A novel bioprospecting strategy via 13C-based high-throughput probing of active methylotrophs inhabiting oil reservoir surface soil.

Methane-oxidizing bacteria (MOB) have long been considered as a microbial indicator for oil and gas prospecting. However, due to the phylogenetically narrow breath of ecophysiologically distinct MOB, classic culture-dependent approaches could not discriminate MOB population at fine resolution, and accurately reflect the abundance of active MOB in the soil above oil and gas reservoirs. Here, we presented a novel microbial anomaly detection (MAD) strategy to quantitatively identify specific indicator methylotrophs in the surface soils for bioprospecting oil and gas reservoirs by using a combination of 13C-DNA stable isotope probing (SIP), high-throughput sequencing (HTS), quantitative PCR (qPCR) and geostatistical analysis. The Chunguang oilfield of the Junggar Basin was selected as a model system in western China, and type I methanotrophic Methylobacter was most active in the topsoil above the productive oil wells, while type II methanotrophic Methylosinus predominated in the dry well soils, exhibiting clear differences between non- and oil reservoir soils. Similar results were observed by quantification of Methylobacter pmoA genes as a specific bioindicator for the prediction of unknown reservoirs by grid sampling. A microbial anomaly distribution map based on geostatistical analysis further showed that the anomalous zones were highly consistent with petroleum, geological and seismic data, and validated by subsequent drilling. Over seven years, a total of 24 wells have been designed and drilled into the targeted anomaly, and the success rate via the MAD prospecting strategy was 83 %. Our results suggested that molecular techniques are powerful tools for oil and gas prospecting. This study indicates that the exploration efficiency could be significantly improved by integrating multi-disciplinary information in geophysics and geomicrobiology while reducing the drilling risk to a greater extent.

Bacterial crude oil and polyaromatic hydrocarbon degraders from Kazakh oil fields as barley growth support.

Bacterial strains of the genera Arthrobacter, Bacillus, Dietzia, Kocuria, and Micrococcus were isolated from oil-contaminated soils of the Balgimbaev, Dossor, and Zaburunye oil fields in Kazakhstan. They were selected from 1376 isolated strains based on their unique ability to use crude oil and polyaromatic hydrocarbons (PAHs) as sole source of carbon and energy in growth experiments. The isolated strains degraded a wide range of aliphatic and aromatic components from crude oil to generate a total of 170 acid metabolites. Eight metabolites were detected during the degradation of anthracene and of phenanthrene, two of which led to the description of a new degradation pathway. The selected bacterial strains Arthrobacter bussei/agilis SBUG 2290, Bacillus atrophaeus SBUG 2291, Bacillus subtilis SBUG 2285, Dietzia kunjamensis SBUG 2289, Kocuria rosea SBUG 2287, Kocuria polaris SBUG 2288, and Micrococcus luteus SBUG 2286 promoted the growth of barley shoots and roots in oil-contaminated soil, demonstrating the enormous potential of isolatable and cultivable soil bacteria in soil remediation. KEY POINTS: • Special powerful bacterial strains as potential crude oil and PAH degraders. • Growth on crude oil or PAHs as sole source of carbon and energy. • Bacterial support of barley growth as resource for soil remediation.

Micro-occurrence characteristics and charging mechanism in continental shale oil from Lucaogou Formation in the Jimsar Sag, Junggar Basin, NW China.

The micro-occurrence characterization of shale oil is a key geological issue that restricts the effective development of continental shale oil in China. In order to make up for the lack of research in this area, this paper carries out a series of experiments on the shale oil of the Lucaogou Formation using a multi-step extraction method, with the aim of exploring the micro-occurrence types and mechanisms of shale oil in the Lucaogou Formation, as well as exploring its direct connection with production and development. In this paper, shale oil in the reservoir is divided into two categories: free oil and residual oil. The polar substances and OSN compounds are the key factors determining the occurrence state of shale oil. Abundant polar substances and OSN compounds can preferentially react with mineral surfaces (including coordination, complexation, ionic exchange, and so on) to form a stable adsorption layer, making it difficult to extract residual oil in actual exploitation. Free oil is mainly composed of aliphatic hydrocarbons, and its adsorption capacity is related to the length of the carbon chain, i.e. long carbon chain, strong adsorption capacity, and poor movability. Free oil is widely stored in pores and cracks, and that with high mobility can be the most easily extracted, making it the main target at present exploitation. In the current state of drilling and fracturing technology, research should prioritize understanding the adsorption and desorption mechanisms of crude oil, particularly residual oil. This will help optimize exploitation programs, such as carbon dioxide fracturing and displacement, to enhance shale oil production.

