Laboratory Studies to Determine Suitable Chemicals to Improve Oil Recovery from Garzan Oil Field

Garzan oil field is located at the south east of Turkey. It is a mature oil field and the reservoir is fractured carbonate reservoir. After producing about 1% original oil in place (OOIP) reservoir pressure started to decline. Waterflooding was started in order to support reservoir pressure and also to enhance oil production in 1960. Waterflooding improved the oil recovery but after years of flooding water breakthrough at the production wells was observed. This increased the water/oil ratio at the production wells. In order to enhance oil recovery again different techniques were investigated. Chemical enhanced oil recovery (EOR) methods are gaining attention all over the world for oil recovery. Surfactant injection is an effective way for interfacial tension (IFT) reduction and wettability reversal. In this study, 31 different types of chemicals were studied to specify the effects on oil production. This paper presents solubility of surfactants in brine, IFT and contact angle measurements, imbibition tests, and lastly core flooding experiments. Most of the chemicals were incompatible with Garzan formation water, which has high divalent ion concentration. In this case, the usage of 2-propanol as co-surfactant yielded successful results for stability of the selected chemical solutions. The results of the wettability test indicated that both tested cationic and anionic surfactants altered the wettability of the carbonate rock from oil-wet to intermediate-wet. The maximum oil recovery by imbibition test was reached when core was exposed 1-ethly ionic liquid after imbibition in formation water. Also, after core flooding test, it is concluded that considerable amount of oil can be recovered from Garzan reservoir by waterflooding alone if adverse effects of natural fractures could be eliminated.     

Towards an integrated neonatal brain and cardiac examination capability at 7 T: electromagnetic field simulations and early phantom experiments using an 8-channel dipole array

Objective

Neonatal brain and cardiac imaging would benefit from the increased signal-to-noise ratio levels at 7 T compared to lower field. Optimal performance might be achieved using purpose designed RF coil arrays. In this study, we introduce an 8-channel dipole array and investigate, using simulations, its RF performances for neonatal applications at 7 T.

Methods

The 8-channel dipole array was designed and evaluated for neonatal brain/cardiac configurations in terms of SAR efficiency (ratio between transmit-field and maximum specific-absorption-rate level) using adjusted dielectric properties for neonate. A birdcage coil operating in circularly polarized mode was simulated for comparison. Validation of the simulation model was performed on phantom for the coil array.

Results

The 8-channel dipole array demonstrated up to 46% higher SAR efficiency levels compared to the birdcage coil in neonatal configurations, as the specific-absorption-rate levels were alleviated. An averaged normalized root-mean-square-error of 6.7% was found between measured and simulated transmit field maps on phantom.

Conclusion

The 8-channel dipole array design integrated for neonatal brain and cardiac MR was successfully demonstrated, in simulation with coverage of the baby and increased SAR efficiency levels compared to the birdcage. We conclude that the 8Tx-dipole array promises safe operating procedures for MR imaging of neonatal brain and heart at 7 T.

     

Zinc oxide-decorated multiwalled carbon nanotubes: a selective electrochemical sensor for the detection of Pb(II) ion in aqueous media

Journal of Materials Science: Materials in Electronics - Multiwalled carbon nanotubes, due to high conductivity, stability, and large specific surface area, have a potential ability to promote...     

A hybrid knowledge and ensemble classification approach for prediction of venous thromboembolism

