U.S. Geological Survey National Produced Waters Geochemical Database v2.0 

(PROVISIONAL)

Documentation

04/04/2014

by Madalyn S. Blondes1*, Kathleen D. Gans2, James J. Thordsen2, Mark E. Reidy1, Burt Thomas2, Mark A. 

Engle1,3, Yousif K. Kharaka2, Elizabeth L. Rowan1

1

U.S. Geological Survey, Eastern Energy Resources Science Center, Reston, VA, USA 

2

U.S. Geological Survey, National Research Program, Menlo Park, CA, USA 

3

Dept. of Geological Sciences, University of Texas at El Paso, El Paso, TX, USA

*

Corresponding Author: Madalyn S. Blondes, email: mblondes@usgs.gov, telephone: (703) 648-4848

Disclaimers

Disclaimer for Provisional Database:

The data you have secured from the U.S. Geological Survey (USGS) National Produced Waters Geochemical 

Database v2.0 are provisional and subject to revision. The data are released on the condition that neither 

the USGS nor the United States Government may be held liable for any damages resulting from its 

authorized or unauthorized use.

Distribution Liability:

Although the data have been processed on computer systems at the USGS, U.S. Department of the Interior, 

no warranty, expressed or implied, is made by the Geological Survey regarding the utility of the data on any 

other system, nor shall the act of distribution constitute any such warranty. No responsibility is assumed by 

the USGS in the use of these data.

Additional Limitations: 

The information in the USGS National Produced Waters Geochemical Database v2.0 should be used with 

careful consideration of its limitations. The database is considered sufficiently accurate to provide an 

indication of tendencies in water composition from geographically and geologically defined areas. It is not 

appropriate for depiction of modern produced water compositions or examination of trends on small scales. 

The USGS makes no warranty regarding the accuracy or completeness of information presented in this 

database. Specific limitations of the database should be considered. Much of the information in the 

database cannot be independently verified. Methods of collection, sample preservation, analysis, 

assignment of geologic units and record keeping were not rigorous or standardized. Because of these 

uncertainties, users are advised to check data for inconsistencies, outliers, and obviously flawed 

information. Methods of well construction, sample collection and chemical analysis have changed over 

time. The distribution and relative amount of water produced within a province and among geologic units 

may not be fully represented by the samples in the database. No sampling was planned to accurately depict 

the aggregate water composition of any area whether it be province, state, county or field. The geologic 

unit nomenclature developed for petroleum production may have changed over time. Data from a province 

collected 30 years ago may not resemble current production. The composition of produced water within a 

province, field or even well may change in time as a result of water flooding, recompletion in other 
intervals, and workovers. Water samples are commonly collected when a well has production problems or 

during the initial development of a well. Although criteria were applied to remove the obviously 

contaminated samples, the culling of unrepresentative data is considered incomplete. Most obvious

redundant entries were removed from the database, many of the records represent multiple samples of the 

same well. Therefore aggregate statistics may be weighted by relatively few wells.

Introduction

During hydrocarbon exploration and extraction, water is typically co-produced from the same subsurface 

geologic formations. Understanding the composition of these produced waters is important to help 

investigate the regional hydrogeology, the source of the water and hydrocarbons, the necessary water 

treatment and disposal plans, potential economic benefits of commodities in the fluids, and the safety of 

potential sources of drinking or agricultural water. Additionally, during geothermal development or 

exploration, other deep formation waters are brought to the surface and may be sampled. This U.S. 

Geological Survey (USGS) Produced Waters Geochemical Database, which contains geochemical and other 

information for produced waters and other deep formation waters of the United States, is a provisional,

updated version of the 2002 USGS Produced Waters Database (Breit and others, 2002). In addition to the 

major element data presented in the original, the new database contains trace elements, isotopes, and 

time-series data, as well as nearly 100,000 new samples with greater spatial coverage and from both 

conventional and unconventional well types, including geothermal. The database is a compilation of 25 

individual databases, publications, or reports. The database was created in a manner to facilitate addition 

of new data and fix any compilation errors, and is expected to be updated with new data as provided and 

needed. Table 1 shows the abbreviated names (IDDB) of each input database, the number of samples from 

each, and its reference. Table 2 defines the 241 variables contained in the database and their descriptions. 

The database variables are organized first with identification and location information, followed by well 

descriptions, dates, rock properties, physical properties of the water, and then chemistry. The chemistry is 

organized alphabetically by elemental symbol, each element is followed by any associated compounds (e.g. 

