Ricardo A. Olea, Ph.D. (Former Employee)
Science and Products
Filter Total Items: 83
Mapping of compositional properties of coal using isometric log-ratio transformation and sequential Gaussian simulation – A comparative study for spatial ultimate analyses data
Chemical properties of coal largely determine coal handling, processing, beneficiation methods, and design of coal-fired power plants. Furthermore, these properties impact coal strength, coal blending during mining, as well as coal's gas content, which is important for mining safety. In order for these processes and quantitative predictions to be successful, safer, and economically feasible, it is
Authors
C. Özgen Karacan, Ricardo A. Olea
Carbon dioxide enhanced oil recovery performance according to the literature
IntroductionThe need to increase the efficiency of oil recovery and environmental concerns are bringing to prominence the use of carbon dioxide (CO2) as a tertiary recovery agent. Assessment of the impact of flooding with CO2 all eligible reservoirs in the United States not yet undergoing enhanced oil recovery (EOR) requires making the best possible use of the experience gained in 40 years of appl
Authors
Ricardo A. Olea
A database and probabilistic assessment methodology for carbon dioxide enhanced oil recovery and associated carbon dioxide retention in the United States
The U.S. Geological Survey (USGS) has developed an assessment methodology for estimating the potential incremental technically recoverable oil resources resulting from carbon dioxide-enhanced oil recovery (CO2-EOR) in reservoirs with appropriate depth, pressure, and oil composition. The methodology also includes a procedure for estimating the CO2 that remains in the reservoir after the CO2-EOR pro
Authors
Peter D. Warwick, Mahendra K. Verma, Emil D. Attanasi, Ricardo A. Olea, Madalyn S. Blondes, Philip Freeman, Sean T. Brennan, Matthew D. Merrill, Hossein Jahediesfanjani, Jacqueline Roueche, Celeste D. Lohr
Resampling of spatially correlated data with preferential sampling for the estimation of frequency distributions and semivariograms
Spatial data are commonly minimal and may have been collected in the process of confirming the profitability of a mining venture or investigating a contaminated site. In such situations, it is common to have measurements preferentially taken in the most critical areas (sweet spots, allegedly contaminated areas), thus conditionally biasing the sample. While preferential sampling makes good practica
Authors
Ricardo A. Olea
Calorific value and compositional ultimate analysis with a case study of a Texas lignite
Measurements to determine coal quality as fuel include proximate analysis, ultimate analysis and calorific value. The latter is an attribute taking non-negative real values, so a simple transformation is sufficient for its spatial modeling applying geostatistics. The analyses, however, involve proportions that follow the properties of compositional data, thus requiring special preprocessing for an
Authors
Ricardo A. Olea, James Luppens, Juan J. Egozcue, Vera Pawlowsky-Glahn
Mapping of coal quality using stochastic simulation and isometric logratio transformation with an application to a Texas lignite
Coal is a chemically complex commodity that often contains most of the natural elements in the periodic table. Coal constituents are conventionally grouped into four components (proximate analysis): fixed carbon, ash, inherent moisture, and volatile matter. These four parts, customarily measured as weight losses and expressed as percentages, share all properties and statistical challenges of compo
Authors
Ricardo A. Olea, James A. Luppens
Stochastic reservoir simulation for the modeling of uncertainty in coal seam degasification
Coal seam degasification improves coal mine safety by reducing the gas content of coal seams and also by generating added value as an energy source. Coal seam reservoir simulation is one of the most effective ways to help with these two main objectives. As in all modeling and simulation studies, how the reservoir is defined and whether observed productions can be predicted are important considerat
Authors
C. Özgen Karacan, Ricardo A. Olea
Cokriging of compositional balances including a dimension reduction and retrieval of original units
Compositional data constitutes a special class of quantitative measurements involving parts of a whole. The sample space has an algebraic-geometric structure different from that of real-valued data. A subcomposition is a subset of all possible parts. When compositional data values include geographical locations, they are also regionalized variables. In the Earth sciences, geochemical analyses are
Authors
V. Pawlowsky-Glahn, J. J. Egozcue, Ricardo A. Olea, E Pardo-Igúzquiza
Robust and resistant semivariogram modelling using a generalized bootstrap
The bootstrap is a computer-intensive resampling method for estimatingthe uncertainty of complex statistical models. We expand on anapplication of the bootstrap for inferring semivariogram parameters andtheir uncertainty. The model fitted to the median of the bootstrap distributionof the experimental semivariogram is proposed as an estimator ofthe semivariogram. The proposed application is not res
