Influence of pH on dynamics of microbial enhanced oil recovery processes using biosurfactant producing Pseudomonas putida: Mathematical modelling and numerical simulation

Research Advances of Microbial Enhanced Oil Recovery

Microbial enhanced oil recovery (MEOR), characterized with the virtues of low cost and environmental protection, reflects the prevalent belief in environmental protection, and is attracting the attention of more researchers. Nonetheless, with the prolonged slump in global oil prices, how to further reduce the cost of MEOR has become a key factor in its development. This paper described the recent development of MEOR technology in terms of mechanisms, mathematical models, and field application, meanwhile the novel technologies of MEOR such as genetically engineered microbial enhanced oil recovery (GEMEOR) and enzyme enhanced oil recovery (EEOR) were introduced. The paper proposed three possible methods to decrease the cost of MEOR: using inexpensive nutrients as substrates, applying a mixture of chemical and biological agents, and utilizing crude microbial products. Additionally, in order to reduce the uncertainty in the practical application of MEOR technology, it is essential to refine the reservoir screening criteria and establish a sound mathematical model of MEOR. Eventually, the paper proposes to combine genetic engineering technology and microbial hybrid culture technology to build a microbial consortium with excellent oil displacement efficiency and better environmental adaptability. This may be a vital part of the future research on MEOR technology, which will play a major role in improving its economic efficiency and practicality.

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Mechanisms of microbial enhanced oil recovery.

• The novel technology of microbial enhanced oil recovery.

• Field trails of microbial enhanced oil recovery.

Predicting performance of in-situ microbial enhanced oil recovery process and screening of suitable microbe-nutrient combination from limited experimental data using physics informed machine learning approach

Screening of suitable microbe-nutrient combination and prediction of oil recovery at the initial stage is essential for the success of Microbial Enhanced Oil Recovery (MEOR) technique. However, experimental and physics-based modelling approaches are expensive and time-consuming. In this study, Physics Informed Machine Learning (PIML) framework was developed to screen and predict oil recovery at a relatively lesser time and cost with limited experimental data. The screening was done by quantifying the influence of parameters on oil recovery from correlation and feature importance studies. Results revealed that microbial kinetic, operational and reservoir parameters influenced the oil recovery by 50%, 32.6% and 17.4%, respectively. Higher oil recovery is attained by selecting a microbe-nutrient combination having a higher ratio of value between biosurfactant yield and microbial yield parameters, as they combinedly influence the oil recovery by 27%. Neural Network is the best ML model for MEOR application to predict oil recovery (R²≈0.99).

Study on Numerical Simulation for Component Transportation and Oil Displacement of a Microbial System

Component transportation is one of the main mechanisms for numerical simulation in microbial oil recovery. However, the research on the component transportation considering the inhibition of metabolites is very limited. A mathematical model of oil displacement in a microorganism system including microbial growth and metabolism equation, component transport equation, and porous media physical property variation equation was established in this paper. The equation was discretized and solved by implicit pressure and explicit saturation. The MATLAB simulation results showed that the chromatographic separation between microorganisms and nutrients happened because of the adsorption of porous media and the activity of microorganisms during the transportation, and the separation degree of the chromatography became higher as the permeability became lower and the injection speed became slower. The multislug alternative injection mode could reduce the degree of chromatographic separation, and the recovery rate can be increased to 50.82%. The results of this study could provide theoretical guidance for the popularization and application of microbial enhanced oil recovery (MEOR).

Biosurfactants: The green generation of speciality chemicals and potential production using Solid-State fermentation (SSF) technology

Surfactants are multipurpose products found in most sectors of contemporary industry. Their large-scale manufacturing has been mainly carried out using traditional chemical processes. Some of the chemical species involved in their production are considered hazardous and some industrial processes employing them categorised as "having potential negative impact on the environment". Biological surfactants have therefore been generally accepted worldwide as suitable sustainable greener alternatives. Biosurfactants exhibit the same functionalities of synthetic analogues while having the ability to synergize with other molecules improving performances; this strengthens the possibility of reaching different markets via innovative formulations. Recently, their use was suggested to help combat Covid-19. In this review, an analysis of recent bibliography is presented with descriptions, statistics, classifications, applications, advantages, and challenges; evincing the reasons why biosurfactants can be considered as the chemical specialities of the future. Finally, the uses of the solid-state fermentation as a production technology for biosurfactants is presented.

Statistical Optimisation of Rhamnolipid Production using a Pseudomonas putida Strain Cultivated on Renewable Carbon Sources of Waste Vegetable Oils

Herein, synthesis of rhamnolipid surfactants was performed using a non-pathogenic Pseudomona s putida strain cultured on a variety of waste frying oils (WFOs) under Taguchi multi-objective optimization design. The effect of substrate types, fermentation setups and incubation time on the biomass concentration, rhamnolipid yield and surface tension of the cultivate media has been investigated. The results demonstrate that the multi-objectives investigation helps to document the optimal limits of the process parameters based on Gray relational analysis. After finding the optimal conditions, a validati on run was performed; therein, the rhamnolipid yield increased from 3.4 to 4.1 g/L; the biomass concentration decreased by 4.84% with an additional surface tension reduction of 2.19% due to an increase of rhamnolipids yield. Overall, soybean WFO was observed to be a preferred substrate for P. putida strain both under Taguchi design and the validation run. The present study proposes a low total of runs and optimum product yield under the Taguchi based multi-objective optimization.

Biochemical, Molecular, and Transcriptional Highlights of the Biosynthesis of an Effective Biosurfactant Produced by Bacillus safensis PHA3, a Petroleum-Dwelling Bacteria

Petroleum crude oil (PCO)-dwelling microorganisms have exceptional biological capabilities to tolerate the toxicity of petroleum contaminants and are therefore promising emulsifier and/or degraders of PCO. This study describes a set of PCO-inhabiting bacterial species, one of which, identified as Bacillus safensis PHA3, produces an efficient biosurfactant which was characterized as a glycolipid. Fourier transform infrared spectrometer, nuclear magnetic resonance, Thin layer chromatography, HPLC, and GC-MS analysis of the purified biosurfactant revealed that the extracted molecule under investigation is likely a mannolipid molecule with a hydrophilic part as mannose and a hydrophobic part as hexadecanoic acid (C16:0). The data reveal that: (i) PHA3 is a potential producer of biosurfactant (9.8 ± 0.5 mg mL^-1); (ii) pre-adding 0.15% of the purified glycolipid enhanced the degradation of PCO by approximately 2.5-fold; (iii) the highest emulsifying activity of biosurfactant was found against the PCO and the lowest was against the naphthalene; (iv) the optimal PCO-emulsifying activity was found at 30-60°C, pH 8 and a high salinity. An orthologous gene encodes a putative β-diglucosyldiacylglycerol synthase (β-DGS) was identified in PHA3 and its transcripts were significantly up-regulated by exogenous PAHs, i.e., pyrene and benzo(e)pyrene but much less by mid-chain n-alkanes (ALKs) and fatty acids. Subsequently, the accumulation of β-DGS transcripts coincided with an optimal growth of bacteria and a maximal accumulation of the biosurfactant. Of particular interest, we found that PHA3 actively catalyzed the degradation of PAHs notably the pyrene and benzo(e)pyrene but was much less effective in the mono-terminal oxidation of ALKs. Such characteristics make Bacillus safensis PHA3 a promising model for enhanced microbial oil recovery and environmental remediation.