Core-scale characterisation of flow in tight Arabian formations

Akanji, Lateef; Nasr, G. G.; Bageri, Mohamed

doi:10.1007/s13202-013-0062-1

Cited by 12 publications

(5 citation statements)

References 16 publications

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“…With the increasing demands on energy and exhausting conventional resources, unconventional tight oil reservoirs are becoming important, and how to effectively develop them becomes a focus (Akanji et al 2013;Yang et al 2013). Tight oil reservoirs normally have complicated pore throat parameters, which determine the reservoirs quality and affect the oilfield development.…”

Section: Introductionmentioning

confidence: 99%

Quantitative determination of pore and throat parameters in tight oil reservoir using constant rate mercury intrusion technique

Gao

Ling

2015

J Petrol Explor Prod Technol

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The development of tight oil depends on the characteristics of complicated pore throat parameters. In this study, the tight oil samples obtained from the Yanchang group of Ordos basin (China) are tested using the constant rate mercury intrusion technique to quantitatively determine the size of pore and throat parameters, as well as analyze the key parameters that control the quality of tight oil reservoir. The pore radius of sample analogously distributes in 100-200 lm and average pore radius varies from 103.7 to 139.74 lm. When the permeability is less than 1 9 10 -3 lm 2 , the throat peak radius and the average throat radius will be less than 1 lm; furthermore, the variation of throat distribution is in the range of 0.2-0.5 and 0.2-1.0 lm. On the contrary, if the permeability is greater than 1 9 10 -3 lm 2 , the average throat radius will be greater than 1 lm and the distribution range of throat will spread from 0.2-3.4 to 0.2-8.8 lm. As for the eleven samples, the main flow throat radius lies in the range of 0.41-3.71 lm, the throat quantity changes wildly from 1324 to 4271 number/cm 3 , the average pore throat ratio varies from 503.59 to 86.11, the pore mercury saturation alters in 17.65-55.95 % and the throat mercury saturation distributes in 13.44-27.6 %. It can be learned that there is no obvious difference in pore parameters for tight oil reservoir. Therefore, the difference of pore throat structure mainly existed in throat parameters, and the throat parameters are the key factors that affect the physical properties and recovery results.

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Section: Introductionmentioning

confidence: 99%

Quantitative determination of pore and throat parameters in tight oil reservoir using constant rate mercury intrusion technique

Gao

Ling

2015

J Petrol Explor Prod Technol

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“…These approaches include mercury injection porosimetry (MIP), nuclear magnetic resonance (NMR), core analysis method developed by Gas Research Institute (GRI), and pulse decay 9 – 16 . Despite being frequently employed, these direct experimental measurements have significant limitations in current laboratory operating conditions, such as the involvement of significant time, cost-effectiveness, and a few cores samples 17 . These limitations motivate us to develop a new efficient algorithm for analyzing the pore structure characterization and permeability in a porous medium, which can produce reliable results within a short time and be cost effective.…”

Section: Introductionmentioning

confidence: 99%

Estimation of pore structure and permeability in tight carbonate reservoir based on machine learning (ML) algorithm using SEM images of Jaisalmer sub-basin, India

Yalamanchi,

Datta Gupta

2024

Sci Rep

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Analyzing the pore structure in carbonate reservoirs plays a crucial role in predicting fluid flow characteristics within these formations. The goal of the study was to use machine learning techniques for pore structure analysis and estimation of permeability in carbonate reservoirs. We implemented these algorithms by examining 2D scanning electron microscope (SEM) images of carbonate samples from the Jaisalmer sub-basin captured at various magnifications. In the initial stage of the analysis, various binarization algorithms were applied to determine carbonate sample porosity. Among these algorithms, the MaxEntropy algorithm gave a porosity value closely aligned with those obtained through petrography analysis. We employed the watershed algorithm to find the pore network parameters of carbonate samples at various magnifications. We observed that changes in magnification affected pore network parameters, resulting in a reduction in pore size distribution, throat radius, and grain size. Subsequently, we employed the numerical lattice Boltzmann method (LBM) to estimate the permeability of carbonate samples and compared to values derived from well logs. We employed machine learning (ML) algorithms, specifically Artificial Neural Network (ANN) and Support Vector Machine (SVM), to predict the permeability of carbonate samples. The input features for these models were the pore network parameters, while the LBM permeability values served as the output. We examine the prediction performance of these methods against the measured LBM permeability by conducting the error analysis and the coefficient of determination ($${R}^{2}$$ R 2 ) calculation. Our findings revealed that the ANN models outperformed the SVM models. Specifically, the ANN model displayed an impressive R2 value of 0.892, along with root mean square error (RMSE), mean squared error (MSE) and, mean absolute error (MAE) values of 1.927, 3.716 and 1.580, respectively. In contrast, the SVM model yielded an R2 value of 0.849, with RMSE, MSE and, MAE values of 2.324, 5.401 and, 2.166 respectively, when assessed on testing data of measured permeability. This study found that ANN is more dependable, robust, and precise than SVM in forecasting carbonate sample permeability.