H2S is found after S). After Zr, molecules containing carbon follow, including measures of alkalinity, 

dissolved organic carbon (DOC), and hydrocarbons. Isotopic data are found at the end of the dataset. 

Database Compilation Procedure

Modification of the data or variable names is necessary to create a database with consistent headers, 

compositional units, and numeric data that can be plotted or analyzed as a whole. One of the main goals of 

this updated database is to create a compiled dataset where every change to the original datasets is

reversible and recorded. Thus if errors are found, there is a coded record that can be adjusted as needed, 

and the compiled dataset can be easily recreated from scratch. To meet this goal, the USGS National 

Produced Waters Geochemical Database v2.0 is compiled using the statistical and data analysis program,

Stata (StataCorp, 2014)1. A Stata routine is written for each input database that imports the original data, 

 1 Disclaimer: Use of brand or trade names are for descriptive purpose and do not imply endorsement by the 

U.S. Government.
renames the variables to match the template (table 2), and then appends the existing columns to a template 

header. Non-numeric characters within numeric variables (for example, chemistry and pH) are fixed, 

deleted, or replaced with the following numeric codes:

-1 = Trace, minor, present, or a qualitative description of some amount.

-2 = None detected, absent, null, or negative 

-3 = NA, not analyzed, unknown

-4 = Transcription error or otherwise nonsensical entry

Negative values are used for concentration data codes because all true concentrations are positive and 

therefore will not overlap with the codes. Negative values can easily be removed by the user when 

manipulating data. Furthermore, dates are formatted into a consistent date form and extra variables are 

removed. Units for all variables other than the major and minor ions are defined in table 2. The major and 

minor ions are generally reported in units of milligrams per liter (mg/L) or parts per million (ppm) on a mass

basis, also defined as milligrams per kilogram (mg/kg). If the ion concentrations were originally reported in 

mg/L, a “1” is added to the MGL variable column of the database. If the ion concentrations were originally 

reported in ppm, a “1” is added to the PPM variable column of the database. The user of this database must 

be careful to examine these units when using the data, and can convert between the two using 

measurements or estimates of brine density.

Each individual input database is then appended to the template using a global Stata routine. The database 

is further standardized here with internally consistent 14-digit American Petroleum Institute well 

identification numbers (API), state names (STATE), and one of seven well type (WELLTYPE) designations 

(Conventional Hydrocarbon, Shale Gas, Tight Oil, Tight Gas, Coal Bed Methane, Geothermal, and 

Groundwater). Future standardization will be performed on other important variables such as FORMATION.

Removing duplicates

Duplicates were found within single datasets and between them. Duplicate culling is done using API well 

numbers and the concentrations of variables with large numbers of significant figures because it is highly 

unlikely that even samples taken from the same well at the same time will have the exact same values for

three or more elements. API, Calcium (Ca), Chloride (Cl), and bicarbonate (HCO3) concentrations are used to 

search for duplicates. Care was taken to avoid false duplicates (for example, where all three ions had the 

code of “-4” or all three ions had null data). There were 91,007 unique observations according to these

duplicate search criteria, 8,352 groups of 2 observations (duplicates), 1,173 groups of 3 observations

(triplicates), 156 groups of 4 observations, 13 groups of 5 observations, 5 groups of 6 observations, and 2 

groups of 7 observations (table 3). After locating these duplicates, a second check was often performed 

using Mg, Na, or sample collection date to determine if they were true duplicates. The duplicate 

observation retained was generally the one in the database that contained more information. The order of 

which database had primacy follows the order of table 1.
Culling data based on chemistry

Quality control of the dataset can be performed by culling based on geochemical criteria. In this version 2.0 

of the provisional database, the data that fall outside of the bounds of the following criteria are flagged, 

rather than culled. There are six temporary columns in the database that represent the failure of specific 

culling criteria, based on those published in Hitchon and Brulotte (1994). An “X” is placed in the columns 

shown in table 4 where the sample falls outside of the pH range of 4.5 – 10.5, where Mg > Ca, K > Cl, K > 

5xNa, and the charge balance is greater than 5%.

 

 
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brines from three oil- and gas-producing sandstones in eastern Ohio, with applications to the 

geochemical tracing of brine sources: U.S. Geological Survey Water-Resources Investigations Report 

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http://www.dcnr.state.pa.us/topogeo/pub/openfile/pdfs/ofog10_01.pdf.

