Salinity Mapping

Determining where protected groundwater resources are in relation to oil and gas resources and production activities is a key step in answering the question What lies between oil and gas operations and protected water?

We are using a number of different approaches

  • Compiling water-quality sampling data from existing records and plotting them in three dimensions (3D)
  • Expanding spatial coverage by using borehole measurements made when oil and water wells are drilled to calculate salinity
  • Expanding spatial coverage beyond drilled wells and oil fields using ground-based and aerial measurements

The descriptions below will lead you through our process for defining the study area and mining information from exising oil and water well records.

Compiling existing water-quality sample data and mapping it in three dimensions

Data are obtained from oil and water well records at each oil field.

However, we do not have well log data for much of the area where protected groundwater resources likely exist.

map of an oil field showing that the oil and gas wells are not evenly distributed across the oil field

Map of oil and gas wells clustered in the northern and southern ends of an oil field (Division of Oil, Gas, and Geothermal Resources, 2015).

Using geophysical log measurements obtained when an oil well is drilled to fill gaps in water-quality data

When oil wells are drilled, several different kinds of information may be collected, including information about the rocks and sediments and borehole geophysical logs. These geophysical logs measure various characteristics of the rocks and fluids and often include resistivity (or conductivity) data. Fluid salinity strongly affects resistivity values, and resistivity logs, in conjunction with porosity, self-potential, and gamma ray logs, can be used to calculate changes in salinity. Borehole geophysical log data from oil wells commonly span the depth intervals between where water and oil well casings are perforated and can be used to estimate salinity in these gaps.

Scanned images of borehole geophysical logs from most oil wells are available from the Division of Oil, Gas, and Geothermal Resources (DOGGR); shown here are examples from different wells with scanned logs of lithology and geophysical sensor responses.

Example of a geophysical log

Image of a driller's log.

Example of a driller's log

Example of an oil well geophysical log.

Using the traced geophysical logs

To calculate salinity along the depth profile of an individual well, we trace the resistivity lines on the scanned image to create a numerical record. We then calculate Total Dissolved Solids (TDS) values from selected intervals on the resistivity line that reflect the right conditions for applying salinity equations. Once we have calculated TDS points for multiple wells, we apply statistical techniques to generate a three-dimensional TDS model across the landscape (Gillespie and others, 2016; Shimabukuro and Ducart, 2016; Shimabukuro and others, 2016; Shimabukuro and Stephens, 2016).

The basic procedure for digitizing scanned images is labor-intensive and finding more efficient techniques is important.

Using ground-based and aerial electromagnetic surveys to map subsurface

After compiling existing water-quality data and calculating salinity profiles from digitized oil well-log information, there are still gaps in groundwater salinity data between wells, especially in the buffer areas outside the oilfield footprint where there are fewer wells. Using electromagnetic (EM) techniques, subsurface resistivity can be surveyed from the surface or air, even for areas without wells (Fitterman and Stewart, 1986). The resulting resistivity model is somewhat similar to a low-resolution borehole resistivity log. By collecting these data near wells with logs, the interpretation of the electromagnetic data is grounded in independent data on lithology and salinity. We can then make interpretations about how the geologic structure and salinity change between wells are guided by the airborne and surface data collected between wells.

These electromagnetic surveys can be completed using geophysical instruments on the ground or suspended from aircraft. Ground measurements are useful to collect data in strategic locations at single sites, while airborne systems are able to efficiently collect high resolution data over large regions in a series of survey flight lines, usually arranged in blocks of evenly spaced lines.

Airborne EM data can be used to create high-resolution cross sections and depth-slice maps of resistivity over large regions. These resistivity sections and maps can then be tied to salinity values from compiled water-quality data and digitized well-log information to map salinity changes between wells.

plots of depth versus resistivity and depth versus specific gravity

These two plots compare a resistivity model from an airborne electromagnetic survey of Paradox Valley, Colorado, to a measurement of salinity by depth at a nearby well (Ball and others, written commun., 2017). (Depth is in meters and resistivity is in Ohm-meters.)

Electormagnetic induction being taken on the ground, Mojave Desert near Twentynine Palms, California. Photo taken by L. Ball, USGS, 2014

Ground-based electromagnetic system (Ball, L.B., written commun., 2017).

electromagnetic survey being taken from air, Poplar, Montana. Photo taken by L. Ball, USGS, 2014

Airborne electromagnetic system in flight (Ball, L.B., written commun., 2017).

cross-section view of resistivity values

In this resistivity cross section, we can see the very low resistivity values (pink and red) associated with highly saline groundwater such as the brine observed at the river and in the well (total dissolved solids concentrations are given in milligrams per liter). Using these correlations, we can map the brine-saturated parts of the aquifer and map the freshwater-brine interface (Ball and others, written commun., 2017).

