A novel method to estimate resistivity index of tight sandstone reservoirs using nuclear magnetic resonance logs

Feng, Cheng; Yang, Zhiqiang; Feng, Ziyan; Zhong, Yuntao; Ling, Kegang

doi:10.1016/j.jngse.2020.103358

Cited by 13 publications

(6 citation statements)

References 17 publications

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“…Resistivity data is produced from the fluids in the pore spaces and by the interaction between the fluids and the rock surface [ 32 ]. A nuclear magnetic resonance has also been used to estimate the resistivity index of a sandstone reservoir [ 33 ]. The theory of the resistivity calculation is obtained using Ohm's Law [ 34 ]; this is expressed through Equations (1) , (2) ).…”

Section: Introductionmentioning

confidence: 99%

Application of foam assisted water-alternating-gas flooding and quantification of resistivity and water saturation by experiment and simulation to determine foam propagation in sandstone

Khan,

Kim,

Irawan

et al. 2024

Heliyon

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Section: Introductionmentioning

confidence: 99%

Application of foam assisted water-alternating-gas flooding and quantification of resistivity and water saturation by experiment and simulation to determine foam propagation in sandstone

Khan,

Kim,

Irawan

et al. 2024

Heliyon

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“…Based on the variation of mercury injection rate with pressure, further research is conducted on the pore structure parameters of reservoir rocks [10]. Cheng et al (2020) and Andrew et al (2012) [11,12] applied nuclear magnetic resonance radiography to characterize pore diameters from 2 nm to 1000 nm. The processing and interpreting relaxation time data and its indirect conversion to porosity values had the advantages of not damaging the core and having high speed, high accuracy, and strong experimental operability, making it one of the important tools for reservoir evaluation and exploration engineering in oil and gas reservoirs.…”

Section: Introductionmentioning

confidence: 99%

Optimization and Application of XGBoost Logging Prediction Model for Porosity and Permeability Based on K-means Method

Zhang,

Wang,

Jia

et al. 2024

Applied Sciences

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The prediction and distribution of reservoir porosity and permeability are of paramount importance for the exploration and development of regional oil and gas resources. In order to optimize the prediction methods of porosity and permeability and better guide gas field development, it is necessary to identify the most effective approaches. Therefore, based on the extreme gradient boosting (XGBoost) algorithm, laboratory test data of the porosity and permeability of cores from the southern margin of the Ordos Basin were selected as the target labels, conventional logging curves were used as the input feature variables, and the mean absolute error (MAE) and the coefficient of determination (R2) were used as the evaluation indicators. Following the selection of the optimal feature variables and optimization of the hyper-parameters, an XGBoost porosity and permeability prediction model was established. Subsequently, the innovative application of homogeneous clustering (K-means) data preprocessing was applied to enhance the XGBoost model’s performance. The results show that logarithmically preprocessed (LOG(PERM)) target labels enhanced the performance of the XGBoost permeability prediction model, with an increase of 0.26 in its test set R2. Furthermore, the application of K-means improved the performance of the XGBoost prediction model, with an increase of 0.15 in the R2 of the model and a decrease of 0.017 in the MAE. Finally, the POR_0/POR_1 grouped porosity model was selected as the final predictive model for porosity in the study area, and the Arctan(PERM)_0/Arctan(PER0M)_1 grouped model was selected as the final predictive model for permeability, which has better prediction accuracy than logging curves. The combination of K-means and the XGBoost modeling method provides a new approach and reference for the efficient and relatively accurate evaluation of porosity and permeability in the study area.

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“…In the above models, water saturation is the key parameter in the relative permeability calculation. Methods to obtain water saturation are mainly established on the basis of formation electrical properties. − To reduce relative permeability calculation errors caused by water saturation calculation, models building directly on the relationship between relative permeability and rock electrical properties are investigated . In clay-free rock, the flow of water is similar to that of an electric current; by this mechanism, a method of relative permeability calculation from electrical properties is proposed by Li .…”

Section: Introductionmentioning

confidence: 99%

Estimating the Relative Permeability from the Electrical Parameters of Sandstone with a Complex Pore Structure

Xie

Yin²,

Guan³

et al. 2020

Energy Fuels

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Relative permeability is a crucial parameter for reservoir fluid-producing evaluation. In clay-free rock, water flow and electric current are dependent on the same controlling factors. The impact of pore structure on rock electrical properties and fluid flow is significant when calculating relative permeability from electrical properties in complex pore structure sandstone. In this paper, the pore geometry of complex pore structure sandstone is equivalent to tubular-and micromembrane-like shapes. A conduction model and a fluid flow model for two shapes of pores are studied. The study result shows that the flow path of water is the same as the conductive path in tubular-like-shaped pores; however, in micromembrane-like-shaped pores, water does not flow but electric current flows. Based on the above, the relative permeability calculation method from electrical properties in complex pore structure sandstone is proposed. A total of 16 rock samples selected from a complex pore structure reservoir of Dongying Formation in Nanpu Sag are used to verify the validity of the relative permeability calculation method. Rock samples are classified into five pore size distribution types according to NMR experimental data; for each type, relative permeability is calculated using the new method. The result shows that the new method-calculated relative permeability is in accordance with the experimental values and parameter calculation accuracy is improved. The relative permeability calculation method from electrical properties in complex pore structure sandstone has good application prospects and can provide important guidance for high-precision evaluation of complex pore structure reservoirs and research of rock mechanical characteristics.

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A novel method to estimate resistivity index of tight sandstone reservoirs using nuclear magnetic resonance logs

Cited by 13 publications

References 17 publications

Application of foam assisted water-alternating-gas flooding and quantification of resistivity and water saturation by experiment and simulation to determine foam propagation in sandstone

Application of foam assisted water-alternating-gas flooding and quantification of resistivity and water saturation by experiment and simulation to determine foam propagation in sandstone

Optimization and Application of XGBoost Logging Prediction Model for Porosity and Permeability Based on K-means Method

Estimating the Relative Permeability from the Electrical Parameters of Sandstone with a Complex Pore Structure

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