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Colorado, and New Mexico: Chemical Geology, v. 4, p. 263-164.

Hayes, T., 2009, Sampling and analysis of water streams associated with development of Marcellus Shale 

gas, Final Report, December 31, 2009: Marcellus Shale Coalition, p. 107-356, Accessed 

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Geochemistry, v. 9, p. 637-645.

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Report of Investigations, no. 1, p. 1-21.

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Survey Occasional Paper 41.

Lowry, R. M., Faure, G., Mullet, D. I., and Jones, L. M., 1988, Interpretation of chemical and isotopic 

compositions of brines based on mixing and dilution, "Clinton" sandstones, eastern Ohio, U.S.A.: Applied 

Geochemistry, v. 3, p. 177-184.

McGrain, P., 1953, Miscellaneous analyses of Kentucky brines: Kentucky Geological Survey- Report of 

Investigations No. 7, p. 1-16.

McGrain, P., and Thomas, G. R., 1951, Preliminary report on the natural brines of eastern Kentucky: 

Kentucky Geological Survey, v. Report of Investigations No. 3, p. 1-22.
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occurrence and chemical composition: Illinois State Geological Survey, Illinois Petroleum no. 66, 38 p.

Meredith, E., Kuzara, S., Wheaton, J.R., Bierbach, S., Chandler, K., Donato, T., Gunderson, .J., and 

Schwartz, C., 2011, 2010 Annual coalbed methane regional groundwater monitoring report: Powder 

River Basin, Montana, Montana Bureau of Mines and Geology Open File Report 600, 130 p., 6 sheets, 

Accessed http://www.mbmg.mtech.edu/pdf-open-files/mbmg600-2010CBM-Report.pdf. 

Mills, R. V. A., and Wells, R. C., 1919, The evaporation and concentration of waters associated with 

petroleum and natural gas: U.S. Geological Survey Bulletin 693, 104 p.

Moldovanyi, E.P. and Walter, L.M., 1992, Regional trends in water chemistry, Smackover Formation, 

southwest Arkansas: Geochemical and Physical Controls, AAPG Bulletin, v. 76, no. 6, p 864-894.

New Mexico Water and Information Data System (NM WAIDS), Accessed 2013 at 

http://octane.nmt.edu/waterquality.

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New York State Department of Environmental Conservation, 2009, Draft supplemental generic 

environmental impact statement on the oil, gas, and solution mining regulatory program, well permit 

issuance for horizontal drilling and high-volume hydraulic fracturing to develop the Marcellus Shale and 

other low-permeability gas reservoirs: New York State Department of Environmental Conservation 

(DEC), Appendix 13, Accessed http://www.dec.ny.gov/energy/58440.html. 

Osborn, S.G., and McIntosh, J.C., 2010, Chemical and isotopic tracers of the contribution of microbial gas in 

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elemental geochemistry of northern Appalachian Basin brines: evidence for basinal-scale fluid migration 

and clay mineral diagenesis: American Journal of Science, v. 312, p. 263-287.

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Survey Summary, Accessed 

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Fourth Series, Bulletin M 47, 53 p.

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Chemical and isotopic composition and volumes, International Journal of Coal Geology, 56: 141-169.

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waters in the northern Appalachian Basin: Summary and discussion of data: U.S. Geological Survey, 

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Sandstone), eastern Ohio: AAPG Bulletin, v. 75, p. 1593-1608.
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Michigan Basin. Final Report, Gas Research Institute, 5093-220-2704, 98 p.

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Tables

 

Table 1. Short names of input databases, number of samples after removal of duplicates, and references on input 

databases. 

ID of database Samples Reference

USGSMAIN 62,792 Breit and others (2002)

USGSOK 9,304 Breit and others (2002)

USGSARK 1,125 Breit and others (2002)

ROCKIES 3,190 Department of Energy, National Energy Technology Laboratory (2005)

MICHIGAN 429 Vugrinovich (2013, written communication)

WYOGCC 9,263 Wyoming Oil and Gas Conservation Commission (2013)

BAKKEN 12 Thamke (2013, written communication)

PARADOX 89 Hanshaw and Hill (1969)

POWDERRIVERCBM 48 Rice and others (2000)

APPALACHIAN 1,644 multiple – see references

INDIANA 470 Keller (1983)

CBM 3,220 Dahm (2013, writen communication)

OHBRINE 579 Ohio DNR, Division of Geologic Survey (2013, written communication

PASHIN 126 Alabama Geological Survey (2013, written communication)

