Water Content In Oil Research Articles

Advances in heat‐pulse methods: Measuring near‐surface soil water content

AbstractSoil water content (θ) influences physical, chemical, and biological processes in the soil. Near‐surface θ (<1‐cm depth) is particularly important for surface energy partitioning, but few techniques are available for near‐surface in situ θ measurements. Heat‐pulse sensors can be used to determine the soil volumetric heat capacity, which is linearly related to θ. Here we describe the principles and procedures of determining near‐surface in situ θ with a heat pulse sensor. The main limitations and potential errors associated with the method are also presented. When ambient soil temperature drift and the soil–air interface effects are addressed, the error in the heat‐pulse‐determined θ is greatly reduced. For an example, data series with θ data determined by gravimetric initial θ and heat‐pulse‐based change in θ (Δθ), results agree well with gravimetric θ values, yielding a coefficient of determination of 0.95. We conclude that heat‐pulse sensors are useful tools for continuously and nondestructively determining near‐surface θ of non‐shrink–swell soils.

Applying ultrasonic fields to separate water contained in medium-gravity crude oil emulsions and determining crude oil adhesion coefficients

Separating produced water is a key part of production processing for most crude oils. It is required for quality reasons, and to avoid unnecessary transportation costs and prevent pipework corrosion rates caused by soluble salts present in the water. A complicating factor is that water is often present in crude oil in the form of emulsions. Experiments were performed to evaluate the performance of ultrasonic fields in demulsifying crude oil emulsions using novel pipe-form equipment. A horn-type piezoelectric ultrasonic transducer with a frequency of 20 kHz and power ranging from 80 W to 1000 W was used for experimental purposes. The influences of the intensity of ultrasonic fields, ultrasonic irradiation time, and the initial water content of crude oils were evaluated to establish the rate of water segregation from oil. The experiments applied ultrasonic-field intensities of 0.25 W/cm3, 0.5 W/cm3, 0.75 W/cm3 and 1 W/cm3 to synthetic emulsions with 10%, 15%, 20%, and 25% of the water in crude oil. Crude oil demulsification occurred for each ultrasonic field intensity tested for all the samples tested. Function β involving adhesion coefficients was expressed in terms of wave-field intensity and initial concentration of water in each of the three crude oil samples tested. The experiments demonstrated that despite the absence of any chemical demulsifier involved, water separation caused by applying ultrasonic fields was effective and occurred rapidly. As the intensity of the ultrasonic field applied increased, the amount of water segregated from crude oil also increased. Subjected to constant field intensity, higher initial water cuts (up to 15% or so) in the crude oil samples and higher ultrasonic irradiation times, resulted in greater segregation of water from crude oil in percentage terms. However, in samples with initial water cuts of 20+% long irradiation times (~5 min), resulted in a decline in water separation compared to 2-min tests. Ultrasonic field treatments offer commercially-viable and environmentally-friendly alternatives to treatments using chemical demulsifiers as they reduce desalination requirements of wastewater.

Error Correction Method of Crude Oil Moisture Content Detection Based on BP Neural Network

Microwave phase-shifting sensor is one of the effective means to realize online detection of water content in high water-cut crude oil, but its detection accuracy is easily affected by salinity. Aiming at the mineralization components (NaCl and CaCl2) existing in water-bearing crude oil, the influence of different proportion and content of dual-component mineralization on the accuracy of microwave phase-shifting crude oil water content detection sensor was studied experimentally, and the influence rule of dual-component mineralization (NaCl and CaCl2) on the accuracy of crude oil water content detection was obtained. It is difficult to establish an accurate error compensation model because the relationship between the composition and content of salinity and the measured water content is affected by many factors. Therefore, a BP neural network model for error correction is established, which reduces the detection error of microwave phase-shifting crude oil moisture sensor from 13.912% to 1.821%, and improves the detection accuracy. BP neural network prediction model is superior to multiple linear regression prediction model.

