Microbially Induced Corrosion of Carbon Steel in Oilfield Waters from the Romashkino Oilfield (Republic of Tatarstan): Immersion Corrosion Testing

Abstract

Microbially induced corrosion is a common problem in the petroleum industry. In this study, weight loss and surface analysis of grade 20 carbon steel corrosion witness samples were used to evaluate biocorrosion in produced fluids from different wells (Romashkino oilfield, Republic of Tatarstan, Russia). The structure of the resulting microbial communities in the systems with high corrosion indicators was elucidated. The addition of acetate/lactate, yeast extract, and sulfate was found to promote the growth of individual microorganisms in the designed systems and to increase the corrosion rate in several samples (to an average of 0.12 mm year⁻¹). The results of 16S rRNA gene sequence analysis showed that water from different wells from the Romashkino oilfield had distinct microbial compositions. The main genera in the analyzed waters were Oleidesulfovibrio, Halanaerobium, Proteiniphilum, Acetobacterium, Fusibacter, and Methanocrinis, but their relative abundances depended on the water itself and the type of stimulation. Acetogenic bacteria of the genera Fusibacter, Proteiniphilum, Acetobacterium, and acetoclastic methanogenic archaea Methanocrinis became dominant in the microbial community structure in the acetate-enriched systems in water from one of the studied wells. Electron donors, generated by various bacteria and artificially introduced ones, facilitated active dissimilatory sulfate reduction by Oleidesulfovibrio, Desulfotignum, Desulfocurvus, and Pseudodesulfovibrio in water from another production well. The obtained results are important for identifying the causes of premature failures of oilfield equipment, particularly in areas where microbial enhanced oil recovery is used.

1. Introduction

Corrosion, both a natural process and caused by certain factors, has a significant impact on economic integrity and environmental well-being worldwide. Corrosion primarily affects metals due to interactions with environmental factors, particularly moisture, corrosive gases, acids, and microbial activity in the surrounding environment. The susceptibility of metals and alloys to corrosion requires continuous maintenance and repair to ensure the safety and functionality of infrastructure, including the oil industry, throughout its entire life cycle [1,2].

Corrosion processes in oil–water systems are multifaceted, with biocorrosion making a significant contribution to the degradation of the petroleum infrastructure. In the petroleum industry, microbially influenced/induced corrosion (MIC), or more commonly known as biocorrosion, closely coexists with electrochemical corrosion. Biocorrosion is a process in which various microorganisms can initiate or contribute to the degradation of engineering materials by producing aggressive metabolites (acids, acid-forming gases, sulfides) or by directly participating in electrochemical reactions on the surface of the corroded substrate. In any specific environment, MIC can result from various reactions carried out by individual species of bacteria, archaea, fungi, and microalgae [3,4,5,6]. Assessing the diversity of microbial community structure and function associated with microbial oil production is of key importance for developing different strategies in the oil production industry, especially in light of the rapidly evolving technology of microbial enhanced oil recovery (MEOR) [7].

Given the gaps in understanding the actors and mechanisms, the impact of microbes and their economic and environmental consequences are greatly underestimated [5]. These gaps include an unjustified neglect of monitoring this mechanism and limitations in field diagnostics, particularly the lack of reliable corrosion monitoring tools. Among the studies devoted to uncovering the mechanisms of MIC, a separate stratum is devoted to elucidating the role of biotic sulfides produced by a wide range of sulfate-reducing microorganisms (SRM) and developing approaches to mitigate their impacts [8]. Thus, it is noted that among the studies devoted to the characterization of the microorganisms responsible for MIC in industrial samples, in the overwhelming majority of cases studied, only SRM were the main objects of analysis [5]. At the same time, increasing amounts of data are accumulating on the diversity of other physiological groups of microbes (such as sulfur-, manganese-, and iron-oxidizing prokaryotes; iron- and thiosulfate-reducing prokaryotes; and methanogenic archaea) that contribute to the development of MIC through the production of aggressive metabolites such as acids and gases and the formation of biofilms [4,5,9]. However, due to their highly specialized lifestyle and the use of culture methods, they cannot always be detected.

Data on the nature of surface changes caused by microorganisms and their biofilms; data on the role of various aggressive biotic agents in the development of corrosion [2,8]; and immersion experiments that allow us to assess the contribution of formed microbial communities to material degradation under specific conditions in aggressive environments (oilfield waters [10]) make a significant contribution to the development of this field. Thus, in this latter area, we note a study that investigated the mechanisms of MIC in immersion experiments in produced water from the Adıyaman oilfield (Türkiye) [11]. The authors used non-sterile formation water and sterile water (abiotic control) to conduct corrosion tests on N80 steel samples under stirring at +70 °C for 30 days. The authors noted the aggressiveness of the produced water used towards N80 steel and noted that the corrosion rate of experimental samples was higher than that of abiotic control samples. Among the few studies devoted to the disclosure of the characteristics and participants of the corrosion effect of consortia of microorganisms on various carbon steels, it is also necessary to note a study that examined the effect of crude oil and water from the Hassi Messaoud oilfield (Algeria) on X52 steel coupons in immersion experiments at +37 °C for 28 days [12]. In another study [13], the authors also confirmed the significant role of microorganisms in oilfield waters in the development of corrosion on X80 steel subjected to immersion for 360 days. Thus, in biotic systems, the corrosion rate was significantly higher compared to abiotic systems (0.304 g cm⁻² versus 0.022 g cm⁻²).

