U.S. Department of the Interior

U.S. Geological Survey

Scientific Investigations Report 2020–5037

Compositional Analysis of Formation Water Geochemistry 

and Microbiology of Commercial and Carbon Dioxide-Rich 

Wells in the Southwestern United States

Compositional Analysis of Formation 

Water Geochemistry and Microbiology 

of Commercial and Carbon Dioxide-Rich 

Wells in the Southwestern United States

By Jenna L. Shelton, Robert S. Andrews, Denise M. Akob, Christina A. DeVera, 

Adam C. Mumford, Mark Engle, Michael R. Plampin, and Sean T. Brennan

Scientific Investigations Report 2020–5037

U.S. Department of the Interior

U.S. Geological Survey
U.S. Department of the Interior

DAVID BERNHARDT, Secretary

U.S. Geological Survey

James F. Reilly II, Director

U.S. Geological Survey, Reston, Virginia: 2020

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Although this information product, for the most part, is in the public domain, it also may contain copyrighted materials 

as noted in the text. Permission to reproduce copyrighted items must be secured from the copyright owner.

Suggested citation:

Shelton, J.L., Andrews, R.S., Akob, D.M., DeVera, C.A., Mumford, A.C., Engle, M., Plampin, M.R., and Brennan, 

S.T., 2020, Compositional analysis of formation water geochemistry and microbiology of commercial and carbon 

dioxide-rich wells in the southwestern United States: U.S. Geological Survey Scientific Investigations Report 

2020–5037, 26 p., https://doi.org/10.3133/sir20205037.

ISSN 2328-0328 (online)
iii

Acknowledgments

We thank Whiting Petroleum Corporation, Kerry Sharer (land owner), and Ray Hartley (land 

lessee) for allowing access to wells. We thank Yesha Shrestha and Jeanne Jaeschke of the 

U.S. Geological Survey (USGS) for helpful discussions and laboratory assistance. We thank 

Christina Kellogg, Nancy Stamm, Bill Orem, Madalyn Blondes, Tina Roberts-Ashby, and 

Rachel Gidley for thorough and helpful reviews that greatly increased the quality of this work.

v

Contents

Acknowledgments........................................................................................................................................iii

Abstract...........................................................................................................................................................1

Introduction.....................................................................................................................................................1

Background and Study Sites .......................................................................................................................2

Bravo Dome ...........................................................................................................................................2

Oakdale Field .........................................................................................................................................2

Rafter “K” Ranch...................................................................................................................................4

Methods...........................................................................................................................................................4

Field Sampling .......................................................................................................................................4

Analytical Methods for Geochemical and Isotopic Analysis ........................................................5

Characterization of Microbial Community Composition .................................................................6

Cultivation of Microbial Functional Groups ......................................................................................7

Compositional Data Analysis ..............................................................................................................8

Produced Fluid Geochemistry......................................................................................................................9

Microbial Community Composition and Diversity ..................................................................................14

Growth and Activity of Microbial Functional Groups in the Rafter “K” Ranch and Oakdale 

Field Samples ..................................................................................................................................18

Conclusions...................................................................................................................................................19

References Cited..........................................................................................................................................19

Figures

1. Map showing sample sites and locations of legacy data .....................................................3

2. Compositional biplot that represents a principle component (PC) analysis of 

centered log ratio (clr)-transformed water-chemistry data for produced water 

samples and legacy data ...........................................................................................................10

3. Isometric log-ratio ion plot showing the major ion composition of produced 

water samples and legacy data ...............................................................................................11

4. Graph showing water isotope data for produced water samples and legacy 

data relative to the global meteoric water line and a local meteoric water line .............12

5. A, Graph showing strontium concentrations and isotope ratios (strontium-87/

strontium-86) for the four produced water samples and legacy water data.

B, Graph showing Sr isotope ratios for the legacy rock data .............................................13

6. Nonmetric multidimensional scaling plots based on UniFrac distance matrices, 

with point locations represented by pie charts showing microbiology of the 

water samples at the class level ..............................................................................................17

Tables

1. Summary of study sites and samples collected ......................................................................5

2. Field-measured water-quality parameters, concentrations of ions and trace 

elements, and isotopic composition of produced fluids ........................................................6

3. Results of 16S ribosomal ribonucleic acid (rRNA) gene amplicon sequencing ..............15
vi

4. Growth and activity for microbial functional groups enriched from the Rafter 

“K” Ranch and Oakdale Field water samples under 20 or 100 percent carbon 

dioxide (CO2) headspace ...........................................................................................................18

Conversion Factors

International System of Units to U.S. customary units

Multiply By To obtain

Length

nanometer (nm) 3.937 × 10−8 inch (in.)

micrometer (μm) 3.937 × 10−5 inch (in.)

centimeter (cm) 0.3937 inch (in.)

meter (m) 3.281 foot (ft)

kilometer (km) 0.6214 mile (mi)

meter (m) 1.094 yard (yd)

Volume

microliter (μL) 0.3382 × 10−4 ounce, fluid (fl. oz)

milliliter (mL) 0.03382 ounce, fluid (fl. oz)

liter (L) 33.81402 ounce, fluid (fl. oz)

liter (L) 2.113 pint (pt)

liter (L) 1.057 quart (qt)

liter (L) 0.2642 gallon (gal)

liter (L) 61.02 cubic inch (in3)

Flow rate

liter per second (L/s) 15.85 gallon per minute (gal/min)

Mass

gram (g) 0.03527 ounce, avoirdupois (oz)

kilogram (kg) 2.205 pound avoirdupois (lb)

Temperature in degrees Celsius (°C) may be converted to degrees Fahrenheit (°F) as 

°C = (°F – 32) / 1.8.

Supplemental Information

Concentrations of chemical constituents in water are given in either milligrams per liter (mg/L) 

or micrograms per liter (μg/L).

Results for measurements of stable isotopes of hydrogen, carbon and oxygen are given in per 

mil (‰) using delta (δ) notation, as described in the equation:

δ18O = (

(

 

_18O _16O)sample

(

 

_18O 16O)standard

− 1) × 1000‰
vii

Abbreviations ‰ per mil

CaCO

3 calcium carbonate

CH

4 methane

clr centered log-ratio

CO

2 carbon dioxide

CO

3

2− carbonate

CoDA compositional data analysis

DIC dissolved inorganic carbon

DNA deoxyribonucleic acid

EOR enhanced oil recovery

FeRB iron-reducing bacteria

GC gas chromatograph

GMWL global meteoric water line H2S hydrogen sulfide

HCl hydrochloric acid

HCO

3

− bicarbonate

HDPE high-density polyethylene

ilr isometric log-ratio

kg/mg kilogram per milligram

mM millimolar N2 nitrogen gas

NaCl sodium chloride

NO

2

− nitrite

NO

3

− nitrate

NMDS nonmetric multidimensional scaling

NRB nitrate-reducing bacteria

OTU operational taxonomic unit

PC principal component

PCR polymerase chain reaction

PO

4

3− phosphate

rRNA ribosomal ribonucleic acid

SO

4

2− sulfate

SRB sulfate-reducing bacteria

TDS total dissolved solids

USGS U.S. Geological Survey
viii
Compositional Analysis of Formation Water Geochemistry 

and Microbiology of Commercial and Carbon Dioxide-Rich 

Wells in the Southwestern United States

By Jenna L. Shelton, Robert S. Andrews, Denise M. Akob, Christina A. DeVera, Adam C. Mumford, 

Mark Engle, Michael R. Plampin, and Sean T. Brennan

Abstract

Studies of naturally occurring subsurface carbon dioxide (CO2) accumulations can provide useful information for 

potential CO2 injection projects; however, the microbial communities and formation water geochemistry of most reservoirs 

are understudied. Formation water and microbial biomass 

were sampled at four CO2-rich reservoir sites: two within 

Bravo Dome, a commercial CO2 field in New Mexico; one 

northwest of Bravo Dome in Colorado (Oakdale Field); and 

one southwest of Bravo Dome in New Mexico (Rafter “K” 

Ranch). Aside from the Rafter “K” Ranch site, minor differences were observed in the geochemistry of formation water 

collected from these sites compared to historical data. No 

organisms were significantly associated with Oakdale Field 

compared to the other three sites, nor were any hydrogeochemical or gas geochemical parameters (for example, CO2

concentration) found to have significant associations with the 

microbial ecology of these four sites. Microorganisms from 

these sites were metabolically diverse and had the potential to 

(1) generate methane, (2) produce corrosive hydrogen sulfide 

(H2S), and (3) rapidly biofoul and (or) clog pore spaces by 

shifting microbial communities with changes in salinity or 

nutrient supply. This study demonstrates that high concentrations of CO2 in subsurface reservoirs apparently have not 

imparted a distinct geochemical or microbiological signature 

on the associated formation waters and that the microorganisms in these reservoirs are metabolically diverse and could 

adapt to geochemical changes in the subsurface.

Introduction

Geologic carbon sequestration, where carbon dioxide 

(CO2) is injected into subsurface formations and retained in 

porous strata beneath a seal unit, is one method proposed to 

mitigate rising atmospheric CO2 concentrations and associated climate change. The first commercial geologic CO2

sequestration project was initiated in 1996 when the Sleipner 

CO2 Storage Facility offshore Norway was brought online. 

Currently, there are no long-term (more than 100 years) CO2

sequestration studies, but analogues such as naturally occurring CO2-rich reservoirs can be studied to examine the biogeochemical processes that may occur during long-term CO2

storage (for example, Ballentine and others, 2001; Haszeldine 

and others, 2005; Gilfillan and others, 2009; Sathaye and others, 2014). Many naturally occurring CO2-rich reservoirs exist 

across the United States (for example, Allis and others, 2001; 

Stevens and others, 2001; Stevens, 2005) and have been studied to determine the sources of the emplaced CO2 (by using 

stable and noble gas isotopes) and CO2 storage mechanisms 

(for example, Gilfillan and others, 2008; Crossey and others, 

2009; Zhou and others, 2012; Craddock and others, 2017). To 

date, only one study has reported on microbial communities 

from commercial CO2 reservoirs (Freedman and others, 2017).

The current study is part of a larger study by the U.S. 

Geological Survey (USGS) to examine natural CO2 accumulations across the United States in order to gain insight on topics 

such as sources of naturally occurring CO2, the effects of high 

CO2 concentrations on the geochemistry and microbiology 

of reservoirs, possible subsurface migration pathways for the 

CO2 accumulations, and timing of CO2 entrainment within 

traps (for related studies by USGS scientists, see Shelton 

and others, 2016; Brennan, 2017; and Craddock and others, 

2017). Studying CO2-rich reservoirs is beneficial because 

they are currently used as sources of CO2 for enhanced oil 

recovery (EOR) and could eventually serve as reservoirs 

for geologic CO2 sequestration, as they have proven to be 

capable of trapping large volumes of CO2 for millions of 

years. Understanding the microbial communities of CO2-rich 

reservoirs is crucial because these microbial populations may 

affect the fate and transport of injected CO2 and geologic CO2

storage mechanisms (for example, Peet and others, 2015). 

Therefore, understanding how microbial populations and their 

potential metabolic functions in deep, CO2-rich subsurface 

systems adapt to high CO2 concentrations over long time 

scales (for example, thousands of years) may help to predict 

microbial population changes and their effects on potential 

geologic CO2 sequestration projects.
2 Analysis of Formation Water Geochemistry and Microbiology of Commercial and Carbon Dioxide-Rich Wells

The purpose of this study is to delineate the formation 

water geochemistry and microbial community structures of 

formations with high CO2 concentrations to predict possible 

geochemical and microbiological changes that could occur in 

various reservoir settings after long-term CO2 sequestration. It 

is important to note that no studies to date have analyzed the 

chemical composition of co-produced water from any commercial CO2 site, and only one study (Freedman and others, 

2017) has analyzed the microbial community composition of 

co-produced water from a commercial CO2 site. Therefore, 

the current study provides a rare opportunity to observe these 

systems, where there is currently a dearth of data, and to 

understand how such systems may behave geochemically. We 

seek to determine whether a particular “microbial signature” 

is associated with naturally occurring CO2 reservoirs and 

to characterize the potential activity of microorganisms in 

CO2-rich sites. Furthermore, we examine potential changes in 

microbial community structure and function that may occur 

in shallow aquifers in the event of CO2 leakage from deep 

sequestration sites.

We collected formation water, microbial biomass, and 

co-produced gas from four CO2-rich reservoirs across southeastern Colorado and northeastern New Mexico: two sites 

in the greater Bravo Dome CO2 unit region; one in Oakdale 

Field, northwest of Bravo Dome; and one effervescent shallow groundwater well at Rafter “K” Ranch, southwest of 

Bravo Dome. For more information on these sites, readers are 

referred to Brennan (2017). To our knowledge, these are the 

first formation water and microbial samples collected from the 

Bravo Dome unit. Although we collected a small number of 

samples, studying these sites, where large volumes of relatively pure CO2 are produced from the subsurface, and similar 

CO2 accumulations across the United States can provide more 

insight into how high CO2 concentrations could affect microbial communities and formation water geochemistry (and thus, 

possibly affect geologic CO2 sequestration) in large-scale, 

permanent CO2 injection sites.

Background and Study Sites

Bravo Dome

Two water samples were collected from producing wells 

associated with the West Bravo Dome CO2 exploration unit, 

a large commercial CO2 field in northeastern New Mexico 

(fig. 1). The gas produced from Bravo Dome was historically 

used to produce dry ice (Johnson, 1983) and now is primarily 

piped to the Permian Basin and used for CO2-EOR operations. 

Most of the CO2 produced from Bravo Dome is sourced from 

Permian strata, specifically the Abo Formation and the Tubb 

sandstone (basal unit of the Yeso Formation); small volumes of CO2 are also produced from the Triassic Santa Rosa 

Formation (after Broadhead, 1990). The Abo-Tubb strata are 

eolian and fluvial sandstones containing discrete intervals of 

dolomitic paleosols with high concentrations of manganese, 

low strontium and sodium concentrations, and variable iron 

content (Hartig and others, 2011). The Triassic Santa Rosa 

Formation was subdivided into three members by Lucas and 

Hunt (1987): the Tecolotito Member, the Los Esteros Member, 

and the Tres Lagunas Member. The Tres Lagunas Member is 

the uppermost and most described member of the Santa Rosa 

and is a predominantly orange and yellowish-brown, mediumgrained quartzarenite sandstone. Stratigraphically below 

the Tres Lagunas is the Los Esteros Member, a yellow and 

reddish-brown mudstone with intervals of very fine- to finegrained quartzarenite sandstone. The Tecolotito Member has a 

basal limestone-cobble conglomerate, and the overlying rocks 

are grayish-orange to pale-orange, laminated and crossbedded, 

medium-grained quartzarenite.

Bravo Dome has been studied because of the large 

volume of CO2 emplaced in the subsurface there; studies have 

included analyzing the long-term effects of CO2 sequestration in saline aquifers (Gilfillan and others, 2009; Hartig 

and others, 2011), estimating the timing of CO2 emplacement in the dome (Gilfillan and others, 2008; Broadhead 

and others, 2009), delineating the current CO2 flux into the 

reservoir (Baines and Worden, 2004; Sathaye and others, 

2014; Brennan, 2017), and analyzing the system’s suitability as a target and (or) analogue reservoir for geologic CO2

sequestration (Rochelle and others, 1999; Allis and others, 

2001; Stevens and others, 2001; Gilfillan and others, 2009). 

Despite the numerous studies of Bravo Dome, no data on 

either co-produced waters or subsurface microbiology have 

been published. Previous research suggested that the main 

CO2-producing reservoir of Bravo Dome, the Permian Tubb 

sandstone, is hydrologically sealed and that producing regions 

of the reservoir are compartmentalized and therefore hydrologically disconnected from adjacent reservoirs (Akhbari and 

Hesse, 2017). If the Tubb sandstone is compartmentalized 

in northeastern New Mexico, the formation water geochemistry of Bravo Dome may deviate from regional trends. 