The Development of Paeonia ostii Seeds and Oil Quality Formation

Paeonia ostii is a woody oil crop with potential value as an edible oil. With the aim of acquiring systematic knowledge of the development of P. ostii seeds, the oil content, biomass, and water content of the seeds were determined. Changes in the distribution of hydrogen protons in P. ostii seeds during follicle development were traced using magnetic resonance imaging (MRI). The formation of oil bodies in the endosperm and embryo was observed using transmission electron microscopy (TEM). Dynamic changes in oleic acid, linoleic acid, and α-linolenic acid contents were assessed by gas chromatography-mass spectrometry (GC-MS). The magnetic resonance images showed that, during early follicle development [45–85 days after flowering (DAF)], a greater quantity of liquid mucus was present within the seeds, and seeds in the same follicle developed at different rates. At 95 to 115 DAF, proton density was distributed evenly in all areas of the seed. A small dark area appeared in the center of the seed, and mucus in the follicles and water in the pericarp disappeared gradually. TEM observations showed that at 45 DAF, a few oil bodies were scattered at the cell periphery in the endosperm, and oil bodies were more numerous in the embryo. With the progression of seed development, the number and size of oil bodies in the embryo and endosperm continued to increase. The fresh and dry mass of P. ostii seeds increased from 45 to 105 DAF, then decreased after 105 DAF. The moisture content decreased, whereas the oil content increased and attained 33.1% at seed maturity. The three predominant unsaturated fatty acids accumulated simultaneously and showed stages of initial accumulation (45–65 DAF) and rapid accumulation (65–105 DAF). The results suggest that 65 to 105 DAF is a critical period for unsaturated fatty acid accumulation in P. ostii seeds.

Measurement of water content in heavy oil with cavity resonator

The study of optical microcavity sensors in current micro optical electromechanical systems (MOEMS) devices is an important research direction in this field. In this study, a surface plasmon optical waveguide structure with MIM (Metal Insulator Metal), semi-circular resonator, and T-shaped resonator was examined. The effects of the coupling distance, the geometrical size of the T-shaped cavity and its asymmetry, and the radius of the semi-circular cavity on the Fano resonance spectrum were analyzed numerically. The sensitivity of the refractive index sensor was up to1066.67nm/RIU. The detection of the water content of the heavy oil found that the Fano resonance line shifted to the short-wave direction as the volume percentage of the contained water increased. The volume percentage resolution of the sensor's heavy oil water content could be as low as2.05×10-9. The proposed structure can overcome the shortcomings of common refractive index sensors and therefore has great application prospects in chemical and biological sensing.

Processing scintillation gamma-ray spectra by artificial neural network

Elemental analysis can be performed using obtained gamma-ray spectrum of the sample under study. In this work, simple Multi-Layer Perceptron (MLP) neural network models are proposed for analyzing a gamma-ray emitting sample using whole information of its obtained gamma-ray spectrum. Elemental analysis is performed in two fields of study using 3 × 3 inch NaI(Tl) detectors: Radio-Isotope Identification (RIID) and Prompt Gamma Neutron Activation Analysis (PGNAA). The gamma-ray point sources are used for an empirical study in RIID field, while a Monte Carlo simulation study is considered for determining chlorine and water content of crude oil using combination of PGNAA technique and a MLP model. According to the obtained results of both empirical and simulation studies, the proposed ANN models are appropriate for elemental analysis using whole gamma-ray spectral information of sample under study.

Determination of water content of crude oil by azeotropic distillation Karl Fischer coulometric titration

