Ricardo A. Olea, Ph.D.
Ricardo Olea is a Research Mathematical Statistician with the USGS Geology, Energy & Minerals (GEM) Science Center in Reston, VA.
Ricardo has extensive experience in quantitative modeling in the earth sciences and public health, primarily in the areas of petroleum geology and engineering, coal resource assessment, geostatistics, classical statistics, compositional data modeling, economic evaluation, well log analysis, marine geology, medical geography, geophysics, and geohydrology.
Professional Experience
2006 to Present: U.S. Geological Survey. Statistical Support: Coal Resource Assessment Methodology Implementation; Mathematical Model Enhancement; Exploitation of subsurface geologic resources in the land loss in coastal Louisiana; Advance the application of statistics to the earth sciences world-wide; and Reducing the risk of explosions at underground coal mines
Department of Petroleum Engineering, Stanford University
Marine Geology Section, Baltic Research Institute, University of Rostock, Warnemünde, Germany
Department of Environmental Sciences and Engineering, School of Public Health, University of North Carolina Chapel Hill
Research Scientist, Kansas Geological Survey, Lawrence, Kansas
Exploration Seismologist, Geostatistician, Log Analyst, Economic Analyst, and Reservoir Engineer, National Oil Company of Chile (ENAP)
Education and Certifications
Ph.D. Engineering, Chemical and Petroleum Engineering, University of Kansas
Mining Engineer Degree, University of Chile
Affiliations and Memberships*
Compositional Data Association, Member
Society of Petroleum Engineers, Member
American Association of Petroleum Geologists, Member
International Association for Mathematical Geosciences, Member
Sigma Xi and serves as an Associate Editor of the Springer journal Stochastic Environmental Research and Risk Assessment
International Association for Mathematical Geology (IAMG), Secretary General (1992–96) and President (1996–2000)
Honors and Awards
IAMG Krumbein Medal - Science and Professional Contributions, 2004
Science and Products
National assessment of carbon dioxide enhanced oil recovery and associated carbon dioxide retention resources - data release
In 2020, the U.S. Geological Survey (USGS) completed a probabilistic assessment of the volume of technically recoverable oil resources available if current carbon dioxide enhanced oil recovery (CO2-EOR) technologies were applied in amenable oil reservoirs underlying the onshore and State waters area of the conterminous United States. The assessment also includes estimates of the magnitude of CO2 s
Filter Total Items: 83
A residual oil zone (ROZ) assessment methodology with application to the central basin platform (Permian Basin, USA) for enhanced oil recovery (EOR) and long-term geologic CO2 storage
Residual oil zones (ROZ) form due to various geologic conditions and are located below the oil/water contact (OWC) of main pay zones (MPZ). Since ROZs usually contain immobile oil, they have not typically been considered commercially attractive for development by conventional primary recovery methods used in the initial phases of oil production. However, during the last decade some operators of th
Authors
C. Özgen Karacan, Sean T. Brennan, Marc L. Buursink, Philip A. Freeman, Celeste D. Lohr, Matthew D. Merrill, Ricardo A. Olea, Peter D. Warwick
Geology and assessment of coal resources for the Cherokee coal bed in the Fort Union Formation, south-central Wyoming
The Cherokee coal bed is a locally thick and laterally continuous coal bed in the Overland Member of the Paleocene Fort Union Formation in south-central Wyoming. It represents a significant resource that is easily accessible and may be extractable through both surface and underground mining methods. A database of more than 600 data points, comprising coalbed methane wells, coal exploration drill h
Authors
Brian N. Shaffer, Ricardo A. Olea
National assessment of carbon dioxide enhanced oil recovery and associated carbon dioxide retention resources — Summary
IntroductionIn 2020, the U.S. Geological Survey (USGS) completed a probabilistic assessment of the volume of technically recoverable oil resources that might be produced by using current carbon dioxide enhanced oil recovery (CO2-EOR) technologies in amenable conventional oil reservoirs underlying the onshore and State waters areas of the conterminous United States. The assessment also includes est
Authors
Peter D. Warwick, Emil D. Attanasi, Madalyn S. Blondes, Sean T. Brennan, Marc L. Buursink, Steven M. Cahan, Colin A. Doolan, Philip A. Freeman, C. Özgen Karacan, Celeste D. Lohr, Matthew D. Merrill, Ricardo A. Olea, Jenna L. Shelton, Ernie R. Slucher, Brian A. Varela
National assessment of carbon dioxide enhanced oil recovery and associated carbon dioxide retention resources — Results
In 2020, the U.S. Geological Survey (USGS) completed a probabilistic assessment of the volume of technically recoverable oil resources available if current carbon dioxide enhanced oil recovery (CO2-EOR) technologies were applied to amenable oil reservoirs underlying the onshore and State waters areas of the conterminous United States. The assessment also includes estimates of the mass of CO2 that
Authors
Peter D. Warwick, Emil D. Attanasi, Madalyn S. Blondes, Sean T. Brennan, Marc L. Buursink, Steven M. Cahan, Colin A. Doolan, Philip A. Freeman, C. Özgen Karacan, Celeste D. Lohr, Matthew D. Merrill, Ricardo A. Olea, Jenna L. Shelton, Ernie R. Slucher, Brian A. Varela
Total alkali-silica diagram
The total alkali-silica (TAS) diagram is a scatterplot of the chemical concentrations of silica oxide (SiO2) versus total alkali-sodium oxide (Na2O) plus potassium oxide (K2O) – in volcanic rocks.