Furthermore, producing wells across Bravo Dome may be 

geochemically different if they produce from different compartmentalized regions.

Oakdale Field

Oakdale Field is a gas-producing field within the Raton 

Basin in Huerfano County, Colorado, northwest of Bravo 

Dome. The main reservoirs of Oakdale Field are the Jurassic 

Entrada Sandstone and the Cretaceous Dakota Sandstone that, 

in addition to natural gas, produce large volumes of CO2. 

The Entrada Sandstone is a fine- to coarse-grained, parallelbedded, white to pink and red, well-sorted sandstone with 

mostly rounded and frosted quartz grains (Baltz, 1965). Chert 

and feldspar grains are also present in the sandstone, and the 

sandstone’s cement is typically calcareous and, in some places, 

gypsiferous (Baltz, 1965). The Dakota Sandstone in this area 

is gray to buff colored and interbedded with gray shale. Lenses 
Background and Study Sites 3

UNION COLFAX

QUAY

TAOS

SAN MIGUEL

LAS ANIMAS

MORA

TORRANCE

RIO ARRIBA

GUADALUPE

HARDING

PUEBLO

CURRY

BENT

SAGUACHE

OTERO

SANTA FE

HUERFANO

COSTILLA

CONEJOS

SANDOVAL

DE BACA

CUSTER

RIO GRANDE ALAMOSA

BERNALILLO

LOS ALAMOS

106° 105° 104° 103°

38°

37°

36°

35°

COLORADO

NEW

MEXICO

MEXICO

ARIZONA CALIFORNIA

NEVADA UTAH

TEXAS

OKLAHOMA

KANSAS

WYOMING NEBRASKA

COLORADO

NEW MEXICO

San Luis

Basin

Raton

Basin

Las Vegas

Basin

Tucumcari

Basin

Estancia

Basin

Albuquerque

Basin

Baca

Basin

Espanola

Basin

Study

area

McElmo

Dome

NEW MEXICO

TEXAS

Permian

Basin

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Base-map image is the intellectual property of Esri and

is used herein under license. Copyright 2018 Esri and

its licensors. All rights reserved.

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EXPLANATION

Approximate extent of Bravo Dome Field,

including the Western Exploration Unit

Structural basin boundary

U.S. Geological Survey station 08382650

Oakdale Field

Candelario (Bravo Dome)

Lewis (Bravo Dome)

Rafter "K" Ranch

Legacy water data

Legacy strontium rock data

Capulin volcano

0 20 40 60 80 100 KILOMETERS

0 10 20 30 40 50 MILES

Raton

volcanic

field

Figure 1. Map showing sample sites and locations of legacy data (U.S. Environmental Protection Agency, 

2016; Blondes and others, 2018; EarthChem, 2018; Petroleum Recovery Research Center, 2018; U.S. Geological 

Survey, 2018).
4 Analysis of Formation Water Geochemistry and Microbiology of Commercial and Carbon Dioxide-Rich Wells

of conglomerate, as well as areas of pure sandstone, are common in the western part of the Raton Basin (Baltz, 1965). The 

Dakota Sandstone is loosely cemented and well sorted in some 

areas, and in other areas it is fine grained to finely conglomeratic (Baltz, 1965) and has a lenticular, nonmarine shale at its 

base (Owen, 1966). These two sandstones also produce large 

volumes of CO2 from other areas of southeastern Colorado, 

such as Sheep Mountain and Dike Mountain Fields (Roth, 

1983; Worrall, 2004). The third producing (gas only as of 

2004) reservoir is a felsite dike, emplaced as a magmatic fluid, 

with primary and fracture porosity. The felsitic section has historically produced mostly methane (CH4) with complementary 

volumes of CO2 (15–20 percent; Worrall, 2004).

These sandstone producing formations typically have 

double the average porosity of rocks in the Raton Basin 

(Worrall, 2004). This high porosity is likely due to a lack of 

silicification caused by lack of recharge; silicification has been 

identified in other areas of the basin and attributed to active 

recharge (Worrall, 2004). Historically, wells in Oakdale Field 

have produced gas with a CO2 content ranging from 24 to 

97 percent on average, with the remainder of the gas typically 

dominated by hydrocarbons (for example, ethane; Worrall, 

2004). In 2016, nine wells were producing from Oakdale 

Field, specifically from the Entrada and Dakota Sandstones 

and the Cretaceous Pierre Shale (Colorado Oil and Gas 

Conservation Commission, 2018).

Rafter “K” Ranch

The Rafter “K” Ranch is in San Miguel County, New 

Mexico, approximately 15 kilometers southwest of the 

greater West Bravo Dome CO2 exploration unit (Brennan, 

2017). The samples collected for this study originated from a 

shallow (47.25 meters [m] deep), nonpumping groundwater 

well, which began effervescing CO2 upon completion of the 

well (Ray Hartley, oral commun., 2015). The well is drilled 

into exposed Triassic strata, similar to that of the West Bravo 

Dome CO2 exploration unit; Brennan (2017) hypothesized that 

the well is, like Bravo Dome, producing from the Santa Rosa 

Formation. The well was sampled to determine if the produced 

CO2 had a source similar to that of the CO2 produced from 

Bravo Dome (Brennan, 2017) and to assess the long-term 

microbial and geochemical effects of a CO2 leak into a shallow aquifer.

Methods

Field Sampling

During sampling campaigns in June 2015 and 

August 2016 (table 1, fig. 1), we collected formation waters 

at the four sites for chemical and microbiological analyses. 

Co-produced gases were also collected, and methods for this 

work can be found in Brennan (2017). Samples came from 

the Candelario well and the Lewis well in Bravo Dome, the 

Oakdale Field water storage tank, and the Rafter “K” Ranch 

water well (fig. 1). Although low volumes of water were 

produced, water was collected directly from the Candelario 

and Lewis wellheads into sterile 2-liter (L) glass bottles. 

The Oakdale Field water was collected from a water storage 

tank that was open to the atmosphere and contained a mixture of produced water from all nine wells within the field. 

Water was obtained from the Rafter “K” Ranch groundwater 

well by using a Geocontrol PRO bladder pump (Geotech 

Environmental Equipment, Inc., Denver, Colorado) after 

purging at a rate of 6.3 liters per hour for 2 hours. Solid 

material from these producing formations could not be 

obtained to analyze biofilms or organisms present on the 

surfaces. Sterile plastic Nalgene tubing was inserted into each 

bottle, once filled with sample water, and was attached to a 

0.22-micrometer (μm) Sterivex GP filter unit using a peristaltic pump. Water was pumped through the filter until the filter 

clogged, and the filter was immediately stored on dry ice. The 

remaining water was filtered according to the geochemical 

analysis protocol listed below and collected into high-density 

polyethylene (HDPE) or glass sample bottles (major and 

minor geochemistry and isotopes), preserved according to the 

analysis protocol, and stored immediately on ice. Unfiltered 

water was also collected in anoxic (nitrogen gas [N2] headspace) 120-milliliter (mL) glass serum bottles for microbial 

cultivation. Each serum bottle was filled with approximately 

60 mL of produced water.

All samples collected for trace element and cation 

analysis were filtered at 0.45 μm and acidified to a pH below 

2 using Optima-grade nitric acid; samples collected for the 

analysis of anions, alkalinity, and total dissolved solids (TDS) 

were simply filtered using a 0.45-μm filter unit. Water for 

stable hydrogen and oxygen isotopes of water (δ2H and δ18O) 

and strontium isotope (strontium-87/strontium-86 [87Sr/86Sr]) 

analysis was filtered at 0.45 μm with a Geotech Environmental 

Equipment, Inc. capsule filter. All water sample bottles were 

filled (leaving no headspace), stored on ice, and shipped to the 

USGS in Reston, Virginia, where they were stored at 4 degrees 

Celsius (°C) until analysis. All Sterivex GP filter units for 

microbial community analysis were shipped on dry ice to the 

USGS where they were held at −80 °C until shipment to Jonah 

Ventures (Boulder, Colorado) for sample analysis. A field 

blank was collected for each analysis (for example, cations) 

as a quality-control check. The blanks for water samples were 

18-megaohm water collected following filtering and preservation methods for a given sample type (for example, cations). 

The blanks for the Sterivex filters were prepared by passing 

2 L of 18.2-megaohm-centimeter water through a Sterivex GP 

filter unit.
Methods 5

Analytical Methods for Geochemical and 

Isotopic Analysis

Produced water temperature (not indicative of downhole 

temperature), conductivity, and pH were measured in the 

field immediately after water collection by using a Thermo 

Scientific Orion Star A325 portable pH/conductivity/temperature multiparameter meter kit with an Orion ROSS Triode 

pH/automatic temperature compensation (ATC) gel-filled 

electrode and an Orion DuraProbe conductivity cell. Stable 

isotopes of water—δ2H-H2O and δ18O-H2O—were measured 

to a precision of ±2.0 per mil (‰) and ±0.3 ‰, respectively, 

by Isotech Laboratories, Inc. in Champaign, Illinois. The δ13C 

of dissolved inorganic carbon (DIC) in water was measured 

to a precision of ±0.2 ‰ by Isotech Laboratories, Inc. in 

Champaign, Illinois. Anions and trace metals were measured by Activation Laboratories Ltd. in Ancaster, Ontario, 

Canada. Anions were measured by using a Dionex DX-120 

ion chromatograph system, and trace metals were analyzed 

by inductively coupled plasma-optical emission spectroscopy 

(ICP-OES) on an Agilent Axial 730-ES (emission spectrometer), with detection limits varying for the measured elements (table 2). Field blanks for both anions and trace metals 

contained negligible amounts of the measured elements (that 

is, below laboratory detection limits). Charge balance errors 

ranged from −14.2 to 15.4 percent and did not include a direct 

measurement of DIC (only alkalinity) or the dissolved organic 

composition constituents, as they were not measured.

Strontium isotopes were measured on a Nu Plasma 

multiple-collector inductively coupled plasma mass spectrometer at the Center for Earth and Environmental Isotope 

Research at the University of Texas at El Paso after column 

separation in a class-100 clean room. Samples were purified 

by using Eichrom Technologies Inc. strontium resin, dried 

down, and brought up in 2 percent nitric acid. Strontium 

isotope ratios were corrected on-line for any interferences with 

krypton (Konter and Storm, 2014). Accuracy was acceptable, as shown through the average result of 0.70918 for the 

secondary standard USGS EN-1 versus the accepted value of 

0.709174. External error (2s) was 0.000023 on the basis of 

variation in the USGS EN-1 standard (n=5) over the 2 days of 

analysis. Field blanks contained negligible amounts of strontium (less than 100 millivolts).

To increase the robustness of the dataset and to compare the samples from this study to other data from the 

region, produced water data from similar strata in Colorado 

and New Mexico were obtained from a variety of external 

databases and literature. Data were selected if they were 

from the same county as any of the four samples collected 

in this study (Huerfano County, Colorado; Harding County, 

New Mexico; and San Miguel County, New Mexico), the 

Las Vegas Basin, or the Raton Basin, or were within these 

general regions and contained relevant data (for example, 

87Sr/86Sr values). External data sources included the USGS 

National Produced Waters Geochemical Database version 2.3 

(https://doi.org/10.5066/F7J964W8; Blondes and others, 2018), the USGS National Water Information System 

(https://nwis.waterdata.usgs.gov/nwis; U.S. Geological 

Survey, 2018), a U.S. Environmental Protection Agency 

study on hydraulic fracturing (U.S. Environmental Protection 

Agency, 2016), and the New Mexico Produced Water Quality 

Database version 2 (http://gotech.nmt.edu/gotech/Water/

producedwater.aspx; Petroleum Recovery Research Center, 

Table 1. Summary of study sites and samples collected.

[API, American Petroleum Institute; NA, not applicable]

Site Sample date API number Geologic 

formation State (county) Coordinates

Lower 

depth, in 

meters

Sample type

Lewis (Bravo 

Dome)

6/15/2015 30-012-20587 Santa Rosa 

Formation and 

Tubb sandstone

New Mexico 

(Harding)

35.904125, 

−103.93255

1,067 Water chemistry 

and microbial 

sequencing

Candelario 

(Bravo 

Dome)

5/15/2015 30-021-20659 Santa Rosa 

Formation and 

Tubb sandstone

New Mexico 

(Harding)

35.88815, 

−103.950342

1,158 Water chemistry 

and microbial 

sequencing

Oakdale 

Field

8/15/2016 NA Pierre Shale, 

Dakota 

Sandstone, 

and Entrada 

Sandstone

Colorado 

(Huerfano)

37.539059, 

−105.104617

1,720* Water chemistry, microbial 

sequencing, and 

cultivation

Rafter “K” 

Ranch

6/10/2015; 

8/18/2016

NA Triassic strata 

and Santa Rosa 

Formation

New Mexico 

(San 

Miguel)

35.705738, 

−104.238507

47 Water chemistry, microbial 

sequencing, and 

cultivation

*Average depth of producing wells from Oakdale Field.
6 Analysis of Formation Water Geochemistry and Microbiology of Commercial and Carbon Dioxide-Rich Wells

2018). These data are hereafter referred to as the “legacy water 

samples,” and they include water from multiple surface-water 

sites, monitoring wells, domestic water wells, and production 

wells, as well as time-series data from many of these sites. 

Furthermore, additional outside data concerning hard-rock 

strontium concentrations and isotopic values (87Sr/86Sr) were 

compiled for the study region from the EarthChem Portal 

(http://www.earthchem.org/portal; EarthChem, 2018).

Characterization of Microbial Community 

Composition

Deoxyribonucleic acid (DNA) extractions, amplifications, and Illumina MiSeq 16S ribosomal ribonucleic acid 

(rRNA) gene sequencing were completed by Jonah Ventures 

in Boulder, Colorado. Following Jonah Ventures protocol, 

DNA was extracted by opening the Sterivex GP filter units 

Table 2. Field-measured water-quality parameters, concentrations of ions and trace elements, and isotopic composition of 

produced fluids.

[Total dissolved solids (TDS) includes the sum of trace ions that were measured but not presented in this table. Dissolved inorganic carbon (DIC) and dissolved 

organic carbon were not measured and could not be included in the TDS sum. The laboratory detection limits for the analytes were as follows: sodium (Na+), 

5 micrograms per liter (μg/L); potassium (K+), 30 μg/L; calcium (Ca2+), 700 μg/L; magnesium (Mg2+), 2 μg/L; strontium (Sr), 0.04 μg/L; silicon (Si), 200 μg/L; 

iron (Fe), 10 μg/L; chloride (Cl−), 30 μg/L; bromine (Br−), 30 μg/L; nitrate (NO3

−) as nitrogen (N), 10 μg/L; nitrite (NO2−) as N, 10 μg/L; phosphate (PO43−) 

as phosphorus (P), 20 μg/L; and sulfate (SO4

2−), 30 μg/L. °C , degree Celsius; NA, not measured or not available; mg/L, milligram per liter; CaCO3, calcium 

carbonate; <, a precise concentration could not be generated because the sample was diluted and close to the laboratory detection limit; 87Sr/86Sr, strontium-87/

strontium-86; ‰, per mil; CO2, carbon dioxide; %, percent; CH4, methane; Ar, argon; ND, not detected; He, helium; C2+, hydrocarbons measured in the gas with 

greater than or equal to two carbon atoms]

Parameter Units

Sample

Candelario 

(Bravo Dome)

Lewis 

(Bravo Dome) Oakdale Field* Rafter “K” Ranch

Temperature °C NA NA 25.3 32.5

pH Unitless 7.2 6.6 6.5 6.4

Alkalinity mg/L as CaCO3 5,446 1,575 15,737 10,825

Na+ mg/L 11,300 8,880 19,000 63

K+ mg/L 127 62 123 25

Ca2+ mg/L 2,200 3,560 358 573

Mg2+ mg/L 2,650 540 102 127

Sr mg/L 41.2 59.6 37.5 50.6

Si mg/L 35.2 65.6 33.3 7.1

Fe mg/L 100 112 35 5

Cl− mg/L 15,200 15,900 16,000 19

Br− mg/L 46.2 46.5 91.4 <0.3

NO2

− (as N) mg/L <2.0 <2.0 <2.0 <0.1

NO3

− (as N) mg/L 3.2 2.1 <2.0 <0.1

PO4

3− (as P) mg/L <3.0 <3.0 <3.0 <0.2

SO4

2− mg/L 3,340 1,750 577 573

TDS mg/L 31,013 31,013 36,426 1,400

87Sr/86Sr Unitless 0.72421 0.72899 0.70855 0.70856

δ18O-H2O ‰ −9.04 −9.22 0.03 −7.01

δ2H-H2O ‰ −62.5 −62.4 −17.5 −47.7

δ13C-DIC ‰ 3.4 1.7 2.3 0.3

CO2 % 99.5 99.8 76.2 99.5

CH4 % 0.002 0.001 18.758 0.001

Ar % 0.008 ND 0.024 0.007

He % 0.027 0.020 0.047 0.008

C2+ % ND ND 3.76 ND

*Value is the average mole percent of gas components (standard deviation = 28.0) in wells that produce from Oakdale Field (n=7).
Methods 7

and vigorously swabbing the entire surface of the filter with 

a clean sterile swab. This method was performed to reduce 

contamination induced by slicing the filter and to obtain the 

entire community present on the filter, as using slices of filter 

might not capture communities present on unused portions (for 

examples of this method, see Grice and others, 2008; Ramirez 

and others, 2014; Barberán and others, 2015; Leff and others, 2015; Luongo and others, 2016). The swab was then used 

for extraction in the MO BIO Laboratories, Inc. (Carlsbad, 

California) PowerSoil-htp 96-Well DNA isolation kit following the manufacturer’s given protocol. For quality-control 

purposes, eight extraction blanks and two swab blanks were 

included in the dataset.