Biosurfactant and biopolymer producing microorganisms from West Kazakhstan oilfield.

Microbiological enhanced oil recovery (MEOR) uses indigenous or exogenous microorganisms and nutrients to enhance oil production through synthesis of metabolites reducing oil viscosity and surface tension. In order to find bacteria suitable for MEOR, we studied 26 isolates from wells in the Akingen oilfield in West Kazakhstan. Six of them were selected for further analysis based on their ability to reduce surface tension to less than 40 mN/m, with the A9 isolate exhibiting tension reduction values of 32.76 ± 0.3 mN/m. Based on the morphological features, biochemical activities, and the 16S rRNA gene, the isolates were classified to the Bacillus subtilis group. In the phylogenetic analysis the isolates grouped into two main clusters. Genes encoding the surfactin synthetase subunits were found in A2, A8, A9, A12, PW2, only the PW2 strain had lchAA encoding lichenysin, while sacB encoding levan was noted in A2, A8, A9, and A12. The expression of srfAB, srfAC, and sacB tested with qPCR varied among strains. Nevertheless, whereas temperature moderately affects the expression level, with the highest level recorded at 40 °C, salinity significantly impacts the expression of the genes encoding biosurfactants. B. subtilis strains isolated in the study, especially A9, are promising for microbial-enhanced oil recovery.

Structures and diversities of bacterial communities in oil-contaminated soil at shale gas well site assessed by high-throughput sequencing.

Currently, there is limited understanding of the structures and variabilities of bacterial communities in oil-contaminated soil within shale gas development. The Changning shale gas well site in Sichuan province was focused, and high-throughput sequencing was used to investigate the structures of bacterial communities and functions of bacteria in soil with different degrees of oil pollution. Furthermore, the influences of the environmental factors including pH, moisture content, organic matter, total nitrogen, total phosphorus, oil, and the biological toxicity of the soil on the structures of bacterial communities were analyzed. The results revealed that Proteobacteria and Firmicutes predominated in the oil-contaminated soil. α-Proteobacteria and γ-Proteobacteria were the main classes under the Proteobacteria phylum. Bacilli was the main class in the Firmicutes phylum. Notably, more bacteria were only found in CN-5 which was the soil near the storage pond for abandoned drilling mud, including Marinobacter, Balneola, Novispirillum, Castellaniella, and Alishewanella. These bacteria exhibited resilience to higher toxicity and demonstrated proficiency in oil degradation. The functions including carbohydrate transport and metabolism, energy metabolism, replication, recombination and repair replication, signal transduction mechanisms, and amino acid transport and metabolism responded differently to varying concentrations of oil. The disparities in bacterial genus composition across samples stemmed from a complex play of pH, moisture content, organic matter, total nitrogen, total phosphorus, oil concentration, and biological toxicity. Notably, bacterial richness correlated positively with moisture content, while bacterial diversity showed a significant positive correlation with pH. Acidobacteria exhibited a significant positive correlation with moisture content. Litorivivens and Luteimonas displayed a significant negative correlation with pH, while Rhizobium exhibited a significant negative correlation with moisture content. Pseudomonas, Proteiniphilum, and Halomonas exhibited positive correlations not only with organic matter but also with oil concentration. Total nitrogen exhibited a significant positive correlation with Taonella and Sideroxydans. On the other hand, total phosphorus showed a significant negative correlation with Sphingomonas. Furthermore, Sphingomonas, Gp6, and Ramlibacter displayed significant negative correlations with biological toxicity. The differential functions exhibited no significant correlation with environmental factors but displayed a significant positive correlation with the Proteobacteria phylum. Aridibacter demonstrated a significant positive correlation with cell motility and cellular processes and signaling. Conversely, Pseudomonas, Proteiniphilum, and Halomonas were negatively correlated with differential functions, particularly in amino acid metabolism, carbohydrate metabolism, and membrane transport. Compared with previous research, more factors were considered in this research when studying structural changes in bacterial communities, such as physicochemical properties and biological toxicity of soil. In addition, the correlations of differential functions of communities with environmental factors, bacterial phyla, and genera were investigated.