Authors
Ricardo A. Olea
Frequency distribution
Given a numerical dataset, a frequency distribution is a summary displaying fluctuations of an attribute within the range of values. In contrast to an analytical probability distribution, a frequency distribution always deals with empirically observed values (Everitt and Skondall 2010). In general, the larger the number of values, the more useful is the frequency distribution relative to listing a
Authors
Ricardo A. Olea
Revisiting the declustering of spatial data with preferential sampling
Preferential sampling is a form of data collection that may significantly distort the histogram and the semivariogram of spatially correlated data. Typical situations are a higher sampling density at high-valued areas favorable for mining, and highly contaminated areas in need of environmental remediation. Multiple statistical procedures are devoted to obtaining representative statistics, whose ma
Authors
Ricardo A. Olea
Random variable
A random variable is a function that assigns a value in a sample space to an element of an arbitrary set (James 1992; Pawlowsky-Glahn et al. 2015). It is a model for a random experiment: the arbitrary set is an abstraction of the experimental conditions, the values taken by the random variable are in the sample space, and the function itself models the assignment of outcomes, thus also describing
Authors
Ricardo A. Olea
Probabilistic methodology for the assessment of original and recoverable coal resources, illustrated with an application to a coal bed in the Fort Union Formation, Wyoming
Executive SummaryThe U.S. Geological Survey (USGS) has been using its Circular 891 for evaluating uncertainty in coal resource assessments for more than 35 years. Calculated cell tonnages are assigned to four qualitative reliability classes depending exclusively on distance to the nearest drill hole. The main appeal of this methodology, simplicity, is also its main drawback. Reliability may depend
Authors
Ricardo A. Olea, Brian N. Shaffer, Jon E. Haacke, James A. Luppens
Multivariate classification of the crude oil petroleum systems in southeast Texas, USA, using conventional and compositional data analysis of biomarkers
Chemically, petroleum is an extraordinarily complex mixture of different types of hydrocarbons that are now possible to isolate and identify because of advances in geochemistry. Here, we use biomarkers and carbon isotopes to establish genetic differences and similarities among oil samples. Conventional approaches for evaluating biomarker and carbon isotope relative abundances include statistical t
Authors
Ricardo A. Olea, J. A Martin-Fernandez, William H. Craddock
Insights on the characteristics and sources of gas from an underground coal mine using compositional data analysis
Coal mine gas originates from the gas emission zone (GEZ) of the mine, as well as the longwall face and pillars. Gas emissions are controlled directly at the sources using horizontal or vertical boreholes drilled from surface or from the entries in advance of mining, or it is captured from the fractured and caved zones (gob) using ventholes during mining. The rest of the gas, especially that gas t
Authors
C. Özgen Karacan, Josep Antoni Martín-Fernández, Leslie F. Ruppert, Ricardo A. Olea
Non-USGS Publications**
Buatois, L.A., Mángano, M.G, Olea, R.A., Wilson, M.A., 2016. Decoupled evolution of soft and hard substrate communities during Cambrian Explosion and Great Ordovician Biodiversification Event. Proceedings of the National Academy of Sciences, vol. 113, no. 25, p. 6945−6948 and 28 pp. of Supporting Information.