It is worth noting that most studies focus primarily on general biocorrosion mechanisms, often overlooking the issue of nutrient availability for microorganisms (both individual microbes and microbial associations), especially in oilfield samples where MEOR methods are applied. It is necessary to comprehensively consider the combined effects of natural or artificially created associations and the growing corrosion problems in such oilfields (especially in aging ones). In this study, model grade 20 carbon steel (known as steel 20), widely used in corrosion studies in the petroleum industry, was selected as the material for assessing the corrosion potential of oilfield waters from the Romashkino oilfield (also known as the Romashkinskoye oilfield). The Romashkino oilfield in the Republic of Tatarstan is the largest and most important oilfield in Russia. Due to its long history of operation (since 1952), waterflooding, and microbial activity, primarily sulfidogenic microorganisms [14], this field is considered an oilfield with significant corrosion problems. Furthermore, as demonstrated in our previous study [15], the waters of this region are rich in other microorganisms from the phyla Bacillota, Pseudomonadota, Bacteroidota, Spirochaetota, and Synergistota. These microbes also have the potential to be involved in biocorrosion.

The novelty of this study lies in its exploration of the potential of natural microbial communities in oilfield waters and their functioning under conditions that stimulate corrosion. The study’s uniqueness lies in its explanation of biocorrosion stimulation by providing energy and carbon building blocks to the prokaryotes of produced waters responsible for corrosion, as well as the use of real water samples from oil production sites with existing biocorrosion damage. Given that studying carbon steel biocorrosion requires an interdisciplinary approach, this study focused on collecting scientific data using a combination of modern and standardized methods, namely, weight loss and surface analysis of corrosion samples with the analysis of microbial communities formed under the influence of various nutritional factors. The results will be useful both for assessing the risks of implementing MEOR technologies and for protecting infrastructure susceptible to microbial contamination, particularly in the oil/gas production and processing industries.

2. Materials and Methods

2.1. Production Mixture Sampling and Analysis

The objects of the study were oilfield waters, namely produced waters (a mixture of formation water naturally present in an oil reservoir and injection water) from production wells of the supergiant Romashkino oilfield located in the Republic of Tatarstan (Russia). Samples representing heterogeneous oil/water mixtures were collected from six production wells (labeled as 5705, 6024, 10,081, 11,030, 11,407, and 21,498). Samples were collected in triplicate in sterile plastic bottles. Sampling was carried out jointly with the staff of the laboratory for the protection of oilfield equipment from internal corrosion (PJSC «Tatneft», Almetyevsk, Republic of Tatarstan). Sampling from each production well was carried out on a clear day in the summer of 2024.

After sampling, samples were immediately transported to the laboratory in a portable laboratory thermobox and subsequently used for chemical characterization (aqueous phase analysis was performed after separation from the oil phase) and corrosion simulation experiments. The samples were analyzed for pH, total solids, the oil content, and essential ions. pH measurements were obtained using a Starter 300 pH meter (OHAUS Corporation, Shanghai, China) and an ESC-10601 electrode (Measuring Equipment, Moscow, Russia). Standard buffer solutions (pH 4.01 and 6.86) (Uralcheminvest, Ufa, Russia) were used to calibrate and validate the pH meter. Total solids content was determined according to the standard method using an SHS-10-02 SPU drying oven (Smolensk, Russia). Ammonium levels were estimated using Nessler’s reagent (Sigma-Aldrich, St. Louis, MO, USA) as described previously but for different samples [16]. Sodium, potassium, calcium, and magnesium ion concentrations were analyzed using a Capel 105M capillary electrophoresis system (Lumex, Saint Petersburg, Russia), while total iron, nitrite, nitrate, phosphate, sulfate, and chloride concentrations were analyzed using different test kits (Hanna Instruments, Nusfalau, Romania; Hack, West Hollywood, CA, USA). When necessary, anion concentrations were also analyzed using a Dionex ICS-900 ion chromatography system (Thermo Fisher Scientific, Wilmington, NC, USA), an IonPac AG22 (4 × 50 mm) guard column, and an IonPac AS22 (4 × 250 mm) analytical column. All samples were analyzed in triplicate, and the results are presented as the mean value with standard deviations.

2.2. Corrosion Experiments

Immersion tests in produced waters were conducted in accordance with the ASTM G31 standard guide to determine the contribution of native microorganisms to the degree of biological corrosion of steel specimens. The experiments were conducted under mesophilic conditions (+32 °C). Corrosion experiments with waters (after oil phase removal) from production wells 5705, 6024, 10,081, 11,030, 11,407, and 21,498 were designated as Exp_1, Exp_2, Exp_3, Exp_4, Exp_5, and Exp_6, respectively. Production wells were identified as having a corrosion problem. Taking into account the high salinity of the water samples, they were diluted with sterile distilled water (dilution factor of 4) before the immersion tests. The description of the experiments is provided in

Table 1. Description of the conditions for conducting corrosion experiments.

Experiments	Production Wells	Brief Description of Tests
Exp_1a	5705	Control experiments
Exp_1b		Stimulation with acetate, yeast extract, and sulfate
Exp_1c		Stimulation with lactate, yeast extract, and sulfate
Exp_2a	6024	Control experiments
Exp_2b		Stimulation with acetate and yeast extract
Exp_2c		Stimulation with lactate and yeast extract
Exp_3a	10,081	Control experiments
Exp_3b		Stimulation with acetate, yeast extract, and sulfate
Exp_3c		Stimulation with lactate, yeast extract, and sulfate
Exp_4a	11,030	Control experiments
Exp_4b		Stimulation with acetate, yeast extract, and sulfate
Exp_4c		Stimulation with lactate, yeast extract, and sulfate
Exp_5a	11,407	Control experiments
Exp_5b		Stimulation with acetate, yeast extract, and sulfate
Exp_5c		Stimulation with lactate, yeast extract, and sulfate
Exp_6a	21,498	Control experiments
Exp_6b		Stimulation with acetate, yeast extract, and sulfate
Exp_6c		Stimulation with lactate, yeast extract, and sulfate

.