Following extraction, the V4 region of the 16S rRNA 

gene was amplified by using the 515F (5’ – GTGYCAGCMGCCGCGGTAA – 3’) and 806R (5’ – GGACTACNVGGGTWTCTAAT – 3’) primer pair (Apprill and others, 

2015; Walters and others, 2015; Parada and others, 2016). 

Both primers included 5’ Illumina adaptor sequences to 

allow for indexing and sequencing. Polymerase chain reaction (PCR) was performed by using the Promega PCR 

Master Mix (Promega Corp. catalog no. M5133; Madison, 

Wisconsin) according to the manufacturer’s protocol, using 

the primers (both 0.2 micromolar [μM]) and 1 microliter (μL) 

of sample DNA. The following conditions were used for 

the first PCR amplification: initial denaturation at 95 °C for 

5 minutes (min), followed by 35 cycles for 45 seconds (s) of 

denaturation at 95 °C, annealing for 60 s at 50 °C, extension 

for 90 s at 72 °C, and a final elongation at 72 °C for 10 min. 

Unincorporated single-stranded DNA and DNA polymerase 

were removed from PCR products by incubating the amplicons with Exo1/SAP (Shrimp Alkaline Phosphatase) for 

30 min at 37 °C, followed by an inactivation step at 95 °C for 

5 min. A second round of PCR was performed to incorporate 

a unique 12-nucleotide index sequence into each sample. The 

indexing PCR included the primers (0.5 μM each), Promega 

PCR Master Mix, and 2 μL of template DNA (that is, the 

cleaned amplicon from the first PCR reaction). Initial denaturation was at 95 °C for 3 min, followed by eight cycles 

for 30 s at 95 °C, annealing at 55 °C for 30 s, and extension 

at 72 °C for 30 s. After both PCR reactions, 5 μL of PCR 

products from each sample was normalized and cleaned using 

SequalPrep Normalization Plates (Life Technologies Corp., 

Carlsbad, California). The samples were then pooled together 

for sequencing on an Illumina MiSeq (Illumina, Inc., San 

Diego, California) at the University of Colorado Boulder 

BioFrontiers Sequencing Facility, running 1 x 150 base pair 

chemistry and using the v2 300-cycle kit (Illumina Inc. catalog 

no. MA-102-2002).

QIIME 2 version 2017.11 (Caporaso and others, 2010; 

www.qiime2.org) was used for downstream processing. 

The data were processed following the protocol outlined 

in the “Moving Pictures” tutorial (QIIME 2 Development 

Team, 2017; https://docs.qiime2.org/2017.11/tutorials), with 

some modifications. Sequences were trimmed and truncated 

where the quality score dropped below 30 by using the 

DADA2 plugin of QIIME 2 (--p-trim-left 14; --p-trunc-len 

150). Phylogenetic classification was performed by using 

a Naive Bayes classifier trained on the SILVA 119 database within QIIME 2 (QIIME 2 Development Team, 2018; 

https://docs.qiime2/org/2018.4/data-resources/) (Pruesse and 

others, 2007; Quast and others, 2013), and the following 

parameters were modified: --p-pre-dispatch 1, --p-chunksize 1000.

The final data were read into R version 3.3.3 (R Core 

Team, 2017) for all additional downstream processing steps 

and statistical analyses. Sequences matching chloroplast 

phylotypes were removed. The operational taxonomic units 

(OTUs) identified at greater than 1-percent abundance in 

the blanks (28 OTUs) were removed from the sample set 

to reduce contamination (for example, Salter and others, 

2014), and the samples were rarefied to 24,000 sequences per 

sample. Sequence reads for each sample were deposited in 

the National Center for Biotechnology Information Sequence 

Read Archive under BioProject PRJNA470686 and BioSample accession numbers SRR7140487–SRR7140489. Data 

and associated metadata are available in Shelton, DeVera, and 

others (2018).

Cultivation of Microbial Functional Groups

Microbial functional groups were cultured from the 

Rafter “K” Ranch and Oakdale Field water samples in 

anaerobic media selective for six microbial functional groups 

at three sodium chloride (NaCl) salinities (freshwater, 1 gram 

per liter [g/L]; seawater, 20.0 g/L; and brine, 100 g/L) and at 

two CO2 concentrations (20 percent and 100 percent) for a 

total of 36 cultivation conditions. A broad range of salinities 

were tested to provide a proxy for geochemical changes that 

could result from mixing of high- and low-salinity waters in 

aquifers. In addition, by testing multiple salinities, we aimed 

to provide information on the range of salinity tolerated by 

the native microbial communities. Two CO2 concentrations 

were tested to evaluate the microbial response to various CO2

concentrations because CO2 concentrations could vary in situ.

The microbial functional groups targeted included CO2

fixers and hydrogenotrophic methanogens (autotrophs), ironreducing bacteria (FeRB), acetoclastic methanogens (methanogens), nitrate-reducing bacteria (NRB), sulfate-reducing bacteria (SRB), and heterotrophs/fermenters (heterotrophs). The 

functional groups tested were chosen to evaluate (1) microbial 

responses to inputs of deep or shallow waters with varying 

geochemical conditions and (2) the potential activity of microorganisms in a CO2 sequestration analogue.

An anoxic, sterile, bicarbonate-buffered mineral media 

(modified from Widdel and Bak, 1992; pH 7) was used as the 

base media for enrichment cultures. Per liter, freshwater media 

contained the following: 0.4 gram (g) magnesium chloride 

(MgCl2)∙6H2O, 0.1 g calcium chloride (CaCl2)∙2H2O, 0.3 g 

ammonium chloride (NH4Cl), and 0.6 g monopotassium 

phosphate (KH2PO4). Each liter of seawater and brine media 
8 Analysis of Formation Water Geochemistry and Microbiology of Commercial and Carbon Dioxide-Rich Wells

contained 3.0 g MgCl2∙6H2O, 0.15 g CaCl2∙2H2O, 0.25 g 

NH4Cl, and 0.2 g KH2PO4. Per liter, all media contained 

0.5 g potassium chloride (KCl), 3.2 g sodium bicarbonate 

(NaHCO3), 1 mL of trace element solution SL-9 (Tschech 

and Pfennig, 1984), and 1 mL of 0.1 percent resazurin solution as redox indicator. Media (10 mL) was dispensed under 

80/20 N2/CO2 into Balch pressure tubes containing approximately 0.7 g of 0.5-mm glass beads, which were added to 

act as an inert surface for microbial growth. The tubes were 

capped with butyl rubber stoppers (Bellco Glass Inc.) and 

aluminum crimp seals and then autoclaved at 121 °C for 

20 min. After autoclaving, media was amended with 1 milliliter per liter Wolfe’s vitamin solution (Zeikus and others, 

1983), selenite-tungstate solution (the final concentration in 

media was 1 μM Na2SeO3 and Na2WO4∙2H2O), and cysteinesulfide reductant (Zeikus and others, 1983) from sterile, anoxic 

stocks. Enrichment cultures for NRB and FeRB also contained 

0.5 millimolar (mM) iron chloride (FeCl2) as reductant.

Media were further amended with electron acceptors and donors to selectively enrich for the six microbial 

functional groups. The final concentrations of amendments were as follows: (1) autotrophs—approximately 

0.001 percent yeast extract and 10 mL hydrogen gas (H2); 

(2) heterotrophs—6.4 g/L Bacto Peptone (Difco Laboratories), 

1.1 g/L yeast extract, and 8.5 g/L glucose; (3) FeRB—approximately 50 mM amorphous iron oxide (FeOOH), 4 mM citrate, 

4 mM acetate, and 4 mM lactate; (4) NRB—200 mM glycerol and 50 mM sodium nitrate (NaNO3); (5) SRB—citrate, 

acetate, and lactate, all 4mM, and 20 mM sodium sulfate 

(NaSO4); and (6) methanogens—13 mM acetate. Amorphous 

FeOOH was synthesized according to the method of Lovley 

and Phillips (1986). Prior to inoculation, pressure tubes were 

briefly flushed by using aseptic technique with 80/20 N2/CO2

or 100 percent CO2 for low- or high-CO2 conditions, respectively, and left overpressured. Cultures were inoculated with 

1 mL of water sample. A sterile control was prepared for each 

experimental combination by omitting the inoculant. Pressure 

tubes were incubated in the dark at 37 °C while shaking at 

75 rotations per minute.

Cultures were visually monitored for approximately 

5 weeks and scored at least weekly. Scoring consisted of 

a subjective scale from negative to four-plus based on turbidity and any other changes in appearance that indicated 

biological activity. Geochemical analyses were performed 

to confirm visual observations. The NRB culture samples 

were filtered (0.22-μm Supor filters), then nitrate concentrations were determined by ion chromatography using a 

Dionex ICS-1000 ion chromatograph with an ED50 electrochemical detector and a high-capacity AS14 anion-exchange 

column. Sulfate reduction by SRBs was verified by using 

lead acetate strips (Fisher Scientific), where a dark color 

change indicated H2S production. Dissolved divalent iron 

(Fe[II]) concentrations in FeRB cultures were determined by 

extracting samples in 0.5-molar hydrochloric acid (HCl) for 

1 hour. The HCl-extractable Fe(II) in extracts was quantified colorimetrically by analysis in ferrozine buffer: 50-mM 

4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid (HEPES), 

0.1 percent ferrozine, pH 7 (Kostka and Luther, 1994). 

Absorbance was measured at 562 nanometers and converted to 

iron concentrations on the basis of a standard curve of known 

Fe(II) concentrations.

Methane was measured in methanogen, autotroph, and 

heterotroph cultures by using a gas chromatograph (GC) with 

thermal conductivity detection. Samples were collected from 

culture tubes by using a sampling valve and 1-mL pressurelock, tight syringes (Valco Instruments Co. Inc.) with noncoring needles. The sampling valve consisted of a Hamilton 

HV plug valve (Hamilton Co., Reno, Nevada), sealed with 

Thermogreen LB-2 5-mm septa (Supelco, Inc., Bellefonte, 

Pennsylvania), and Kel-F female and male luer fittings 

(Hamilton Co. no. 35031 and no. 35030). A sterile syringe 

needle was attached to the male end and then inserted into 

the flamed stopper of a microcosm bottle. Using a pressure 

lock syringe, 0.2 mL of gas was removed and injected into a 

Hewlett Packard 6890 series GC (GMI Inc.). Separation was 

performed using a HayeSep N 80/100 mesh column with a 

3-m, 1/8-inch Nafion dryer. The GC operated with nitrogen 

as the carrier gas (20 milliliters per minute [mL/min] total 

flow); temperatures of 40 °C, 155 °C, and 180 °C for the oven, 

injector, and detector, respectively; and an injector flow rate 

of 20 mL/min total flow. The GC signals were analyzed with 

VP CLASS 7.3 software (Shimadzu, Columbia, Maryland). 

Instrument responses were calibrated with CH4 standards 

(Scott Specialty Gases, Plumsteadville, Pennsylvania). A 

GMH 3111 digital pressure meter with a GMSD needle pressure transducer (Greisinger Electronic GmbH, Germany) 

was used to measure gas pressure in culture tubes. Methane 

concentrations measured by the GC in parts per million were 

converted to micromoles of CH4 gas in headspace by using the 

Ideal Gas Law (eq. 1).

(

___________ Patm + PHS) × VHS

R(T + 273.15) × 

_

XCH4

106 = nCH4 (1)

where

Patm is the room pressure in millibars;

PHS is the headspace overpressure in millibars;

 XCH4 is the concentration of methane in headspace 

in parts per million;

VHS is the headspace volume in milliliters;

R is the ideal gas constant (8.314 × 104 milliliter 

millibar per mole per degree kelvin); and

T is the laboratory temperature in 

degrees Celsius.

Compositional Data Analysis

Chemical data from waters are typically measured and 

statistically analyzed as concentrations of specific elements 

(for example, as milligrams per liter, millimoles per liter, and 

so on). Water-chemistry datasets, however, are fundamentally 

compositional (Lovell and others, 2011; Engle and Rowan, 
Produced Fluid Geochemistry 9

2013, 2014) and require particular mathematical treatment to 

successfully interpret the data. Many issues with data interpretation, such as spurious relations or misleading conclusions, have been noted when using standard mathematical 

and statistical techniques on ion and elemental data, particularly in brines (for example, Aitchison, 1986; Buccianti and 

Pawlowsky-Glahn, 2005; Engle and Rowan, 2013, 2014; 

Engle and Blondes, 2014). Therefore, we used methods of 

compositional data analysis (CoDA) to analyze the subcompositions of the nonisotopic chemical data. These methods were 

created to avoid and overcome issues surrounding traditional 

water-quality assessment methods and plotting techniques (for 

example, Piper plots). For an in-depth explanation of CoDA, 

as well as the centered log-ratio (clr) and isometric log-ratio 

(ilr) transformations, we refer readers to fundamental papers 

(Aitchison, 1986; Egozcue and others, 2003; PawlowskyGlahn and Buccianti, 2011; Engle and Rowan, 2013).

Produced Fluid Geochemistry

Produced water was collected from four sites during 

the two sampling campaigns (table 1). In this section, Rafter 

“K” Ranch results are highlighted individually because of 

the difference in setting compared to the other sites (shallow 

groundwater versus deep hydrocarbon environments). The 

water temperature was 25.3 °C at Oakdale Field and 32.5 °C 

at Rafter “K” Ranch; water temperature was not recorded at 

Candelario and Lewis wells (Bravo Dome samples). The pH 

of the samples ranged from 6.4 (Rafter “K” Ranch) to 7.2, 

and alkalinity ranged from 1,575 milligrams per liter (mg/L) 

as calcium carbonate (CaCO3) to 15,737 mg/L as CaCO3

(10,825 mg/L as CaCO3 at Rafter “K” Ranch). Sodium (Na+) 

concentrations ranged from 63 mg/L (Rafter “K” Ranch) to 

19,000 mg/L, and chloride (Cl−) concentrations ranged from 

19 mg/L (Rafter “K” Ranch) to 16,000 mg/L. Calcium (Ca2+) 

concentrations ranged from 358 to 3,560 mg/L (573 mg/L at 

Rafter “K” Ranch), magnesium (Mg2+) concentrations ranged 

from 102 to 2,650 mg/L (127 mg/L at Rafter “K” Ranch), and 

sulfate (SO4

2−) concentrations ranged from 573 (Rafter “K” 

Ranch) to 3,340 mg/L (table 2). Most concentrations of nitrite 

(NO2

−) (as nitrogen [N]), nitrate (NO3−) (as N) and phosphate 

(PO4

3−) (as phosphorus [P]) were at or below laboratory 

detection limits. Produced gas data and results are described in 

Brennan (2017) and can be found in table 2.