Schuenemeyer, J. H., Olea, R.A., 2014. Distributional assumptions and parametric uncertainties in the aggregation of geologic resources. In Mathematics of Planet Earth, Proceedings of the 15th Annual Conference of the International Association for Mathematical Geosciences, Pardo-Igúzquiza, E., Guardiola-Albert, C., Heredia, J., Moreno-Merino, L., Durán, J.J., Vargas-Guzmán, J.J., editors, p. 49−52.
Pardo-Igúzquiza, E., Olea, R. A., Dowd, P.A, 2014. Semivariogram model inference using the median bootstrap statistics. In Mathematics of Planet Earth, Proceedings of the 15th Annual Conference of the International Association for Mathematical Geosciences, Pardo-Igúzquiza, E., Guardiola-Albert, C., Heredia, J., Moreno-Merino, L., Durán, J.J., Vargas-Guzmán, J.J., editors, p. 79−82.
Karacan, C. Ö., Olea, R.A., 2014. Coalbed methane production analysis and filter simulation for quantifying gas drainage from coal seams. In Mathematics of Planet Earth, Proceedings of the 15th Annual Conference of the International Association for Mathematical Geosciences, Pardo-Igúzquiza, E., Guardiola-Albert, C., Heredia, J., Moreno-Merino, L., Durán, J.J., Vargas-Guzmán, J.J., editors, p. 549−552.
Olea, R.A., Luppens, J.A., Tewalt, S.J., 2014. Moving away from distance classifications as measures of resource uncertainty. In Mathematics of Planet Earth, Proceedings of the 15th Annual Conference of the International Association for Mathematical Geosciences, Pardo-Igúzquiza, E., Guardiola-Albert, C., Heredia, J., Moreno-Merino, L., Durán, J.J., Vargas-Guzmán, J.J., editors, p. 585−588.
Olea, R.A., Houseknecht, D.W., Garrity, C. P. and Cook, T.A., 2011, Assessment of shale-gas resources using correlated variables and application to the Woodford play, Arkoma basin, southeast Oklahoma: Special issue on New Quantitative Applications of Geomathematics in Earth Sciences of the Geological Survey of Spain Bulletin, Boletín Geológico y Minero, vol. 122, no.4, p. 483–496.
Martín-Fernández, J. A., Palarea-Alabaladejo, J., and Olea, R.A., 2011, Dealing with zeros. In V. Pawlowsky-Glahn and A. Buccianti (eds.), Compositional Data Analysis—Theory and Applications: Wiley & Sons, Ltd, Chichester, UK, p. 43–58.
Martín-Fernández, J. A., Palarea-Alabaladejo, J., and Olea, R.A., 2011, Dealing with zeros. In V. Pawlowsky-Glahn and A. Buccianti (eds.), Compositional Data Analysis—Theory and Applications: Wiley & Sons, Ltd, Chichester, UK, p. 43–58.
Bunnell, J. E., Garcia, L. V., Furst, J. M., Lerch, H., Olea, R. A., Suitt, S. E., and Kolker, A., 2010, Navajo coal combustion and respiratory health near Shiprock, New Mexico. Journal of Environmental and Public Health, vol. 2010, article ID 260525, DOI:10.1155/2010/260525, 14 p.
Olea, R. A., 2009, Crossvalidation of cumulative probabilities for parameter selection in geostatistical estimation and simulation: Proceedings of the 2009 Conference of the International Association for Mathematical Geosciences, http://iamg09.stanford.edu
Martín-Fernández, J. A., Olea, R. A., and Palarea-Albaladejo, J., 2009, Multivariate approach using bootstrapping for the inference of distributional parameters of samples containing compositional values below detection limit. Abstract in Proceedings of the 31st Spanish Congress of Statistics and Operations Research, Murcia, Spain, p. 54, CD-ROM. (ISBN: 978-84-691-8159-1)
Kolker, A , Engle, M. A., Hower, J. C., O’Keefe, J. M. K., Heffern, E. L., Radke, L. F., Prakash, A., ter Schure, A., Román-Colón, Y., and Olea, R., 2009, Measuring CO2 emissions from coal fires in the U.S.: Proceedings, Annual International Coal Conference, Pittsburgh, PA, September, 2009, 7 p.