For corrosion modeling, microbial communities of produced waters were provided with carbon and electron donors in the form of sodium acetate or sodium L-lactate (Sigma-Aldrich, Darmstadt, Germany), as well as growth stimulants (as part of yeast extract, Helicon, Moscow, Russia) (stimulation of microbial communities of produced waters). Control experiments without any stimulation (labeled as «a») were also conducted. Stimulated systems were enriched with 18 mM C₂H₃O₂Na and 1.0 g L⁻¹ of yeast extract (hereinafter referred to as «b») or 18 mM of C₃H₅NaO₃ and 1.0 g L⁻¹ of yeast extract (hereinafter referred to as «c»). Nutrients were added twice in all experiments: at the beginning of the experiment (day 0) and after 14 days. After 14 days, sulfates were added at a concentration of 200 mg L⁻¹ to stimulate the development of sulfidogenic microorganisms in all systems except for the experiments in the Exp_2 group. MgSO₄*7H₂O served as the source of sulfate ions.

To assess the corrosion behavior of steel samples immersed in oilfield water samples and to determine the corrosion rate, special corrosion witness samples (CWS) made of structural carbon steel (grade 20, 60 × 15 × 3.5 mm in size; LLC. “Stroysnabservice”, Samara, Russia) were used. Carbon steel grade 20 was chosen due to its widespread use in oil and gas gathering and transportation [17]. Carbon steel grade 20 has the following chemical composition in weight percentage (wt.%): Fe (~98), C (0.17–0.24), Si (0.17–0.37), Mn (0.35–0.65), S (up to 0.04), P (up to 0.04), Ni (up to 0.25), Cr (up to 0.25), Cu (up to 0.25), and As (up to 0.08).

A total of 200 mL of final water samples were added to sterile 250 mL glass serum bottles, and one CWS was vertically inserted in each bottle using a sterile fishing line. The surfaces of commercial CWS were degreased with 70% ethanol to remove industrial and other organic contaminants, then rinsed with sterile distilled water and exposed to UV light for 30 min prior to experiments. Grinding and more aggressive chemical treatments were avoided in these experiments to preserve the natural state formed during the manufacturing process, to avoid significant changes in microbial colonization, and to replicate biocorrosion processes similar to those observed in real infrastructure. Before experiments, the bottles were purged with N₂ to remove O₂ and then tightly sealed with sterilized rubber caps. All manipulations were performed under aseptic conditions and using the required sterile instruments. The bottles were incubated for 60 days in RI 53 Red Line thermostats (Binder, Tuttlingen, Germany). Considering that flow rate significantly influences biofilm formation, with lower flow rates promoting biofilm development and increasing the steel’s susceptibility to corrosion [18], all tests were conducted under static conditions. Throughout the experiment, the systems were regularly monitored for any observed changes.

2.3. Corrosion Degree Analysis

At the end of experiments, water samples were collected for microbial and chemical analyses, and the corrosion witness samples were analyzed for the degree and products of corrosion. The steel coupons were carefully removed from the systems, cleaned according to the protocol described in [19], and completely dried before weight measurement. The initial weight of CWS before immersion and the weight of CWS at the end of experiments were measured to the nearest 0.0001 g using an ER-120A analytical electronic balance (A&D Company LTD., Tokyo, Japan). The degree of corrosion was determined by a standard method based on the total weight loss of steel coupons and using scanning electron microscopy (SEM). The corrosion rate was determined by the weight loss of steel coupons and converted to mm year⁻¹ using the following formula [20,21].

CR = (K × W)/(A × T × D)

where CR is the corrosion rate in mm year⁻¹; K is a constant for unit conversion = 8.76 × 10⁴; W is the weight loss in g; A is the surface area of the sample in cm²; T is the testing time in h; D is the density of the material in g cm⁻³.

2.4. Scanning Electron Microscopy and Elemental Analysis

Prior to SEM analysis, CWS were stored in a desiccator to prevent exposure to the atmosphere. The surfaces of certain coupons were examined using a MERLIN Field Emission Scanning Electron Microscope (Carl Zeiss, Wetzlar, Germany), and energy-dispersive X-ray spectroscopy (EDS; X-max 80, Oxford Instruments, Oxford, UK) was used for the elemental analysis of CWS surfaces (at 20 kV and probe current 1 nA). Samples for surface analysis were cleaned to remove biofilms and loose corrosion products. Non-abrasive, non-metallic brushes with soft bristles and cotton pads were used for cleaning CWS. This gentle mechanical removal of surface deposits prevented abrasion of the true corrosion profile. Images were acquired at an accelerating voltage of 5 kV and a working distance of 8.5–14.2 mm. Intensity with weight percent of chemical elements was averaged from two locations on each CWS. The analyses were carried out at the Interdisciplinary Center for Analytical Microscopy of Kazan (Volga Region) Federal University (Kazan, Republic of Tatarstan, Russia).

2.5. Analysis of Microbial Communities

The diversity of microbial communities formed in the Exp_2b, Exp_2c, Exp_5b, and Exp_5c tests was analyzed based on the 16S rRNA gene amplicon sequencing approach. Water samples were used immediately for DNA extraction after being precipitated by centrifugation at 14,000× g for 10 min (replicate samples were pooled before DNA extraction). DNA extraction was performed using bead grinding in a FastPrep-24 homogenizer (MP Biomedicals, Solon, OH, USA) and a FastDNA spin kit for soil (MP Biomedicals, Illkirch, France). DNA was then assessed for quality and used to generate amplicon libraries of the V3–V4 region of the 16S rRNA gene as described in detail previously [15]. Negative controls were also provided for DNA extraction and PCR steps. High-throughput sequencing was performed with the Illumina MiSeq sequencing platform (Illumina, San Diego, CA, USA). The sequences of the amplicon libraries were processed using the QIIME2 analysis package (version 2025.10) [22] according to recommended protocols, and taxonomic affiliation was established using the Greengenes2 database. The Venn diagram showing the distribution of OTUs was constructed using the online website (http://bioinformatics.psb.ugent.be/webtools/Venn/; accessed on 10 February 2026).