Figure 2 is a covariance clr biplot that allows for interpretation of the variance of different ratios of cations and 

anions across the study area. When interpreting a clr biplot, 

it is most important to analyze the position and length of the 

links between the rays instead of simply the size and direction 

of the rays themselves. Principal component (PC) 1 explains a 

majority of the variance in the dataset, 84.5 percent, and PC1 

and PC2 combined explain almost all of the variance present 

in the dataset (95.8 percent total). The links between concentrations of Mg2+ and Na++ potassium (K+), Mg2+ and Cl−, and 

Mg2+ and SO4

2− are all subparallel to PC1, meaning that PC1 

reflects variation in the ratios Mg2+/Na++K+, Mg2+/Cl−, and 

Mg2+/SO4

2− across the sample set. Almost all links from DIC 

to the other elements are subparallel to PC2, meaning that PC2 

explains the variation in DIC concentrations across the sample 

sites. Short links between concentrations of Na++K+ and Cl−

and Cl− and SO4

2− suggest that these constituents occur proportionally and may be associated with each other across the 

studied region. The fact that PC1 explains most variance in the 

dataset suggests that most of the variance is due to differences 

in Na++K+, Cl−, and SO4

2− concentrations compared to Mg2+

concentrations across the dataset.

The ilr-ion plot is a CoDA alternative to the Piper 

diagram that shows ilr-transformed concentrations of major 

cations and anions, similar to a Piper diagram (the ilr-ion 

plot is described fully in Shelton, Engle, and others, 2018). 

Most water samples in the current study (4 original samples 

and 108 legacy samples from other sources) are Na++K+ type 

(lower left panel of fig. 3), with variation in the dominating anion (upper right panel of fig. 3). Minimal clustering of 

samples is apparent, meaning that, in general, the current and 

legacy water samples tend to be geochemically diverse. The 

clusters that do appear are samples that were collected as timeseries data from the same location or samples from similar 

stratigraphic settings (U.S. Environmental Protection Agency, 

2016). The Bravo Dome samples are generally similar in that 

both are Na++K+- and Cl−-type waters. The water produced 

from the Lewis well, however, has a greater Ca2+ concentration than Mg2+ concentration, whereas the Candelario well 

sample has a greater Mg2+ concentration than Ca2+ concentration (left panels of fig. 3). The Rafter “K” Ranch sample is 

the most dissimilar of the four CO2-rich reservoir samples 

collected, with water produced being Ca2+ and bicarbonate 

(HCO3

−)+carbonate (CO32−) type.

The four water samples collected for this study are, in 

general, isotopically similar to regional waters, in that all 

appear to be of meteoric origin (fig. 4). The current data and 

the legacy water data, in general, fall near the global meteoric 

water line (GMWL; Craig, 1961) and the local meteoric water 

line (LMWL; developed for the Pecos River above Santa Rosa 

Lake, New Mexico; USGS station number 08382650; Coplen 

and Kendall, 2000). The samples collected in the current study 

generally have more enriched δ2H-H2O and δ18O-H2O values 

than the legacy data, with the Oakdale Field and Rafter “K” 

Ranch samples being obvious outliers (fig. 4). These isotopic 

differences in the Rafter “K” Ranch and Oakdale Field samples compared to the other samples in the dataset may be due 

to differences in recharge temperatures, the CO2-rich condition 

of the reservoirs, or evaporation during recharge (the Oakdale 

Field sample may have been affected by evaporation while in 

the storage tank). For example, three evaporation scenarios 

are plotted in figure 4, showing how the isotopic composition of water could shift during evaporation at 25, 50, and 

75 percent humidity. Oxygen exchange is an expected isotopic deviation for waters in high-CO2 environments, meaning 

oxygen-16 from the in situ CO2 would preferentially exchange 
10 Analysis of Formation Water Geochemistry and Microbiology of Commercial and Carbon Dioxide-Rich Wells

with oxygen-18 in the water, causing the δ18O-H2O value to 

decrease over time; however, isotopic equilibrium is quickly 

achieved, and this fractionation is rarely observed in nature 

(Clark and Fritz, 1997). Exchange with CO2 would not cause 

the deviation observed in the dataset. These samples may 

also be influenced by microbial activity (for example, microbial methanogenesis; Balabane and others, 1987; Whiticar, 

1999) and mixing of water sources. Moreover, the isotopic 

composition of these waters may simply reflect the isotopic values during recharge and could be slightly influenced 

by mixing with basinal brines (Clayton and others, 1966). 

Because this study does not have known mixing endmembers 

for either water isotope, establishing mixing trends is difficult.

The 87Sr/86Sr isotopic system is typically used to determine mixing of groundwaters or used as a tracer for sources 

of salinity or water-rock interactions (Geyh and others, 2001). 

Na+ + K+

Ca2+

Mg2+

Cl−

SO4

2−

DIC

−0.2 −0.1 0 0.1 0.2 0.3

PC1 (84.5% of variance)

0.4

0.3

0.2

0.1

0

−0.2

−0.1 PC2 (11.3% of variance)

Oakdale Field

Candelario (Bravo Dome)

Lewis (Bravo Dome)

Rafter "K" Ranch

Legacy water data

EXPLANATION

Figure 2. Compositional biplot that represents a principle component (PC) analysis of centered 

log ratio (clr)-transformed water-chemistry data for produced water samples and legacy data. 

PC1 explains 84.5 percent (%) of the variance in the dataset, and PC2 explains 11.3 percent of 

the variance. The dashed lines represent examples of links between the rays. Ca2+, calcium; 

Cl−, chloride; DIC, dissolved organic carbon; K+, potassium; Mg2+, magnesium; Na+, sodium; 

SO4

2−, sulfate.
Produced Fluid Geochemistry 11

0 1 2 3 4

HCO3 + CO3 −type 

Cl type

Ca type

Na+K type

1

0

−1

−2

−3

−4

−5

[Ca][Na + K]

[Mg] 2

3

ln

1

0

−1

−2

−3

−4

−5

[Ca][Na + K]

[Mg] 2

3

ln

0

−2

2

4

[Cl]

[SO4

]

1

2 ln

0

−2

2

4

[Cl]

[SO4

]

1

2 ln

ln 1 [Ca]

[Mg] 2

0 1 2 3 4

ln 1 [Ca]

[Mg] 2

−3 −2 −1 0 1 2 3

SO4 type

[Cl]

[HCO3 + CO3

]

[SO4 2 ]

3

ln

−3 −2 −1 0 1 2 3

[Cl]

[HCO3 + CO3

]

[SO4 2 ]

3

ln

Oakdale Field

Candelario (Bravo Dome)

Lewis (Bravo Dome)

Rafter "K" Ranch

Legacy water data

EXPLANATION

Figure 3. Isometric log-ratio ion plot (as described in Shelton, Engle, and others, 2018) showing the major ion composition of 

produced water samples and legacy data. Square brackets indicate concentration in milliequivalents per kilogram. Ca, calcium; 

Cl, chloride; CO3, carbonate; HCO3, bicarbonate; K, potassium; ln, natural logarithm; Mg, magnesium; Na, sodium; SO4, sulfate. 

Gray dashed lines indicate which species dominates in each quadrant, as labeled.
12 Analysis of Formation Water Geochemistry and Microbiology of Commercial and Carbon Dioxide-Rich Wells

The two Bravo Dome samples, Lewis and Candelario, have 

more radiogenic strontium (Sr) than the Rafter “K” Ranch and 

Oakdale Field waters, meaning that the Lewis and Candelario 

87Sr/86Sr values are greater than the Rafter “K” Ranch and 

Oakdale Field 87Sr/86Sr values (fig. 5). The Oakdale Field sample is the only sample that conforms to the general regional 

trend for Sr isotopes and concentrations; the Rafter “K” Ranch 

sample has a much lower Sr concentration than the other samples, and the Bravo Dome samples are much more radiogenic 

than the legacy water samples. The legacy water data, which 

are time-series data from multiple surface-water sites, monitoring wells, domestic water wells, and production wells, show 

little variation between time points, only small changes in the 

Sr concentrations in the sampled water (the 87Sr/86Sr values 

for the same locations at different time points remain more 

constant). All of the water data, including the four samples 

collected for the current study and the legacy data, are within 

the isotopic range of the data for the regional rocks, which are 

volcanic, xenolithic, plutonic, or unknown rock types. The 

hard rock data are much more variable than the legacy water 

data, with 87Sr/86Sr values ranging from 0.70274 to 0.80837 

and 1/Sr values ranging from 0.00029 kilogram per milligram 

(kg/mg) to 192.3 kg/mg (EarthChem, 2018).

The Lewis and Candelario samples (from the West Bravo 

Dome exploration unit) and the Oakdale Field sample generally align with overall regional geochemical trends, except 

for the few differences outlined above: the Oakdale Field 

sample is isotopically enriched in oxygen-18 and deuterium 

(2H) compared to the legacy water data, and the Bravo Dome 

samples (Lewis and Candelario) have greater 87Sr/86Sr values 

compared to the legacy water data. The Rafter “K” Ranch 

sample appears to be an outlier, as it generally deviates from 

regional water trends outlined by the legacy water data (see 

figs. 2–4). The greater amounts of radiogenic strontium in the 

25 percent humidity

50 percent humidity

75 percent humidity

−150

−130

−110

−90

−70

−50

−30

−10

10

30

50

−20 −15 −10 −5 0 5

δ18O−H2O, in per mil

δ2

H−H O, in per mil

2

GMWL

LMWL

Oakdale Field

Candelario (Bravo Dome)

Lewis (Bravo Dome)

Rafter "K" Ranch

Legacy water data

EXPLANATION

Figure 4. Graph showing water isotope data for produced water samples and legacy data relative to the global meteoric 

water line (GMWL) and a local meteoric water line (LMWL; developed for U.S. Geological Survey station number 08382650; 

Coplen and Kendall, 2000). Humidity trajectories were calculated using 25, 50, and 75 percent humidity (solid blue lines), 

a temperature of 25 degrees Celsius, and fractionation factors for water-vapor exchange for oxygen-18 and deuterium 

from Kakiuchi and Matsuo (1979). δ2H-H2O and δ18O-H2O are measured relative to Vienna Standard Mean Ocean 

Water (VSMOW). 
Produced Fluid Geochemistry 13

Legacy Sr rock sample

0.70

−0.1 0.1 0.3 0.5 0.7 0.9 1.1 1.3 1.5

0.760.750.740.730.720.71

87Sr/86Sr

Three points have

87SR/86Sr >0.76 

1/Sr concentration, in liters per milligram

A B

Oakdale fieldCandelario (Bravo Dome)Lewis (Bravo Dome)Rafter K RanchLegacy water dataUnknown rock typePlutonic rockVolcanic rockXenolithic rock

EXPLANATION

Figure 5. A, Graph showing strontium (Sr) concentrations and isotope ratios (strontium-87/strontium-86 [87Sr/86Sr]) for the four produced water samples and legacy water data. The x-axis has been scaled to better display the four samples from the current study. B, Graph showing Sr isotope ratios for the legacy rock data. Three of the points are outside the range of the y-axis, in the direction indicated by the black arrow (values are 0.768, 0.808, and 0.808). No data are plotted on the x-axis in B.
14 Analysis of Formation Water Geochemistry and Microbiology of Commercial and Carbon Dioxide-Rich Wells

Lewis and Candelario samples cannot be explained by the 

high CO2 content of the reservoir and is more likely explained 

by volcanism in the localized area. Previous volcanic activity 

occurred near Bravo Dome, specifically in the Raton Volcanic 

Field (Broadhead and others, 2009). Sathaye and others (2014)

hypothesized that the CO2 gas that charged Bravo Dome was 

likely sourced from the formation of the Capulin Volcano in 

the Raton Volcanic Field and traveled into the basin via faults 

generated by magmatic activity. It is also possible that the high 

CO2 content (that is, acidity) of these waters may be dissolving formation rock, thus releasing radiogenic strontium. The 

similarity of the strontium isotope values and concentrations 

of the Lewis and Candelario samples may indicate a common 

source for the groundwater, similar residence times, and (or) 

similar flow paths.

The Oakdale Field sample is most different from the 

legacy water data in terms of isotopic composition. The 

Oakdale Field water has much more positive δ2H and δ18O 

values (fig. 4). The Oakdale Field sample could have been 

affected by evaporation during recharge, which is a process 

that can increase both the δ2H and δ18O values in water, causing the sampled water to have larger δ2H and δ18O values 

than the GMWL (for example, Clark and Fritz, 1997). These 

high δ2H and δ18O values could imply different recharge areas 

or time of recharge than the other samples examined in this 

study. Also, because the Oakdale Field sample was collected 

from an open storage tank, water may have evaporated from 

the storage tank itself, altering the isotopic composition of the 

water post-production. The tank was not well mixed, however, 

and the sample was collected from the bottom of the tank, 

which might have deterred major evaporative and depositional effects. Microbial activity may also affect the isotopes 

of produced water, such as δ18O-H2O; Oakdale Field may be 

actively methanogenic because of the CH4 produced from the 

field (Worrall, 2004).

The Rafter “K” Ranch sample is the most geochemically distinct of the four samples collected in the current 

study, differing both isotopically and compositionally. This 

deviation from regional trends may be due to the shallow 

sampling depth. Much of the legacy data, however, are from 

regional surface and monitoring wells, which would also 

reflect shallow conditions. The difference in depth between 

Rafter “K” Ranch and the other three CO2-rich samples 

collected in this study may explain some of the differences 

observed between those two groups of samples. The Bravo 

Dome (Lewis and Candelario) and Oakdale Field samples 

are all Na++K+- and Cl−-type waters, typical of basinal brines 

(Kharaka and Hanor, 2003), whereas Rafter “K” Ranch is 

Ca2+- and HCO3

−+CO32−-type water, typical of low-salinity, 

shallow groundwaters. This observation is consistent with 

the much lower TDS value of the Rafter “K” Ranch sample 

compared to the other three sites (see table 2). The shallow 

groundwater samples from the legacy water data are also 

typically dominated by SO4

2−, with some samples being 

HCO3

−+CO32− type, and are either Ca2+ type or do not have a 

dominant cation (fig. 3).

Two differences between the shallow legacy groundwater 

samples and the Rafter “K” Ranch sample are CO2 concentration and producing strata. The CO2 concentration of the Rafter 

“K” Ranch sample is much higher than those of the legacy 

data, as the legacy data are not from either naturally producing 

CO2 wells or gas wells. This difference most likely explains 

the dominance in DIC for Rafter “K” Ranch compared to 

SO4

2− for most of the shallow legacy groundwater samples 

because CO2 injection into shallow groundwaters increases 

the alkalinity as the CO2 dissolves into formation water (for 

example, Kharaka and others, 2010; Peter and others, 2012). 

Unfortunately, the exact lithological effects are uncertain 

because the producing strata for the legacy water data are 

unknown and the producing strata for Rafter “K” Ranch 

are uncertain.