The determination of water content in crude oil is important for oil transportation, refining, and trade. However, the sensitivity and accuracy of the conventional azeotropic distillation (AD) method are inadequate. Karl Fischer titration methods may give false high results because of the reducing sulfur compounds in crude oil. The present study developed an azeotropic distillation Karl Fischer coulometric titration (AD-KFCT) method which required a modified instrument and a new calibration procedure. The method was modified to decrease the interference caused by reducing sulfur compounds. A certified reference material for water content in liquid was used to determine the recovery of water mass achieved using the AD-KFCT method. The effect of the sample polarity on the method accuracy was assessed. The relative error and relative standard deviations of the water content in three crude oils containing known amounts of water were -7.5% to 2.9% and 0.4% to 6.0%, respectively. The interference by reducing sulfur compounds was studied. The crude oil containing 1-propanethiol was measured using a sulfur dioxide-free anolyte, and the amount of iodine consumed by the distilled 1-propanethiol was determined. The contribution of 1-propanethiol was then subtracted from the water content measured using the normal Karl Fischer reagent. Finally, the relative error of the modified water content in the crude oil samples containing 1-propanethiol was -4.4% to 0.7%. Therefore, the modified AD-KFCT method is accurate and convenient for crude oil.

Nonlinear studies of graphene oxide and its application to moisture detection in transformer oil using D-shaped optical fibre

ABSTRACT This paper reports nonlinear optical response studies of thin layers using graphene oxide (GO) and their performance for detecting water content in transformer oil using three sets of approaches. The sensor performance is evaluated based on bare optical fibre, D-shape optical fibre integrated with GO and the effects of the covering device with polydimethylsiloxane (PDMS). The improvement of this study is to ensure the stability of the recorded signal. The nonlinear optical response of the prepared dispersion was explored using the Z-scan technique with an 800 nm continuous wave laser beam. Taking advantage of the graphene-induced evanescent field using D-shape optical fibre with PDMS covers on the device can give high sensitivity and good stability for water dissolved in the oil at 1550 nm. We measured fluctuations in transmitted light associated with varying water contents ranging from 16 to 38 ppm.

Enhancement of hydrocarbons production through co-pyrolysis of acid-treated biomass and waste tire in a fixed bed reactor

The elution of metallic content from cotton stalk (CS) and its co-pyrolysis with waste tires (WT) was investigated in fixed bed reactor. Hydrochloric acid (HCl) was used for leaching and successful removal of metals from cotton stalk was observed. Removal efficiencies of 86%, 58%, 48%, 58% and 35% for potassium, calcium, magnesium, sodium, and iron metals were achieved, respectively. Pyrolysis and co-pyrolysis using various mixing ratios of raw (R-CS) and acid washed cotton stalk (W-CS) with waste tire were carried out at 550 °C. Co-pyrolyzing W-CS with WT not only resulted in increased liquid yield with reduced char and gas yields, but also improved the quality of pyrolytic oil evincing the occurrence of strong positive synergistic effect. The addition of WT reduced oxygenates, density and water content of oil whilst pH and calorific value are increased compared to both, R-CS and W-CS pyrolytic oils. Relative percentage area of hydrocarbons increased to 65% in co-pyrolysis of WT with W-CS as compared to 47% for that of R-CS at optimum blend ratio (CS:WT 1:3). Likewise, 19% higher reduction in oxygenated compounds was observed in W-CS and WT co-pyrolytic oil. Co-pyrolyzing WT with R-CS and W-CS resulted in improved quality of oil. However, the synergistic effect was less significant for R-CS suggesting that the presence of intrinsic metals in R-CS hampered the occurrence of synergistic effects.

A novel freezing point determination method for oil–contaminated soils based on electrical resistance measurement and its influencing factors

The traditional testing methods for freezing point measurement cannot accurately and quickly determine the freezing points of soils with a low water content and/or oil. Therefore, a new measurement method, which is more precise and has less error or deviation, was developed to determine the freezing point of soil and was verified by a series of laboratory tests. Additionally, the effects of oil content, water content, soil type, and dry density on freezing point were investigated. The results show that the water/oil mixing sequence remarkably affects the freezing point of sandy organic silt and lean clay; however, it does not affect the freezing point of poorly graded sand with silty clay. At water contents of <15%, the water content affects the freezing point more than the oil content does. At a water content of 5%, the freezing point decreases with increasing oil content. The effect of oil content on freezing point gradually decreases with increasing water content. At the same water and oil contents, the freezing point decreases with decreasing grain size. Moreover, the dry density has little effect on freezing point. The experimental results reveal the factors affecting the freezing point and their influencing mechanism, and provide important thermal parameters for thermal calculation for cold regions engineering.