Metagenomic analysis reveals the microbial response to petroleum contamination in oilfield soils.

The response of the microbes to total petroleum hydrocarbons (TPHs) in three types of oilfield soils was researched using metagenomic analysis. The ranges of TPH concentrations in the grassland, abandoned well, working well soils were 1.16 × 102-3.50 × 102 mg/kg, 1.14 × 103-1.62 × 104 mg/kg, and 5.57 × 103-3.33 × 104 mg/kg, respectively. The highest concentration of n-alkanes and 16 PAHs were found in the working well soil of Shengli (SL) oilfield compared with those in Nanyang (NY) and Yanchang (YC) oilfields. The abandoned well soils showed a greater extent of petroleum biodegradation than the grassland and working well soils. Α-diversity indexes based on metagenomic taxonomy showed higher microbial diversity in grassland soils, whereas petroleum-degrading microbes Actinobacteria and Proteobacteria were more abundant in working and abandoned well soils. RDA demonstrated that low moisture content (MOI) in YC oilfield inhibited the accumulation of the petroleum-degrading microbes. Synergistic networks of functional genes and Spearman's correlation analysis showed that heavy petroleum contamination (over 2.10 × 104 mg/kg) negatively correlated with the abundance of the nitrogen fixation genes nifHK, however, in grassland soils, low petroleum content facilitated the accumulation of nitrogen fixation genes. A positive correlation was observed between the abundance of petroleum-degrading genes and denitrification genes (bphAa vs. nirD, todC vs. nirS, and nahB vs. nosZ), whereas a negative correlation was observed between alkB (alkane- degrading genes) and amo (ammonia oxidation), hao (nitrification). The ecotoxicity of petroleum contamination, coupled with petroleum hydrocarbons (PH) degradation competing with nitrifiers for ammonia inhibited ammonia oxidation and nitrification, whereas PH metabolism promoted the denitrification process. Moreover, positive correlations were observed between the abundance of amo gene and MOI, as well as between the abundance of the dissimilatory nitrate reduction gene nirA and clay content. Thus, improving the soil physicochemical properties is a promising approach for decreasing nitrogen loss and alleviating petroleum contamination in oilfield soils.

Investigation of the transport and metabolic patterns of oil-displacing bacterium FY-07-G in the microcosm model using X-CT technology.

AIMS: Microbial enhanced oil recovery (MEOR) is dedicated to enhancing oil recovery by harnessing microbial metabolic activities and their byproducts within reservoir rocks and fluids. Therefore, the investigation of microbial mobility and their extensive distribution within crude oil is of paramount importance in MEOR. While microscale models have been valuable for studying bacterial strain behavior in reservoirs, they are typically limited to 2D representations of porous media, making them inadequate for simulating actual reservoir conditions. Consequently, there is a critical need for 3D models and dependable visualization methods to observe bacterial transport and metabolism within these complex reservoir environments. METHODS AND RESULTS: Bacterial cellulose (bc) is a water-insoluble polysaccharide produced by bacteria that exhibits biocompatibility and biodegradability. It holds significant potential for applications in the field of MEOR as an effective means for selective plugging and spill prevention during oil displacement processes. Conditionally cellulose-producing strain, FY-07-G, with green fluorescent labeling, was engineered for enhanced oil recovery. 3D micro-visualization model was constructed to directly observe the metabolic activities of the target bacterial strain within porous media and to assess the plugging interactions between cellulose and the medium. Additionally, X-ray computed tomography (X-CT) technology was employed for a comprehensive analysis of the transport patterns of the target strain in oil reservoirs with varying permeabilities. The results indicated that FY-07-G, as a microorganism employing biopolymer-based plugging principles to enhance oil recovery, selectively targets and seals regions characterized by lower permeability and smaller pore spaces. CONCLUSIONS: This work provided valuable insights into the transport and metabolic behavior of MEOR strains and tackled the limitation of 2D models in faithfully replicating oil reservoir conditions, offering essential theoretical guidance and insights for the further application of oil-displacing bacterial strains in MEOR processes.

Bioaccumulation, biomagnification, and ecological risk of trace metals in the ecosystem around oilfield production area: A case study in Shengli Oilfield.