2.6. Statistical Analysis

All experiments were performed with three separate repetitions (n = 3). Data were preliminarily tested for normal distribution using the Kolmogorov–Smirnov or Shapiro–Wilk tests. The values of corrosion rates and total iron level were then statistically compared using the Kruskal–Wallis test combined with Conover-Iman test. RStudio (version 2024.12) was used for the statistical analyses.

3. Results and Discussion

3.1. Characteristics of Oilfield Waters

Large volumes of water are consumed and generated during the oil production process. After processing, this water can be used for various purposes, including waterflooding. Analysis of produced water allows not only the detection of the presence of corrosive substrates but also the determination of factors that contribute to the development of corrosion, including MIC at oil production sites. This allows for a comprehensive assessment of the operational and environmental risks associated with produced water. This type of water, as the largest type of wastewater generated during the oil production process, is mainly characterized by high chemical oxygen demand levels, contents of total solids, total organic carbon, heavy metals, and individual contaminants. The characteristics of this water are influenced by the nature of the reservoir, the age of the oilfield, the production technology, and the rate of production [10,23,24,25].

Produced waters from the Romashkino oilfield are classified as highly mineralized waters [26]. The results of the analysis of the water samples studied in this work are presented in

Table 2. Results of the study of the produced water samples (aqueous phase) from the Romashkino oilfield.

Parameters	Produced Water Samples
	5705	6024	10,081	11,030	11,407	21,498
pH	6.08 ± 0.16	5.80 ± 0.15	6.04 ± 0.13	5.94 ± 0.21	6.01 ± 0.15	6.14 ± 0.09
Total solids (%)	20.46 ± 0.71	10.01 ± 0.41	21.31 ± 0.45	21.70 ± 0.47	22.50 ± 0.60	10.85 ± 0.36
Total Fe (mg L−1)	n.d.	n.d.	2.0 ± 0.5	1.1 ± 0.3	1.5 ± 0.4	n.d.
NH4+ (mg L−1)	171.2 ± 5.6	126.1 ± 3.9	193.7 ± 3.8	245.9 ± 3.0	231.8 ± 3.3	126.4 ± 4.2
Na+ (g L−1)	66.9 ± 0.3	26.7 ± 1.4	71.2 ± 0.9	73.2 ± 1.1	75.4 ± 1.3	25.9 ± 1.1
K+ (g L−1)	0.4 ± 0.1	0.3 ± 0.1	0.3 ± 0.1	0.5 ± 0.1	0.3 ± 0.1	0.7 ± 0.2
Ca2+ (g L−1)	11.4 ± 0.1	5.8 ± 0.2	16.7 ± 0.8	11.8 ± 0.8	11.7 ± 0.5	7.0 ± 0.4
Mg2+ (g L−1)	3.2 ± 0.9	1.7 ± 0.1	4.0 ± 0.2	2.9 ± 0.5	3.1 ± 0.1	1.3 ± 0.1
NO2− (mg L−1)	n.d.	n.d.	n.d.	n.d.	n.d.	n.d.
NO3− (mg L−1)	n.d.	n.d.	n.d.	n.d.	n.d.	n.d.
PO43− (mg L−1)	1.5 ± 0.4	1.2 ± 0.2	3.1 ± 0.4	1.5 ± 0.5	1.8 ± 0.3	2.5 ± 0.8
SO42− (mg L−1)	125 ± 14	2230 ± 75	154 ± 17	380 ± 47	450 ± 44	187 ± 14
Cl− (g L−1)	103.2 ± 1.2	53.3 ± 2.3	97.8 ± 0.8	98.2 ± 0.5	102.5 ± 0.9	53.9 ± 0.3

n.d.—not detected.

. Thus, the water samples taken for this study were characterized by a high total solids content (on average from 10.0% to 22.5%) and a high content of compounds responsible for hardness (e.g., calcium and magnesium) and chloride ions. The pH of the samples was in the slightly acidic range, on average from 5.8 to 6.14. High concentrations of sodium (up to 75.4 g L⁻¹) and calcium (up to 16.7 g L⁻¹) were detected in analyzed samples. It should be noted that chloride and sodium ions are considered the most detectable in produced waters [23,26]. All water samples were found to have high salinity and can be characterized as sodium-chloride brines. In addition, the results showed that all water samples contained no oxidized forms of nitrogen and low levels of phosphates and total iron. Ammonium ions were detected as the primary nitrogen source in the waters used in the study. It should be mentioned that the levels of individual components in the analyzed waters may have been influenced by the use of certain chemical reagents and drilling fluids and may have changed during the operation of production wells, which could affect the overall water quality and environmental impact of the drilling process.

3.2. Corrosion Potential of Unstimulated and Stimulated Microbial Communities of Produced Waters

During the incubation of corrosion witness samples in diluted waters from various wells under various nutrient conditions, the color of the solutions changed significantly and varied between experiments. This was due to both general corrosion processes and biocorrosion processes caused by the activity of individual microorganisms. Thus, in the control experiments (Table 1; labeled as «a»), the water color changed to orange in most of the samples and to black in some, whereas in the experiments with the addition of nutrients (Table 1; labeled as «b» and «c»), blackening of the water was observed in all samples, as well as the formation of a black sediment and a strong rotten egg odor (at the end of the experiments). This indicates the reduction of sulfates, both original and artificially added, and the formation of sulfides in the water.

