Interactions of Microbial-Enhanced Oil Recovery Processes

Date-Leaf Carbon Particles for Green Enhanced Oil Recovery

Green enhanced oil recovery (GEOR) is an environmentally friendly enhanced oil recovery (EOR) process involving the injection of green fluids to improve macroscopic and microscopic sweep efficiencies while boosting tertiary oil production. Carbon nanomaterials such as graphene, carbon nanotube (CNT), and carbon dots have gained interest for their superior ability to increase oil recovery. These particles have been successfully tested in EOR, although they are expensive and do not extend to GEOR. In addition, the application of carbon particles in the GEOR method is not well understood yet, requiring thorough documentation. The goals of this work are to develop carbon nanoparticles from biomass and explore their role in GEOR. The carbon nanoparticles were prepared from date leaves, which are inexpensive biomass, through pyrolysis and ball-milling methods. The synthesized carbon nanomaterials were characterized using the standard process. Three formulations of functionalized and non-functionalized date-leaf carbon nanoparticle (DLCNP) solutions were chosen for core floods based on phase behavior and interfacial tension (IFT) properties to examine their potential for smart water and green chemical flooding. The carboxylated DLCNP was mixed with distilled water in the first formulation to be tested for smart water flood in the sandstone core. After water flooding, this formulation recovered 9% incremental oil of the oil initially in place. In contrast, non-functionalized DLCNP formulated with (the biodegradable) surfactant alkyl polyglycoside and NaCl produced 18% more tertiary oil than the CNT. This work thus provides new green chemical agents and formulations for EOR applications so that oil can be produced more economically and sustainably.

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.

Natural source zone depletion of LNAPL: A critical review supporting modelling approaches

Natural source zone depletion (NSZD) of light non-aqueous phase liquids (LNAPLs) includes partitioning, transport and degradation of LNAPL components. NSZD is being considered as a site closure option during later stages of active remediation of LNAPL contaminated sites, and where LNAPL mass removal is limiting. To ensure NSZD meets compliance criteria and to design enhanced NSZD actions if required, residual risks posed by LNAPL and its long term behaviour require estimation. Prediction of long-term NSZD trends requires linking physicochemical partitioning and transport processes with bioprocesses at multiple scales within a modelling framework. Here we expand and build on the knowledge base of a recent review of NSZD, to establish the key processes and understanding required to model NSZD long term. We describe key challenges to our understanding, inclusive of the dominance of methanogenic or aerobic biodegradation processes, the potentially changeability of rates due to the weathering profile of LNAPL product types and ages, and linkages to underlying bioprocesses. We critically discuss different scales in subsurface simulation and modelling of NSZD. Focusing on processes at Darcy scale, 36 models addressing processes of importance to NSZD are investigated. We investigate the capabilities of models to accommodate more than 20 subsurface transport and transformation phenomena and present comparisons in several tables. We discuss the applicability of each group of models for specific site conditions.

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

By incorporating a temperature-dependent biokinetic and thermal model, the novel method, cold-water microbial enhanced oil recovery (MEOR), was developed under nonisothermal conditions. The suggested model characterized the growth for Bacillus subtilis (microbe) and Surfactin (biosurfactant) that were calibrated and confirmed against the experimental results. Several biokinetic parameters were obtained within approximately a 2% error using the cardinal temperature model and experimental results. According to the obtained parameters, the examination was conducted with several injection scenarios for a high-temperature reservoir of 71 °C. The results proposed the influences of injection factors including nutrient concentration, rate, and temperature. Higher nutrient concentrations resulted in decreased interfacial tension by producing Surfactin. On the other hand, injection rate and temperature changed growth condition for Bacillus subtilis. An optimal value of injection rate suggested that it affected not only heat transfer but also nutrient residence time. Injection temperature led to optimum reservoir condition for Surfactin production, thereby reducing interfacial tension. Through the optimization process, the determined optimal injection design improved oil recovery up to 53% which is 8% higher than waterflooding. The proposed optimal injection design was an injection sucrose concentration of 100 g/L, a rate of 7 m3/d, and a temperature of 19 °C.

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

In present work, the influence of reservoir pH conditions on dynamics of microbial enhanced oil recovery (MEOR) processes using Pseudomonas putida was analysed numerically from the developed mathematical model for MEOR processes. Further, a new strategy to improve the MEOR performance has also been proposed. It is concluded from present study that by reversing the reservoir pH from highly acidic to low alkaline condition (pH 5-8), flow and mobility of displaced oil, displacement efficiency, and original oil in place (OOIP) recovered gets significantly enhanced, resulting from improved interfacial tension (IFT) reduction by biosurfactants. At pH 8, maximum of 26.1% of OOIP was recovered with higher displacement efficiency. The present study introduces a new strategy to increase the recovery efficiency of MEOR technique by characterizing the biosurfactants for IFT_min/IFT_max values for different pH conditions and subsequently, reversing the reservoir pH conditions at which the IFT_min/IFT_max value is minimum.

