Long-Term Dynamics of Microbial Communities in a High-Permeable

Sep 12, 2017 - To assess the dynamics of microbial communities in a petroleum reservoir during microbial enhanced oil recovery (MEOR), injected and pr...
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Cite This: Energy Fuels 2017, 31, 10588-10597

Long-Term Dynamics of Microbial Communities in a High-Permeable Petroleum Reservoir Reveals the Spatiotemporal Relationship between Community and Oil Recovery Zhiyong Song,*,† Fengmin Zhao,‡ Gangzheng Sun,‡ and Weiyao Zhu† †

School of Civil & Resource Engineering, University of Science and Technology Beijing, Beijing, 100083, China Research Institute of Petroleum Engineering, Shengli Oil Field Ltd. Co., SinoPEC, Dongying, 257000, China



S Supporting Information *

ABSTRACT: To assess the dynamics of microbial communities in a petroleum reservoir during microbial enhanced oil recovery (MEOR), injected and produced fluids from multiple wells were monitored using molecular microbial methods over 20 months. In this highly permeable (1.5−2.5 μm2) and high-temperature (65 °C) reservoir, communities contain phyla Euryarchaeota, Proteobacteria, Deferribacteres, and Firmicutes, which may be collected by flooding fluids from different habitats through strata. Since the oil-rich areas in the flooded reservoir generally gather around oil wells with high temperatures and strictly anaerobic conditions, the dominance of thermophilic and anaerobic microorganisms, which are capable of inhabiting oil-rich areas, is consistent with positive oil-output responses (temporarily enhanced by 5 × 103 kg per day). During later periods, the communities were dominated by Enterobacter without high-temperature adaptability, which corresponds to a considerable decline in oil-output. Meanwhile, an abnormal increase of community similarity, acetate, and cell concentrations in produced fluids simultaneously indicated a severe enhancement of reservoir permeability along the flooding route, which reveals the direct reason for the community shift and the oil output decline. Therefore, an understanding of the long-term dynamics of reservoir communities is essential for distinguishing functional species and to establish a reservoir-scale connection between microbiology and porous flow.

1. INTRODUCTION Crude oil is typically recovered by a primary recovery that uses natural reservoir pressure, and a secondary recovery that utilizes water flooding to maintain pressure in a reservoir.1 Because the produced water will be reinjected into the reservoir, a circulation system is established (see Supporting Information Figure 1). After this, tertiary oil recovery, also known as enhanced oil recovery (EOR), is then undertaken.2 Microbial EOR (MEOR) utilizes indigenous and/or exogenous microorganisms and/or their metabolites (such as biosurfactants, biopolymers, acids, and biogases) to mobilize and recover residual oil from reservoir pores, which demands an increased understanding of microbial activity in petroleum reservoirs to improve field applications.2,3 The taxonomical compositions of microbial communities in a number of reservoirs have been reported utilizing 16S rRNA gene amplifications and sequencing, including high-throughput sequencing.4−8 In addition, recent investigations using the whole metagenomics have provided knowledge of functional genes and species unique to the environments of reservoirs.9,10 Both lab experiments and field applications suggest that MEOR is a dynamic process with community variations and corresponding oil output enhancement.11,12 To achieve better performance, microbial proliferation and metabolism are required to be activated in situ in oil-rich areas, which requires that nutrients or cells are carried by floodwater and migrate a long distance (several hundreds of meters) before reaching the oil-rich area in the reservoir.13 Therefore, the reservoir application of MEOR should contain a large-scale spatial© 2017 American Chemical Society

temporal variation of in situ communities, an understanding of which is critical for optimizing the performance of the MEOR. However, field tests in previous literature mostly report isolated community results on some specific time points and seldom considered time course dynamics.4,8 Furthermore, unlike laboratory experiments, which can be designed with sufficient sampling points to demonstrate spatial distributions, the sampling locations of field investigations are limited in oil wells.13 Therefore, to investigate complex spatiotemporal information, the duration of community monitoring is required to be comparable to the period of field application, and multiple wells in the same group should be compared to help reveal possible spatial distributions. A MEOR pilot field study was carried out in the Shengli oil field, China, a high-temperature, highpermeability reservoir that has been heavily flooded with water. To reveal subsurface microbial activities and correlate oil output with microbial community composition in the reservoir under the MEOR, a 16S rRNA gene library method was used to monitor community dynamics in five wells over 20 months. This work aimed to (i) investigate community dynamics, especially of dominant species, using a 16S rRNA gene library over the period of MEOR; (ii) reveal correlations between oil output, biochemical characteristics, and microbial community dynamics; and (iii) discuss the possibility that microbial Received: June 16, 2017 Revised: August 28, 2017 Published: September 12, 2017 10588