Clinical narratives such as progress summaries, lab reports, surgical reports, and other narrative texts contain key biomarkers about a patient's health. Evidence-based preventive medicine needs accurate semantic and sentiment analysis to extract and classify medical features as the input to appropriate machine learning classifiers. However, the traditional approach of using single classifiers is limited by the need for dimensionality reduction techniques, statistical feature correlation, a faster learning rate, and the lack of consideration of the semantic relations among features. Hence, extracting semantic and sentiment-based features from clinical text and combining multiple classifiers to create an ensemble intelligent system overcomes many limitations and provides a more robust prediction outcome. The selection of an appropriate approach and its interparameter dependency becomes key for the success of the ensemble method. This paper proposes a hybrid knowledge and ensemble learning framework for prediction of venous thromboembolism (VTE) diagnosis consisting of the following components: a VTE ontology, semantic extraction and sentiment assessment of risk factor framework, and an ensemble classifier. Therefore, a component-based analysis approach was adopted for evaluation using a data set of 250 clinical narratives where knowledge and ensemble achieved the following results with and without semantic extraction and sentiment assessment of risk factor, respectively: a precision of 81.8% and 62.9%, a recall of 81.8% and 57.6%, an F measure of 81.8% and 53.8%, and a receiving operating characteristic of 80.1% and 58.5% in identifying cases of VTE.     

Can social media usage of scientific literature predict journal indices of AJG,SNIP and JCR? An altmetric study of economics

Scientometrics - Altmetrics are often praised as an alternative or complement to classic bibliometric metrics, especially in the social sciences discipline. However, empirical investigations of...     

Experimental investigation of Co and Fe-Doped CuO nanostructured electrode material for remarkable electrochemical performance

The current research work presents a facile and cost–effective co-precipitation method to prepare doped (Co & Fe) CuO and undoped CuO nanostructures without usage of any type of surfactant or capping agents. The structural analysis reveals monoclinic crystal structure of synthesized pure CuO and doped-CuO nanostructures. The effect of different morphologies on the performance of supercapacitors has been found in CV (cyclic voltammetry) and GCD (galvanic charge discharge) investigations. The specific capacitances have been obtained 156 (±5) Fg^?1, 168(±5) Fg^?1 and 186 (±5) Fg^?1 for CuO, Co-doped CuO and Fe-doped CuO electrodes, respectively at scan rate of 5 mVs^?1, while it is found to be 114 (±5) Fg^?1, 136 (±5) Fg^?1 and 170 (±5) Fg^?1 for CuO, Co–CuO and Fe–CuO, respectively at 0.5 Ag^-1 as calculated from the GCD. The super capacitive performance of the Fe–CuO nanorods is mainly attributed to the synergism that evolves between CuO and Fe metal ion. The Fe-doped CuO with its nanorods like morphology provides superior specific capacitance value and excellent cyclic stability among all studied nanostructured electrodes. Consequently, it motivates to the use of Fe-doped CuO nanostructures as electrode material in the next generation energy storage devices.     

Effect of Boronizing on Operating Stability of Steel AISI 304L under Erosion Impact of Hard Particles

Metal Science and Heat Treatment - The effect of solid boronizing at 950°C for 2 and 4 h on the phase composition, microstructure, hardness and abrasive wear of steel AISI 304L is studied...     

Correlation between instrumental texture and colour quality attributes with sensory analysis of selected cheeses as affected by fat contents

This study evaluated several physical and sensory parameters of different types of cheese available in the Polish market. The measurements of textural properties were conducted in an Instron universal testing machine, while the colour properties of cheeses were measured using a Minolta chromameter. The chemical composition was determined by means of the near‐infrared spectroscopy (NIRs). Moreover, a trained sensory panel was invited to assess the cheese texture‐related properties. Generally, cheeses with reduced fat content were characterised by higher hardness, adhesiveness, cohesiveness and elasticity. Texture‐related parameters of cheese with canola oil were comparable to that of most of full‐fat cheeses. The correlation analysis between physical and sensory attributes related to cheese textural properties indicated the potential applications of TPA, shear and penetration tests (r = 0.766, r = 0.75 and r = 0.765, respectively) for the evaluation of sensory properties related to the hardness. Meanwhile, the elasticity of cheese obtained from sensory evaluation was strongly correlated with the elasticity determined from the shear test (r = 0.722) and moderately correlated with the elasticity from penetration test (r = 0.588), indicating a need to refine the method of penetration test. In addition, cheeses exhibited higher meltability during convection heating at 230 °C than microwave heating. The values of meltability for cheese with reduced fat content were lower than those of full‐fat cheese.