References

Ball, L.B., Bloss, B.R., Bedrosian, P.A., Grauch, V.J.S., and Smith, B.D., 2015, Airborne electromagnetic and magnetic survey data of the Paradox and San Luis Valleys, Colorado: U.S. Geological Survey Open-File Report 2015–1024, 19 p., https://dx.doi.org/10.3133/ofr20151024.

https://pubs.usgs.gov/of/2015/1024/

Ball, L.B., Bloss, B.R., Bedrosian, P.A., Grauch, V.J.S., and Smith, B.D., 2015, Airborne electromagnetic and magnetic survey data of the Paradox and San Luis Valleys, Colorado, Chapter G of Buesch, D.C., Geology and geophysics applied to groundwater hydrology at Fort Irwin, California: U.S. Geological Survey Open-File Report 2015–1024, 19 p., http://dx.doi.org/10.3133/ofr20151024.

https://pubs.er.usgs.gov/publication/ofr20131024G

Blondes, M.S., Gans, K.D., Rowan, E.L., Thordsen, J.J., Reidy, M.E., Thomas, B., Engle, M.A., Kharaka, Y.K., and Thomas, B., 2016, U.S. Geological Survey National Produced Waters Geochemical Database v2.2 (provisional): U.S. Geological Survey web page accessed March 1, 2016 at

http://energy.usgs.gov/EnvironmentalAspects/EnvironmentalAspectsofEnergyProductionandUse/ProducedWaters.aspx#3822349-data

California Department of Water Resources, 2015, Water quality data reports: Digital spatial data with water quality data for groundwater wells; data received June 2015 via email.

http://www.water.ca.gov/waterdatalibrary/waterquality/index.cfm/

California State Water Resources Control Board, 2015, Electronic Data Transfer Library, accessed February 2015 at

http://www.waterboards.ca.gov/drinking_water/certlic/drinkingwater/EDTlibrary.shtml

Division of Oil, Gas, and Geothermal Resources, 2015, DOGGR Well Finder: Digital spatial data for oil wells in California; California Department of Conservation, accessed February 28, 2015 at

http://www.conservation.ca.gov/dog/Pages/Wellfinder.aspx

Division of Oil, Gas, and Geothermal Resources, 1982, California Oil & Gas Fields Volume III - Northern California: California Department of Conservation, report CD-1, 330 p.

ftp://ftp.consrv.ca.gov/pub/oil/publications/Datasheets/Dtasheet_vol_3.pdf

Division of Oil, Gas, and Geothermal Resources, 1998, California Oil & Gas Fields Volume I -- Central California: California Department of Conservation, report CD-1, 499 p.

ftp://ftp.consrv.ca.gov/pub/oil/publications/Datasheets/Dtasheet_vol_1.pdf

Division of Oil, Gas, and Geothermal Resources, 1992, California Oil & Gas Fields Volume II -- Southern, Central Coast, and Offshore California Oil and Gas Fields: California Department of Conservation, report CD-1, 645 p.

ftp://ftp.consrv.ca.gov/pub/oil/publications/Datasheets/Dtasheet_vol_2.pdf

Fitterman, D., and Stewart, M., 1986, Transient electromagnetic sounding for groundwater: Geophysics, v. 51, p. 995-1005, http://dx.doi.org/10.1190/1.1442158.

http://geophysics.geoscienceworld.org/content/51/4/995

Gillespie, J.M., Kong, D., and Anderson, Stephen D., 2017, Groundwater salinity in the southern San Joaquin Valley: American Association of Petroleum Engineers Bulleting, v. 101, no. 8, p. 1239-1261, http://dx.doi.org/10.1306/09021616043.

http://aapgbull.geoscienceworld.org/content/101/8/1239/article-info

Gillespie, J.M., Shimabukuro, D.H., Stephens, M.J., Chang, W., Ball, L.B., Everett, R.R., Metzger, L.F., Landon, M.K., 2016, Mapping deep aquifer salinity trends in the southern San Joaquin Valley using borehold geophysical data constrained by chemical analyses, in American Geophysical Union Fall 2016 Meeting, San Francisco, Calif., December 12-16, 2016: American Geophysical Union, unpaginated.

Shimabukuro, D.H. and Ducart, A., 2016, Converting scanned oil well data into usable digital data: in California Oil, Gas, and Groundwater 2016 Symposium, Bakersfield, Calif., November 2-3, 2016: Groundwater Resources Association, unpaginated.

Shimabukuro, D.H., Stephens, M.J., Ducart, A., and Skinner, S.M., 2016, Rapid estimation of aquifer salinity structure from oil and gas geophysical logs, in American Geophysical Union Fall 2016 Meeting, San Francisco, Calif., December 12-16, 2016: American Geophysical Union, unpaginated.

U.S. Geological Survey, 2015, National Water Information System - Web interface: U.S. Geological Survey water database, accessed February 3, 2015, at http://dx.doi.org/10.5066/F7P55KJN.

http://waterdata.usgs.gov/ca/nwis/