Transformer Oil Dielectric Characteristics in Microwave Assisted Reconditioning Processes

Maintenance of transformer oil is needed to maintain the quality of power service. Thermal heating and filtering are the main ways to remove contaminants from the oil. In this research, a preliminary study was carried out using microwaves as thermal heaters in the reconditioning process of used transformer oil. The reconditioning process is carried out by filtering and thermal heating varies from temperatures of 40–100 °C using a microwave oven. Dielectric characteristics are shown by analyzing breakdown voltage, dielectric power loss, viscosity, and dc conductivity measurements. The amount of moisture content is also taken into account in measuring the level of thermal efficiency of the heater. Under the influence of microwaves, an increase in the characteristics of the dielectric strength in the form of an increase in breakdown voltage reaches 140.50%. Microwave heating is very good in reducing the water content in oil with a level of thermal efficiency reaching 25.55–40.40%. Removal of contaminants is better done by microwaves characterized by a decrease in the value of the dielectric power loss and dc conductivity at each treatment.

Modeling and optimization of palm oil moisture loss as biodiesel pretreatment

One solution to the problem of energy that can be used as a substitute for fuel oil is biodiesel. Palm oil can be used as biodiesel raw material. The advantage of palm oil is its sustainable availability. However, the water content of palm oil still cannot meet the biodiesel quality requirements based on ASTM D975-08a and ASTM D6751-12 which is less than 0.05%. The purpose of this study is to model and optimize the concentration of zeolite and adsorption times to decrease water content in palm oil. The method in this research is to use activated zeolite adsorption. Data from the results of water loss in palm oil as a pretreatment in the manufacture of biodiesel will be processed using response surface methodology (RSM) with the central composite design (CCD) so that a model and optimum point of zeolite concentration and adsorption time can be found. The model produced using the response surface methodology (RSM) method with a central composite design (CCD) design in the form of quadratic equations. The optimization results produce an optimum value of water loss of 2.74% with an error rate of 4.20%. This optimum value is achieved by zeolites concentration of 13.20% and adsorption time of 126.11 minutes.

Gray-level Co-Occurrence Matrix application to Images Processing of crushed Olives fruits.

This paper shows the results obtained from images processing digitized, taken with a 'smartphone', of 56 samples of crushed olives, using the methodology of the gray-level co-occurrence matrix (GLCM). The values ​​of the appropriate direction (θ) and distance (D) that two pixel with gray tone are neighbourhood, are defined to extract the information of the parameters: Contrast, Correlation, Energy and Homogeneity. The values ​​of these parameters are correlated with several characteristic components of the olives mass: oil content (RGH) and water content (HUM), whose values ​​are in the usual ranges during their processing to obtain virgin olive oil in mills and they contribute to generate different mechanical textures in the mass according to their relationship HUM / RGH. The results indicate the existence of significant correlations of the parameters Contrast, Energy and Homogeneity with the RGH and the HUM, which have allowed to obtain, by means of a multiple linear regression (MLR), mathematical equations that allow to predict both components with a high degree of correlation coefficient, r = 0.861 and r = 0.872 for RGH and HUM respectively. These results suggest the feasibility of textural analysis using GLCM to extract features of interest from digital images of the olives mass, quickly and non-destructively, as an aid in the decision making to optimize the production process of virgin olive oil.

