Evaporation of Heavy Crude Oil in Soil

Heavy crude oil spillage on soil threatens productivity and affects the natural biota of the ecosystem. Evaporation is an important parameter increases crude oil density, viscosity and fraction of lower molecular weight substances which reduce its infiltration into the soil and groundwater. The evaporation of heavy crude oil showed API of 21.5, viscosity of 15mm2/s, density 0.8952 g/cm3, pour point of 11.37. The crude oil was exposed to solar radiation for 35 days. The percentage reduction in mass of the crude oil and temperature on five day interval showed 8.22(38OC) on day 0, on day 5 was 8.13(34oC), on day 10 was 5.92(39oC), on day 15 was 5.38(39oC), on day 20 was 3.16(37oC), on day 25 was 2.94(31oC), on day 20 was 2.56 (41oC) and on day 35 was 1.79(38oC). The lighter molecules evaporated first leaving the heavier molecules behind causing a reduction in the rate of evaporation with time. This analysis will be provide insight to modelling oil spill in terrestrial ecosystem.

Pengaruh Waktu Ekstraksi, Rasio Bahan/Pelarut, dan Daya Microwave Terhadap Hasil Ekstraksi Minyak Serai Dapur dengan Bantuan Gelombang Mikro

Lemongrass, one type of source of essential oils, is widely cultivated in Indonesia. There are several methods for extracting the essential oils from lemongrasses, such as hydro-distillation, steam distillation, soxhlet extraction, extraction with supercritical fluids, ultrasonic extraction, and microwave-assisted hydro-distillation. In this study, microwave-assisted hydro-distillation was used as the extraction method. The purpose of this study was to determine the effect of extraction time (60 minutes, 75 minutes, and 90 minutes), lemongrass/solvent ratio (1:4 g/mL and 1:5 g/mL), and microwave power (500 watt and 600 watt) on quantity and quality of lemongrass essential oil. The essential oils obtained were analyzed in the form of calculation of the essential oil density, yield, and GC-MS analysis. The results of the analysis showed that the density of the extracted lemongrass oil ranged from 0.880 g/mL – 0.920 g/mL at a temperature of 30 oC, with the highest yield ranging from 0.0044% – 0.0046% in samples with a material/solvent ratio of 1:5 g/mL. The components found in lemongrass oil were Z-citral, geranyl acetate, geraniol.

Developing a Model to Predict Oil Viscosity Using Specific Gravity and Formation Volume Factor as Correlating Parameters

This paper presents the research work on using a machine learning algorithm to predict the viscosity of Niger Delta oil reservoirs using formation volume factor and fluid density at bubble point pressure as correlating parameters. Oil Viscosity stands out when considering the amount of oil recoverable from the reservoir hence it is an important input into the recovery factor computation, material balance analysis, reservoir simulation/history match, EOR evaluations and many other applications. Laboratory techniques of obtaining oil viscosity are quite expensive and time consuming, hence the need for various mathematical correlations developed for its estimation. Majority of the correlations make use of empirical and experimental relationships developed from analyzing oil samples to obtain a trend to predict viscosity mostly for a basin. None of these has been developed for oil viscosity for Niger Delta fluids. Viscosity has been globally defined as the resistance to shear stresses within the fluid or the resistance of the fluid molecules to deformation. For a typical reservoir fluid system, where the liquid and gas exist in dynamic equilibrium, reservoir fluid composition along with temperature and pressure has been established to determine reservoir fluid viscosity1. Hence for an isothermal system and at a defined pressure in the reservoir the viscosity will be dependent on largely the composition. The reservoir fluid composition is also represented by the reservoir fluid density and the formation volume factor; therefore it is possible to deduce the viscosity of reservoir fluids from the oil density and formation volume factor even though a direct relationship has not been established between these parameters. Therefore, a correlation that can establish a relationship between the specific gravity (density) and FVF with viscosity will have significant value in the oil and industry. The data used for this analysis includes viscosity, formation volume factor, oil density at 2800 sample bubble point pressure. The data was obtained by analyzing over 3500 PVT Analysis reports, extracting the data points using a python work program, cleaning up the data and removing erroneous data, performing preliminary analysis to establish baseline relationships between the data. Supervised learning using a classification tree model was used as the machine learning approach. Seven different machine learning algorithms were reviewed, and the Random Forest Regressor was selected as the most suitable algorithm for the prediction. The model prediction results were quiet encouraging as the model was able to predict viscosity within 10% deviation from the experimental viscosity for over 80% of the cases resulting in about 90% prediction accuracy. The analysis of the results further revealed that the model could better predict viscosity of Medium to Light oil with an R2 value of between 0.90-0.96 without adjusting some obvious erroneous data points. Future of this research work will involve further in-depth analysis which will merge the preliminary QC plots with the results to evaluate the effect of the outlier sample points on the final predictability of the model. Also explore other machine learning models to further improve predictability and be able to predict viscosity across other pressure values other than the bubble point pressure to capture viscosity along the producing life of the reservoir.