DOI: 10.1021/acs.energyfuels.7b01713 Energy Fuels 2017, 31, 10588−10597

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Energy & Fuels community dynamics can be correlated with porous flow dynamics in a reservoir.

process during stage II. Because this MEOR project originally attempted to stimulate bacteria to produce biosurfactants, the bacterial community was investigated more frequently than Archaea. Interwell tracer tests were utilized to demonstrate a injection− production connection before MEOR.14 Two injection-wells (6-313 and 8-313), were subjected to tracers SCN− and NO3−, respectively. The results indicated that almost all the central wells were connected with both the injection wells, while each edge well was connected to just one injection well (Table S1). No tracer was detected in the control well. Notably, fluid temperature varies considerably along the oilproducing system cycle (Figure 1). As a result of the geothermal gradient (4.5 °C per 100 m depth), fluid temperature drops from 65 °C to a lower level (20−40 °C) during vertical upward flow in the well bore. Subsequently, fluid temperature declines to 10−25 °C along surface pipelines because of heat dissipation. After being reinjected, the fluid is gradually reheated to 65 °C again by the geothermal effect. Therefore, the temperature of surface facilities is suitable for mesophiles, while the reservoir could include both mesophiles and thermophiles. 2.2. Sample Collection. One injection (A) and four production wells, including central wells 6-13(B) and 6-413 (C), edge well 8 × 815 (D), and control well 3C15 (E) were selected (Table 3). Eight sampling times were used to assess microbial dynamics (Table 3). Of these, T1 is in the original status before MEOR, T2 to T7 are during MEOR, and T8 is one year after MEOR termination. Injection fluids were sampled from the main pipeline before being distributed to injection wells, and production fluids were taken directly from the well heads of the production wells. The first 200 L of fluid was discarded before sampling to reduce the influence of residual fluid in valves and pipes.15 Each sample was then fully filled and sealed in a five-liter sterilized barrel, which had been previously swept with nitrogen to prevent possible oxidation. After collection, samples were transported to the laboratory within 4 h and then preserved at 4 °C until DNA extraction and chemical analysis on the second day. 2.3. Measurements of Cell Number, Nutrients, and Metabolites. The cell number of samples was measured using a Helber bacteria counting chamber (Hawksley, Lancing, UK), rather than the optical density (OD) method, because emulsified micro-oil drops can significantly affect optical density. Dissolved oxygen (DO) was determined by JPB-607A portable dissolved oxygen meter (INESA Scientific Instrument, Shanghai, China) on site. pH was determined using a pH meter combined with an E-201-C pH electrode (INESA Scientific Instrument). The measurements of total phosphorus and total nitrogen follow a method published in the literature.16 Glucose was measured using biosensor SBA-40C (Shandong Biology Institution, Jinan, China), which uses an electrode to measure the electrical current intensity generated by the H2O2 from the enzymatic reaction of glucose.17 Organic acids, including acetate, were analyzed by an Agilent 4890 GC system (Agilent technology, Santa Clara, CA, USA) equipped with a flame ionization detector and capillary column. Nitrogen was used as the carrier gas. The temperatures of the injector and detector were 250 and 300 °C, respectively. The column temperature was 240 °C. 2.4. DNA Extraction. DNA extractions were conducted in batches after each field sampling period. The emulsion was broken by adding 1 /4 volume of saturated NaCl solution and heating at 70 °C for 30 min. Subsequently, because of the low cell number in the production well (104−106 cells mL−1), 500−1000 mL of the lower water phase was successively pumped through 8-μm and 0.22-μm filters (Millipore, Bedford, MD, USA) to collect cells. These cells were then suspended in water (1 mL) to accumulate the cell number to 106−108 cells mL−1 before extraction.18 Finally, the genomic DNA of these cells was extracted, purified, and stored as reported prior to 16S rRNA gene amplification.19 2.5. 16S rRNA Gene Clone Library and Statistical Analysis. The 16S rRNA genes were amplified using bacterial universal primers 27F (5′-AGAGTTTGATCATGGCTCAG-3′) and 1492R (5′TAGGGTTACCTTGTTACGACTT-3′), and Archaeal primers A3F

