Generalized effective medium resistivity model for low resistivity reservoir

Abstract

With the advancement in oil exploration, producible oil and gas are being found in low resistivity reservoirs, which may otherwise be erroneously thought as water zones from their resistivity. However, the evaluation of low resistivity reservoirs remains difficult from log interpretation. Since low resistivity in hydrocarbon bearing sands can be caused by dispersed clay, laminated shale, conductive matrix grains, microscopic capillary pores and high saline water, a new resistivity model is required for more accurate hydrocarbon saturation prediction for low resistivity formations. Herein, a generalized effective medium resistivity model has been proposed for low resistivity reservoirs, based on experimental measurements on artificial low resistivity shaly sand samples, symmetrical anisotropic effective medium theory for resistivity interpretations, and geneses and conductance mechanisms of low resistivity reservoirs. By analyzing effects of some factors on the proposed model, we show theoretically the model can describe conductance mechanisms of low resistivity reservoirs with five geneses. Also, shale distribution largely affects water saturation predicted by the model. Resistivity index decreases as fraction and conductivity of laminated shale, or fraction of dispersed clay, or conductivity of rock matrix grains increases. Resistivity index decreases as matrix percolation exponent, or percolation rate of capillary bound water increases, and as percolation exponent of capillary bound water, or matrix percolation rate, or free water percolation rate decreases. Rock sample data from low resistivity reservoirs with different geneses and interpretation results for log data show that the proposed model can be applied in low resistivity reservoirs containing high salinity water, dispersed clay, microscopic capillary pores, laminated shale and conductive matrix grains, and thus is considered as a generalized resistivity model for low resistivity reservoir evaluation. low resistivity reservoir, symmetrical anisotropic effective medium conductance theory, microscopic capillary pores, dispersed clay, laminated shale, conductive matrix grain, generalized resistivity model Now hydrocarbon-bearing low resistivity reservoirs have been found in most of oilfields in China. Since low resistivity reservoirs have commercially-produced oil and potential oil reserves, they have become an important source for increasing oil reserves and oil productions in oilfields. Many analysts have studied geneses of low resistivity reservoirs in detail. Their achievements show that low resistivity in shaly sands can be caused by intrinsic factors, extrinsic factors and complex factors [1][2][3][4][5][6][7][8][9][10][11][12][13] . Intrinsic factors include high saline formation water, high irreducible water saturation caused by microscopic capillary pores, excess conductivity of dispersed clay, conductive minerals in rock matrix and thin sand-shale interlayers. Extrinsic factors contain salt mud invasion, different conditions between hydrocarbon b...

Optimization of gas saturation calculation model for deep clastic reservoirs under strong compression stress

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A New Method for Predicting the Gas Content of Low-Resistivity Shale: A Case Study of Longmaxi Shale in Southern Sichuan Basin, China

“…To determine the resistivity of the wet clay, the statistical method of data was utilized. Due to the large number of factors in low-resistivity shale that can lead to reduced resistivity in logging, it is not appropriate to select low-resistivity shale to determine the resistivity of wet clay [39]. The shale of well R2 was selected for the wet clay resistivity value, and the organic matter in the Longmaxi Formation shale of this well did not lead to a decrease in log resistivity (Figure 6a).…”

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