The production for crude oil usually leads to contamination of the soil with trace metals and organic contaminants from spilled petroleum. Organic contaminants were generally paid more attention than trace metals in the oilfield pollution. Many studies have investigated the impacts of some petroleum hydrocarbon pollutants, however, the impacts and risk assessment of trace metals remain largely unexplored. Moreover, under some circumstances, the risks associated with trace metals are not necessarily lower than those associated with organic contaminants. This study aimed to investigate methods to evaluate the possible risks associated with 11 trace metals (Ti, Ba, Sr, Rb, V, Li, Mo, Co, Cs, Bi, and Tl) in soil and biota samples from the Shengli Oilfield using ICP-MS. The results showed that 11 trace metals in the surface soils exceeded the local background levels. The geo-accumulation index (Igeo) indicated that the soils had light-moderate to moderate contamination levels, with higher Igeo value of Ba, V, Li, Mo, Co, and Cs. The individual potential ecological risk indices ([Formula: see text]) demonstrated moderate Bi and Tl pollution in soils. Comparatively, the [Formula: see text] is recommended for the risk assessment of trace metals on the ecosystem around the oilfield area. Mo, Bi, and Sr easily accumulate in plants, as reflected by their bioaccumulation factor. Ti, Ba, V, Li, Co, Cs, Bi, and Tl exhibited considerable biomagnification, particularly in birds. In this study, trace metals showed considerable bioaccumulation and biomagnification, and the risks of these trace metals on the ecosystem around oilfield production area need more attention.

Providing a comprehensive approach to oil well blowout risk assessment.

Drilling is one of the most dangerous activities in the oil and gas process industries. Therefore, a holistic approach was presented to prevent and control risks and reduce the uncertainty of blowouts, kick scenarios, and control layers based on the Fuzzy Bayesian Network (FBN). Four independent protection layers (IPLs) were used to evaluate the blowout outcome, and the failure probabilities of IPL1 and IPL2 were calculated with Fault Tree Analysis (FTA). Then, different events were transferred to the Bayesian Network (BN) in GeNIe software, and updated the probabilities. The Fuzzy Fault Tree (FFT) results reveal that the failure probabilities for IPL1 and IPL2 amount to 8.94×10-4 and 4.97×10-21, respectively. Also, the blowout probability results based on FFT were larger than FBN. According to FBN, the probability of the kick event was equal to 6.60×10-34. Sensitivity analysis showed that X1 (Mud volume/flow change) had the highest degree of importance in the blowout of oil wells. The results of this study can be used in both a preventive and reactive approach. Deductive and inductive reasoning, the dynamic nature and conditional dependencies, and causal relationships between events can make the model more realistic.

Sources, spatial-distributions and fluxes of PAH-contaminated dusts in the Athabasca oil sands region.

Atmospheric deposition of polycyclic aromatic hydrocarbons (PAHs) has increased in northern Alberta, Canada, due to industrial development in the Athabasca oil sands region (AOSR). However, the sources, summertime deposition fluxes and associated spatial patterns are poorly characterized, and the magnitude of contamination has not been directly contrasted with comparable measurements around large Canadian cities. PAHs were measured in Sphagnum moss collected from 30 bogs in the AOSR and compared with reference moss collected from various remote, rural and near-urban sites in Alberta and Ontario. At all 39 locations, strong correlations between depositional fluxes of PAHs and accumulation rates of ash (n = 117, r = 0.877, p < 0.001) implied that the main source of PAHs to moss was atmospheric deposition of particles. Average PAH concentrations at near-field AOSR sites (mean [SD], 62.4 [24.3] ng/g) were significantly higher than at far-field AOSR sites (44.9 [20.8] ng/g; p = 0.038) or the 7 reference sites in Alberta (20.6 [3.5] ng/g; p < 0.001). In fact, average PAH concentrations across the entire AOSR (7,850 km2) were approximately twice as high as in London, Ontario, or near petroleum upgrading and major traffic corridors in Edmonton, Alberta. A chemical mass balance model estimated that both delayed petcoke (33 % of PAHs) and fine tailings (38 % of PAHs) were the major sources of PAHs in the AOSR. Over the 2015 summer growing season, we estimate that 101-110 kg of PAHs (on 14,300-17,300 tonnes of PAH-containing dusts) were deposited to the AOSR within a 50 km radius of surface mining. Given that the highest PAH deposition was to the northern quadrant of the AOSR, which includes the First Nations community of Fort MacKay, further dust control measures should be considered to protect human and environmental health in the region.