After 60 days of experiments, predominantly black and orange corrosion products were observed on the surface of CWS recovered from the systems. Figure 1 shows photographs of the original and corroded CWS (one of three replicates). The average corrosion rates of CWS under different experimental conditions were determined by the weight loss (Figure 2). Thus, the highest corrosion rates were observed for samples from the Exp_5b tests (0.115 ± 0.005 mm year⁻¹), where the produced water was enriched with sodium acetate, yeast extract, and sulfates, followed by coupons from the Exp_5c tests (0.071 ± 0.006 mm year⁻¹), where the water was enriched with sodium lactate, yeast extract, and sulfates. In the Exp_5b tests, the film of corrosion products/biofilm was quite thick but loose, with easily exfoliated areas, compared to CWS removed from the lactate-exposed systems. The formation of loose and defective coatings may have contributed to enhanced corrosion, in part by providing large cathodic surfaces for proton reduction [27] or by allowing corrosive agents from aggressive environments such as oilfield waters to penetrate the steel. These exfoliated corrosion products were also examined (designated below as Exp_5b_f (film)). The second system in which the effect of nutrient addition on corrosion rate was also observed was the Exp_2 group; however, no additional sulfates were added to this system (since this water originally contained high levels of sulfates; Table 2). Samples from the Exp_2 and Exp_5 systems were included in the subsequent analysis of the microbial communities that formed under different enriched conditions.

Overall, across all experiments, the average corrosion rates of CWS in tests without any modifications (labeled as “a”) were lower than the corrosion rates of CWS in tests with the addition of acetate and yeast extract (labeled as “b”) (although in some cases these values were statistically insignificant) (Figure 2). It is worth noting that no inhibitory effect of acetate was observed (due to possible adsorption of acetate ions on the carbon steel surface) [28,29]. In experiments with lactate and yeast extract (labeled as “c”), the corrosion rates of CWS in individual tests were lower than those observed in the control group. Taking into account the experimental period (60 days), it can be assumed that the indigenous microorganisms of some studied waters in the control tests did not experience a significant deficiency of the carbon source, since its limitation can aggravate the corrosion of carbon steel (electro-induced biological corrosion), in particular due to the use of Fe⁰ as an electron donor by sulfate-reducing bacteria [30] or acetogenic bacteria [31]. At the same time, the biofilm formed on the surface of CWS can hinder the diffusion of corrosive ions and the release of iron into the medium. This may explain similar or lower corrosion rate values in the presence of nutrients (especially lactate). Although the microbial cell concentration was not measured in our experiments, the supply of nutrients to the culture medium could have increased the number of attached microbial cells and induced biofilm formation. This could suppress the mass transfer process and potentially protect the steel from corrosion [32]. It should also be noted that the soluble total iron concentration was higher in the fed-batch tests (measured in the Exp_2 and Exp_5 groups) than in the control tests (Figure 3), and elevated total Fe content in aqueous solutions correlates with high rates of steel corrosion [33,34]. In these two groups, sulfate ion concentrations were also measured at the end of the experimental period. Thus, sulfate removal efficiencies were 14.7 ± 2.1%, 23.8 ± 1.7%, 26.5 ± 1.5%, 16.3 ± 0.8%, 95.4 ±1.1%, and 58.3 ± 1.5% in the experiments Exp_2a, Exp_2b, Exp_2c, Exp_5a, Exp_5b, and Exp_5c, respectively. However, it is worth noting that the initial sulfate ion concentration varied between the different waters.

Changes in pH at the end of experiments were also measured. The pH values in the control and enriched media increased toward the end of the experimental period (6.4–7.5), which may be related, in part, to chemical reactions consuming hydrogen ions or the activity of individual microorganisms. In this study, the corrosion of CWS in tests with the addition of acetate and lactate (potentially related to the activity of sulfate-reducing microorganisms) was specific to the produced water used. In many selective culture media for SRM (e.g., modifications of Postgate’s medium), lactate is used as a preferred carbon and energy source due to the high growth rate it provides, while acetate is an important substrate for acetate-utilizing sulfate reducers, sulfur-reducing microorganisms, and acetoclastic methanogenic archaea. Acetate is the most important intermediate in the anaerobic conversion of carbon flow, including the anaerobic conversion of oil by consortia of syntrophic bacteria and methanogens [35]. Sulfate-reducing microorganisms form specific relationships with acetogens and methanogens, and the nature of these relationships depends on nutrient conditions. Specifically, in the presence of sulfate, SRM compete with methanogens, whereas in the absence of sulfate, they enter into syntrophic relationships with them [36]. If SRM do not experience a deficiency of organic substrates, then the conversion of specific organic acids associated with the reduction of sulfate proceeds to acetate, which, in turn, contributes to methanogenesis [37]. In the present study, after 60 days of experiments, the sulfate level in enriched systems decreased, which may indicate an active sulfate reduction process under the established conditions.

The images of the surfaces of CWS exposed to abiotic and biotic factors promoting corrosion/biocorrosion in the studied produced waters showed the presence of corrosion products represented by oxygen, iron, and a relatively high sulfur content, as detected by the EDS method (Figure 4;

Table 3. Atomic percentages of corrosion product elements formed on CWS during 60-day immersion tests as determined by energy dispersive spectroscopy. Experimental conditions are described in Table 1.