Numerical modelling of biophysicochemical effects on multispecies reactive transport in porous media involving Pseudomonas putida for potential microbial enhanced oil recovery application

pH and resident time of injected slug plays a critical role in characterizing the reservoir for potential microbial enhanced oil recovery (MEOR) application. To investigate MEOR processes, a multispecies (microbes-nutrients) reactive transport model in porous media was developed by coupling kinetic and transport model. The present work differs from earlier works by explicitly determining parametric values required for kinetic model by experimental investigations using Pseudomonas putida at different pH conditions and subsequently performing sensitivity analysis of pH, resident time and water saturation on concentrations of microbes, nutrients and biosurfactant within reservoir. The results suggest that nutrient utilization and biosurfactant production are found to be maximum at pH 8 and 7.5 respectively. It is also found that the sucrose and biosurfactant concentrations are highly sensitive to pH rather than reservoir microbial concentration, while at larger resident time and water saturation, the microbial and nutrient concentrations were lesser due to enhanced dispersion.

Modification of rock/fluid and fluid/fluid interfaces during MEOR processes, using two biosurfactant producing strains of Bacillus stearothermophilus SUCPM#14 and Enterobacter cloacae: a mechanistic study

During any microbial enhanced oil recovery process, both cells and the metabolic products of bacteria govern the tertiary oil recovery efficiency. However, very accurate examination is needed to find the functionality of these tiny creatures at different reservoir conditions. In this regard, the effect of cell structure on ultimate microbial recovery efficiency which is the most dominant mechanism based on the microorganism types (gram-negative or gram-positive) was systematically investigated. At the first stage, possible different active mechanisms using Bacillus stearothermophilus SUCPM#14 strain were tested using specially designed injection protocol, in situ and ex situ core flooding experiments, interfacial tension, viscosity, pH and Amott wettability index measurements. At the second stage, comparing functionality of B. stearothermophilus SUCPM#14 (a gram-positive type) with the previously examined strain namely Enterobacter cloacae as a gram-negative type, proposed this hypothesis that the cell structure significantly affects the interfacial behaviors. New designed protocols were utilized to check the individual effects of cells, bioproducts and interaction of these together on the oil/water and also fluids/rock interfaces. The final results showed that the cells of B. stearothermophilus SUCPM#14 adhere more into the oil/water interface compared to E. cloacae and change its rheological properties; e.g. its elastic properties which affect the ultimate microbial oil recovery efficiency. Eventually, contradicting results revealed that biosurfactant produced by E. cloacae was able to considerably reduce the interfacial tension and alter the wettability of the rock (to neutral conditions) while biosurfactant produced by B. stearothermophilus SUCPM#14 was not very effective.

Evaluation of a genome-scale in silico metabolic model for Geobacter metallireducens by using proteomic data from a field biostimulation experiment

Accurately predicting the interactions between microbial metabolism and the physical subsurface environment is necessary to enhance subsurface energy development, soil and groundwater cleanup, and carbon management. This study was an initial attempt to confirm the metabolic functional roles within an in silico model using environmental proteomic data collected during field experiments. Shotgun global proteomics data collected during a subsurface biostimulation experiment were used to validate a genome-scale metabolic model of Geobacter metallireducens-specifically, the ability of the metabolic model to predict metal reduction, biomass yield, and growth rate under dynamic field conditions. The constraint-based in silico model of G. metallireducens relates an annotated genome sequence to the physiological functions with 697 reactions controlled by 747 enzyme-coding genes. Proteomic analysis showed that 180 of the 637 G. metallireducens proteins detected during the 2008 experiment were associated with specific metabolic reactions in the in silico model. When the field-calibrated Fe(III) terminal electron acceptor process reaction in a reactive transport model for the field experiments was replaced with the genome-scale model, the model predicted that the largest metabolic fluxes through the in silico model reactions generally correspond to the highest abundances of proteins that catalyze those reactions. Central metabolism predicted by the model agrees well with protein abundance profiles inferred from proteomic analysis. Model discrepancies with the proteomic data, such as the relatively low abundances of proteins associated with amino acid transport and metabolism, revealed pathways or flux constraints in the in silico model that could be updated to more accurately predict metabolic processes that occur in the subsurface environment.