ResearchPad - crude-oil Default RSS Feed en-us © 2020 Newgen KnowledgeWorks <![CDATA[Instigation of indigenous thermophilic bacterial consortia for enhanced oil recovery from high temperature oil reservoirs]]> The purpose of the study involves the development of an anaerobic, thermophilic microbial consortium TERIK from the high temperature reservoir of Gujarat for enhance oil recovery. To isolate indigenous microbial consortia, anaerobic baltch media were prepared and inoculated with the formation water; incubated at 65°C for 10 days. Further, the microbial metabolites were analyzed by gas chromatography, FTIR and surface tension. The efficiency of isolated consortia towards enhancing oil recovery was analyzed through core flood assay. The novelty of studied consortia was that, it produces biomass (600 mg/l), bio-surfactant (325 mg/l), and volatile fatty acids (250 mg/l) at 65°C in the span of 10 days, that are adequate to alter the surface tension (70 to 34 mNm -1) and sweep efficiency of zones facilitating the displacement of oil. TERIK was identified as Clostridium sp. The FTIR spectra of biosurfactant indicate the presence of N-H stretch, amides and polysaccharide. A core flooding assay was designed to explore the potential of TERIK towards enhancing oil recovery. The results showed an effective reduction in permeability at residual oil saturation from 2.14 ± 0.1 to 1.39 ± 0.05 mD and 19% incremental oil recovery.

<![CDATA[A Novel Analysis Method for Paired-Sample Microbial Ecology Experiments]]>

Many microbial ecology experiments use sequencing data to measure a community’s response to an experimental treatment. In a common experimental design, two units, one control and one experimental, are sampled before and after the treatment is applied to the experimental unit. The four resulting samples contain information about the dynamics of organisms that respond to the treatment, but there are no analytical methods designed to extract exactly this type of information from this configuration of samples. Here we present an analytical method specifically designed to visualize and generate hypotheses about microbial community dynamics in experiments that have paired samples and few or no replicates. The method is based on the Poisson lognormal distribution, long studied in macroecology, which we found accurately models the abundance distribution of taxa counts from 16S rRNA surveys. To demonstrate the method’s validity and potential, we analyzed an experiment that measured the effect of crude oil on ocean microbial communities in microcosm. Our method identified known oil degraders as well as two clades, Maricurvus and Rhodobacteraceae, that responded to amendment with oil but do not include known oil degraders. Our approach is sensitive to organisms that increased in abundance only in the experimental unit but less sensitive to organisms that increased in both control and experimental units, thus mitigating the role of “bottle effects”.

<![CDATA[Causes of Stranding and Mortality, and Final Disposition of Loggerhead Sea Turtles (Caretta caretta) Admitted to a Wildlife Rehabilitation Center in Gran Canaria Island, Spain (1998-2014): A Long-Term Retrospective Study]]>


The aims of this study were to analyze the causes of stranding of 1,860 loggerhead turtles (Caretta caretta) admitted at the Tafira Wildlife Rehabilitation Center in Gran Canaria Island, Spain, from 1998 to 2014, and to analyze the outcomes of the rehabilitation process to allow meaningful auditing of its quality.


Primary causes of morbidity were classified into seven categories: entanglement in fishing gear and/or plastics, ingestion of hooks and monofilament lines, trauma, infectious disease, crude oil, other causes, and unknown/undetermined. Final dispositions were calculated as euthanasia (Er), unassisted mortality (Mr), and release (Rr) rates. Time to death (Td) for euthanized and dead turtles, and length of stay for released (Tr) turtles were evaluated.


The most frequent causes of morbidity were entanglement in fishing gear and/or plastics (50.81%), unknown/undetermined (20.37%), and ingestion of hooks (11.88%). The final disposition of the 1,634 loggerhead turtles admitted alive were: Er = 3.37%, Mr = 10.34%, and Rr = 86.29%. Er was significantly higher in the trauma category (18.67%) compared to the other causes of admission. The highest Mr was observed for turtles admitted due to trauma (30.67%). The highest Rr was observed in the crude oil (93.87%) and entanglement (92.38%) categories. The median Tr ranged from 12 days (unknown) to 70 days (trauma).


