Development of Coupled Biokinetic and Thermal Model to Optimize Cold-Water Microbial Enhanced Oil Recovery (MEOR) in Homogenous Reservoir

Study on the kinetics of formation process of emulsion of heavy oil and its functional group components

Enhanced oil recovery (EOR) by in situ formation of oil-in-water emulsion in heavy oil cold production technology has received growing interest from the petroleum industry. We present an experimental study of emulsification of model oils prepared by heavy oil and its functional group compositions dissolved into toluene brought into contact with a surfactant solution. The effects of functional group composition, emulsifier concentration, temperature, pH and stirring speed on the emulsification rate of heavy oil was investigated. A second-order kinetic model characterizing the temporal variation of conductivity during the emulsification has been established. The results show that acidic and amphoteric fractions exhibit higher interfacial activity, larger emulsification rate constant and faster emulsification rate. With the increase of emulsifier concentration, the emulsification rate constant increase to the maximum value at a concentration of 0.05 mol/L before decreasing. Temperature increase benefits the emulsification rate and the activation energy of the emulsification process is 40.28 kJ/mol. Higher pH and stirring speed indicate faster emulsification rate. The heterogeneity of emulsions limits the accuracy of dynamic characterization of the emulsification process and the determination method of emulsification rate has always been controversial. The conductivity method we proposed can effectively evaluates the emulsification kinetics. This paper provides theoretical guidance for an in-depth understanding of the mechanism and application of cold recovery technology for heavy oil.

DeepSTABp: A Deep Learning Approach for the Prediction of Thermal Protein Stability

Proteins are essential macromolecules that carry out a plethora of biological functions. The thermal stability of proteins is an important property that affects their function and determines their suitability for various applications. However, current experimental approaches, primarily thermal proteome profiling, are expensive, labor-intensive, and have limited proteome and species coverage. To close the gap between available experimental data and sequence information, a novel protein thermal stability predictor called DeepSTABp has been developed. DeepSTABp uses a transformer-based protein language model for sequence embedding and state-of-the-art feature extraction in combination with other deep learning techniques for end-to-end protein melting temperature prediction. DeepSTABp can predict the thermal stability of a wide range of proteins, making it a powerful and efficient tool for large-scale prediction. The model captures the structural and biological properties that impact protein stability, and it allows for the identification of the structural features that contribute to protein stability. DeepSTABp is available to the public via a user-friendly web interface, making it accessible to researchers in various fields.

Exploiting Microbes in the Petroleum Field: Analyzing the Credibility of Microbial Enhanced Oil Recovery (MEOR)

Crude oil is a major energy source that is exploited globally to achieve economic growth. To meet the growing demands for oil, in an environment of stringent environmental regulations and economic and technical pressure, industries have been required to develop novel oil salvaging techniques. The remaining ~70% of the world’s conventional oil (one-third of the available total petroleum) is trapped in depleted and marginal reservoirs, and could thus be potentially recovered and used. The only means of extracting this oil is via microbial enhanced oil recovery (MEOR). This tertiary oil recovery method employs indigenous microorganisms and their metabolic products to enhance oil mobilization. Although a significant amount of research has been undertaken on MEOR, the absence of convincing evidence has contributed to the petroleum industry’s low interest, as evidenced by the issuance of 400+ patents on MEOR that have not been accepted by this sector. The majority of the world’s MEOR field trials are briefly described in this review. However, the presented research fails to provide valid verification that the microbial system has the potential to address the identified constraints. Rather than promising certainty, MEOR will persist as an unverified concept unless further research and investigations are carried out.

An overstability analysis of vertically vibrated suspension of active swimmers subjected to thermal stratification

The present article focuses on the analytical approach to discuss the thermo–vibrational convection in a suspension of the active (gyrotactic) swimmers. The onset of instability criterion is investigated for the stationary and oscillatory modes of convection in a shallow fluid layer with no–slip and rigid–free walls. The eigenvalue problem is tackled by Galerkin scheme to get the desired stability diagram and the correlation between the critical Rayleigh numbers. The overstability in suspension is possible when the unstable density gradient of the gyrotactic particles is opposed by the density variation due to thermo–vibrational influence. The suspension is destabilized due to gyrotactic up–swimming while the increase in Péclet number stabilizes the system. The stabilizing influence of vertical vibration is considerably affected due to thermal gradient which destabilizes the suspension. An interesting result of this study is the influence of thermo–vibrational parameter which is associated with applied thermal and vibrational properties. We reported that the destabilizing nature of thermo–vibrational parameter becomes thermally or vibrationally governed when the suspension is heated or cooled from below. When compared to the rigid–rigid boundaries, the displayed profiles for rigid–free walls yielded less stableness in the suspension.

Analyzing transient respirometric data by analytical algorithm for Monod kinetic parameters

This study aims to develop an analytical algorithm with oxygen update (O_u) data obtained from transient respirometric measurement. Based on Monod kinetics, this study formulates a novel two-phase analytical model for an oxygen uptake rate plot (OUR vs. O_u) obtained by respirometric techniques. The first phase is a hyperbolic equation relating to exogenous and endogenous respiration, while the second phase is a linear equation for endogenous respiration only. An algorithm was therefore developed to analyze four Monod parameters by locating the best phase-separating point at which the absolute average relative error (ARE) of OUR is minimized. An analysis using test data on acetate verified that the algorithm is capable of transient kinetic parameter estimation with an ARE below 5-10%. A sensitivity analysis on domestic wastewater coupled with a Monte Carlo simulation concluded that the kinetic test must be conducted at a relatively high initial substrate level (S_o/X_o ≧ 1 and S_o/K_s ≧ 10) for reliable parameter estimation. Moreover, it is crucial to conduct the kinetic test with sufficient and acclimated seed culture for the degradation of substrate. The results of this study can be used to develop an automatic transient kinetic analyzer with modern programmable respirometers.

Microbial Surfactants: The Next Generation Multifunctional Biomolecules for Applications in the Petroleum Industry and Its Associated Environmental Remediation

Surfactants are a broad category of tensio-active biomolecules with multifunctional properties applications in diverse industrial sectors and processes. Surfactants are produced synthetically and biologically. The biologically derived surfactants (biosurfactants) are produced from microorganisms, with Pseudomonas aeruginosa, Bacillus subtilis Candida albicans, and Acinetobacter calcoaceticus as dominant species. Rhamnolipids, sophorolipids, mannosylerithritol lipids, surfactin, and emulsan are well known in terms of their biotechnological applications. Biosurfactants can compete with synthetic surfactants in terms of performance, with established advantages over synthetic ones, including eco-friendliness, biodegradability, low toxicity, and stability over a wide variability of environmental factors. However, at present, synthetic surfactants are a preferred option in different industrial applications because of their availability in commercial quantities, unlike biosurfactants. The usage of synthetic surfactants introduces new species of recalcitrant pollutants into the environment and leads to undesired results when a wrong selection of surfactants is made. Substituting synthetic surfactants with biosurfactants resolves these drawbacks, thus interest has been intensified in biosurfactant applications in a wide range of industries hitherto considered as experimental fields. This review, therefore, intends to offer an overview of diverse applications in which biosurfactants have been found to be useful, with emphases on petroleum biotechnology, environmental remediation, and the agriculture sector. The application of biosurfactants in these settings would lead to industrial growth and environmental sustainability.