2. EXPERIMENTAL SECTION 2.1. Study Site. The petroleum reservoir under study is located in the delta of the Yellow River, northern China (Supplementary Figure 2). The porosity and permeability of this sandstone reservoir are 33% and 1.5−2.5 μm2, respectively, and oil strata are located at depths between 1173 and 1230 m, at 65 °C and 14.2 MPa. The viscosity of crude oil is about 35.2 mPa·s at 70 °C; the characteristics of fluids are presented in Table 1.

Table 1. Physicochemical Characteristics of Injected and Produced Water from the Oil Reservoir Investigated in This Study parameters

injected water

temp (°C) 10−25 pH 7.4−7.8 Chemical Characteristics (mg L−1) Cl− 4045 CO32− 33 HCO3− 854 Mg2+ 41 K+ + Na+ 2795 SO42− 16 Ca2+ 92

produced water 20−40 7.2−7.5 3697 1013−1113 41 2338 104

A production well group in the reservoir was selected to test the MEOR, which was designed to activate indigenous biosurfactantproducing microorganisms by injecting nutrients from injection wells. This group included two rows of injection wells and three rows of production wells arranged alternately (Supplementary Figure 3). The wells in the middle production row, between the two injection rows, were categorized as the central wells and included wells 6-13 and 6413. Other production wells were categorized as edge wells. Fluids produced from all single oil wells were pumped through the same water treatment facility and were then distributed to different injection wells to be reinjected. As a control, well 3C15, 1.2 km away from the test well group, was not subject to MEOR. This reservoir has been exploited since 1971 with three years of polymer-flooding (1994−1997).1 Before MEOR, accumulated oil recovery and water cut exceeded 53% and 97%, respectively. The MEOR process was carried out between January 2009 and March 2012, including stages I and II (each with a duration of 20 months). In order to test the performance of different injection strategies, nutrient solutions (Table 2) were injected continuously during stage I, while

Table 2. Nutrient Compositions of the Injected Slugs during Different MEOR Stages Stage I Stage II

glucose (g L−1)

peptone (g L−1)

NH4NO3 (g L−1)

.

4 40

0.4 4

0.4 4

0.2 2

during stage II, they were injected every 10 days with 10 times the original concentration. During stage I, the oil outputs were elevated to a higher level (the total block more than 10 tons per day) for nine months, while declining considerably in the last four months (Figure 1a), even though the injection process remained constant during this stage. These dynamics indicated that the in situ microorganisms in reservoir were possibly changing in terms of community and function. However, microbial community was not included in the monitoring plan of stage I; therefore, in the subsequent period (stage II) it is determined that the investigation on the subsurface microbial dynamics would be supplemented as one of the monitoring items, which enables us to study the dynamic of microbial oil-recovery 10589

DOI: 10.1021/acs.energyfuels.7b01713 Energy Fuels 2017, 31, 10588−10597

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Figure 1. Time courses of daily oil outputs and water cuts of the produced fluids in the total block (a), central wells 6-13 (b) and 6-413 (c), edge well 8 × 815 (d), and control well (e). Dashed lines indicate the starting and ending times of the MEOR stages, of which stage II is the investigated period of this study.

the well group under MEOR increased at an average of 5 × 103 kg per day for a few months after the initiation of stage II (Figure 1a). Subsequently, the output of central wells dropped (Figure 1b,c). Thus, stage II can roughly be divided into two parts, stage II-a (from September 2010 to June 2011) with higher output, and stage II-b (from July 2011 to March 2012) with lower output. Regarding single wells, the outputs of the central wells increased successively (Figure 1b,c), while the edge well declined (Figure 1d). Therefore, increased oil output during stage II-a came mostly from central wells. The cell numbers of produced fluids varied in the range 104− 105 cells mL−1, 102 lower than the injection samples (Figure 2a). However, the cell numbers in the central wells increased up to the range 106−107 cells mL−1 during the last three months of stage II. During the investigation period, DO varied between limited ranges (0.5−2.6 mg L−1) in injection fluids,