This survey is the first large-scale epidemiological study on causes of stranding and mortality of Eastern Atlantic loggerheads and demonstrates that at least 71.72% of turtles stranded due to anthropogenic causes. The high Rr (86.29%) emphasizes the importance of marine rehabilitation centers for conservation purposes. The stratified analysis by causes of admission of the three final disposition rates, and the parameters Td and Tr should be included in the outcome research of the rehabilitation process of sea turtles in order to allow comparative studies between marine rehabilitation centers around the world.

<![CDATA[Demulsification of crude oil-in-water emulsions by means of fungal spores]]>

The present feature describes for the first time the application of spores from Aspergillus sp. IMPMS7 to break out crude oil-in-water emulsions (O/W). The fungal spores were isolated from marine sediments polluted with petroleum hydrocarbons. The spores exhibited the ability to destabilize different O/W emulsions prepared with medium, heavy or extra-heavy Mexican crude oils with specific gravities between 10.1 and 21.2°API. The isolated fungal spores showed a high hydrophobic power of 89.3 ± 1.9% and with 2 g of spores per liter of emulsion, the half-life for emulsion destabilization was roughly 3.5 and 0.7 h for extra-heavy and medium crude oil, respectively. Then, the kinetics of water separation and the breaking of the O/W emulsion prepared with heavy oil through a spectrofluorometric technique were studied. A decrease in the fluorescence ratio at 339 and 326 nm (I339/I326) was observed in emulsions treated with spores, which is similar to previously reported results using chemical demulsifiers.

<![CDATA[The potential of indigenous Paenibacillus ehimensis BS1 for recovering heavy crude oil by biotransformation to light fractions]]>

Microbial Enhanced Oil Recovery (MEOR) is a potential technology for residual heavy oil recovery. Many heavy oil fields in Oman and elsewhere have difficulty in crude oil recovery because it is expensive due to its high viscosity. Indigenous microbes are capable of improving the fluidity of heavy oil, by changing its high viscosity and producing lighter oil fractions. Many spore-forming bacteria were isolated from soil samples collected from oil fields in Oman. Among the isolates, an autochthonous spore-forming bacterium was found to enhance heavy oil recovery, which was identified by 16S rDNA sequencing as Paenibacillus ehimensis BS1. The isolate showed maximum growth at high heavy oil concentrations within four days of incubation. Biotransformation of heavy crude oil to light aliphatic and aromatic compounds and its potential in EOR was analyzed under aerobic and anaerobic reservoir conditions. The isolates were grown aerobically in Bushnell-Haas medium with 1% (w/v) heavy crude oil. The crude oil analyzed by GC-MS showed a significant biotransformation from the ninth day of incubation under aerobic conditions. The total biotransformation of heavy crude oil was 67.1% with 45.9% in aliphatic and 85.3% in aromatic fractions. Core flooding experiments were carried out by injecting the isolates in brine supplemented with Bushnell-Haas medium into Berea sandstone cores and were incubated for twelve days under oil reservoir conditions (50°C). The extra recovered oil was analyzed by GC-MS. The residual oil recovered from core flood experiments ranged between 10–13% compared to the control experiment. The GC-MS analyses of the extra recovered oil showed 38.99% biotransformation of heavy to light oil. The results also indicated the presence of 22.9% extra aliphatic compounds in the residual crude oil recovered compared to that of a control. The most abundant compound in the extra recovered crude oil was identified as 1-bromoeicosane. The investigations showed the potential of P. ehimensis BS1 in MEOR technology by the biotransformation of heavy to lighter crude oil under aerobic and reservoir conditions. Heavy oil recovery and biotransformation to lighter components are of great economic value and a few studies have been done.

<![CDATA[Study on the biodegradation of crude oil by free and immobilized bacterial consortium in marine environment]]>

Five strains of bacteria, namely, Exiguobacterium sp. ASW-1, Pseudomonas aeruginosa strain ASW-2, Alcaligenes sp. ASW-3, Alcaligenes sp. ASS-1, and Bacillus sp. ASS-2, were isolated from the Zhejiang coast in China. The mixed flora of the five strains performed well with degrading 75.1% crude oil (1%, w/v) in 7 days. The calcium alginate—activated carbon embedding carrier was used to immobilize bacterial consortium. Immobilized cells performed better than free ones in variations of environmental factors containing incubated temperature, initial pH, salinity of the medium and crude oil concentration. The degradation process of crude oil by immobilized bacteria was accelerated compared with that of the free ones. Bacterial consortium showed better performance on biodegradation of normal alkanes than that of PAHs. Improvement of immobilization on the biodegradation efficiency of normal alkanes (31.9%) was apparently high than that of PAHs (1.9%).