Conventional Fossil Fuel Extraction, Associated Biogeochemical Processes, and Topography Influence Methane Groundwater Concentrations in Appalachia.

The production of fossil fuels, including oil, gas, and coal, retains a dominant share in US energy production and serves as a major anthropogenic source of methane, a greenhouse gas with a high warming potential. In addition to directly emitting methane into the air, fossil fuel production can release methane into groundwater, and that methane may eventually reach the atmosphere. In this study, we collected 311 water samples from an unconventional oil and gas (UOG) production region in Pennsylvania and an oil and gas (O&G) and coal production region across Ohio and West Virginia. Methane concentration was negatively correlated to distance to the nearest O&G well in the second region, but such a correlation was shown to be driven by topography as a confounding variable. Furthermore, sulfate concentration was negatively correlated with methane concentration and with distance to coal mining in the second region, and these correlations were robust even when considering topography. We hypothesized that coal mining enriched sulfate in groundwater, which in turn inhibited methanogenesis and enhanced microbial methane oxidation. Thus, this study highlights the complex interplay of multiple factors in shaping groundwater methane concentrations, including biogeochemical conversion, topography, and conventional fossil extraction.

Novel strategy for treating high salinity oilfield produced water: Pyrite-activated peroxymonosulfate coupled with heterotrophic ammonia assimilation.

Existing conventional biological treatment techniques face numerous limitations in effectively removing total petroleum hydrocarbons (TPHs) and ammonia (NH4+-N) from oilfield-produced water (OPW), highlighting the pressing need for innovative pre-oxidation and biological treatment processes. In this study, a pyrite-activated peroxymonosulfate (PMS)-coupled heterotrophic ammonia assimilation (HAA) system was established to achieve satisfactory system performance for OPW treatment. Pyrite sustained-release Fe2+-activated PMS was used to produce SO4•- and •OH, and 71.0 % of TPHs were effectively removed from the oil wastewater. The average TPHs and NH4+-N removal efficiencies in the test group with pre-oxidation were 96.9 and 98.3 %, compared to 46.5 and 77.1 % in the control group, respectively. The maximum fluorescence intensities of tryptophan protein and aromatic protein in the test group declined by 83.7 %. Fourier transform ion cyclotron resonance mass spectrometry revealed that pre-oxidation degraded more long-chain hydrocarbons and aromatic family compound, whereas the HAA process produced more proteins and carbohydrates. Pyrite-PMS promoted the enrichment of ammonia-assimilating bacteria, alleviating the explosive increase in extracellular polymeric substances and reducing sludge settleability. The low cost, efficiency, green chemistry principles, and synergies of this approach make it a powerful solution for practical OPW treatment to reduce environmental impacts and promote sustainable wastewater treatment.

Controls on Barite (BaSO4) Precipitation in Unconventional Reservoirs.

Barite (BaSO4) precipitation is one of the most ubiquitous examples of secondary sulfate mineral scaling in shale oil and gas reservoirs. Often, a suite of chemical additives is used during fracturing operations to inhibit the accumulation of mineral scales, though their efficacy is widely varied and poorly understood. This study combines experimental data and multi-component numerical reactive transport modeling to offer a more comprehensive understanding of the geochemical behavior of barite accumulation in shale matrices under conditions typical of fracturing operations. A variety of additives and conditions are individually tested in batch reactor experiments to identify the factors controlling barite precipitation. Our experimental results demonstrate a pH dependence in the rate of barite precipitation, which we use to develop a predictive model including a pH-dependent term that satisfactorily reproduces our observations. This model is then extended to consider the behavior of three major shale samples of highly variable mineralogy (Eagle Ford, Marcellus, and Barnett). This data-validated model offers a reliable tool to predict and ultimately mitigate against secondary mineral accumulation in unconventional shale reservoirs.

Performance Evaluation and Oil Displacement Effect of Amphiphilic Polymer Heavy Oil Activator.