Olea, R. A., 2008, Basic Statistical Concepts and Methods for Earth Scientists: U.S. Geological Survey, Open-File Report 2008-1017, http://pubs.usgs.gov/of/2008/1017/, 191 p.
**Disclaimer: The views expressed in Non-USGS publications are those of the author and do not represent the views of the USGS, Department of the Interior, or the U.S. Government.
Computer programs for the assessment of coal resources (ver. 2.0, April 2021)
The USGS assessment and methodology reports cited within this software release require extensive processing using computational methods and modeling. The most demanding aspects of the modeling were performed using publicly available software: SGeMS and GSLIB (See the 'related External Resources' section on this webpage to learn more about this software). This publication releases the FORTRAN sourc
Computer programs for the assessment of coal resources (ver. 2.0, April 2021)
The USGS assessment and methodology reports cited within this software release require extensive processing using computational methods and modeling. The most demanding aspects of the modeling were performed using publicly available software: SGeMS and GSLIB.
Science and Products
- Data
National assessment of carbon dioxide enhanced oil recovery and associated carbon dioxide retention resources - data release
In 2020, the U.S. Geological Survey (USGS) completed a probabilistic assessment of the volume of technically recoverable oil resources available if current carbon dioxide enhanced oil recovery (CO2-EOR) technologies were applied in amenable oil reservoirs underlying the onshore and State waters area of the conterminous United States. The assessment also includes estimates of the magnitude of CO2 s - Publications
Filter Total Items: 83
A residual oil zone (ROZ) assessment methodology with application to the central basin platform (Permian Basin, USA) for enhanced oil recovery (EOR) and long-term geologic CO2 storage
Residual oil zones (ROZ) form due to various geologic conditions and are located below the oil/water contact (OWC) of main pay zones (MPZ). Since ROZs usually contain immobile oil, they have not typically been considered commercially attractive for development by conventional primary recovery methods used in the initial phases of oil production. However, during the last decade some operators of thAuthorsC. Özgen Karacan, Sean T. Brennan, Marc L. Buursink, Philip A. Freeman, Celeste D. Lohr, Matthew D. Merrill, Ricardo A. Olea, Peter D. WarwickGeology and assessment of coal resources for the Cherokee coal bed in the Fort Union Formation, south-central Wyoming
The Cherokee coal bed is a locally thick and laterally continuous coal bed in the Overland Member of the Paleocene Fort Union Formation in south-central Wyoming. It represents a significant resource that is easily accessible and may be extractable through both surface and underground mining methods. A database of more than 600 data points, comprising coalbed methane wells, coal exploration drill hAuthorsBrian N. Shaffer, Ricardo A. OleaNational assessment of carbon dioxide enhanced oil recovery and associated carbon dioxide retention resources — Summary
IntroductionIn 2020, the U.S. Geological Survey (USGS) completed a probabilistic assessment of the volume of technically recoverable oil resources that might be produced by using current carbon dioxide enhanced oil recovery (CO2-EOR) technologies in amenable conventional oil reservoirs underlying the onshore and State waters areas of the conterminous United States. The assessment also includes estAuthorsPeter D. Warwick, Emil D. Attanasi, Madalyn S. Blondes, Sean T. Brennan, Marc L. Buursink, Steven M. Cahan, Colin A. Doolan, Philip A. Freeman, C. Özgen Karacan, Celeste D. Lohr, Matthew D. Merrill, Ricardo A. Olea, Jenna L. Shelton, Ernie R. Slucher, Brian A. VarelaNational assessment of carbon dioxide enhanced oil recovery and associated carbon dioxide retention resources — Results
In 2020, the U.S. Geological Survey (USGS) completed a probabilistic assessment of the volume of technically recoverable oil resources available if current carbon dioxide enhanced oil recovery (CO2-EOR) technologies were applied to amenable oil reservoirs underlying the onshore and State waters areas of the conterminous United States. The assessment also includes estimates of the mass of CO2 thatAuthorsPeter D. Warwick, Emil D. Attanasi, Madalyn S. Blondes, Sean T. Brennan, Marc L. Buursink, Steven M. Cahan, Colin A. Doolan, Philip A. Freeman, C. Özgen Karacan, Celeste D. Lohr, Matthew D. Merrill, Ricardo A. Olea, Jenna L. Shelton, Ernie R. Slucher, Brian A. VarelaTotal alkali-silica diagram