Despite the possible effects of CO2 described above, and 

even though all four samples have different geochemical signatures, the samples generally fit regional geochemical trends 

associated with producing wells across southern Colorado and 

northeastern New Mexico. Regional dissimilarities between 

the two Bravo Dome samples and the legacy data may be due 

to different flow paths, causing differing water-rock interactions (specifically, accumulation of radiogenic strontium). The 

Oakdale Field sample generally conforms to regional trends, 

except for the isotopic values of the formation water (δ18O and 

δ2H of H2O). This deviation may be due to different recharge 

times, evaporation during recharge, evaporation in the storage 

tank, and (or) microbial activity. The Rafter “K” Ranch sample 

appears to be the most distinct when comparing geochemistry 

to the legacy data; the sample has much less strontium, more 

enriched δ18O and δ2H values for H2O, and is Ca-HCO3-type 

water. Some of these deviations can easily be attributed to 

the well’s shallow sampling depth and higher CO2 concentration compared to other shallow groundwaters included in the 

legacy data. Because some of the legacy data are from surface 

waters and shallow groundwater wells, it appears that depth 

alone is not driving the differences observed. Differences may 

be driven by lithology because the Rafter “K” Ranch producing formation is like that of Bravo Dome, which produces 

from much greater depths than the shallow legacy samples.

Microbial Community Composition and 

Diversity

To better understand how high-CO2 environments affect 

the microbial communities in produced water, the microbial community compositions of the four collected samples 

were analyzed. The average number of sequences per sample 

prior to rarefaction was 38,488, with the minimum and 

maximum number of sequences equal to 26,762 and 64,702, 

respectively (table 3). Samples were rarefied by random 

subsampling to 24,000 sequences per sample for community 

analysis. After rarefaction, the average number of OTUs 

identified in each sample was 141, with Candelario having 
Microbial Community Composition and Diversity 15

the most OTUs identified (252 OTUs) and Lewis having 

the fewest (41 OTUs). The microbes identified in these four 

samples span 28 phyla and 480 OTUs, with OTUs from only 

5 of the 28 phyla present in each sample (Actinobacteria, 

Bacteroidetes, Euryarchaeota, Firmicutes, and Proteobacteria). 

Most OTUs identified (84.0 percent) were found in only one 

of the four samples collected, and only one OTU was identified in all four samples. Rafter “K” Ranch, the shallowest 

groundwater sample and the hydrogeochemical outlier, had the 

highest Shannon diversity index (Shannon, 1948), 3.94. The 

Lewis sample (collected from the West Bravo Dome Unit) had 

the lowest Shannon diversity index, 1.80. Bacteria dominated 

all samples, with Archaea present in the four water samples at 

a percent abundance between 0.0 and 0.3 percent (table 3). On 

average, the most prominent phyla in the four water samples 

were Firmicutes (30.5 percent), Proteobacteria (28.8 percent), 

Bacteroidetes (26.8 percent), and Chloroflexi (5.0 percent).

The most prominent genera identified in the four 

water samples, on average, were Acetobacterium (8.0 percent), Desulfovibrio (5.7 percent; the only genus present 

in all four water samples), Pseudomonas (4.9 percent), 

Sphingobacterium (4.7 percent), and Sulfurospirillum (4.3 percent). The Lewis well sample is dominated by unclassified 

Bacteroidetes (50.8 percent), Desulfotomaculum arcticum

(12.0 percent), and Meniscus sp. (10.5 percent). The genus 

Meniscus is understudied; however, the few existing studies 

have suggested that the genus is aerotolerant and heterotrophic (Irgens, 1977). Desulfotomaculum arcticum is a relatively thermophilic SRB isolated from sediment (Vandieken 

and others, 2006); other species of the Desulfotomaculum

genus were identified in an aquifer used for natural gas storage (Berlendis and others, 2016). Some species of the genus 

Desulfotomaculum can oxidize organic compounds to CO2, 

whereas other species use CO2 and H2 to grow autotrophically (Kuever and Rainey, 2015). Therefore, some of the CO2

co-produced at the Lewis well could have been microbially 

modified, either added or removed from the system by the in 

situ organisms. Bacteroidetes is a very diverse phylum, with 

species identified in various environments, such as soils, the 

guts of humans and animals, sludge, and biodegraded oil 

reservoirs (for example, Grabowski and others, 2005; Weon 

and others, 2006; De Filippo and others, 2010; Sun and others, 

2016; Sierra-Garcia and others, 2017).

The water produced from the Candelario well is 

dominated by Sphingobacterium faecium (16.9 percent), 

Pseudomonas sp. (15.2 percent), and unclassified organisms 

(10.6 percent). Little is known about S. faecium other than that 

they are aerobic and “of feces”; however, species of the genus 

Sphingobacterium have been identified in soils, compost, 

and industrial applications and are known etiological agents 

of infection (Takeuchi and Yokota, 1992; Lambiase, 2014). 

Species of the genus Pseudomonas have been identified in 

many different habitats and have been isolated from environments including human clinical specimens, soils, marshes, and 

marine environments (for example, Hardalo and Edberg, 1997; 

Stover and others, 2000; Palleroni, 2015).

The difference in microbial communities between the two 

Bravo Dome sites (Lewis and Candelario) combined with dissimilar hydrogeochemistry and similar producing strata may 

support the hypothesis that the Bravo Dome hydrologic system 

is compartmentalized. If the two wells were hydrologically 

connected, they would be expected to be more microbiologically and geochemically similar. Due to the difference in well 

depth (approximately 90 m), however, differences in pressure 

and water residence time could also be driving these general 

microbial and geochemical differences.

The Oakdale Field sample contained mostly 

Acetobacterium sp. (31.7 percent), Desulfovibrio dechloracetivorans (18.0 percent), Sulfurospirillum sp. (16.0 percent), uncultured Marinobacterium sp. (14.3 percent), and 

Campylobacteraceae (11.6 percent). Species of the genus 

Acetobacterium are diverse in their functions and habitats 

(Stackebrandt, 2014) and are categorized as CO2-reducing, 

hydrogen-oxidizing anaerobes (Balch and others, 1977). 

Desulfovibrio dechloracetivorans is a dechlorinating SRB 

that has been isolated from marine and tidal mudflat sediment, 

as well as from crude oil facilities (Sun and others, 2000). 

Species of the genus Sulfurospirillum are free-living bacteria 

Table 3. Results of 16S ribosomal ribonucleic acid (rRNA) gene amplicon sequencing.

[The total number of sequences is the number identified after singleton removal. Diversity statistics and percent Bacteria and Archaea were determined after 

removal of singletons and contaminants and rarefaction to 24,000 sequences per sample. OTU, operational taxonomic unit]

Sample

Total 

sequences 

per sample

Species 

richness

Shannon 

diversity 

index

Pielou’s 

evenness

Percent 

Bacteria

Percent 

Archaea

Most abundant OTU

(percent abundance)

Lewis (Bravo 

Dome)

27,743 41 1.80 0.484 100 0 Unknown Bacteroidetes (50.8)

Candelario 

(Bravo Dome)

26,762 252 3.75 0.679 99.7 0.3 Sphingobacterium feacium (16.9)

Oakdale Field 34,743 70 1.96 0.462 100 0 Acetobacterium spp. (31.7)

Rafter “K” 

Ranch

64,702 199 3.94 0.744 99.8 0.2 Uncultured Blvii28 wastewatersludge group (9.3)
16 Analysis of Formation Water Geochemistry and Microbiology of Commercial and Carbon Dioxide-Rich Wells

that have been isolated from water produced from an oil field 

(Hubert and Voordouw, 2007), as well as anaerobic sludge, 

surface water, and anoxic muds (Lastovica and others, 2014). 

The genus Marinobacterium contains species that have been 

identified in mostly marine environments, including pulp mill 

effluent water, tidal flats, and marine sediment (González and 

others, 1997). Genera of the family Campylobacteraceae are 

very diverse, have a wide range of growth characteristics, and 

tend to be identified in humans, animals, surface water, and 

groundwater (Lastovica and others, 2014).

The Rafter “K” Ranch sample is dominated by the 

Blvii28 wastewater-sludge group (9.3 percent), Leptolinea sp. 

(7.3 percent), and uncultured Veillonellaceae (6.5 percent). 

The Blvii28 wastewater-sludge group is a poorly characterized 

group of organisms commonly identified in sewage-sludge 

digesters or anaerobic wastewater that have yet to be isolated 

(Su and others, 2014). Species of the genera Leptolinea are 

strict mesophilic anaerobes and have been isolated from an 

artificial wastewater-sludge digestor (Yamada and others, 

2006). Genera of the family Veillonellaceae are identified in 

the microbiomes of many animals and humans (Marchandin 

and Jumas-Bilak, 2014). Because all three of these bacteria 

types are frequently associated with human or animal waste, it 

appears that water infiltrating into the shallow, likely unconfined aquifer is carrying surficial animal waste products into 

the subsurface during recharge. Ranching in the surrounding 

areas, mostly cattle and horses, could contribute to the microbiological signature observed in this shallow groundwater 

well. Furthermore, because the well could not be adequately 

purged prior to sample collection (see the “Methods” section), 

the microbes may have been concentrated near the wellbore.

A nonmetric multidimensional scaling (NMDS) plot 

using a UniFrac distance matrix shows that the four water 

samples plot separately from each other, indicating some 

differences in sample composition at the OTU level (fig. 6A). 

Notably, the Oakdale Field sample was the most distinct of the 

four, and this difference was confirmed by using permutated 

analysis of variance with the adonis2 function in the vegan 

package of R (Oksanen and others, 2013), resulting in a R2

value of 1 and a p-value of 0.25 (fig. 6A). This result may be 

due to either the mixture of waters creating the Oakdale Field 

sample or the open-air tank possibly causing changes in the 

microbial community post-production. Multilevel pattern 

analysis (multipatt function in the indicspecies package of 

R; De Cáceres and Legendre, 2009) was used on five groups 

and did not identify any indicator species. The groups analyzed were (1) Candelario versus the remaining three water 

samples, (2) Lewis versus the remaining three water samples, 

(3) Oakdale Field versus the remaining three water samples, 

(4) Rafter “K” Ranch versus the remaining three water 

samples, and (5) the two Bravo Dome samples (Lewis and 

Candelario) versus the Rafter “K” Ranch and Oakdale Field 

water samples.

Data from Freedman and others (2017) were added to 

the analysis to compare McElmo Dome, a commercial CO2

reservoir in Colorado, to Bravo Dome (fig. 6B). McElmo 

Dome produces CO2 at a comparable quality (approximately 

99 percent CO2 by composition) to Bravo Dome (Shelton and 

others, 2016; Freedman and others, 2017). The six samples—

two from Bravo Dome, two from McElmo Dome well 3, and 

two from McElmo Dome well 10—were dissimilar, the only 

clustering being the two points for each McElmo Dome well. 

An adonis2 analysis between the four McElmo Dome samples 

(group 1) and the two Bravo Dome samples (group 2) yielded 

an R2 value of 0.40 and a p-value of 0.067, indicating that the 

differences across the groups are greater than the differences 

within the groups.

The significance of relations between any hydrologic or 

gas phase parameters (for example, Na+, SO4

2−) and microbial 

community structure was tested with the envfit function in 

the R package vegan. No hydrologic data were significantly 

associated with the UniFrac-based ordination; p-values ranged 

from 0.1250 (sodium) to 1.0000 (magnesium). Furthermore, 

the associated gas composition data collected by Brennan 

(2017) were used to determine if the CO2 concentration (or 

any other identified gas) had any significant linkage to differences in microbial community structure. No significant results 

were obtained; the p-value for CO2 concentration was 0.4806, 

and p-values for helium (He), argon (Ar), N2, CH4, and 

hydrocarbons measured in the gas with greater than or equal 

to two carbon atoms (C2+) concentrations were all greater than 

0.5. These results indicate that neither gas composition nor 

water chemistry have any significant effect on the differences 

between the microbial communities of the four water samples 

collected for the current study.

This result is particularly interesting considering that the 

Oakdale Field sample, when compared to the three other water 

samples, is associated with an analysis of similarities R value 

of 1 and a p-value of 0.25. The Oakdale Field water sample is 

a composite of water from wells producing water and gas with 

varying concentrations of CO2 and was the only sample that 

was not associated with gas at greater than 99 percent CO2. 

It was also the only sample of the four that had co-produced 

hydrocarbons and biogenic gas. Given that the CO2 concentration was not a statistically significant driver of the microbial 

differences observed between the four samples, differences in 

CO2 concentrations are not driving the observed differences in 

microbial community structure.

These results differ from the findings of Ham and others 

(2017), who observed significant variation between microbial 

communities in two sites with high CO2 concentrations. They 

observed that some geochemical factors were significantly 

associated with the microbial communities—total dissolved 

solids, alkalinity, pH, strontium, lithium, cesium, and CH4—

and CO2 concentrations were also linked to the microbial data 

(Ham and others, 2017). Their results suggest that CO2 concentrations, as well as some geochemical factors, may drive 

the observed microbial community differences in CO2-rich 

aquifers. The authors stated, however, that oxidation-reduction 

(redox) conditions in the subsurface aqueous environment 

may be more of a driving factor for microbial community 

diversity than CO2 concentrations, which may be applicable 
Microbial Community Composition and Diversity 17 Axis 1

Axis 2

Axis 2

adonis2 result:R2 = 1

Significance = 0.25

−0.50 −0.25 −0.25 0 0.25 0.50

Axis 1

Candelario (Bravo Dome)

Oakdale Field

Rafter "K" Ranch

Lewis (Bravo Dome)

Candelario (Bravo Dome)

Lewis (Bravo Dome)

K3 (McElmo Dome)

P3 (McElmo Dome)

K10 (McElmo Dome)

P10 (McElmo Dome)

−0.4 −0.2 0 0.2 0.4 0.6 −0.3 −0.1 0.1 0.3 0.5 0.7

−0.1−0.2−0.3−0.4−0.5

0

0.40.20.1

A B

0.3

−0.10

0

0.400.350.300.250.200.150.100.050.050.150.20

ActinobacteriaAlphaproteobacteria

AnaerolineaeBacilli

BacteroidiaBetaproteobacteria

ClostridiaCytophagia

DeltaproteobacteriaEpsilonproteobacteria

FusobacteriaGammaproteobacteria

NegativicutesSphingobacteriia

Unclassified bacteriaLow abundance (<1%)

EXPLANATION

Figure 6. Nonmetric multidimensional scaling (NMDS) plots based on UniFrac distance matrices, with point locations represented by pie charts showing microbiology of the water samples at the class level. All classes listed were observed at an abundance of at least 1 percent (%); all classes identified at less than 1 percent were grouped together. A, NMDS plot for the four samples collected in the current study; the adonis2 result shown is for Oakdale Field versus the remaining three samples. B, NMDS plot for the two Bravo Dome samples collected for the current study and four samples collected from McElmo Dome in southwestern Colorado (Freedman and others, 2017). The McElmo Dome data are for two samples collected from two wells.
18 Analysis of Formation Water Geochemistry and Microbiology of Commercial and Carbon Dioxide-Rich Wells

in the current study. These differences between the current 

study and the study by Ham and others (2017) may be due 

to differences in DNA extraction methods, as observed by 

others (Cruaud and others, 2014; Mazziotti and others, 2018), 

or may be because the current study is more diverse in that 

the four samples analyzed were taken from three different 

subsurface environments.

Growth and Activity of Microbial 

Functional Groups in the Rafter “K” 

Ranch and Oakdale Field Samples

To assess the potential activity of microorganisms in a 

CO2 sequestration analogue, six microbial functional groups 

were targeted by using anaerobic cultivation in selective media 

under elevated CO2 headspace and varying salinities. Six 

microbial functional groups (autotrophs, FeRB, methanogens, 

NRB, SRB, and heterotrophs) were successfully cultured from 

both the Rafter “K” Ranch and Oakdale Field water samples 

(table 4). Water was not collected from the two Bravo Dome 

sites for anaerobic cultivation. The most growth and activity 

were observed in cultures with media salinities approximating 

that of the produced waters: 1 g/L NaCl for Rafter “K” Ranch 

and 20 g/L NaCl for Oakdale Field. No growth was observed 

in any of the cultivation controls (no inoculum).

Heterotroph and NRB cultures grew to the highest 

densities, as indicated by visual observations, which is not 

surprising because they were provided high concentrations of 

easily metabolized carbon substrates (peptone yeast extract 

glucose and glycerol, respectively). Growth was observed 

more quickly for heterotrophs compared to NRB cultures 

from the same media salinity, CO2 level, and site. Despite 

the ample growth and high level of biomass observed, nitrate 

Table 4. Growth and activity for microbial functional groups enriched from the Rafter “K” Ranch and Oakdale Field water samples 

under 20 or 100 percent carbon dioxide (CO2) headspace.