A heavy oil activator is an amphiphilic polymer solution that contains hydrophilic and oleophobic groups. It can enhance heavy oil recovery efficiency. This paper studied the changes in the distribution of the remaining oil after activator flooding and the performance of heavy oil's active agent. Nuclear magnetic resonance spectroscopy, laser confocal microscopy, microscopic visualization, and CT scanning techniques were used to analyze crude oil utilization, and the distribution characteristics of the remaining oil during activator flooding of heavy oil. The results showed that the heavy oil activator solution presented a dense spatial network and good viscosification ability. The activator could reduce the interfacial tension of oil and water, disassemble the heavy components of dispersed heavy oil and reduce the viscosity of heavy oil. The utilization degree of the remaining oil in small and middle pores increased significantly after activator flooding, the remaining oil associated with membranous-like and clusterlike structures was utilized to a high degree, and the decline of light/heavy fraction in heavy oil slowed down. Heavy oil activator improved the swept volume and displacement efficiency of heavy oil, playing a significant role in improving the extent of recovery of heavy oil reservoirs.

Baseline study of water, soil, and identification of potential native phytoremediators of total petroleum hydrocarbon from oil-contaminated areas in the vicinity of Geleky oilfield of Assam.

Petrochemical contamination has been one of the significant causes of pollution all over the world. The upper Assam of Northeast India has been known for its oil industries and their contribution to India's economy. With tremendous oil production, an adequate amount of petroleum contamination is also observed. Several works have been furnished in the oilfields of Assam; however, the knowledge of heavy metal contamination and hydrocarbon pollution in nearby water bodies and soil, along with risk assessment and statistical validation in the vicinity of the Geleky oilfield of Sibsagar district of Assam, is still limited. The study also reveals native potential phytoremediators that can uptake heavy metals and hydrocarbons to help clean the environment through a greener approach. The presence of aromatic hydrocarbon derivatives in water, soil, plants, and sludge samples, including groundwater, is an alarming concern due to their high toxicity to the surrounding ecosystem and potential threat to the groundwater system. The Principal Component Analysis (PCA) further corroborates the significant and common origin of the heavy metals and total petroleum hydrocarbon (TPH), which inclines toward the oil exploration activities in the nearby oilfield. Among all the six plant species studied, Colocasia esculenta proved to be a noteworthy phytoremediator of both heavy metals and TPH, having an uptake efficiency of 78% of Zn, 46% of Pb, and 75% of Fe, and 70% of TPH. The study provides baseline information to help us identify future threats and suitable endemic phytoremediators, which can be advantageous for future remediation.

Site-specific spatiotemporal occurrence and molecular congener distributions of naphthenic acids in Athabasca oil sands wetlands of Alberta, Canada.

The Athabasca oil sands region (AOSR) of Alberta, Canada is notable for its considerable unconventional petroleum extraction projects, where bitumen is extracted from naturally-occurring oil sands ore. The large scale of these heavy crude oil developments raises concerns because of their potential to distribute and/or otherwise influence the occurrence, behaviour, and fate of environmental contaminants. Naphthenic acids (NAs) are one such contaminant class of concern in the AOSR, so studies have examined the occurrence and molecular profiles of NAs in the region. We catalogued the spatiotemporal occurrence and characteristics of NAs in boreal wetlands in the AOSR over a 7-year period, using derivatized liquid chromatography-tandem mass spectrometry (LC-MS/MS). Comparing median concentrations of NAs across these wetlands revealed a pattern of NAs suggesting NAs in surface waters derived from oil sands deposits. Opportunistic wetlands that formed adjacent to reclaimed overburden and other reclamation activities had the highest concentrations of NAs and consistent patterns suggestive of bitumen-derived inputs. However, similar patterns in the occurrence of NAs were also observed in undeveloped natural wetlands located above the known surface-mineable oil sands deposit that underlies the region. Intra-annual sampling results along with inter-annual comparisons across wetlands demonstrated that differences in the spatial and temporal NA concentrations were dependent on local factors, particularly when naturally occurring oil sands ores were observed in the wetland or drainage catchment.

Biodegradation of 2-methylpentane in fluid fine tailings amended with a mixture of iso-alkanes under sulfate-reducing conditions.

Anaerobic microorganisms in Canada Natural Upgrading Limited (CNUL) fluid fine tailings (FFT) are sustained by residual solvent hydrocarbons. Although FFT are methanogenic in nature, sulfate-reducing microorganisms represent a significant portion of FFT bacterial community. In this study, we examined biodegradation of three iso-alkanes (2-methylbutane, 2-methylpentane, and 3-methylpentane), representing major iso-alkanes in paraffinic solvent, in CNUL FFT under sulfate-reducing conditions. During ∼1100 days of incubation, only 2-methylpentane was degraded partially, whereas 2-methylbutane and 3-methylpentane were not degraded. During active degradation of 2-methylpentane, the bacterial community was dominated by Anaerolineaceae followed by Syntrophaceae, Peptococcaceae, Desulfobacteraceae, and Desulfobulbaceae. The archaeal community was co-dominated by acetoclastic (Methanosaetaceae) and hydrogenotrophic (Methanobacteriaceae) methanogens. This study underlines the limited capability of the microbial community indigenous to CNUL FFT in degrading recalcitrant iso-alkanes under sulfate-reducing conditions.