(5′-TTCCGGTTGATCCTGCCGGA-3′) and A927R (5′-CCCGCCAATTCCTTTAAGTTTC-3′), respectively.20,21 The polymerase chain reaction (PCR), product purification, clone library construction, and sequencing procedures used here were the same as previously reported, while the operational taxonomic unit (OTU) screening, taxonomic richness, and diversity analyses were carried out using Mothur v1.36.1 software.19,22 In addition, Yue− Clayton similarity between communities was measured, and all sequences were assigned taxonomic affiliations with an assignment cutoff of 0.03.23 The ribosomal database project classifier was used to assign taxonomic data to each representative sequence.24

3. RESULTS 3.1. Dynamics of Oil Output, Cell Numbers, Nutrients, and Metabolites. The oil output of the control well (3C15) maintained less than 200 kg per day without significant changes during the entire period (Figure 1e). Whereas, the oil output of 10590

DOI: 10.1021/acs.energyfuels.7b01713 Energy Fuels 2017, 31, 10588−10597

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Energy & Fuels

Table 3. Numbers of Sequenced Bacterial Clones in Each Sample, Alongside GenBank Accession Numbers and Alpha Diversity Calculated Based on 97% Similarity Clustering sampling date

no. of OTUs

Chao

2007.05(T1) 2010.10(T2) 2011.03(T3) 2011.06(T4) 2011.08(T5) 2011.11(T6) 2012.01(T7) 2013.03(T8)

A1 A2 A3 A4 A5 A6 A7 A8

48 37 21 26 23 8 5 2

131 146 61 69 74 16 11 2

2007.05(T1) 2010.10(T2) 2011.03(T3) 2011.06(T4) 2011.08(T5) 2011.11(T6) 2012.01(T7) 2013.03(T8)

B1 B2 B3 B4 B5 B6 B7 B8

10 17 18 12 17 7 4 10

31 26 25 48 35 8 5 15

2010.10(T2) 2011.03(T3) 2011.06(T4) 2011.08(T5) 2011.11(T6) 2012.01(T7) 2013.03(T8)

C2 C3 C4 C5 C6 C7 C8

21 17 5 13 18 9 8

42 35 5 24 57 17 29

2007.05(T1) 2010.10(T2) 2011.03(T3) 2011.06(T4) 2011.08(T5) 2012.01(T7)

D1 D2 D3 D4 D5 D7

10 12 18 17 17 9

11 15 48 26 39 14

2007.05(T1) 2011.03(T3) 2011.06(T4) 2011.08(T5) 2012.01(T7)

E1 E3 E4 E5 E7

18 12 5 21 21

25 57 6 56 44

Shannon Injection Well 3.43 3.41 2.56 3.04 2.71 0.73 0.37 0.10 Well 6-13 1.31 2.48 2.35 1.47 2.19 0.86 0.39 1.43 Well 6-413 2.30 2.30 1.36 2.04 2.33 1.07 0.66 Well 8X815 1.58 1.36 1.89 2.11 1.91 1.51 3C15 Control Well 2.33 1.47 0.84 2.53 2.53

while it remained zero in produced fluids. The pH of produced fluids also remained relatively constant (7.2−8.1). Glucose was not detected in production samples during the entire period (stage II), and total phosphorus (0.06−0.52 mg L−1) and total nitrogen (0−3.5 mg L−1) in produced fluids were kept at low levels. In contrast, considerable volumes of acetate emerged from the production wells at the beginning, but during the middle period of stage II, the acetate declined severely below the detection limit (Figure 2b). Later, as with the cell number dynamics in the last three months of stage II, the acetate in the central wells also increased. 3.2. Richness and Diversity of Microbes. In total, 34 bacterial and seven Archaeal clone libraries were constructed, and sequences with similarities greater than 97% were clustered into OTUs. Rarefaction curves (Figure S4) exhibited the coverage of bacterial and Archaeal libraries. Table 3 shows that before MEOR, injection samples (A1, A2) had higher bacterial richness (Chao, >130) and diversity (Shannon, >3.40) than production samples (Chao,