The total alkali-silica (TAS) diagram is a scatterplot of the chemical concentrations of silica oxide (SiO2) versus total alkali-sodium oxide (Na2O) plus potassium oxide (K2O) – in volcanic rocks.AuthorsRicardo A. OleaFrequency distribution
Given a numerical dataset, a frequency distribution is a summary displaying fluctuations of an attribute within the range of values. In contrast to an analytical probability distribution, a frequency distribution always deals with empirically observed values (Everitt and Skondall 2010). In general, the larger the number of values, the more useful is the frequency distribution relative to listing aAuthorsRicardo A. OleaRevisiting the declustering of spatial data with preferential sampling
Preferential sampling is a form of data collection that may significantly distort the histogram and the semivariogram of spatially correlated data. Typical situations are a higher sampling density at high-valued areas favorable for mining, and highly contaminated areas in need of environmental remediation. Multiple statistical procedures are devoted to obtaining representative statistics, whose maAuthorsRicardo A. OleaRandom variable
A random variable is a function that assigns a value in a sample space to an element of an arbitrary set (James 1992; Pawlowsky-Glahn et al. 2015). It is a model for a random experiment: the arbitrary set is an abstraction of the experimental conditions, the values taken by the random variable are in the sample space, and the function itself models the assignment of outcomes, thus also describingAuthorsRicardo A. OleaProbabilistic methodology for the assessment of original and recoverable coal resources, illustrated with an application to a coal bed in the Fort Union Formation, Wyoming
Executive SummaryThe U.S. Geological Survey (USGS) has been using its Circular 891 for evaluating uncertainty in coal resource assessments for more than 35 years. Calculated cell tonnages are assigned to four qualitative reliability classes depending exclusively on distance to the nearest drill hole. The main appeal of this methodology, simplicity, is also its main drawback. Reliability may dependAuthorsRicardo A. Olea, Brian N. Shaffer, Jon E. Haacke, James A. LuppensMultivariate classification of the crude oil petroleum systems in southeast Texas, USA, using conventional and compositional data analysis of biomarkers
Chemically, petroleum is an extraordinarily complex mixture of different types of hydrocarbons that are now possible to isolate and identify because of advances in geochemistry. Here, we use biomarkers and carbon isotopes to establish genetic differences and similarities among oil samples. Conventional approaches for evaluating biomarker and carbon isotope relative abundances include statistical tAuthorsRicardo A. Olea, J. A Martin-Fernandez, William H. CraddockInsights on the characteristics and sources of gas from an underground coal mine using compositional data analysis
Coal mine gas originates from the gas emission zone (GEZ) of the mine, as well as the longwall face and pillars. Gas emissions are controlled directly at the sources using horizontal or vertical boreholes drilled from surface or from the entries in advance of mining, or it is captured from the fractured and caved zones (gob) using ventholes during mining. The rest of the gas, especially that gas tAuthorsC. Özgen Karacan, Josep Antoni Martín-Fernández, Leslie F. Ruppert, Ricardo A. OleaNon-USGS Publications**
Buatois, L.A., Mángano, M.G, Olea, R.A., Wilson, M.A., 2016. Decoupled evolution of soft and hard substrate communities during Cambrian Explosion and Great Ordovician Biodiversification Event. Proceedings of the National Academy of Sciences, vol. 113, no. 25, p. 6945−6948 and 28 pp. of Supporting Information.
Schuenemeyer, J. H., Olea, R.A., 2014. Distributional assumptions and parametric uncertainties in the aggregation of geologic resources. In Mathematics of Planet Earth, Proceedings of the 15th Annual Conference of the International Association for Mathematical Geosciences, Pardo-Igúzquiza, E., Guardiola-Albert, C., Heredia, J., Moreno-Merino, L., Durán, J.J., Vargas-Guzmán, J.J., editors, p. 49−52.Pardo-Igúzquiza, E., Olea, R. A., Dowd, P.A, 2014. Semivariogram model inference using the median bootstrap statistics. In Mathematics of Planet Earth, Proceedings of the 15th Annual Conference of the International Association for Mathematical Geosciences, Pardo-Igúzquiza, E., Guardiola-Albert, C., Heredia, J., Moreno-Merino, L., Durán, J.J., Vargas-Guzmán, J.J., editors, p. 79−82.