Effect of Changing Crude Oil Grade on Slug Characteristics and Flow Induced Mechanical Stresses in Pipes

Slug multiphase flow is known to be the most prevalent regime because of its extensive encounters associated with chaotic behaviour, complexity and instability that cause significant fluctuations in operating conditions and thus lead to undesirable effects. In this study, the effect of varying crude oil grades on slug characteristics is numerically investigated. A partitioned one-way coupling framework of fluid–structure interaction (FSI) one-way coupling framework is adopted to investigate the influence of changing oil grades and slug characteristics on the maximum induced stresses in horizontal carbon steel pipe. It was found that increasing crude oil density causes frequent slugging and promotes the formation of liquid slugs further upstream near the inlet with high translational velocity and short wavelength. Therefore, the maximum induced stresses resulting from the interaction between slugs and the inner surface of pipes are strongly dependent on crude oil grade. In modelling extra heavy crude oil, a 40% increase in maximum induced stresses is recorded when the liquid superficial velocity decreases from 1 to 0.86 m/s at a constant natural gas superficial velocity.

Experimental and computational studies of an antiplasmodial derivative of allantoin; antimycobacterial essential oil from Cordia batesii WERNHAM (Boraginaceae)

Background Chemical and pharmacological investigations were performed on the stems of Cordia batesii (Boraginaeae); chemical studies included quantum calculations applied on a newly described compound. Results A new derivative of allantoin (1) named batesiin (2) was characterized. Thirteen other known compounds involving allantoin (1) were either isolated or identified. GC–MS enabled the identification of six compounds from a fraction containing essential oil. MeOH extract and some isolated compounds were tested in vitro against Pf7G8 CQS and Pf Dd2 CQR strains of Plasmodium falciparum; extract disclosed a moderate antiplasmodial activity (IC50 = 50 μg mL−1). Meantime, the CH2Cl2 extract and essential oil fraction were tested on a resistant mycobacterial strain of Mycobacterium tuberculosis; a potent antimycobacterial activity with a MIC = 9.52 μg mL−1 was deduced from essential oil. Density functional theory (DFT) calculations were carried on batesiin (2). Calculated chemical shifts at B3LYP/6-31G(d,p) and MPW1PW91/6-31G+(d,p) showed much better correlations with the experimental data. Time dependent DFT at B3LYP/6-31G+(d,p) displayed a major absorption band 3.01 nm higher than the experimental value. Conclusion Cordia batesii can be considered as promising in search of compounds with antimalarial and antitubercular properties. DFT studies are very helpful when trying to learn more about the spectroscopic insights of a derivative of allantoin (1).

Investigation on the biodegradation levels of super heavy oils by parameter-striping method and refined Manco scale: a case study from the Chepaizi Uplift of Junggar Basin