Atomic %	C	O	Na	Mg	Al	Si	P	S	Cl	K	Ca	Cr	Mn	Fe	Cu
Exp_2b	37.26	29.30	2.13	–	–	–	0.17	0.95	1.47	–	0.44	–	0.20	28.08	–
Exp_2c	37.01	18.91	1.61	0.37	–	–	1.06	0.73	0.56	–	0.89	–	0.23	38.63	–
Exp_5b	20.83	41.12	–	–	0.26	0.34	0.09	1.97	2.58	–	0.17	0.17	0.26	31.90	0.31
Exp_5b_f	31.00	21.48	3.91	0.90	–	–	–	15.59	2.17	0.05	1.03	–	–	23.87	–
Exp_5c	17.84	41.37	0.89	–	–	0.13	–	2.68	3.73	–	0.11	0.07	0.18	32.86	0.14

). The detachment of corrosion products from CWS from the Exp_5b tests had a characteristic corrosion product pattern (Figure 4d–f) and contained substantially more sulfur relative to the coupon surface itself (15.59 atomic % versus 1.97 atomic %, respectively), which may indicate the sulfide nature of some corrosion products. It is worth noting that the Fe content and Fe/O ratio differed in the samples from the Exp_5b (Fe/O: 0.78) and Exp_5b_f (Fe/O: 1.11), which can be explained by the composition of the formed corrosion products, particularly iron oxides. In the experiments Exp_2b and Exp_2c, the studied corrosion products had lower sulfur contents than observed in the experiment Exp_5 with additives. The other chemical elements were obtained from the produced waters, added nutrients, and microbial cells.

SEM-EDS analysis of the coupons revealed differences in the corrosion products formed in various systems, which can be explained by the different chemical compositions of produced waters used and the microbial diversity formed under enriched conditions. Based on the EDS analysis of the coupons’ surfaces and the corrosion products formed under enrichment, it can be suggested that the main corrosion products were iron sulfides and iron oxides. In our recent study, we also noted that microorganisms present in produced waters from wells near Leninogorsk (Republic of Tatarstan, Russia), which have a lower salinity than the produced waters used in this study, could enhance the corrosion rate of grade 20 steel when supplemented with electron donors and growth factors (2.0 g L⁻¹ of Na lactate and 1.0 g L⁻¹ of yeast extract) [15]. A similar study also found that in lactate-enriched systems (produced water was obtained from a shale-gas-gathering and transportation system with varying Na lactate contents), samples of L245 steel pipes, exposed to corrosion, experienced more severe corrosion than the control samples within 10 days [38]. The authors noted that the macro- and microscopic appearance of the sample surface and the corrosion rate were dependent on the lactate concentration. Thus, at a 3.5 g L⁻¹ Na lactate concentration, the corrosion rate was the highest (0.077 mm year⁻¹).

In a previous study investigating biocorrosion under seawater-simulating conditions [19], the authors discussed differences in the composition of biofilms/corrosion products, weight loss of marine grade DH36 carbon steel, and damage patterns in sterile marine broth after the addition of a pure culture of the sulfate-reducing bacterium Desulfovibrio desulfuricans, different bacterial combinations (marine isolates of Halomonas korlensis, Bacillus aquimaris, Prolixibacter bellariivorans, and Sulfitobacter pontiacus with and without D. desulfuricans), and a consortium of microbes of orange tubercle from the steel sheet piling. The researchers added fresh, sterile nutrient medium every two weeks during the incubation period (8 weeks) to maintain the viability of the tested microorganisms and consortium. The highest corrosion rate in this study was recorded in tests with D. desulfuricans, while microbial consortia showed lower overall corrosion rates compared to tests with D. desulfuricans and the control group (without microbial introduction). However, tests with D. desulfuricans under anaerobic conditions and in combination with marine isolates showed significantly more pronounced localized pitting.

In another study evaluating the effect of acetate on the MIC of internal pipeline surfaces under simulated anaerobic testing conditions in formation water (with 3% NaCl to simulate the condition in a pipeline environment) and Postgate Medium B (a selective medium for SRM), the authors attributed the increased corrosion to an intensification of the metabolism of sulfate reducers [29]. However, studies on enrichment of oilfield waters for biocorrosion assessment are relatively limited. These studies highlight both the importance of nutrient supply and the influence of microbial agents’ nature on the degree of corrosion. It should be noted that the biogeochemical behavior of Fe is the subject of research not only in connection with electrochemical and microbial corrosion but also with bioremediation since Fe acts as an agent affecting the fate of contaminants [39,40].

This study notes that the rate of corrosion and the corrosion products generated by native microbial communities of oilfield waters (rather than individual species) vary significantly depending on the nutrient medium. Weight loss analysis demonstrating significant variations in the corrosion rates of carbon steel surfaces exposed to studied oilfield waters and microbial activity under nutrient-rich conditions highlights the urgent need to develop biocorrosion control strategies, especially in enhanced oil recovery operations and future water resource management [25,41]. Such systems will potentially be characterized by a high risk of developing localized biocorrosion. Microbial growth and the formation of specific microenvironments on metal surfaces will allow anaerobic microbes, primarily sulfate-reducing members, to thrive and produce aggressive hydrogen sulfide, as well as support the growth of other microorganisms involved in metal degradation.

3.3. Taxonomic Distribution of Microbial Communities

This study further assessed the effect of introducing various carbon sources and electron donors on the structure of microbial communities formed by the end of the experiments (60 days) in the Exp_2 and Exp_5 groups, which showed some differences in corrosion rates compared to the control tests. Information on the alpha diversity indices of microbial communities from these experiments is provided in

Table 4. Alpha diversity of the microbial communities formed in the Exp_2b, Exp_2c, Exp_5b, and Exp_5c tests (based on 16S rRNA amplicon sequencing). Experimental conditions are described in Table 1.