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“…Here, tight but thermally highly conductive carbonate rocks bear the potential of playing a vital role in the energy transition (e.g., Gosnold et al 2010;Hofmann et al 2014). Such reservoirs are characterized by very low matrix permeabilities, typically in the range of 0.001-10 mD (Akanji et al 2013), implying that fluid transport in low-permeable or tight carbonate rocks is focused to fractures and faults (Al-Obaid et al 2005;Dimmen et al 2017;Litsey et al 1986;O'Neill 1988;Zeybeck and Kuchuk 2002) with only minor fluid flow through the rock matrix (Bohnsack et al 2020(Bohnsack et al , 2021. However, microporosity and structures may impact fracture pattern, fracture density, fracture propagation, well logging (e.g., PHI, acoustic log, neutron log), and fluid losses, and thus the effectivity of carbonate matrix stimulation treatments (Barri et al 2021;Ziauddin and Bize 2007).…”

Section: Introductionmentioning

confidence: 99%

Petrophysical characterization, BIB-SEM imaging, and permeability models of tight carbonates from the Upper Jurassic (Malm ß), SE Germany

et al. 2022

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Tight carbonate rocks are important hydrocarbon and potential geothermal reservoirs, for example, in CO2-Enhanced Geothermal Systems. We report a study of outcrop samples of tectonically undeformed tight carbonates from the upper Jurassic “Malm ß” formation in Southern Germany near the town of Simmelsdorf (38 km NE of Nuremberg) to understand bulk petrophysical properties in relation to microstructure and to compare models for permeability prediction in these samples. We applied Archimedes isopropanol immersion, Helium pycnometry, mercury injection, gamma density core logging, and gas permeability measurements, combined with microstructural investigations and liquid metal injection (LMI-BIB-SEM). In addition, ultrasonic velocity was measured to allow geomechanical comparison of stratigraphically equivalent rocks in the South German Molasse Basin (SGMB). Results show only small variations, showing that the formation is rather homogeneous with bulk porosities below 5% and argon permeabilities around 1.4E−17 m2. The presence of stylolites in some of the samples has neither a significant effect on porosity nor permeability. Pores are of submicron size with pore throats around 10 nm and connected as shown by Mercury injection and Liquid Metal injection. Samples have high dynamic Young’s Modulus of 73 ± 5 GPa as expected for lithified and diagenetically overmature limestones. Moreover, no trends in properties were observable toward the faults at meter scale, suggesting that faulting was post-diagenetic and that the matrix permeabilities were too low for intensive post-diagenetic fluid–rock interaction. Petrophysical properties are very close to those measured in the SGMB, illustrating the widespread homogeneity of these rocks and justifying the quarry as a reasonable reservoir analog. Permeability prediction models, such as the percolation theory-based Katz-Thompson Model, Poiseuille-based models, like the Winland, the Dastidar, the capillary tube, and the Kozeny-Carman Models, as well as several empirical models, namely, the Bohnsack, the Saki, and the GPPT Models, were applied. It is shown that the capillary tube Model and the Saki Model are best suited for permeability predictions from BIB-SEM and mercury injection capillary pressure results, respectively, providing a method to estimate permeability in the subsurface from drill cuttings. Matrix permeability is primarily controlled by the pore (throat) diameters rather than by the effective porosity.

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Core-scale characterisation of flow in tight Arabian formations

Cited by 12 publications

References 16 publications

Quantitative determination of pore and throat parameters in tight oil reservoir using constant rate mercury intrusion technique

Quantitative determination of pore and throat parameters in tight oil reservoir using constant rate mercury intrusion technique

Estimation of pore structure and permeability in tight carbonate reservoir based on machine learning (ML) algorithm using SEM images of Jaisalmer sub-basin, India

Petrophysical characterization, BIB-SEM imaging, and permeability models of tight carbonates from the Upper Jurassic (Malm ß), SE Germany

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