result indicates that linearized inversions that fail to re-linearize during the inversion process will fail to find meaningful inversion images. The inversion images achieved using the new method recover the important features of the true models, including the approximate magnitudes of the conductivity anomalies and the magnitudes and directions of anisotropy anomalies. The inversion images are generally ‘blurred’, that is sharp edges are smoothed, and the recovered magnitudes of conductivity, anisotropy and anisotropy direction are generally under-estimated.

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Section: Introductionmentioning

confidence: 99%

Anisotropic resistivity inversion

et al. 2003

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“…and finely layered anisotropic sands. (i.e., layers of sand of different grain sizes) (Schoen et al, 1999). Gernez et al (2019) confirmed a strong link between K and electrical resistivity anisotropies using hydraulic tomography and Electrical Resistivity Tomography (ERT) in Saint-Lambert-de-Lauzon, Canada.…”

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confidence: 66%

Estimation of anisotropic hydraulic conductivity using geophysical data in a coastal aquifer of Karnataka, India

Nagaraj

Subbarayappa

Jean-Michel

et al. 2021

Hydrological Processes

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Estimation of hydraulic parameters is essential to understand the interaction between groundwater flow and seawater intrusion. Though several studies have addressed hydraulic parameter estimation, based on pumping tests as well as geophysical methods, not many studies have addressed the problem with clayey formations being present. In this study, a methodology is proposed to estimate anisotropic hydraulic conductivity and porosity values for the coastal aquifer with unconsolidated formations. For this purpose, the one-dimensional resistivity of the aquifer and the groundwater conductivity data are used to estimate porosity at discrete points.The hydraulic conductivity values are estimated by its mutual dependence with porosity and petrophysical parameters. From these estimated values, the bilinear relationship between hydraulic conductivity and aquifer resistivity is established based on the clay content of the sampled formation. The methodology is applied on a coastal aquifer along with the coastal Karnataka, India, which has significant clayey formations embedded in unconsolidated rock. The estimation of hydraulic conductivity values from the established correlations has a correlation coefficient of 0.83 with pumping test data, indicating good reliability of the methodology. The established correlations also enable the estimation of horizontal hydraulic conductivity on twodimensional resistivity sections, which was not addressed by earlier studies. The inventive approach of using the established bilinear correlations at one-dimensional to two-dimensional resistivity sections is verified by the comparison method. The horizontal hydraulic conductivity agrees with previous findings from inverse modelling. Additionally, this study provides critical insights into the estimation of vertical hydraulic conductivity and an equation is formulated which relates vertical hydraulic conductivity with horizontal. Based on the approach presented, the anisotropic hydraulic conductivity of any type aquifer with embedded clayey formations can be estimated. The anisotropic hydraulic conductivity has the potential to be used as an important input to the groundwater models.

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“…The micro genesis of low resistivity oil layers is complex and diverse, generally caused by a combination of one or more factors such as reservoir lithology, physical properties, and oil bearing properties. The micro genesis is not entirely the same under different sedimentary backgrounds (Zheng et al, 2018;Wang et al, 2016;Liao et al, 2010;Schoen et al, 1999). The reason why rocks exhibit low resistivity is mainly due to the particularity of rocks and fluids, and their electrical conductivity is mainly affected by both fluid and rock skeleton.…”

Section: Microgenesis Of Low Resistivity Reservoirsmentioning

confidence: 99%

Study on Geological Genesis and Sedimentary Model of Complex Low Resistivity Reservoir in Offshore Oilfield — A Case of NgIII Formation of X Oilfield in Bohai Sea

Zhang¹,

Tan²,

Wang³

et al. 2023

GEP

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In order to study the micro genetic mechanism and main geological controlling factors of low resistivity reservoir in NgIII formation of X oilfield in Bohai sea in China, the clay mineral composition, irreducible water saturation, salinity and conductive minerals of low resistivity reservoir were studied by using the data of core, cast thin section and analysis, and compared with normal resistivity reservoir. At the same time, the control effect of sedimentary environment on low resistivity reservoir was discussed. The results show that the additional conductivity of high bound water content and high montmorillonite content in the reservoir together leads to the significant reduction of reservoir resistivity, which is the main microscopic cause of the formation of low resistance, and is mainly controlled by the sedimentary background such as paleoclimate and sedimentary cycle. During the deposition period of NgIII formation, the paleoclimate was dry and cold, and it was at the end of the water advance of the medium-term sedimentary cycle. The hydrodynamic force of the river channel was weak, the carrying capacity of the riverbed was weak, and the river channel swayed frequently, resulting in fine lithologic particle size, high shale content and complex pore structure of the reservoir, resulting in significant reduction of reservoir resistance. The research conclusion would have strong guiding significance for the development of low resistivity reservoirs in this area.

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Macroscopic Electrical Anisotropy of Laminated Reservoirs: A Tensor Resistivity Saturation Model

Abstract: This paper was prepared for presentation at the 1999 SPE Annual Technical Conference and Exhibition held in Houston, Texas, 3–6 October 1999.

Cited by 30 publications

References 5 publications

Anisotropic resistivity inversion

Anisotropic resistivity inversion

Estimation of anisotropic hydraulic conductivity using geophysical data in a coastal aquifer of Karnataka, India

Study on Geological Genesis and Sedimentary Model of Complex Low Resistivity Reservoir in Offshore Oilfield — A Case of NgIII Formation of X Oilfield in Bohai Sea

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