Alpha Diversity Metrics	Samples from Stimulated Tests
	Exp_2b	Exp_2c	Exp_5b	Exp_5c
Observed OTU number	36	16	34	19
Chao estimated OTU number	47	24	59	31
Shannon entropy	3.24	3.01	4.07	2.07
Simpson’s dominance	0.84	0.83	0.91	0.54

. Analysis of the diversity of the formed microbial communities in the produced water from these experiments revealed the influence of the nature of the nutrient on their structure. As can be seen in Table 4, the nature of the enrichment influenced the species richness. Thus, both systems with the addition of sodium lactate and yeast extract (Exp_2c and Exp_5c) were characterized by reduced OTU numbers and diversity indices of the formed microbial communities. The diversity indices made it possible to determine the moderate diversity of the microbial communities formed in the studied systems.

In order to assess the distribution of OTUs between samples from the Exp_2 and Exp_5 groups, a Venn diagram was constructed (Figure 5).

A total of 5 and 6 OTUs were common across the tests Exp_2b/Exp_2c and Exp_5b/Exp_5c, respectively, and only 3 OTUs were common across all four groups. The analysis highlighted the uniqueness of the used produced waters from wells 6024 and 11,407, as well as the influence of the nature of the stimulation on the resulting microbial communities in the waters. The microbial composition of samples from the tests Exp_2b and Exp_5b demonstrated greater individuality among the studied samples (72% and 62% of unique OTUs, respectively).

Microbial communities from the production well 6024 formed during immersion tests (the Exp_2b and Exp_2c tests) differed in their structure. The Exp_2b systems were characterized by the following important phyla: Bacillota_A_368345 (45.4%), Bacteroidota (28.2%), Bacillota_I (2.4%), Thermotogota (1.9%), Chloroflexota (1.8%) within the domain Bacteria, and Halobacteriota (17.0%) and Thermoplasmatota (1.1%) within the domain Archaea. Replacing sodium acetate with sodium lactate (Exp_2c) did not substantially affect the relative abundance of Bacillota_A_368345 and Bacteroidota but increased the relative abundance of Bacillota_I (up to 14.1%) and Desulfobacterota_G_459543 (up to 3.5%). This also prevented bacteria of Thermotogota, as well as archaea of Halobacteriota and Thermoplasmatota, from remaining an important component of the formed microbial community. In the Exp_5b systems, the most abundant bacterial phyla were as follows: Desulfobacterota_G_459543 (39.6%), Bacillota_F (26.4%), Bacillota_I (25.4%), and Chloroflexota (7.1%). Representatives of archaea were not detected in these systems. Replacing sodium acetate with sodium lactate substantially affected the structure and relative abundance of the major groups within the bacterial community in the Exp_5c systems. Thus, members of Desulfobacterota_G_459543 (74.6%), Bacillota_F (15.9%), Bacillota_I (7.7%), and Spirochaetota (1.5%) were detected in the Exp_5c tests. Bacteria belonging to the phyla Bacteroidota and Bacillota can be found in various types of wastewaters [42,43].

The distribution of classes and genera for each sample is shown in Figure 6a and Figure 6b, respectively. The taxonomic classification on the class level revealed the presence of 12 bacterial and 2 archaeal classes. The microbial structure of the produced fluids from the well 6024, used for immersion tests under the influence of additional electron donors but without the addition of extra sulfates (the Exp_2b and Exp_2c tests), was represented by members of both the domain Bacteria and the domain Archaea. For both systems, bacteria of the genera Fusibacter_A, Proteiniphilum, Acetobacterium, and an unknown Bacilli_A were identified as important, and their relative abundances depended on the added substrate. Archaeal representatives, however, were characteristic only for the system with the addition of acetate (Exp_2b). Thus, Methanocrinis as a novel genus within the family Methanotrichaceae with acetoclastic metabolism, previously observed in anaerobic and (halo)alkaline habitats [44], was detected only in the Exp_2b systems (16.7%).

The development of Methanocrinis occurred both due to the utilization of acetate introduced into these systems and to their supply with bacterial acetate, in particular, by bacteria from the acetogenic genera Acetobacterium, Fusibacter, and Proteiniphilum. The addition of lactate instead of acetate did not significantly affect the relative abundance of Proteiniphilum (27.6% and 30.3% in the tests Exp_2b and Exp_2c, respectively), while in lactate-feeding tests the relative abundance of Acetobacterium increased and the relative abundance of Fusibacter decreased compared to the acetate-enriched systems (up to 38.7% and 12.1%, respectively). Members of the acid-producing genera Proteiniphilum, Acetobacterium, and Fusibacter were detected in produced water samples in our previous study [15]. Proteiniphilum, a genus of anaerobic bacteria of the class Bacteroidia, possessing a wide range of metabolic capabilities, including hydrolysis, fermentation, and acetate oxidation, is detected in many ecosystems under various inhibitory conditions [45]. In contrast, the obligate anaerobic fermentative bacteria of the genus Fusibacter (class Clostridia) are also detected in oilfield reservoirs and infrastructures and can be associated with biocorrosion through thiosulfate reduction and/or biofilm formation [46,47]. It is worth noting that, in contrast to the Exp_5 tests, the proportion of sulfate-reducing bacteria in the Exp_2 tests was small and was represented by members of Pseudodesulfovibrio (up to 2.2%) and Oleidesulfovibrio (up to 1.2%).