[Growth was assessed visually by changes in turbidity, with growth ranging from low (+) to high (++++) turbidity or no growth (−). The activity of ironreducing bacteria (FeRB) was confirmed by measuring accumulation of divalent iron, Fe(II). The activity of heterotrophs, autotrophs and methanogens was 

confirmed by measuring accumulation of methane (CH4). Decreasing nitrate (NO3

−) concentration confirmed the activity of nitrate-reducing bacteria (NRB). 

For sulfate-reducing bacteria (SRB), the presence (+) or absence (−) of hydrogen sulfide (H2S) was used to confirm activity. The intensity of H2S production 

was based on color change of lead acetate strips when in contact with a droplet of culture medium (none, no color change; +, faint color change; ++, moderately 

strong color change; and +++, intense color change). g/L, gram per liter; mmol/L, millimole per liter; μmol/L, micromole per liter; NaCl, sodium chloride; ND, 

none detected; BDL, below detection limit]

Inputs Outputs

Inoculum 

source

Percent 

headspace 

CO2

Media 

salinity (g/L 

NaCl)

FeRB growth/

Fe(II) (mmol/L)

SRB growth/

H2S

NRB growth/ 

NO3

−

(mmol/L)

Heterotrophs 

growth/CH4

(μmol/L)

Autotrophs 

growth/CH4

(μmol/L)

Acetoclastic 

methanogens 

growth/CH4

(μmol/L)

Oakdale 

Field

20 1 +++/25.84 +/++ +/33.00 +++/2.05 +/5.33 +/0.96

100 1 +++/17.00 +/++ +++/28.42 ++/0.01 +/7.34 +/0.61

20 20 +++/19.21 ++/+++ ++/11.32 ++++/24.34 ++/9.59 +/0.01

100 20 +++/18.61 +++/++ +++/22.42 +++/2.65 ++/8.90 +/0.81

20 100 weak +/2.23 weak +/none +/38.10 ++/0.01 −/ND −/0.02

100 100 +/1.42 −/none −/40.25 ++/0.01 −/ND −/0.01

Rafter “K” 

Ranch

20 1 ++/7.65 ++/++ +++/0.04 ++/0.31 ++/11.75 −/0.01

100 1 ++/8.46 ++/++ +/40.14 +/0.07 ++/7.94 −/BDL

20 20 −/1.02 +/+ +/30.39 +++/0.06 −/ND −/BDL

100 20 −/0.92 −/none ++/38.92 +++/0.04 weak +/0.09 −/BDL

20 100 −/0.97 −/none ++/33.87 −/0.23 −/ND −/0.01

100 100 −/0.97 −/none −/39.32 +/0.20 −/ND −/BDL

Control 20 1 −/1.07 −/none −/40.90 −/0.01 −/ND −/BDL

100 1 −/1.12 −/none −/38.92 −/0.01 −/ND −/0.01

20 20 −/1.07 −/none −/40.88 −/0.01 −/ND −/BDL

100 20 −/1.12 −/none −/41.75 −/0.01 −/ND −/0.01

20 100 −/0.92 −/none −/37.83 −/BDL −/ND −/BDL

100 100 −/0.82 −/none −/41.99 −/BDL −/ND −/BDL
References Cited 19

was reduced in only a subset of the NRB cultures (table 4). 

This result indicates that most organisms enriched in NRB 

cultures were growing fermentatively and were not using the 

supplemental nitrate as a terminal electron acceptor. Taken 

together, these observations suggest that influxes of organic 

carbon to either the Oakdale Field or Rafter “K” Ranch 

groundwater could stimulate rapid microbial growth. The high 

biomass resulting from the addition of organic-rich, fermentable substrates could lead to biofouling during in situ CO2

injection activities.

Methane production was observed under heterotrophic, 

autotrophic, and methanogenic culture conditions (table 4). 

Autotrophic cultures, which were supplied H2 as electron 

donor, were the most consistent producers of CH4, followed 

by heterotrophic cultures from Oakdale Field, heterotrophic 

cultures from Rafter “K” Ranch, and methanogenic cultures 

from Oakdale Field. No growth was observed under methanogenic conditions for cultures from Rafter “K” Ranch, and 

the growth and activity under methanogenic conditions for 

cultures from Oakdale Field were among the lowest of all 

cultures across treatments, suggesting that either the acetate 

supplied as electron donor and (or) the methanogenic culture 

media were not metabolically favored by the microbiota of 

either site. Hydrogenotrophic methanogenesis (CO2 + 4H2 → 

CH4 + 2H2O) was likely the source of all or most observed 

CH4, with H2 provided in autotrophic cultures or generated 

through organic carbon degradation in the other cultures. The 

organic carbon substrates provided (for example, citrate, lactate, glucose, and glycerol) can be degraded via fermentation, 

resulting in the production of H2 (Madigan and others, 2012), 

which can be used by hydrogenotrophic methanogens. The 

viability of methanogens in the Rafter “K” Ranch and Oakdale 

Field samples indicates that these populations have the potential to generate CH4 in situ if a hydrogen source is available.

Significant iron and SO4

2− concentrations were found 

in waters from both Rafter “K” Ranch and Oakdale Field 

(table 2), so it is reasonable to suspect that anaerobic cycling 

of both iron and sulfur occur in these groundwaters. Although 

anaerobic oxidation of these elements was not tested, activity of FeRB and SRB was confirmed by production of Fe(II) 

and H2S as end-products of trivalent iron (Fe[III]) and SO4

2−

reduction, respectively (table 4). Our results indicate that 

Oakdale Field FeRB and SRB are versatile; they were able to 

grow over a range of salinities and CO2 levels, but FeOOH 

appeared to be a more favorable electron acceptor than SO4

2−. 

In contrast, Rafter “K” Ranch FeRB and SRB grew only at the 

1-g/L-NaCl salinity, with only modest growth and activity, and 

neither electron acceptor seemed to be favored. Thus, there 

is potential for well souring via microbial SO4

2− reduction at 

both sites under the in situ conditions. Fluctuations in salinity 

at Rafter “K” Ranch, however, could inhibit microbial iron 

and SO4

2− reduction (as well as microbial growth in general), 

whereas Oakdale Field microbes may show little response to 

any (at least modest) change in salinity.

Conclusions

Studies of natural CO2 in reservoirs have the potential 

to offer insight into the effects of geologic CO2 sequestration. 

Here, samples from four naturally occurring CO2 reservoirs 

were analyzed to determine how these CO2-rich habitats 

affected the regional hydrology and microbial ecology of the 

subsurface. Although the sample size was small (n=4) and 

some sampling conditions were not ideal (for example, few 

sample sites were available from the Bravo Dome commercial 

unit), the hydrogeochemistry of the two Bravo Dome samples 

generally aligned with regional hydrogeochemical trends. The 

two Bravo Dome samples were geochemically different from 

each other, possibly suggesting compartmentalization in the 

reservoir, as suggested by previous studies. The Oakdale Field 

sample was isotopically different from regional trends, and 

the Rafter “K” Ranch sample was dramatically different from 

regional legacy water data, possibly due to high DIC concentrations induced by the high CO2 content in the well.

Although the microbial community composition of the 

Oakdale Field sample differed from the other samples, the 

microbial ecology of the four wells could not be tied to any 

hydrogeochemical or gas geochemical parameters, nor were 

any OTUs significantly associated with a site. Differences in 

microbial ecology across the four sites may be linked to redox 

conditions or differences in lithology. Although no hydrogeochemical parameters were significantly associated with the 

microbial ecology of the samples, they still may be influencing 

the microbial community composition to some extent.

Distinct patterns in microbial growth and activity by site 

underscore the importance of local groundwater geochemistry and microbial ecology in predicting the outcomes of CO2

injection into deep geologic formations. Moreover, the strong 

stimulatory effects of nutrient amendments, particularly bioavailable carbon, on the elevated CO2-tolerant microbes show 

that unintended influxes into the subsurface systems, such 

as septic tank leakage, can greatly alter microbial responses. 

Taken together, these observations suggest that natural biogeochemical conditions and regional anthropogenic activities 

must be accounted for in the long-term planning of a CO2

injection project.

References Cited

Aitchison, J., 1986, The statistical analysis of compositional 

data: London, Chapman & Hall, 416 p.

Akhbari, D., and Hesse, M.A., 2017, Causes of underpressure in natural CO2 reservoirs and implications for geological storage: Geology, v. 45, no. 1, p. 47–50, accessed 

January 2018 at https://doi.org/10.1130/G38362.1.
20 Analysis of Formation Water Geochemistry and Microbiology of Commercial and Carbon Dioxide-Rich Wells

Allis, R., Chidsey, T., Gwynn, W., Morgan, C., White, S., 

Adams, M., and Moore, J., 2001, Natural CO2 reservoirs 

on the Colorado Plateau and southern Rocky Mountains—

Candidates for CO2 sequestration, in Proceedings of 

the First National Conference on Carbon Sequestration, 

Washington, D.C., May 14–17, 2001: Morgantown, W.Va., 

U.S. Department of Energy, National Energy Technology 

Laboratory, 19 p.

Apprill, A., McNally, S., Parsons, R., and Weber, L., 2015, 

Minor revision to V4 region SSU rRNA 806R gene primer 

greatly increases detection of SAR11 bacterioplankton: 

Aquatic Microbial Ecology, v. 75, no. 2, p. 129–137. [Also 

available at https://doi.org/10.3354/ame01753.]

Baines, S.J., and Worden, R.H., 2004, Geological storage of 

carbon dioxide, in Baines, S.J., and Worden, R.H., eds., 

Geological storage of carbon dioxide: London, Geological 

Society of London Special Publication, v. 233, p. 1–6, 

accessed January 2018 at https://doi.org/10.1144/GSL.

SP.2004.233.01.01.

Balabane, M., Galimov, E., Hermann, M., and Létolle, 

R., 1987, Hydrogen and carbon isotope fractionation 

during experimental production of bacterial methane: Organic Geochemistry, v. 11, no. 2, p. 115–119, 

accessed January 2018 at https://doi.org/10.1016/0146-

6380(87)90033-7.

Balch, W.E., Schoberth, S., Tanner, R.S., and Wolfe, R.S., 

1977, Acetobacterium, a new genus of hydrogen-oxidizing, 

carbon dioxide-reducing, anaerobic bacteria: International 

Journal of Systematic and Evolutionary Microbiology, v. 27, 

no. 4, p. 355–361, accessed January 2018 at https://doi.org/

10.1099/00207713-27-4-355.

Ballentine, C.J., Schoell, M., Coleman, D., and Cain, B.A., 

2001, 300-Myr-old magmatic CO2 in natural gas reservoirs of the west Texas Permian Basin: Nature, v. 409, 

p. 327–331. [Also available at https://doi.org/10.1038/

35053046.]

Baltz, E.H., 1965, Stratigraphy and history of Raton Basin and 

notes on San Luis Basin, Colorado-New Mexico: American 

Association of Petroleum Geologists Bulletin, v. 49, 

p. 2041–2075, accessed January 2018 at https://doi.org/

10.1306/A6633882-16C0-11D7-8645000102C1865D.

Barberán, A., Ladau, J., Leff, J.W., Pollard, K.S., Menninger, 

H.L., Dunn, R.R., and Fierer, N., 2015, Continentalscale distributions of dust-associated bacteria and fungi: 

Proceedings of the National Academy of Sciences of the 

United States of America, v. 112, no. 18, p. 5756–5761, 

accessed January 2018 at https://doi.org/10.1073/

pnas.1420815112.

Berlendis, S., Ranchou-Peyruse, M., Fardeau, M.-L., 

Lascourrèges, J.-F., Joseph, M., Ollivier, B., Aüllo, T., 

Dequidt, D., Magot, M., and Ranchou-Peyruse, A., 2016, 

Desulfotomaculum aquiferis sp. nov. and Desulfotomaculum 

profundi sp. nov., isolated from a deep natural gas storage aquifer: International Journal of Systematic and 

Evolutionary Microbiology, v. 66, no. 11, p. 4329–4338, 

accessed January 2018 at https://doi.org/10.1099/

ijsem.0.001352.

Blondes, M.S., Gans, K.D., Engle, M.A., Kharaka, Y.K., 

Reidy, M.E., Saraswathula, V., Thordsen, J.J., Rowan, 

E.L., and Morrissey, E.A., 2018, U.S. Geological Survey 

National Produced Waters Geochemical Database (ver. 2.3, 

Jan 2018): U.S. Geological Survey data release, accessed 

January 2018 at https://doi.org/10.5066/F7J964W8.

Brennan, S.T., 2017, Chemical and isotopic evidence for CO2

charge and migration within Bravo Dome and potential 

CO2 leakage to the southwest: Energy Procedia, v. 114, 

p. 2996–3005, accessed January 2018 at https://doi.org/

10.1016/j.egypro.2017.03.1428.

Broadhead, R.F., 1990, Bravo Dome carbon dioxide gas field, 

in Beaumont, E.A., and Foster, N.H., comps., Structural 

traps I—Tectonic fold traps: Tulsa, Okla., American 

Association of Petroleum Geologists, p. 213–232, accessed 

January 2018 at http://archives.datapages.com/data/

specpubs/fieldst3/data/a015/a015/0001/0200/0213.htm.

Broadhead, R.F., Mansell, M., and Jones, G., 2009, Carbon 

dioxide in New Mexico—Geologic distribution of natural 

occurrences: New Mexico Bureau of Geology and Mineral 

Resources Open-File Report 514, 131 p.

Buccianti, A., and Pawlowsky-Glahn, V., 2005, New perspectives on water chemistry and compositional data analysis: 

Mathematical Geology, v. 37, no. 7, p. 703–727, accessed 

January 2018 at https://doi.org/10.1007/s11004-005-7376-6.

Caporaso, J.G., Kuczynski, J., Stombaugh, J., Bittinger, K., 

Bushman, F.D., Costello, E.K., Fierer, N., Gonzalez Pena, 

A., Goodrich, J.K., Gordon, J.I., Huttley, G.A., Kelley, 

S.T., Knights, D., Koenig, J.E., Ley, R.E., Lozupone, C.A., 

McDonald, D., Muegge, B.D., Pirrung, M., Reeder, J., 

Sevinsky, J.R., Turnbaugh, P.J., Walters, W.A., Widmann, J., 

Yatsunenko, T., Zaneveld, J., and Knight, R., 2010, QIIME 

allows analysis of high-throughput community sequencing data: Nature Methods, v. 7, no. 5, p. 335–336, accessed 

January 2018 at https://doi.org/10.1038/nmeth.f.303.

Clark, I.D., and Fritz, P., 1997, Environmental Isotopes in 

Hydrogeology: Boca Raton, Fla., Lewis Publishers, 342 p.
References Cited 21

Clayton, R.N., Friedman, I., Graf, D.L., Mayeda, T.K., 

Meents, W.F., and Shimp, N.F., 1966, The origin of saline 

formation waters—1. isotopic composition: Journal 

of Geophysical Research, v. 71, no. 16, p. 3869–3882, 

accessed January 2018 at https://doi.org/10.1029/

JZ071i016p03869.

Colorado Oil and Gas Conservation Commission, 2018, 

Colorado Oil and Gas Information System (COGIS): 

Colorado Oil and Gas Conservation Commission, accessed 

January 2018 at https://cogcc.state.co.us/data.html#/cogis.

Coplen, T.B., and Kendall, C., 2000, Stable hydrogen and 

oxygen isotope ratios for selected sites of the US Geological 

Survey’s NASQAN and benchmark surface-water networks: 

U.S. Geological Survey Open-File Report 00–160, 409 p. 

[Also available at https://doi.org/10.3133/ofr00160.]