Karacan, C. Ö., Olea, R.A., 2014. Coalbed methane production analysis and filter simulation for quantifying gas drainage from coal seams. In Mathematics of Planet Earth, Proceedings of the 15th Annual Conference of the International Association for Mathematical Geosciences, Pardo-Igúzquiza, E., Guardiola-Albert, C., Heredia, J., Moreno-Merino, L., Durán, J.J., Vargas-Guzmán, J.J., editors, p. 549−552.
Olea, R.A., Luppens, J.A., Tewalt, S.J., 2014. Moving away from distance classifications as measures of resource uncertainty. In Mathematics of Planet Earth, Proceedings of the 15th Annual Conference of the International Association for Mathematical Geosciences, Pardo-Igúzquiza, E., Guardiola-Albert, C., Heredia, J., Moreno-Merino, L., Durán, J.J., Vargas-Guzmán, J.J., editors, p. 585−588.
Olea, R.A., Houseknecht, D.W., Garrity, C. P. and Cook, T.A., 2011, Assessment of shale-gas resources using correlated variables and application to the Woodford play, Arkoma basin, southeast Oklahoma: Special issue on New Quantitative Applications of Geomathematics in Earth Sciences of the Geological Survey of Spain Bulletin, Boletín Geológico y Minero, vol. 122, no.4, p. 483–496.
Martín-Fernández, J. A., Palarea-Alabaladejo, J., and Olea, R.A., 2011, Dealing with zeros. In V. Pawlowsky-Glahn and A. Buccianti (eds.), Compositional Data Analysis—Theory and Applications: Wiley & Sons, Ltd, Chichester, UK, p. 43–58.
Bunnell, J. E., Garcia, L. V., Furst, J. M., Lerch, H., Olea, R. A., Suitt, S. E., and Kolker, A., 2010, Navajo coal combustion and respiratory health near Shiprock, New Mexico. Journal of Environmental and Public Health, vol. 2010, article ID 260525, DOI:10.1155/2010/260525, 14 p.
Olea, R. A., 2009, Crossvalidation of cumulative probabilities for parameter selection in geostatistical estimation and simulation: Proceedings of the 2009 Conference of the International Association for Mathematical Geosciences, http://iamg09.stanford.edu
Martín-Fernández, J. A., Olea, R. A., and Palarea-Albaladejo, J., 2009, Multivariate approach using bootstrapping for the inference of distributional parameters of samples containing compositional values below detection limit. Abstract in Proceedings of the 31st Spanish Congress of Statistics and Operations Research, Murcia, Spain, p. 54, CD-ROM. (ISBN: 978-84-691-8159-1)
Kolker, A , Engle, M. A., Hower, J. C., O’Keefe, J. M. K., Heffern, E. L., Radke, L. F., Prakash, A., ter Schure, A., Román-Colón, Y., and Olea, R., 2009, Measuring CO2 emissions from coal fires in the U.S.: Proceedings, Annual International Coal Conference, Pittsburgh, PA, September, 2009, 7 p.
Olea, R. A., 2008, Basic Statistical Concepts and Methods for Earth Scientists: U.S. Geological Survey, Open-File Report 2008-1017, http://pubs.usgs.gov/of/2008/1017/, 191 p.
**Disclaimer: The views expressed in Non-USGS publications are those of the author and do not represent the views of the USGS, Department of the Interior, or the U.S. Government.
- Software
Computer programs for the assessment of coal resources (ver. 2.0, April 2021)
The USGS assessment and methodology reports cited within this software release require extensive processing using computational methods and modeling. The most demanding aspects of the modeling were performed using publicly available software: SGeMS and GSLIB (See the 'related External Resources' section on this webpage to learn more about this software). This publication releases the FORTRAN sourcComputer programs for the assessment of coal resources (ver. 2.0, April 2021)
The USGS assessment and methodology reports cited within this software release require extensive processing using computational methods and modeling. The most demanding aspects of the modeling were performed using publicly available software: SGeMS and GSLIB.
*Disclaimer: Listing outside positions with professional scientific organizations on this Staff Profile are for informational purposes only and do not constitute an endorsement of those professional scientific organizations or their activities by the USGS, Department of the Interior, or U.S. Government