The most abundant class in the Exp_5b and Exp_5c tests was Desulfovibrionia (31.0% and 74.6% of total 16S rRNA gene sequences, respectively), followed by Halanaerobiia (26.4% and 15.9%, respectively) and Bacilli_A (25.4% and 7.7%, respectively). Representatives of Desulfovibrionia and Halanaerobiia were not characteristic of the production waters from the Exp_2b and Exp_2c tests. Members of Desulfobacteria were observed only in the Exp_5b test with the addition of acetate. Changing the feeding conditions in the Exp_5 tests substantially affected the relative abundance of Desulfovibrionia. A detailed study on the genus level revealed Oleidesulfovibrio, Desulfocurvus, and Pseudodesulfovibrio, which belong to the class Desulfovibrionia. Other important bacterial genera detected in the Exp_5 tests included Halanaerobium, Brevefilum, Desulfotignum, and the unclassified Bacilli_A, but their relative abundances were determined by the experimental conditions (Figure 6b).

Oleidesulfovibrio alaskensis (formerly Desulfovibrio alaskensis), as one of two species of the genus Oleidesulfovibrio, is a strictly anaerobic, partially lactate-oxidizing, moderately halophilic, mesophilic SRM originally isolated from a soured oil well in Prudhoe Bay (Alaska, USA) using marine Postgate medium C with lactate as a carbon source [48]. The authors showed that the substrates for this microorganism are lactate, pyruvate, and succinate, which can be oxidized in the presence of sulfates, sulfites, and thiosulfates. At the same time, bacteria of this species are unable to use acetate, as well as benzoate, butyrate, propionate, and butanol, as electron donors, which may explain the dominance of these bacteria in the Exp_5c tests with the lactate feeding regimen. Moreover, O. alaskensis can form biofilms, which may also influence the corrosion rate, given that biofilms are able to adsorb aggressive metal ions via extracellular polymeric substances [49].

In the Exp_5 tests, an important bacterial genus detected was Halanaerobium, a genus of strictly anaerobic, halophilic bacteria that produce organic acids and supply them to SRM. Bacteria of this genus have been detected in the production water from the Berkel oilfield located in the western Netherlands [50] and are considered a key agent of reservoir souring and associated corrosion problems in the oil and gas industry, including corrosion caused by the use of organic polymers (particularly guar gum) used in hydraulic fracturing [51,52] and the production of extracellular polymeric substances [53]. The presence of Halanaerobium in the production water from the Exp_5 tests, which can ferment a wide range of substrates and produce thiosulfate-dependent sulfide [51,54], explains the aggressiveness of these waters. Thus, the microbial community in the Exp_5 tests, formed under artificial nutrition conditions, included acid-forming bacteria and numerous lineages of sulfidogenic microorganisms that respond to electron donor changes.

In this study, bacteria of the genus Sphaerochaeta (class Spirochaetia) were further detected in the Exp_2 and Exp_5 systems, with their relative abundances being higher in lactate-containing experiments. It was noted that these chemoorganoheterotrophic anaerobic bacteria with fermentative metabolism were previously isolated from different oilfield waters [55,56]. They were also detected in Fe-corroding microbial consortia enriched from slime-like precipitates from a corroded metal apparatus installed in an artificial deep-sea hydrothermal vent [57]. It is worth noting that non-corrosive representatives of the formed microbial communities can contribute to the nature and rate of corrosion by producing substrates and electron transfer mediators, in particular, by helping corrosive representatives to produce energy and aggressive metabolites.

It should be noted that the presented study examined the effect of introducing different nutrients on the structure of planktonic microbial communities, whereas other studies have focused on the communities of formed biofilms. For example, Elumalai et al. [58] studied the structure of biofilms responsible for the corrosion of API 5L carbon steel incubated in raw (biotic systems) and filter-sterilized (control system) produced water collected from Indian oilfields. The researchers noted that the biofilm systems were mainly represented by various classes of Pseudomonadota, Actinomycetota, Clostridia, Bacilli, and Acidobacteriota. Although planktonic representatives in our work were studied, a certain proportion of the communities have included organisms capable of forming biofilms and direct representatives of biofilms. The research described herein highlights the potentially detrimental consequences that can arise from the activity of various microorganisms that are ignored and remain unaccounted for by existing corrosion diagnostic methods, which primarily focus only on SRM activity.

4. Conclusions

This study investigated the corrosion induced by microbial communities formed in produced waters under recharge conditions using corrosion immersion tests. Changes in corrosion rate, as well as the morphology and corrosion products on steel specimens, were examined, and the structure of microbial communities was deciphered. Overall, across all experiments, the average corrosion rate of CWS in unmodified tests was lower than that in tests with the supplementation of acetate and yeast extract. The results showed that a higher corrosion rate was observed in acetate/yeast extract-enriched systems in water from well 11407 (0.12 mm year⁻¹ against 0.02 mm year⁻¹ in control tests), whereas in other anaerobic systems the corrosion rate was lower. The increased corrosion rate under recharge conditions can be explained by the fact that, under the influence of nutrients, certain microbial species actively produce corrosive agents. The results of 16S rRNA gene sequence analysis showed that water from different wells from the Romashkino oilfield had distinct microbial compositions. The main genera in the analyzed waters were Oleidesulfovibrio, Halanaerobium, Proteiniphilum, Acetobacterium, Fusibacter, and Methanocrinis, but their levels were influenced by the water itself and the type of stimulation. This study showed that the experimental strategy of providing both an electron donor and acceptor can be considered a useful tool for investigating the biocorrosion potential of anthropogenic samples. The significance of this work lies in expanding the scientific basis for the use of non-synthetic, natural environments directly containing corrosive microorganisms, which will expand both the range of detectable microorganisms and the factors that inhibit them. The results of the analysis of the community structure formed under the influence of different nutrient conditions revealed the importance of acetate and lactate as substrates for SRM and highlighted the need to consider non-sulfidogenic microorganisms in these studies.