ARKMOLDOVANY 41 Moldovanyi and Walter (1992)

CIMAREX 2,891 Cimarex Energy Company (2013, written communication)

FERRON 49 Rice (2003)

ILLINOIS 347 Meents and others (1952)

MISSISSIPPI 82 Carpenter and others (1974)

MONTANACBM 21 Meredith and others (2010)

PALODURO 16 Bassett and Bentley (1983)

EASTPOPLAR 22 Thamke (2013, written communication)

NORTHDAKOTA 7,334 North Dakota Oil and Gas Division (2013)

ANTRIM 53 Walter and others (1997)

NATCARB 57,208 Department of Energy, National Energy Technology Laboratory (2013)

Total 160,355

 
Table 2. Variable names and descriptions. 

Variable Name Description

IDORIG ID in original database

IDDB ID of database

SOURCE Source of data

REFERENCE Publication 

LAT Latitude

LONG Longitude

FLAT Field Latitude (estimate)

FLONG Field Longitude (estimate)

API API well number

USGSPROV USGS Province

USGSREGION USGS Region

BASIN Basin

BASINCODE Basin Code

STATE State

STATECODE State Code

COUNTY County

COUNTYCODE County Code

FIELD Field

FIELDCODE Field Code

WELL Well name

WELLCODE Well code

WELLTYPE Well type

WELLCLASS Well class

TOWNSHIP Township

TWNDIR Township Direction

RANGE Range

RNGDIR Range Direction

SECTION Section

QUARTER Quarter

REGDIST Regional District

LOC Location

QUAD Quad

DATESAMPLE Date of sample

DATEANALYS Date of analysis

DATECOMP Date of well completion

METHOD Sample Method

OPERATOR Well operator

DRILLER Well driller

PERMIT Well permit holder

FORMATION Geologic formation name

DFORM Geologic formation name of greatest depth

MEMBER Geologic member name

GEOLAGE Geologic age

AGECODE Geologic Age code

ERA Geologic Era name

SYSTEM Geologic System name

SERIES Geologic Series name

DEPTHUPPER Upper perforation depth

DEPTHLOWER Lower perforation depth

DEPTHSAMP Depth of sample, may be average
Variable Name Description

DEPTHTOTAL Total depth of well

ELEVATION Elevation of well

SUBSEA Depth below seafloor

LAB Laboratory

REMARKS Remarks or comments

LITHOLOGY Lithology

SILT Silt 1 = sample is this rock type

SHALE Shale 1 = sample is this rock type

SAND Sand 1 = sample is this rock type

CHERT Chert 1 = sample is this rock type

CARBONATE Carbonate 1 = sample is this rock type

DOLOMITE Dolomite 1 = sample is this rock type

LIMESTONE Limestone 1 = sample is this rock type

ANHYDRITE Anhydrite 1 = sample is this rock type

OTHERLITH Other Lithology 1 = sample is this rock type

POROSITY Porosity 

PERM Permeability

TEMP Temperature, deg F

PRESSURE Pressure, psi

SPGRAV Specific Gravity

SPGRAVT Temperature of Specific Gravity measurement, deg F

RESIS Resistivity, Ohm m

RESIST Temperature of Resistivity measurement, deg F

PH pH

PHT Temperature of pH measurement, deg F

EHORP Eh / Oxidation Reduction Potential (mV)

COND Conductivity, uS/cm

CONDT Temperature of Conductivity measurement, deg F

TURBIDITY Turbidity

SEDIMENT Sediment

HEM Oil and Grease

MBAS Surfactants and Detergents

MGL Units, mg/L; 1 = data are in these units

PPM Units, mg/kg; 1 = data are in these units

TDS Total Dissolved Solids, measured

TDSCALC Total Dissoved Solids, calculated

TSS Total Suspended Solids

CHARGEBAL Charge Balance (%)

MASSBAL Mass Balance (%)