Fractional condensation of pyrolysis vapours as a promising approach to control bio-oil aging: Dry birch bark bio-oil

Bio-oil has several undesired fuel properties such as high viscosity, high acidity, high molecular weight, instability, and phase separation upon aging. Further, the high oxygen content (typically 45–50 wt%) and the water content (typically 15–30 wt%) of pyrolysis oil result in a lower energy density than conventional fuel oils. Whole bio-oil from the fast pyrolysis of birch bark is phase separated at room temperature, probably because of the high extractive content of the bark. It prevents the application of bio-oil derived from birch bark as a fuel. Therefore, the main objective of this research is to investigate the application of fractional condensation of pyrolysis vapors as a promising method to obtain bio-oils that are more resistant to aging. Bio-oil vapors were separated into three cuts: a hard solid in the first condenser, a viscous oily cut (“second condenser cut”) in the second condenser/electrostatic precipitator, and a water-rich acidic liquid in the third condenser. It was found that fractional condensation is an effective method to separate water, acids and other low molecular weight reactive components from bio-oil and is a promising downstream approach to control the quality of bio-oils, making it more suitable for further upgrading and/or direct application. Performing fractional condensation and mixing the second condenser oil fraction with 25% isopropanol yields a very stable liquid fuel.

Self-cleaning poly(L-dopa)-based coatings with exceptional underwater oil repellency for crude oil/water separation

As a new derivative material of polydopamine, poly(L-dopa) (PDopa) possesses abundant catechol, carboxyl and amino groups, endowing a new platform for construction of multifunctional coatings. In the present work, negatively charged PDopa was synthesized on a large scale by self-polymerization of L-3,4-dihydroxyphenylalanine (L-Dopa) in aqueous solutions. The PDopa-based coatings were fabricated via layer-by-layer assembly of positively charged polyelectrolyte and negatively charged PDopa. The as-obtained coatings demonstrate excellent underwater oil repellency with oil contact angles of 165 ± 2° and ultra-low contact angle hysteresis arising from electrostatically-induced and hydrogen bonding-induced hydration layers formed between functional groups of PDopa and water. Unlike traditional underwater superoleophobic coatings realized by introducing hydrophilic nano/microstructures, the smooth PDopa-based coatings can clean up oil fouling simply by water action. The coatings applied onto steel meshes facilitate high-performance separation of both phase-separated and emulsified oil/water mixtures with high flux and separation efficiency solely driven by gravity. By employing the separation apparatus with a sloping plate structure, crude oil/water mixture collected from oilfield with 75–80% of water can be effectively separated under mixture temperature of 35–50 °C, with oil content in water of ~20 to ~70 ppm, and water content in oil of 1.9–4.3%.

Contactless and Simultaneous Measurement of Water and Acid Contaminations in Oil Using a Flexible Microstrip Sensor.

The assessment of the petroleum product quality often involves multiple indicators, among which water content and acid value are two major parameters. The complexity of an oil sample and the narrow space in pipeline transport make it difficult to monitor the oil quality in real-time. Considering the practical requirements, a new type of flexible microstrip sensor is proposed in this work. The shape and line width of the microstrip sensor are studied and optimized by theory and experiments. The proposed square spiral-based microstrip sensor has good water content detection resolution at high frequencies with less acid interference, and it can determine the acid value in the low-frequency band. The sensor surface is further passivated, protecting it from direct contact with the oil sample to enhance the electrochemical robustness, and still achieves good detection linearity and high sensitivity. After encapsulation on a flexible substrate, the proposed microstrip sensor realized the non-contact determination of the water content and acid value of oil at the same time, which is only a few millimeters in size and can conform to various tubing wall shapes. Due to the fact that the manufacture of the sensor is CMOS-compatible, we expect it to be readily applied to many other miniaturized chemical-sensing applications.

Spectral oil analyzer

We worked out a spectral oil analyzer, implemented the method of Fourier transform infrared spectroscopy, which allow simultaneous detecting characteristic peaks of water absorption and sulfur-containing substances in oil within the wavelength range from 0.2 to 25.0 µm. The usage of fiber-optic delivering channels makes it possible to produce online industrial probes for the control of chemical composition and concentration, what is demanded at oil producing platforms and oil refinery plants. As identifiers, we used the most intense absorption peaks of water (λ – 1.45 µm, 1.95 µm, 3.00 µm, 6.00 µm), oil (λ – 1.72 µm, 2.31 µm, 3.41 µm) and sulfur-containing heterocycles (λ – 8.00 µm). The spectral analyzer consists of a broadband-light source, a flow-cell, a fiber-optic assembly, narrow-band optical filters and photodetectors. For delivering a broadband optical signal, a fiber-optic assembly was developed. It comprises silica fibers and polycrystalline fibers derived from solid solutions of silver and thallium (I) halides. It was calculated the effective area and diameter of each fiber type in the assembly, taking into account attenuation coefficients and overall optical losses of the system. Using eight channels for the probe at the same time, we were able to measure the content of water and sulfur-containing substances in oil in concentrations from 0.1 to 100.0 wt %.

