Matrix Dielectric Permittivity for Enhanced Formation Evaluation

Modern dielectric tools are often run to obtain fundamental formation properties, such as remaining oil saturation, water-filled porosity, and brine salinity. Techniques to extract more challenging reservoir petrophysical properties like Archie m and n parameters are also emerging. The accuracy and representativeness of the obtained petrophysical parameters depend on the input parameter accuracy, such as matrix permittivity. In carbonates, matrix permittivity is known to vary over a wide range, for example, limestone matrix permittivity reported in the literature ranges from 7.5 to 9.2. The main objective of the current study is to reduce matrix dielectric permittivity uncertainty for enhanced formation evaluation in carbonate reservoirs. All dielectric measurements were conducted on 1.5 in. carbonate plug samples by means of a coaxial reflection probe with a range of frequency between 10 MHz and 1 GHz. To calculate matrix mineral dielectric permittivity, sample porosity must be obtained. Stress-corrected helium porosity from routine core analysis is used and samples mineralogy and chemical composition are measured by X-Ray diffraction. Dielectric system calibration is done by utilizing several well-characterized standards with known dielectric properties. Calcite and dolomite matrix permittivity are assessed by laboratory measurements. Results of this study and based on data from 180 core plugs allowed to assess the validity of the defined errors by statistical analysis, resulting in much reduced uncertainties in carbonate rock matrix dielectric permittivity; thus enhancing formation evaluation using dielectric measurements. The current study provides better control on dielectric permittivity values used in dielectric log interpretation for limestone formations. Such knowledge will provide better confidence in interpreted data such as water-filled porosity, flushed zone salinity and water phase tortuosity.

Rapid Detection of Salmonella typhimurium in Drinking Water by a White Light Reflectance Spectroscopy Immunosensor

Biosensors represent an attractive approach for fast bacteria detection. Here, we present an optical biosensor for the detection of Salmonella typhimurium lipopolysaccharide (LPS) and Salmonella bacteria in drinking water, based on white light reflectance spectroscopy. The sensor chip consisted of a Si die with a thin SiO2 layer on top that was transformed into a biosensor through the immobilization of Salmonella LPS. The optical setup included a reflection probe with seven 200 μm fibers, a visible and near-infrared light source, and a spectrometer. The six fibers at the reflection probe circumference were coupled with the light source and illuminated the biosensor chip vertically, whereas the central fiber collected the reflected light and guided it to the spectrometer. A competitive immunoassay configuration was adopted for the analysis. Accordingly, a mixture of LPS or bacteria solution, pre-incubated for 15 min, with an anti-Salmonella LPS antibody was pumped over the chip followed by biotinylated secondary antibody and streptavidin for signal enhancement. The binding of the free anti-Salmonella antibody to chip-immobilized LPS led to a shift of the reflectance spectrum that was inversely related to the analyte concentration (LPS or bacteria) in the calibrators or samples. The total assay duration was 15 min, and the detection limits achieved were 4 ng/mL for LPS and 320 CFU/mL for bacteria. Taking into account the low detection limits, the short analysis time, and the small size of the chip and instrumentation employed, the proposed immunosensor could find wide application for bacteria detection in drinking water.

A Briggs-Rauscher Reaction-based Spectrometric Assay to Determine Antioxidant Content in Complex Matrices in Low Technology Environments

The Briggs-Rauscher (BR) reaction is free radical based where the kinetics of formation of different iodide species leads to potentiometric and color oscillations. These oscillations were monitored in this study using a UV/Vis attenuated total reflection probe to develop an assay to measure the antioxidant content in complex matrices. The periodicity of the BR reaction was found to be very consistent (range 24–25 seconds, n = 16). Adding various amounts of ascorbic acid, a well-known antioxidant, led to an inhibition of the reaction with a linear calibration curve of antioxidant periodicity time (APT, r 2 > 0.99). The validity of this test in complex matrices was studied by determining the APT of nine fruits, and the resulting antioxidant capacity in ascorbic acid equivalency was calculated. The results generated by this assay were found be accurate through comparison with the well-established FRAP assay. These results show that visual or spectrometric monitoring of BR reaction can be used as a reliable, quick, and inexpensive alternative to more established assays with the added advantage that values generated from this assay is at pH 2 which is similar to that in the human stomach.

An Improved Algorithm for Measuring Nitrate Concentrations in Seawater Based on Deep-Ultraviolet Spectrophotometry: A Case Study of the Aoshan Bay Seawater and Western Pacific Seawater

Nowadays, it is still a challenge for commercial nitrate sensors to meet the requirement of high accuracy in a complex water. Based on deep-ultraviolet spectral analysis and a regression algorithm, a different measuring method for obtaining the concentration of nitrate in seawater is proposed in this paper. The system consists of a deuterium lamp, an optical fiber splitter module, a reflection probe, temperature and salinity sensors, and a deep-ultraviolet spectrometer. The regression model based on weighted average kernel partial least squares (WA-KPLS) algorithm together with corrections for temperature and salinity (TSC) is established. After that, the seawater samples from Western Pacific and Aoshan Bay in Qingdao, China with the addition of various nitrate concentrations are studied to verify the reliability and accuracy of the method. The results show that the TSC-WA-KPLS algorithm shows the best results when compared against the multiple linear regression (MLR) and ISUS (in situ ultraviolet spectrophotometer) algorithms in the temperatures range of 4–25 °C, with RMSEP of 0.67 µmol/L for Aoshan Bay seawater and 1.08 µmol/L for Western Pacific seawater. The method proposed in this paper is suitable for measuring the nitrate concentration in seawater with higher accuracy, which could find application in the development of in-situ and real-time nitrate sensors.