Craddock, W.H., Blondes, M.S., DeVera, C.A., and Hunt, 

A.G., 2017, Mantle and crustal gases of the Colorado 

Plateau—Geochemistry, sources, and migration pathways: 

Geochimica et Cosmochimica Acta, v. 213, p. 346–374, 

accessed January 2018 at https://doi.org/10.1016/

j.gca.2017.05.017.

Craig, H., 1961, Isotopic variations in meteoric 

waters: Science, v. 133, no. 3465, p. 1702–1703, 

accessed January 2018 at https://doi.org/10.1126/

science.133.3465.1702.

Crossey, L.J., Karlstrom, K.E., Springer, A.E., Newell, D., 

Hilton, D.R., and Fischer, T., 2009, Degassing of mantlederived CO2 and He from springs in the southern Colorado 

Plateau region—Neotectonic connections and implications 

for groundwater systems: Geological Society of America 

Bulletin, v. 121, nos. 7–8, p. 1034–1053. [Also available at 

https://doi.org/10.1130/B26394.1.]

Cruaud, P., Vigneron, A., Lucchetti-Miganeh, C., Ciron, 

P.E., Godfroy, A., and Cambon Bonavita, M.-A., 2014, 

Influence of DNA extraction method, 16S rRNA targeted 

hypervariable regions, and sample origin on microbial 

diversity detected by 454 pyrosequencing in marine 

chemosynthetic ecosystems: Applied and Environmental 

Microbiology, v. 80, no. 15, p. 4626–4639. [Also available 

at https://doi.org/10.1128/AEM.00592-14.]

De Cáceres, M., and Legendre, P., 2009, Associations between 

species and groups of sites—Indices and statistical inference: Ecology, v. 90, no. 12, p. 3566–3574. [Also available 

at https://doi.org/10.1890/08-1823.1.]

De Filippo, C., Cavalieri, D., Di Paola, M., Ramazzotti, M., 

Poullet, J.B., Massart, S., Collini, S., Pieraccini, G., and 

Lionetti, P., 2010, Impact of diet in shaping gut microbiota 

revealed by a comparative study in children from Europe 

and rural Africa: Proceedings of the National Academy of 

Sciences of the United States of America, v. 107, no. 33, 

p. 14691–14696, accessed January 2018 at https://doi.org/

10.1073/pnas.1005963107.

EarthChem, 2018, EarthChem Portal: EarthChem, accessed 

January 2018 at https://www.earthchem.org/portal.

Egozcue, J.J., Pawlowsky-Glahn, V., Mateu-Figueras, G., 

and Barceló-Vidal, C., 2003, Isometric logratio transformations for compositional data analysis: Mathematical 

Geology, v. 35, no. 3, p. 279–300, accessed January 2018 at 

https://doi.org/10.1023/A:1023818214614.

Engle, M.A., and Blondes, M.S., 2014, Linking compositional data analysis with thermodynamic geochemical 

modeling—Oilfield brines from the Permian Basin, USA: 

Journal of Geochemical Exploration, v. 141, p. 61–70, 

accessed January 2018 at https://doi.org/10.1016/

j.gexplo.2014.02.025.

Engle, M.A., and Rowan, E.L., 2013, Interpretation of 

Na–Cl–Br systematics in sedimentary basin brines—

Comparison of concentration, element ratio, and isometric 

log-ratio approaches: Mathematical Geosciences, v. 45, 

no. 1, p. 87–101, accessed January 2018 at https://doi.org/

10.1007/s11004-012-9436-z.

Engle, M.A., and Rowan, E.L., 2014, Geochemical evolution of produced waters from hydraulic fracturing of the 

Marcellus Shale, northern Appalachian basin—A multivariate compositional data analysis approach: International 

Journal of Coal Geology, v. 126, p. 45–56, accessed 

January 2018 at https://doi.org/10.1016/j.coal.2013.11.010.

Freedman, A.J.E., Tan, B., and Thompson, J.R., 2017, 

Microbial potential for carbon and nutrient cycling in a geogenic supercritical carbon dioxide reservoir: Environmental 

Microbiology, v. 19, no. 6, p. 2228–2245, accessed 

January 2018 at https://doi.org/10.1111/1462-2920.13706.

Geyh, M., D’Amore, F., Darling, G., Paces, T., Pang, Z., and 

Šilar, J., 2001, Groundwater—Saturated and unsaturated 

zone, v. IV of Environmental isotopes in the hydrological 

cycle—Principles and applications: Vienna, International 

Atomic Energy Agency Water Resources Programme., 

p. 311–424.
22 Analysis of Formation Water Geochemistry and Microbiology of Commercial and Carbon Dioxide-Rich Wells

Gilfillan, S.M.V., Ballentine, C.J., Holland, G., Blagburn, 

D., Lollar, B.S., Stevens, S., Schoell, M., and Cassidy, 

M., 2008, The noble gas geochemistry of natural CO2

gas reservoirs from the Colorado Plateau and Rocky 

Mountain provinces, USA: Geochimica et Cosmochimica 

Acta, v. 72, no. 4, p. 1174–1198, accessed January 2018 at 

https://doi.org/10.1016/j.gca.2007.10.009.

Gilfillan, S.M.V., Lollar, B.S., Holland, G., Blagburn, D., 

Stevens, S., Schoell, M., Cassidy, M., Ding, Z., Zhou, 

Z., Lacrampe-Couloume, G., and Ballentine, C.J., 2009, 

Solubility trapping in formation water as dominant 

CO2 sink in natural gas fields: Nature, v. 458, no. 7238, 

p. 614–618, accessed January 2018 at https://doi.org/

10.1038/nature07852.

González, J.M., Mayer, F., Moran, M.A., Hodson, R.E., and 

Whitman, W.B., 1997, Microbulbifer hydrolyticus gen. nov., 

sp. nov., and Marinobacterium georgiense gen. nov., sp. 

nov., two marine bacteria from a lignin-rich pulp mill waste 

enrichment community: International Journal of Systematic 

and Evolutionary Microbiology, v. 47, no. 2, p. 369–376, 

accessed January 2018 at https://doi.org/10.1099/00207713-

47-2-369.

Grabowski, A., Nercessian, O., Fayolle, F., Blanchet, D., 

and Jeanthon, C., 2005, Microbial diversity in production 

waters of a low-temperature biodegraded oil reservoir: 

FEMS Microbiology Ecology, v. 54, no. 3, p. 427–443, 

accessed January 2018 at https://doi.org/10.1016/

j.femsec.2005.05.007.

Grice, E.A., Kong, H.H., Renaud, G., and Young, A.C., 

NISC Comparative Sequencing Program, Bouffard, G.G., 

Blakesley, R.W., Wolfsberg, T.G., Turner, M.L., and Serge, 

J.A., 2008, A diversity profile of the human skin microbiota: 

Genome Research, v. 18, no. 7, p. 1043–1050, accessed 

January 2018 at https://doi.org/10.1101/gr.075549.107.

Ham, B., Choi, B.-Y., Chae, G.-T., Kirk, M.F., and Kwon, 

M.J., 2017, Geochemical influence on microbial communities at CO2-leakage analog sites: Frontiers in 

Microbiology, v. 8, article no. 2203, 15 p., accessed 

January 2018 at https://doi.org/10.3389/fmicb.2017.02203.

Hardalo, C., and Edberg, S.C., 1997, Pseudomonas 

aeruginosa—Assessment of risk from drinking water: 

Critical Reviews in Microbiology, v. 23, no. 1, p. 47–75, 

accessed January 2018 at https://doi.org/10.3109/

10408419709115130.

Hartig, K.A., Soreghan, G.S., Goldstein, R.H., and Engel, 

M.H., 2011, Dolomite in Permian paleosols of the Bravo 

Dome CO2 field, U.S.A.—Permian reflux followed by 

late recrystallization at elevated temperature: Journal of 

Sedimentary Research, v. 81, no. 4, p. 248–265, accessed 

January 2018 at https://doi.org/10.2110/jsr.2011.24.

Haszeldine, R.S., Quinn, O., England, G., Wilkinson, M., 

Shipton, Z.K., Evans, J.P., Heath, J., Crossey, L., Ballentine, 

C.J., and Graham, C.M., 2005, Natural geochemical analogues for carbon dioxide storage in deep geological porous 

reservoirs, a United Kingdom perspective: Oil & Gas 

Science and Technology, v. 60, no. 1, p. 33–49. [Also available at https://doi.org/10.2516/ogst:2005004.]

Hubert, C., and Voordouw, G., 2007, Oil field souring control 

by nitrate-reducing Sulfurospirillum spp. that outcompete 

sulfate-reducing bacteria for organic electron donors: 

Applied and Environmental Microbiology, v. 73, no. 8, 

p. 2644–2652, accessed January 2018 at https://doi.org/

10.1128/AEM.02332-06.

Irgens, R.L., 1977, Meniscus, a new genus of aerotolerant, gas-vacuolated bacteria: International Journal of 

Systematic and Evolutionary Microbiology, v. 27, no. 1, 

p. 38–43, accessed January 2018 at https://doi.org/10.1099/

00207713-27-1-38.

Johnson, R.E., 1983, Bravo Dome carbon dioxide area, northeast New Mexico, in Fassett, J.E., ed., Oil and gas fields of 

the Four Corners area v. III: Durango, Colo., Four Corners 

Geological Society, p. 745–748.

Kakiuchi, M., and Matsuo, S., 1979, Direct measurements 

of D/H and 18O/16O fractionation factors between vapor 

and liquid water in the temperature range from 10 to 40°C: 

Geochemical Journal, v. 13, no. 6, p. 307–311. [Also available at https://doi.org/10.2343/geochemj.13.307.]

Kharaka, Y.K., and Hanor, J.S., 2003, Deep fluids in the 

continents—I. sedimentary basins, chap. 16 of Drever, J.I., 

ed., Surface and ground water, weathering, and soils, v. 5 

of Holland, H.D., and Turekian, K.K., eds., Treatise on 

geochemistry: Amsterdam, Elsevier, 48 p.

Kharaka, Y.K., Thordsen, J.J., Kakouros, E., Ambats, G., 

Herkelrath, W.N., Beers, S.R., Birkholzer, J.T., Apps, J.A., 

Spycher, N.F., Zheng, L., Trautz, R.C., Rauch, H.W., and 

Gullickson, K.S., 2010, Changes in the chemistry of shallow groundwater related to the 2008 injection of CO2 at the 

ZERT field site, Bozeman, Montana: Environmental Earth 

Sciences, v. 60, no. 2, p. 273–284, accessed January 2018 at 

https://doi.org/10.1007/s12665-009-0401-1.

Konter, J.G., and Storm, L.P., 2014, High precision 87Sr/86Sr 

measurements by MC-ICP-MS, simultaneously solving for 

Kr interferences and mass-based fractionation: Chemical 

Geology, v. 385, p. 26–34, accessed January 2018 at 

https://doi.org/10.1016/j.chemgeo.2014.07.009.

Kostka, J.E., and Luther, G.W., III, 1994, Partitioning 

and speciation of solid-phase iron in saltmarsh sediments: Geochimica et Cosmochimica Acta, v. 58, no. 7, 

p. 1701–1710. [Also available at https://doi.org/10.1016/

0016-7037(94)90531-2.]
References Cited 23

Kuever, J., and Rainey, F.A., 2015, Desulfotomaculum, in

Whitman, W.B., ed., Bergey’s manual of systematics 

of archaea and bacteria: Hoboken, N.J., John Wiley & 

Sons, 12 p.

Lambiase, A., 2014, The family Sphingobacteriaceae, chap. 

72 of Rosenberg, E., DeLong, E.F., Lory, S., Stackebrandt, 

E., and Thompson, F., eds., The prokaryotes—Other major 

lineages of bacteria and the archaea: Berlin, Springer, 

p. 907–914.

Lastovica, A.J., On, S.L.W., and Zhang, L., 2014, The family Campylobacteraceae, chap. 23 of Rosenberg, E., 

DeLong, E.F., Loy, S., Stackebrandt, E., and Thompson, 

F., eds., The prokaryotes—Deltaproteobacteria and 

Epsilonpoteobacteria: Berlin, Springer, p. 307–335.

Leff, J.W., Del Tredici, P., Friedman, W.E., and Fierer, 

N., 2015, Spatial structuring of bacterial communities 

within individual Ginkgo biloba trees: Environmental 

Microbiology, v. 17, no. 7, p. 2352–2361, accessed 

January 2018 at https://doi.org/10.1111/1462-2920.12695.

Lovell, D., Müller, W., Taylor, J., Zwart, A., and Helliwell, 

C., 2011, Proportions, percentages, PPM—Do the molecular biosciences treat compositional data right?, chap. 

14 of Pawlowsky-Glahn, V., and Buccianti, A., eds., 

Compositional data analysis—Theory and applications: 

Chichester, England, John Wiley & Sons, p. 191–207.

Lovley, D.R., and Phillips, E.J.P., 1986, Organic matter 

mineralization with reduction of ferric iron in anaerobic 

sediments: Applied and Environmental Microbiology, v. 51, 

no. 4, p. 683–689. [Also available at https://doi.org/10.1128/

AEM.51.4.683-689.1986.]

Lucas, S.G., and Hunt, A.P., 1987, Stratigraphy of the Anton 

Chico and Santa Rosa Formations, Triassic of east-central 

New Mexico: Journal of the Arizona-Nevada Academy of 

Science, v. 22, no. 1, p. 21–33.

Luongo, J.C., Barberán, A., Hacker-Cary, R., Morgan, E.E., 

Miller, S.L., and Fierer, N., 2016, Microbial analyses of airborne dust collected from dormitory rooms predict the sex 

of occupants: International Journal of Indoor Environment 

and Health, v. 27, no. 2, p. 338–344, accessed January 2018 

at https://doi.org/10.1111/ina.12302.

Madigan, M.T., Martinko, J.M., Stahl, D.A., and Clark, D.P., 

2012, Brock biology of microorganisms: San Francisco, 

Benjamin Cummings, 1,152 p.

Marchandin, H., and Jumas-Bilak, E., 2014, The family 

Veillonellaceae, chap. 35 of Rosenberg, E., DeLong, E.F., 

Lory, S., Stackebrandt, E., and Thompson, F., eds., The 

prokaryotes—Firmicutes and Tenericutes: Berlin, Springer, 

p. 433–453.

Mazziotti, M., Henry, S., Laval-Gilly, P., Bonnefoy, A., 

and Falla, J., 2018, Comparison of two bacterial DNA 

extraction methods from non-polluted and polluted soils: 

Folia Microbiologica, v. 63, no. 1, p. 85–92, accessed 

January 2018 at https://doi.org/10.1007/s12223-017-0530-y.

Oksanen, J., Blanchet, F.G., Kindt, R., Legendre, P., Minchin, 

P.R., O’Hara, R.B., Simpson, G.L., Solymos, P., Stevens, 

M.H.H., Szoecs, E., and Wagner, H., 2013, vegan—

Community ecology package, version 2(5-2): R Foundation 

for Statistical Computing software release, accessed 

January 2018 at https://cran.r-project.org/web/packages/

vegan/index.html.

Owen, D.E., 1966, Nomenclature of Dakota Sandstone 

(Cretaceous) in San Juan Basin, New Mexico and 

Colorado—GEOLOGICAL NOTES: American 

Association of Petroleum Geologists Bulletin, v. 50, no. 5, 

p. 1023–1028, accessed January 2018 at https://doi.org/

10.1306/5D25B60F-16C1-11D7-8645000102C1865D.

Palleroni, N.J., 2015, Pseudomonas, in Whitman, W.B., ed., 

Bergey’s manual of systematics of archaea and bacteria: 

Hoboken, N.J., John Wiley & Sons, 56 p.

Parada, A.E., Needham, D.M., and Fuhrman, J.A., 2016, Every 

base matters—Assessing small subunit rRNA primers for 

marine microbiomes with mock communities, time series 

and global field samples: Environmental Microbiology, 

v. 18, no. 5, p. 1403–1414, accessed January 2018 at 

https://doi.org/10.1111/1462-2920.13023.

