A Novel Method to Obtain Permeability in a Dual-Pore System Using Geophysical Logs: A Case Study of an Upper Triassic Formation, Southwest Ordos Basin, China

Qin, Zhihong; Dong, Wu; Luo, Sanzhong; Ma, Xiugang; Huang, Ke; Tian, Fei; Xiao, Kun; Xiao, Chi; Hou, Min; Pan, Heping

doi:10.1007/s11053-019-09612-3

Cited by 8 publications

(2 citation statements)

References 48 publications

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“…Seepage monitoring has always been an essential part of earth-rock dam safety monitoring [2]. By monitoring the seepage behavior of the earth-rock dam, it is possible to predict the seepage development trend, estimate the amount of seepage, detect the abnormal seepage position, and evaluate the operational status of the earth-rock dam [3][4][5]. The seepage behavior of the earth-rock dam is generally reflected by monitoring the internal seepage pressure, the piezometric tube's water level, and the dam's leakage [6].…”

Section: Introductionmentioning

confidence: 99%

Seepage prediction model of the earth-rock dam based on TCN considering rainfall lag effect

2024

Meas. Sci. Technol.

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Renewable energy has the highest conversion efficiency, is the most flexible in regulating peak power in the grid, and has the potential to significantly reduce emissions. Hydropower is one of the main ways to optimize power energy structure by building earth-rock dams that block water and generate electricity. Seepage is a physical quantity that characterizes the safety of earth-rock dams. Studying the intelligent prediction model of earth-rock dams is an effective means of understanding the evolution of seepage behavior, and it is also crucial for the safe operation and energy efficiency of earth-rock dams. To create a rainfall factor expression reflecting the hysteresis effect of rain, actual monitoring data of different piezoelectric tubes on the upstream and downstream sides of the soil core wall of an earth-rock dam is considered. Based on the key influencing factors of the seepage behavior of earth-rock dams, the novel TCN algorithm in deep learning is introduced into the seepage behavior prediction of earth-rock dams, constructing the intelligent prediction model of seepage of earth-rock dams based on TCN. The engineering example shows that the seepage prediction model of the earth-rock dam based on TCN has better prediction performance than the seepage prediction model of the earth-rock dam based on SVR, ELM, and LSTM. The determination coefficient is more significant than 0.9, and the relative error of prediction is less than 1‰. The model's prediction accuracy is high, and the stability of the prediction performance is good. The model's prediction performance also improves after considering the rainfall lag effect.

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Section: Introductionmentioning

confidence: 99%

Seepage prediction model of the earth-rock dam based on TCN considering rainfall lag effect

2024

Meas. Sci. Technol.

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“…Various studies have been performed to estimate the absolute permeability of different carbonate and sandstone reservoirs [15][16][17][18][19]. It is important to mention that predicting permeability and developing a straight equation for permeability as a function of petrophysical properties for carbonate reservoirs is a complicated task because of the availability of several uncertainties (e.g., anisotropy and heterogeneity) in these reservoirs.…”

Section: Introductionmentioning

confidence: 99%

A New Approach to Predicting Vertical Permeability for Carbonate Rocks in the Southern Mesopotamian Basin

Al-Khdheeawi,

Allawi,

Al-Rubaye

et al. 2023

Minerals

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Reservoir performance depends on many factors, and the most important one is permeability anisotropy. In addition, with high heterogeneity, it is essential to find unique relationships to predict permeability. Therefore, this study aims to predict vertical permeability based on horizontal permeability and porosity and to find new equations for carbonate reservoirs. This work relied on the 398 measured points of cores data collected from several wells in carbonate reservoirs. A new correlation for predicting vertical permeability for the whole data (369 samples) as a function of horizontal permeability and porosity has been developed. The results indicate that this new correlation can estimate the vertical permeability with correlation coefficients (RSQ) of 0.853. Then, the used data were divided into four groups depending on the Kv/Kh values: less than 0.1, 1–0.1, 1–10, and more than 10, and a new correlation for permeability prediction for each group has been developed with good RSQ values of 0.751, 0.947, 0.963, and 0.826, respectively. The previous studies lack the correlations to predict vertical permeability in carbonate reservoirs, so this study can be considered as a reference for similar cases.

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Fluid and lithology discrimination using integrated facies, petrophysical modelling and (AI and vp/vs) rock physics template analysis derived from well data in the carbonate fault-controlled reservoir: A case study from the North Beda Field, Amin High, Sirt Basin, Libya

Gumati

2024

Acta Geophys.

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A Novel Method to Obtain Permeability in a Dual-Pore System Using Geophysical Logs: A Case Study of an Upper Triassic Formation, Southwest Ordos Basin, China

Cited by 8 publications

References 48 publications

Seepage prediction model of the earth-rock dam based on TCN considering rainfall lag effect

Seepage prediction model of the earth-rock dam based on TCN considering rainfall lag effect

A New Approach to Predicting Vertical Permeability for Carbonate Rocks in the Southern Mesopotamian Basin

Fluid and lithology discrimination using integrated facies, petrophysical modelling and (AI and vp/vs) rock physics template analysis derived from well data in the carbonate fault-controlled reservoir: A case study from the North Beda Field, Amin High, Sirt Basin, Libya

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