Ag Silver

Al Aluminum

As Arsenic

Au Gold

B Boron

BO3 Borate

Ba Barium

Be Beryllium

Bi Bismuth

Br Bromide

BrO3 Bromate

CO2 Carbon dioxide

CO3 Carbonate
Variable Name Description

HCO3 Bicarbonate

Ca Calcium

Cd Cadmium

Ce Cerium

ClO3 Chlorate

ClO4 Perchlorate

Cl Chloride

ClO2 Chlorite

ClO Hypochlorite

Co Cobalt

Cr Chromium

Cs Cesium

Cu Copper

F Fluoride

FeTot Iron, total

FeIII Iron, 3+

FeII Iron, 2+

FeS Iron sulfide

FeAl Iron plus Aluminum, reported as elements

FeAl2O3 Iron plus Aluminum, reported as oxides

Ga Gallium

Ge Germanium

Hg Mercury

Hf Hafnium

I Iodine

In Indium

Ir Iridium

K Potassium

KNa Potassium plus Sodium

La Lanthanum

Li Lithium

Mg Magnesium

Mn Mangansese

Mo Molybdenum

N Nitrogen, total

NO2 Nitrite

NO3 Nitrate

NO3NO2 Nitrate plus Nitrite

NH3 Ammonia

NH4 Ammonium

TKN Kjeldahl Nitrogen

Na Sodium

Nb Niobium

Ni Nickel

O Oxygen

DO Dissolved Oxygen

OH Hydroxide

Os Osmium

P Phosphorus

PO4 Phosphate

Pb Lead

Pd Palladium
Variable Name Description

Re Rhenium

Rh Rhodium

Rb Rubidium

Ru Ruthenium S Sulfide

SO3 Sulfite

SO4 Sulfate

HS Bisulfide

H2S Hydrogen Sulfide

HSO4 Bisulfate

Sb Antimony

Sc Scandium

Se Selenium

Si Silica

Sn Tin

Sr Strontium

Ta Tantalum

Te Tellurium

Th Thorium

Ti Titanium

Tl Thallium U Uranium V Vanadium W Tungsten Y Yttrium

Zn Zinc

Zr Zirconium

ALKTOTAL Alkalinity, total

ALKCACO3 Alkalinity as CaCO3

ALKHCO3 Alkalinity as HCO3

ALKCO3 Alkalinity as CO3

ACIDITY Acidity as CaCO3

DIC Dissolved Inorganic Carbon

DOC Dissolved Organic Carbon

TOC Total Organic Carbon

CN Cyanide

BOD Biochemical Oxygen Demand

COD Chemical Oxygen Demand

CH4 Methane

C2H3O2 Acetate

C2H4O2 Acetic Acid

C2H6O2 Ethylene Glycol

C3H6O Acetone

C6H6 Benzene

C6H6O Phenols

C7H8 Toluene

C8H10_XY Xylene

C8H10_ETH Ethybenzene

ALPHA Alpha particle (4He), pCi/L

BETA Beta particle, pCi/L

dD delta 2H, per mil

H3 Tritium, 3H, tritium units
Variable Name Description

d11B delta 11B, per mil

B11_10 11B / 10B

d13C delta 13C, per mil

C14 14C, pCi/L

d18O delta 18O, per mil

d34S delta 34S, per mil

d37Cl delta 37Cl, per mil

K40 40K, pCi/L

Sr87_86 87Sr / 86Sr

Cs127 127Cs, pCi/L

I129 129I, pCi/L

Tl206 206Tl, pCi/L

Pb210 210Pb, pCi/L

Pb212 212Pb, pCi/L

Ra223 223Ra, pCi/L

Ra226 226Ra, pCi/L

Bi211 211Bi, pCi/L

Bi212 212Bi, pCi/L

Bi214 214Bi, pCi/L

Pb214 214Pb, pCi/L

Rn222 222Rn, pCi/L

Th227 227Th, pCi/L

Ac227 227Ac, pCi/L

Ac228 228Ac, pCi/L

Ra228 228Ra, pCi/L

Th228 228Th, pCi/L

Th230 230Th, pCi/L

Pa231 231Pa, pCi/L

Th232 232Th, pCi/L

Th234 234Th, pCi/L

Pa234 234Pa, pCi/L

U234 234U, pCi/L

U235 235U, pCi/L

Np237 237Np, pCi/L

U238 238U, pCi/L

 

 
Table 3. Observed duplicates in combined database based on exact same Ca, Cl, HCO3, and API. 

Copies Observations Surplus

1 91007 0

2 16704 8352

3 3519 2346

4 624 468

5 65 52

6 30 25

7 14 12

 

 
Table 4. Chemical culling criteria for water data quality control. 

Criteria Column Name

pH < 4.5 or pH > 10.5 cull_PH

Mg > Ca cull_MgCa

K > Cl cull_KCl

K > 5xNa cull_K5Na

charge balance > 5% cull_CHARGEB and chargebalance