<![CDATA[Investigating the Influence Relationship Models for Stocks in Indian Equity Market: A Weighted Network Modelling Study]]>

The socio-economic systems today possess high levels of both interconnectedness and interdependencies, and such system-level relationships behave very dynamically. In such situations, it is all around perceived that influence is a perplexing power that has an overseeing part in affecting the dynamics and behaviours of involved ones. As a result of the force & direction of influence, the transformative change of one entity has a cogent aftereffect on the other entities in the system. The current study employs directed weighted networks for investigating the influential relationship patterns existent in a typical equity market as an outcome of inter-stock interactions happening at the market level, the sectorial level and the industrial level. The study dataset is derived from 335 constituent stocks of ‘Standard & Poor Bombay Stock Exchange 500 index’ and study period is 1st June 2005 to 30th June 2015. The study identifies the set of most dynamically influential stocks & their respective temporal pattern at three hierarchical levels: the complete equity market, different sectors, and constituting industry segments of those sectors. A detailed influence relationship analysis is performed for the sectorial level network of the construction sector, and it was found that stocks belonging to the cement industry possessed high influence within this sector. Also, the detailed network analysis of construction sector revealed that it follows scale-free characteristics and power law distribution. In the industry specific influence relationship analysis for cement industry, methods based on threshold filtering and minimum spanning tree were employed to derive a set of sub-graphs having temporally stable high-correlation structure over this ten years period.

<![CDATA[Study on the Reutilization of Clear Fracturing Flowback Fluids in Surfactant Flooding with Additives for Enhanced Oil Recovery (EOR)]]>

An investigation was conducted to study the reutilization of clear fracturing flowback fluids composed of viscoelastic surfactants (VES) with additives in surfactant flooding, making the process more efficient and cost-effective. The clear fracturing flowback fluids were used as surfactant flooding system with the addition of α-olefin sulfonate (AOS) for enhanced oil recovery (EOR). The interfacial activity, emulsification activity and oil recovery capability of the recycling system were studied. The interfacial tension (IFT) between recycling system and oil can be reduced by 2 orders of magnitude to 10−3 mN/m, which satisfies the basic demand of surfactant flooding. The oil can be emulsified and dispersed more easily due to the synergetic effect of VES and AOS. The oil-wet surface of quartz can be easily converted to water-wet through adsorption of surfactants (VES/AOS) on the surface. Thirteen core plug flooding tests were conducted to investigate the effects of AOS concentrations, slug sizes and slug types of the recycling system on the incremental oil recovery. The investigations prove that reclaiming clear fracturing flowback fluids after fracturing operation and reuse it in surfactant flooding might have less impact on environment and be more economical.

<![CDATA[Oil Adulteration Identification by Hyperspectral Imaging Using QHM and ICA]]>

To investigate the feasibility of identification of qualified and adulterated oil product using hyperspectral imaging(HIS) technique, a novel feature set based on quantized histogram matrix (QHM) and feature selection method using improved kernel independent component analysis (iKICA) is proposed for HSI. We use UV and Halogen excitations in this study. Region of interest(ROI) of hyperspectral images of 256 oil samples from four varieties are obtained within the spectral region of 400–720nm. Radiation indexes extracted from each ROI are used as feature vectors. These indexes are individual band radiation index (RI), difference of consecutive spectral band radiation index (DRI), ratio of consecutive spectral band radiation index (RRI) and normalized DRI (NDRI). Another set of features called quantized histogram matrix (QHM) are extracted by applying quantization on the image histogram from these features. Based on these feature sets, improved kernel independent component analysis (iKICA) is used to select significant features. For comparison, algorithms such as plus L reduce R (plusLrR), Fisher, multidimensional scaling (MDS), independent component analysis (ICA), and principle component analysis (PCA) are also used to select the most significant wavelengths or features. Support vector machine (SVM) is used as the classifier. Experimental results show that the proposed methods are able to obtain robust and better classification performance with fewer number of spectral bands and simplify the design of computer vision systems.