Nature-inspired chemistry toward hierarchical superhydrophobic, antibacterial and biocompatible nanofibrous membranes for effective UV-shielding, self-cleaning and oil-water separation

Fabrication of environmental-friendly, low-cost, and free-standing superhydrophobic nanofibrous membranes with additional functionalities such as self-cleaning and UV-shielding properties is highly demanded for oil-water separation. Herein, we describe the preparation of multifunctional superhydrophobic nanofibrous membrane by using a facile and novel nature-inspired method, i.e., plant polyphenol (tannic acid) metal complex is introduced to generate rough hierarchical structures on the surface of an electrospun polyimide (PI) nanofibrous membrane, followed by modification of poly (dimethylsiloxane) (PDMS). Taking an as-prepared tannic acid − Al3+-based superhydrophobic membrane as an example, it not only exhibits anti-impact, low-adhesive and self-cleaning functions, but also presents excellent performance in the separation of various oil-water mixtures. A high flux up to 6935 l m−2 h−1 with a separation efficiency of over 99% and the oil contents in water below 5 ppm is obtained even after repeating use for twenty separation cycles. Additionally, the membrane exhibits excellent UV-shielding property, attributing to the inherent UV-absorbing ability of tannic acid. Furthermore, the membrane also possesses additional properties including antibacterial activity, good biocompatibility, robust mechanical strength, and excellent resistance to various harsh conditions. These attractive properties of the as-prepared membrane make it a promising candidate for potential applications in industrial oil-contaminated water treatments and oil-water separation.

Measurement of crude oil water content based on cross-correlation method

In order to measure the proportion of each phase flow of oil-water mixture in practical application and improve the accuracy of crude oil moisture measurement, a method for measuring the water content of crude oil based on cross-correlation method is proposed. The capacitive array sensor is used for measurement to reduce the influence of the flow pattern on the measurement accuracy. The Particle Swarm Optimization BP Neural Network is used to accurately and nonlinearly fit the relationship between the voltage value and the water content to effectively improve the accuracy of the water content measurement.

Analysis of the feasibility of small-biomass power generation from the palm oil mill – study case: palm oil mill in Riau-Indonesia

Solid waste from a palm oil plant in Indonesia is a tremendous potential for power generation, especially on Riau-Sumatra. The potential of electrical energy that can generate is determined by measuring or calculating the calorific value and amount of solid waste palm oil available. To be burned in the boiler continuously and more efficiently, the solid waste water content of palm oil must reduce to no more than 30%. The conservative substantial waste palm oil calorific value (HHV) is 3,500 kcal/kg. As a result, the mass and power plant balance are capable of producing a gross power of 4.6 MW using 80% efficient fluidised bed boilers and a steam turbine capacity of 5 MW with an isentropic efficiency of 85% with assumption percentages combination fibre: 30 % shell: 70 % fibre. The environmental impacts of power generation from empty fruit bunch (EFB) based on steam turbine generator technology evaluated. The results revealed that EFB utilisation for power generation is environmental friendly than fossil fuel power plants regarding global warming potential and acidification potential with GWP are 89.5 kg CO2 eq per MWh, and 0.515 kg SO2 eq per MWh. Also, the financial analysis of the Biomass Power Plant with a lifetime duration of 25 years, which the project is feasible to implement because IRR is 22.70%, higher than Weighted Average Cost of Capital (WACC) which amounted to 15.61%.