The Carboniferous volcanic reservoir in the Chepaizi Uplift became an exploration hot target in recent years for its substantial amount of oils discovered. However, most of the Carboniferous heavy oils were biodegraded to PM7 or higher with orders of magnitude variation in oil viscosities. Two oil groups (I and II) exactly corresponding to the western and eastern Chepaizi Uplift were distinguished according to their source diagnose. Furthermore, three oil families (II1, II2 and II3), with the biodegradation level of PM7, PM8–8+, PM9+, respectively, were classified based on molecular compositions and parameter-stripping method of strongly bioresistant parameters. Allowing for this extremely high biodegradation case, more biodegradation refractory compound class were added to establish a refined Manco scale to quantitatively evaluate the biodegradation extent. Refined Manco number (RMN2) positively correlated with the oil density, NSO contents, and absolute concentrations of diasteranes and gammacerane, negatively correlated with the absolute concentrations of diahopane, summed tricyclic terpanes and pentacyclic terpanes. This refined scale showed higher resolution than the PM one to differentiate the biodegradation extent of Carboniferous heavy oils from the Chepaizi Uplift, especially those with same PM values but different oil viscosities.

MODELING AND SIMULATION OF A HORIZONTAL THREE-PHASE SEPARATOR: INFLUENCE OF PHYSICOCHEMICAL PROPERTIES OF OIL

Fluids produced from oil reservoirs typically contain oil, natural gas, water, sediments, in varying amounts, and contaminating gases. Considering that economic interest usually targets mostly oil and gas, primary processing is used to separate water/oil/gas, in addition to treating these phases. Therefore, the well stream should be processed as soon as possible after reaching the surface. Separator vessels are among the main equipment used at surface production facilities, being responsible for the separation of the produced phases. This work focuses on studying the fluid dynamic behavior in a horizontal three-phase separator. To accomplish this goal, we used the computer fluid dynamics software ANSYS CFX. First, we performed a detailed analysis of a “Standard Case” to understand in detail the entire separation process within the vessel. The results show the three phases through the simulation time, analyses of the separation efficiency, different fluids flow lines, pressure gradient inside the vessel, and effect of the diverter baffle. It also considers a variation of fluid flow at the inlet of the separator. These analyses include pictures of all cases studied. Afterwards, some parameters of the standard case were altered to evaluate its influence on fluid dynamics behavior and the functioning of the separator vessel. At last, we analyzed the influences of oil density and viscosity on the separation. The oil quality affects the primary separation directly, as the oil density and viscosity increase, for example, increases the drag between the fluids and decreases the rate of sedimentation, which stickles the separation process difficult. Two out of the three cases generated satisfactory results. The simulation with the heaviest oil presented the worse results.

Study oil density in flow, system of automated measurement and inaccuracies

The paper reviews the issues of specification of fluid fuel amount with high measuring accuracy transported through oil pipelines. The operation algorithm of vibration-frequency densitometer for automatic measurement of fluid fuel density with high measuring accuracy in technological process in the exploitation conditions is based on the hybrid test method. For this purpose test equations on measuring links using simple additive and multiplicative tests, as well as their combinations have been developed, test equations composed, and as a result of their solution the main test equation obtained. The mathematic-statistic estimation of the results of densitometer measurements correcting test algorithms for the definition of measurement errors and composing inaccuracies, the method of automated calibration are presented as well.

Tea seed oil: Physicochemical profiling

A study was undertaken to evaluate the quality characteristic of tea (Camellia sinensis L.) seed oil. The oil content ranged between 20.84 and 21.90 per cent. Smoke point, iodine value, saponification value, calorific value, refractive index, oil density, oil colour and oil pH were in the range of 247.29 - 251.53 (oC), 82.74 - 85.65 (g I 100-1 g), 185.33 - 185.72 (mg KOH g-1), 6822.53-6891.05 (J per 100 g), 1.46 (at 40 0C), 0.92 - 0.94 (g per cm3), 4.45 - 4.47 (Y+5R) and 4.62 - 4.64, respectively. The oxidation parameters, i.e., peroxide value, ranged from 1.17 - 2.63 meq kg-1. The tea seed oil has PUFA/SFA ratio 0.82 - 1.31 closer to WHO recommended value. Besides, antioxidant activity in term of DPPH free radical scavenging activity ranged between 6.30 - 7.14 per cent, β-carotene 4.62 - 12.93 mg kg-1 and α-tocopherol 90.49 - 366.52 mg kg-1. Highest oleic acid content was found in TSS 1, whereas highest α-tocopherol was found in TS 557. The results open up the possibilities of extracting oil from these bi-clonal seed stocks, which will diversify the use of tea.