Assessment of Spatial Distribution of Porosity in Synthetic Quartz Cores Using Microfocus Computed Tomography (µCT)

Alshibli, Khalid A.; Alramahi, Bashar; Attia, Attia

doi:10.1080/02726350600934606

Cited by 16 publications

(11 citation statements)

References 10 publications

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“…As the X-rays penetrate through the test specimen, some of them are absorbed. The different rates of absorption reflect changes in the specimen density (Alshibli et al, 2006). The tests were carried out using an X-ray CT scanner (Toshiba Asteion S4) on the compacted specimens.…”

Section: Medical Grade Computed Tomography-scanner Testingmentioning

confidence: 99%

Laboratory study of small-strain behavior of a compacted silty sand

2013

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Small-strain behavior is a key indicator for assessing the performance of compacted fills. Compaction conditions, i.e., initial moisture content and applied energy, govern compaction effectiveness and thus, the structure and matric suction of compacted soil. This paper presents an experimental study of the small-strain behavior of compacted silty sand prepared with different compaction conditions. Specimens with varying initial moisture contents and compaction energies were tested with bender elements to determine the smallstrain shear modulus (G0), while the post-compaction matric suction was measured using the filter paper method and tensiometer. The experimental data suggest a pronounced relationship between G0 and the degree of saturation (Sr) of the as-compacted soil specimens. X-ray computed tomography (CT) scans were performed to examine structural changes of selected specimens upon compaction. The laboratory results are also examined in light of common end-product specifications, which show that it is beneficial to compact the soil slightly dry of optimum moisture content from the modulus point of view. Abstract: Small strain behavior is a key indicator for assessing the performance of compacted fills. Compaction conditions i.e. initial moisture content and applied energy, govern compaction effectiveness and, thus, the structure and matric suction of compacted soil. This paper presents an experimental study of the small strain behavior of compacted silty sand prepared with different compaction conditions.Specimens with varying initial moisture contents and compaction energies were tested with Bender elements to determine the small strain shear modulus (G 0 ), while the post-compaction matric suction was measured using the filter paper method and tensiometer. The experimental data suggests a pronounced relationship between G 0 and the degree of saturation (S r ) of the as-compacted soil specimens. X-ray computed tomography (CT) scans were performed to examine structural changes of selected specimens upon compaction. The laboratory results are also examined in light of common end-product specifications, which show that it is beneficial to compact the soil slightly dry of optimum moisture content from the modulus point of view.CE Database subject headings: small strain shear modulus, compaction energy, degree of saturation, matric suction.3

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Section: Medical Grade Computed Tomography-scanner Testingmentioning

confidence: 99%

Laboratory study of small-strain behavior of a compacted silty sand

2013

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“…62,63 Several AI models had been developed for the accurate estimation of different petroleum aspects including PVT properties prediction of retrograde gases, 64,58 estimating the flow assurance parameters such as predicting gas hydrate temperature 65 and asphaltenes precipitation prediction, 66 and predicting reservoir porosity and permeability, 67,68 rather than the typical estimation techniques. 69,70 5. METHODOLOGY In this study, 407 actual datasets were gathered from daily mud reports for invert emulsion mud.…”

Section: Conventional Drilling Fluids Modelsmentioning

confidence: 99%

Prediction of the Rheological Properties of Invert Emulsion Mud Using an Artificial Neural Network

et al. 2021

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Successful drilling operations require optimum well planning to overcome the challenges associated with geological and environmental constraints. One of the main well design programs is the mud program, which plays a crucial role in each drilling operation. Researchers focus on modeling the rheological properties of the drilling fluid seeking for accurate and real-time predictions that confirm its crucial potential as a research point. However, only substantial studies have real impact on the literature. Several AI-based models have been proposed for estimating mud rheological properties. However, most of them suffer from nonbeing field applicable attractive due to using non-readily field parameters as input variables. Some other studies have not provided a comprehensive description of the model to replicate or reproduce results using other datasets. In this study, two novel robust artificial neural network (ANN) models for estimating invert emulsion mud plastic viscosity and yield point have been developed using actual field data based on 407 datasets. These datasets include mud plastic viscosity (PV), yield point (YP), mud temperature (T), marsh funnel viscosity (MF), and solid content. The mathematical base of each model has been provided to provide a clear means for models' replicability. Results of the evaluation criteria depicted the outstanding performance and consistency of the proposed models over extant ANN models and empirical correlations. Statistical evaluation revealed that the plastic viscosity ANN model has a coefficient of determination (R 2 ) of 98.82%, a root-mean-square error (RMSE) of 1.37, an average relative error (ARE) of 0.12, and an absolute average relative error of 2.69, while for yield point, this model has a coefficient of determination (R 2 ) of 94%, a root-mean-square error (RMSE) of 0.76, an average relative error (ARE) of −0.67, and an absolute average relative error of 3.18.

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“…The use of solar energy or waste heat sources is acceptable for water‐producing systems of such a small size 3–5. The relevancy of nanomaterials is to realize the best attainable properties within the smallest possible loadings through homogenized distribution and stable suspension of these nanoparticles 6–11. Often, heat transfer improvement in solar collectors is one of the basic problems in energy saving, compact designs, and different operating temperatures.…”

Section: Introductionmentioning

confidence: 99%

Water Desalination Using Solar Thermal Collectors Enhanced by Nanofluids

et al. 2021

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The absorption efficiency of a solar collector using different types of nanofluids was improved. Experimental work was carried out to investigate the flat‐plate and evacuated‐tube collectors under outdoor conditions to produce distilled water. A pilot plant was designed and installed. The yield of distilled water at different seawater flow rates and the physical properties of nanofluids were determined. Solar intensity, water mass flow rate, and temperature were measured. The performance of the desalination unit was evaluated in the presence of carbon nanotubes in paraffin wax and ethylene glycol nanofluids. The evaporation efficiency of the flat‐plate collector was improved up to 36 % in the presence of ethylene glycol nanofluid at 80–100 °C.

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Assessment of Spatial Distribution of Porosity in Synthetic Quartz Cores Using Microfocus Computed Tomography (µCT)

Cited by 16 publications

References 10 publications

Laboratory study of small-strain behavior of a compacted silty sand

Laboratory study of small-strain behavior of a compacted silty sand

Prediction of the Rheological Properties of Invert Emulsion Mud Using an Artificial Neural Network

Water Desalination Using Solar Thermal Collectors Enhanced by Nanofluids

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