 Pawlowsky-Glahn, V., and Buccianti, A., eds., 2011, 

Compositional data analysis—Theory and applications: 

Chichester, England, John Wiley & Sons, 378 p. [Also 

available at https://doi.org/10.1002/9781119976462.]

Peet, K.C., Freedman, A.J.E., Hernandez, H.H., Britto, V., 

Boreham, C., Ajo-Franklin, J.B., and Thompson, J.R., 2015, 

Microbial growth under supercritical CO2: Applied and 

Environmental Microbiology, v. 81, no. 8, p. 2881–2892, 

accessed January 2018 at https://doi.org/10.1128/

AEM.03162-14.

Peter, A., Lamert, H., Beyer, M., Hornbruch, G., Heinrich, 

B., Schulz, A., Geistlinger, H., Schreiber, B., Dietrich, P., 

Werban, U., Vogt, C., Richnow, H.-H., Großmann, J., and 

Dahmke, A., 2012, Investigation of the geochemical impact 

of CO2 on shallow groundwater—Design and implementation of a CO2 injection test in Northeast Germany: 

Environmental Earth Sciences, v. 67, no. 2, p. 335–349, 

accessed January 2018 at https://doi.org/10.1007/s12665-

012-1700-5.

Petroleum Recovery Research Center, 2018, New Mexico 

Produced Water Quality Database version 2: Petroleum 

Recovery Research Center, New Mexico Institute of 

Mining and Technology, accessed January 2018 at 

http://gotech.nmt.edu/gotech/Water/producedwater.aspx.
24 Analysis of Formation Water Geochemistry and Microbiology of Commercial and Carbon Dioxide-Rich Wells

Pruesse, E., Quast, C., Knittel, K., Fuchs, B.M., Ludwig, 

W., Peplies, J., and Glöckner, F.O., 2007, SILVA—A 

comprehensive online resource for quality checked and 

aligned ribosomal RNA sequence data compatible with 

ARB: Nucleic Acids Research, v. 35, no. 21, p. 7188–7196, 

accessed January 2018 at https://doi.org/10.1093/

nar/gkm864.

QIIME 2 Development Team, 2017, “Moving pictures” tutorial: QIIME 2 web page, accessed 2017 at 

https://docs.qiime2.org/2017.11/tutorials/moving-pictures/.

QIIME 2 Development Team, 2018, Data resources: QIIME 2 

web page, accessed 2018 at https://docs.qiime2.org/2018.4/

data-resources/#.

Quast, C., Pruesse, E., Yilmaz, P., Gerken, J., Schweer, T., 

Yarza, P., Peplies, J., and Glöckner, F.O., 2013, The SILVA 

ribosomal RNA gene database project—Improved data 

processing and web-based tools: Nucleic Acids Research, 

v. 41, D1, p. D590–D596, accessed January 2018 at 

https://doi.org/10.1093/nar/gks1219.

R Core Team, 2017, R—A language and environment 

for statistical computing, version 3.4.3: R Foundation 

for Statistical Computing software release, accessed 

January 2018 at https://www.r-project.org/.

Ramirez, K.S., Leff, J.W., Barberán, A., Bates, S.T., Betley, 

J., Crowther, T.W., Kelly, E.F., Oldfield, E.E., Shaw, E.A., 

Steenbock, C., Bradford, M.A., Wall, D.H., and Fierer, N., 

2014, Biogeographic patterns in below-ground diversity in 

New York City’s Central Park are similar to those observed 

globally: Proceedings of the Royal Society B, v. 281, 

no. 1795, 9 p., accessed January 2018 at https://doi.org/

10.1098/rspb.2014.1988.

Rochelle, C.A., Pearce, J.M., and Holloway, S., 1999, 

The underground sequestration of carbon dioxide—

Containment by chemical reactions in the deep geosphere: 

Geological Society, London, Special Publications, v. 157, 

no. 1, p. 117–129, accessed January 2018 at https://doi.

org/10.1144/GSL.SP.1999.157.01.09.

Roth, G., 1983, Sheep Mountain and Dike Mountain fields, 

Huerfano County, Colorado; a source of CO2 for enhanced 

oil recovery, in Fassett, J.E., ed., Oil and gas fields of the 

Four Corners area v. III: Durango, Colo., Four Corners 

Geological Society, p. 740–744.

Salter, S.J., Cox, M.J., Turek, E.M., Calus, S.T., Cookson, 

W.O., Moffatt, M.F., Turner, P., Parkhill, J., Loman, N.J., 

and Walker, A.W., 2014, Reagent and laboratory contamination can critically impact sequence-based microbiome 

analyses: BMC Biology, v. 12, article no. 87, 12 p., accessed 

January 2018 at https://doi.org/10.1186/s12915-014-0087-z.

Sathaye, K.J., Hesse, M.A., Cassidy, M., and Stockli, D.F., 

2014, Constraints on the magnitude and rate of CO2 dissolution at Bravo Dome natural gas field: Proceedings of 

the National Academy of Sciences of the United States 

of America, v. 111, no. 43, p. 15332–15337, accessed 

January 2018 at https://doi.org/10.1073/pnas.1406076111.

Shannon, C.E., 1948, A mathematical theory of communication: The Bell System Technical Journal, v. 27, no. 3, 

p. 379–423. [Also available at https://doi.org/10.1002/

j.1538-7305.1948.tb01338.x.]

Shelton, J.L., DeVera, C.A., Morrissey, E.A., Akob, D., 

Andrews, R., Mumford, A., Brennan, S., and Plampin, M., 

2018, Microbiology of the greater Bravo Dome region: U.S. 

Geological Survey data release, https://doi.org/10.5066/

F76M361R.

Shelton, J.L., Engle, M.A., Buccianti, A., and Blondes, M.S., 

2018, The isometric log-ratio (ilr)-ion plot—A proposed 

alternative to the Piper diagram: Journal of Geochemical 

Exploration, v. 190, p. 130–141. [Also available at 

https://doi.org/10.1016/j.gexplo.2018.03.003.]

Shelton, J.L., McIntosh, J.C., Hunt, A.G., Beebe, T.L., Parker, 

A.D., Warwick, P.D., Drake, R.M., II, and McCray, J.E., 

2016, Determining CO2 storage potential during miscible 

CO2 enhanced oil recovery—Noble gas and stable isotope 

tracers: International Journal of Greenhouse Gas Control, 

v. 51, p. 239–253. [Also available at https://doi.org/10.1016/

j.ijggc.2016.05.008.]

Sierra-Garcia, I.N., Dellagnezze, B.M., Santos, V.P., Chaves, 

M.R.B., Capilla, R., Santos Neto, E.V., Gray, N., and 

Oliveira, V.M., 2017, Microbial diversity in degraded and 

non-degraded petroleum samples and comparison across oil 

reservoirs at local and global scales: Extremophiles, v. 21, 

no. 1, p. 211–229, accessed January 2018 at https://doi.org/

10.1007/s00792-016-0897-8.

Stackebrandt, E., 2014, The family Eubacteriaceae, chap. 8 

of Rosenberg, E., DeLong, E.F., Lory, S., Stackebrandt, E., 

and Thompson, F., eds., The prokaryotes—Firmicutes and 

Tenericutes: Berlin, Springer, p. 107–108.

Stevens, S.H., 2005, Natural CO2 fields as analogs for geologic CO2 storage, chap. 3 of Benson, S.M., ed., Geologic 

storage of carbon dioxide with monitoring and verification, 

v. 2 of Carbon dioxide capture for storage in deep geologic 

formations—Results from the CO2 capture project: Oxford, 

England, Elsevier, p. 687–697.
References Cited 25

Stevens, S.H., Pearce, J.M., and Rigg, A.A.J., 2001, Natural 

analogs for geologic storage of CO2—An integrated global 

research program, in Proceedings of the First National 

Conference of Carbon Sequestration, Washington, D.C., 

May 14–17, 2001: Morgantown, W.Va., U.S. Department of 

Energy, National Energy Technology Laboratory, 12 p.

Stover, C.K., Pham, X.Q., Erwin, A.L., Mizoguchi, S.D., 

Warrener, P., Hickey, M.J., Brinkman, F.S.L., Hufnagle, 

W.O., Kowalik, D.J., Lagrou, M., Garber, R.L., Goltry, L., 

Tolentino, E., Westbrock-Wadman, S., Yuan, Y., Brody, 

L.L., Coulter, S.N., Folger, K.R., Kas, A., Larbig, K., Lim, 

R., Smith, K., Spencer, D., Wong, G.K.-S., Wu, Z., Paulsen, 

I.T., Reizer, J., Saier, M.H., Hancock, R.E.W., Lory, S., 

and Olson, M.V., 2000, Complete genome sequence of 

Pseudomonas aeruginosa PAO1, an opportunistic pathogen: 

Nature, v. 406, no. 6799, p. 959–964. [Also available at 

https://doi.org/10.1038/35023079.]

Su, X.-L., Tian, Q., Zhang, J., Yuan, X.-Z., Shi, X.-S., Guo, 

R.-B., and Qiu, Y.-L., 2014, Acetobacteroides hydrogenigenes gen. nov., sp. nov., an anaerobic hydrogen-producing 

bacterium in the family Rikenellaceae isolated from a 

reed swamp: International Journal of Systematic and 

Evolutionary Microbiology, v. 64, no. 9, p. 2986–2991, 

accessed January 2018 at https://doi.org/10.1099/

ijs.0.063917-0.

Sun, B., Cole, J.R., Sanford, R.A., and Tiedje, J.M., 2000, 

Isolation and characterization of Desulfovibrio dechloracetivorans sp. nov., a marine dechlorinating bacterium 

growing by coupling the oxidation of acetate to the 

reductive dechlorination of 2-chlorophenol: Applied and 

Environmental Microbiology, v. 66, no. 6, p. 2408–2413, 

accessed January 2018 at https://doi.org/10.1128/

AEM.66.6.2408-2413.2000.

Sun, L., Toyonaga, M., Ohashi, A., Tourlousse, D.M., 

Matsuura, N., Meng, X.-Y., Tamaki, H., Hanada, S., Cruz, 

R., Yamaguchi, T., and Sekiguchi, Y., 2016, Lentimicrobium 

saccharophilum gen. nov., sp. nov., a strictly anaerobic bacterium representing a new family in the phylum 

Bacteroidetes, and proposal of Lentimicrobiaceae fam. 

nov: International Journal of Systematic and Evolutionary 

Microbiology, v. 66, no. 7, p. 2635–2642, accessed 

January 2018 at https://doi.org/10.1099/ijsem.0.001103.

Takeuchi, M., and Yokota, A., 1992, Proposals of 

Sphingobacterium faecium sp. nov., Sphingobacterium 

piscium sp. nov., Sphingobacterium heparinum comb. nov., 

Sphingobacterium thalpophilum comb. nov. and two genospecies of the genus Sphingobacterium, and synonymy of 

Flavobacterium yabuuchiae and Sphingobacterium spiritivorum: The Journal of General and Applied Microbiology, 

v. 38, no. 5, p. 465–482, accessed January 2018 at 

https://doi.org/10.2323/jgam.38.465.

Tschech, A., and Pfennig, N., 1984, Growth yield increase 

linked to caffeate reduction in Acetobacterium woodii: 

Archives of Microbiology, v. 137, no. 2, p. 163–167. [Also 

available at https://doi.org/10.1007/BF00414460.]

U.S. Environmental Protection Agency, 2016, Hydraulic fracturing for oil and gas—Impacts from the hydraulic fracturing water cycle on drinking water resources in the United 

States: Washington, D.C., U.S. Environmental Protection 

Agency, EPA–600–R–16–236F, variously paged, accessed 

January 2018 at https://cfpub.epa.gov/ncea/hfstudy/

recordisplay.cfm?deid=332990.

U.S. Geological Survey, 2018, USGS water data for the 

Nation: U.S. Geological Survey National Water Information 

System database, accessed January 2018 at https://doi.org/

10.5066/F7P55KJN.

Vandieken, V., Knoblauch, C., and Jørgensen, B.B., 2006, 

Desulfotomaculum arcticum sp. nov., a novel sporeforming, moderately thermophilic, sulfate-reducing 

bacterium isolated from a permanently cold fjord sediment of Svalbard: International Journal of Systematic 

and Evolutionary Microbiology, v. 56, no. 4, p. 687–690, 

accessed January 2018 at https://doi.org/10.1099/

ijs.0.64058-0.

Walters, W., Hyde, E.R., Berg-Lyons, D., Ackermann, G., 

Humphrey, G., Parada, A., Gilbert, J.A., Jansson, J.K., 

Caporaso, J.G., Fuhrman, J.A., Apprill, A., and Knight, R., 

2015, Improved bacterial 16S rRNA gene (V4 and V4-5) 

and fungal internal transcribed spacer marker gene primers 

for microbial community surveys: mSystems, v. 1, no. 1, 

article no. e00009-15, 10 p., accessed January 2018 at 

https://doi.org/10.1128/mSystems.00009-15.

Weon, H.-Y., Kim, B.-Y., Yoo, S.-H., Lee, S.-Y., Kwon, S.-W., 

Go, S.-J., and Stackebrandt, E., 2006, Niastella koreensis

gen. nov., sp. nov. and Niastella yeongjuensis sp. nov., 

novel members of the phylum Bacteroidetes, isolated from 

soil cultivated with Korean ginseng: International Journal 

of Systematic and Evolutionary Microbiology, v. 56, no. 8, 

p. 1777–1782, accessed January 2018 at https://doi.org/

10.1099/ijs.0.64242-0.

Whiticar, M.J., 1999, Carbon and hydrogen isotope systematics of bacterial formation and oxidation of methane: Chemical Geology, v. 161, no. 1–3, p. 291–314, 

accessed January 2018 at https://doi.org/10.1016/S0009-

2541(99)00092-3.

Widdel, F., and Bak, F., 1992, Gram-negative mesophilic 

sulfate-reducing bacteria, chap. 183 of Balows, A., Trüper, 

H.G., Dworkin, M., Harder, W., and Schleifer, K.-H., eds., 

The prokaryotes—A handbook on the biology of bacteria—

Ecophysiology, isolation, identification, applications: New 

York, Springer, p. 3352–3378.
26 Analysis of Formation Water Geochemistry and Microbiology of Commercial and Carbon Dioxide-Rich Wells

Worrall, J., 2004, Preliminary geology of Oakdale Field, 

northwest Raton Basin, Huerfano County, Colorado: AAPG 

Search and Discovery Article #20017, 14 p.

Yamada, T., Sekiguchi, Y., Hanada, S., Imachi, H., Ohashi, A., 

Harada, H., and Kamagata, Y., 2006, Anaerolinea thermolimosa sp. nov., Levilinea saccharolytica gen. nov., sp. 

nov. and Leptolinea tardivitalis gen. nov., sp. nov., novel 

filamentous anaerobes, and description of the new classes 

Anaerolineae classis nov. and Caldilineae classis nov. in 

the bacterial phylum Chloroflexi: International Journal of 

Systematic and Evolutionary Microbiology, v. 56, no. 6, 

p. 1331–1340, accessed January 2018 at https://doi.org/

10.1099/ijs.0.64169-0.

Zeikus, J.G., Hegge, P.W., Thompson, T.E., Phelps, T.J., 

and Langworthy, T.A., 1983, Isolation and description of 

Haloanaerobium praevalens gen. nov. and sp. nov., an 

obligately anaerobic halophile common to Great Salt Lake 

sediments: Current Microbiology, v. 9, no. 4, p. 225–233, 

accessed January 2018 at https://doi.org/10.1007/

BF01567586.

Zhou, Z., Ballentine, C.J., Schoell, M., and Stevens, S.H., 

2012, Identifying and quantifying natural CO2 sequestration 

processes over geological timescales—The Jackson Dome 

CO2 Deposit, USA: Geochimica et Cosmochimica Acta, 

v. 86, p. 257–275, accessed January 2018 at https://doi.org/

10.1016/j.gca.2012.02.028.

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ISSN 2328-0328 (online)

https://doi.org/10.3133/sir20205037