Enhanced Oil Recovery Using Indigenous Microbiome of High Temperature Oil Reservoirs.

Crude oil is a primary energy source used for economic expansion across the world. Secondary recovery processes employed by industries to recover oil from oil wells leave behind 70% of the oil trapped in marginal and deleted zones of reservoirs. To recover the oil from depleted zones, microbial enhanced oil recovery (MEOR) tertiary processes were introduced, which involve the production of metabolites from the indigenous microbiome. In this study, the indigenous microbiota was identified as Marinobacterium sp., Silvanigrella sp., Petrothermobacter sp., Pseudomonas sp., Bacillus sp., Nitrincola sp., Halomonas sp., Uncultured Roseovarius sp., and Phaeobacter. Further, the secondary metabolites such as volatile fatty acids (ethanol, acetone, and acetate), biomass, gases (CO2, CH4), and biosurfactants were estimated through gas chromatography and FTIR spectroscopy. Once stable microbial growth was attained in the baltch media, it was optimized through response surface methodology (RSM) to minimize the process cost. The optimized media with 9 g/L of molasses, 1.75 g/L of sodium bicarbonate, and 1.25 g/L of ammonium chloride showed a significant impact on metabolite production. Additionally, core flood studies to simulate field studies were performed that represented that TeriK-1 brought a significant increment of 18.9%, which makes it suitable for MEOR field implementation. This study is one of its kind where the indigenous thermophilic sp. was successfully established and is capable of producing the secondary metabolites that aid in the MEOR process.

Machine learning estimation of crude oil viscosity as function of API, temperature, and oil composition: Model optimization and design space.

Measurement of viscosity of crude oil is critical for reservoir simulators. Computational modeling is a useful tool for correlation of crude oil viscosity to reservoir conditions such as pressure, temperature, and fluid compositions. In this work, multiple distinct models are applied to the available dataset to predict heavy-oil viscosity as function of a variety of process parameters and oil properties. The computational techniques utilized in this work are Decision Tree (DT), MLP, and GRNN which were utilized in estimation of heavy crude oil samples collected from middle eastern oil fields. For the estimation of viscosity, the firefly algorithm (FA) was employed to optimize the hyper-parameters of the machine learning models. The RMSE error rates for the final models of DT, MLP, and GRNN are 40.52, 25.08, and 30.83, respectively. Also, the R2-scores are 0.921, 0. 978, and 0.933, respectively. Based on this and other criteria, MLP is chosen as the best model for this study in estimating the values of crude oil viscosity.

CO2 improves the anaerobic biodegradation intensity and selectivity of heterocyclic hydrocarbons in heavy oil.

Heterocyclic hydrocarbons pollution generated by oil spills and oilfield wastewater discharges threatens the ecological environment and human health. Here we described a strategy that combines the greenhouse gas CO2 reduction with microbial remediation. In the presence of nitrate, CO2 can improve the biodegradation efficiency of the resins and asphaltenes in heavy oil, particularly the biodegradation selectivity of the polar heterocyclic compounds by the newly isolated Klebsiella michiganensis. This strain encoded 80 genes for the xenobiotic biodegradation and metabolism, and can efficiently utilize CO2 when degrading heavy oil. The total abundance of resins and asphaltenes decreased significantly with CO2, from 40.816% to 26.909%, to 28.873% with O2, and to 36.985% with N2. The transcripts per million (TPM) value of accA gene was 57.81 under CO2 condition, while respectively 8.86 and 21.23 under O2 and N2 conditions. Under CO2 condition, the total relative percentage of N1-type heterocyclic compounds was selectively decreased from 32.25% to 22.78%, resulting in the heavy oil viscosity decreased by 46.29%. These results demonstrated a novel anaerobic degradation mechanism that CO2 can promote the anaerobic biodegradation of heterocyclic hydrocarbons in heavy oil, which provides a promising biotreatment technology for the oil-contaminated water.