Authors
Ricardo A. Olea, E. Pardo-Iguzquiza, P. A. Dowd
Modeling uncertainty in coal resource assessments, with an application to a central area of the Gillette coal field, Wyoming
Standards for the public disclosure of mineral resources and reserves do not require the use of any specific methodology when it comes to estimating the reliability of the resources. Unbeknownst to most intended recipients of resource appraisals, such freedom commonly results in subjective opinions or estimations based on suboptimal approaches, such as use of distance methods. This report presents
Authors
Ricardo A. Olea, James A. Luppens
Reply to: Turner, R.E., 2014. Discussion of: Olea, R.A. and Coleman, J.L., Jr., 2014. A synoptic examination of causes of land loss in southern Louisiana as related to the exploitation of subsurface geologic resources, Journal of Coastal Research, 30(5),
To a large extent, geology is a science of solving inverse problems based on some data and scientific principles. Solutions to these types of problems are not unique, especially when using different data, invoking different principles, or both. It is not surprising that the discussant and we have reached different conclusions on the same specific issue of land loss along the coast of Louisiana bec
Authors
Ricardo A. Olea, James L. Coleman
Characterization of the Marcellus Shale based on computer-assisted correlation of wireline logs in Virginia and West Virginia
The Middle Devonian Marcellus Shale in the Appalachian basin extends from central Ohio on the west to eastern New York on the east, and from north-central New York on the north to northern Tennessee on the south. Its thickness ranges from 0 feet (ft) where it pinches out to the west to as much as 700 ft in its eastern extent. Within the Broadtop synclinorium, the thickness of the Marcellus Shale r
Authors
Catherine B. Enomoto, Ricardo A. Olea, James L. Coleman
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.
Science and Products
Filter Total Items: 83
Mapping of compositional properties of coal using isometric log-ratio transformation and sequential Gaussian simulation – A comparative study for spatial ultimate analyses data
Chemical properties of coal largely determine coal handling, processing, beneficiation methods, and design of coal-fired power plants. Furthermore, these properties impact coal strength, coal blending during mining, as well as coal's gas content, which is important for mining safety. In order for these processes and quantitative predictions to be successful, safer, and economically feasible, it is
Authors
C. Özgen Karacan, Ricardo A. Olea
Carbon dioxide enhanced oil recovery performance according to the literature
IntroductionThe need to increase the efficiency of oil recovery and environmental concerns are bringing to prominence the use of carbon dioxide (CO2) as a tertiary recovery agent. Assessment of the impact of flooding with CO2 all eligible reservoirs in the United States not yet undergoing enhanced oil recovery (EOR) requires making the best possible use of the experience gained in 40 years of appl
Authors
Ricardo A. Olea
A database and probabilistic assessment methodology for carbon dioxide enhanced oil recovery and associated carbon dioxide retention in the United States
The U.S. Geological Survey (USGS) has developed an assessment methodology for estimating the potential incremental technically recoverable oil resources resulting from carbon dioxide-enhanced oil recovery (CO2-EOR) in reservoirs with appropriate depth, pressure, and oil composition. The methodology also includes a procedure for estimating the CO2 that remains in the reservoir after the CO2-EOR pro
Authors
Peter D. Warwick, Mahendra K. Verma, Emil D. Attanasi, Ricardo A. Olea, Madalyn S. Blondes, Philip Freeman, Sean T. Brennan, Matthew D. Merrill, Hossein Jahediesfanjani, Jacqueline Roueche, Celeste D. Lohr
Resampling of spatially correlated data with preferential sampling for the estimation of frequency distributions and semivariograms
Spatial data are commonly minimal and may have been collected in the process of confirming the profitability of a mining venture or investigating a contaminated site. In such situations, it is common to have measurements preferentially taken in the most critical areas (sweet spots, allegedly contaminated areas), thus conditionally biasing the sample. While preferential sampling makes good practica
Authors
Ricardo A. Olea
Calorific value and compositional ultimate analysis with a case study of a Texas lignite
Measurements to determine coal quality as fuel include proximate analysis, ultimate analysis and calorific value. The latter is an attribute taking non-negative real values, so a simple transformation is sufficient for its spatial modeling applying geostatistics. The analyses, however, involve proportions that follow the properties of compositional data, thus requiring special preprocessing for an
Authors
Ricardo A. Olea, James Luppens, Juan J. Egozcue, Vera Pawlowsky-Glahn
Mapping of coal quality using stochastic simulation and isometric logratio transformation with an application to a Texas lignite
Coal is a chemically complex commodity that often contains most of the natural elements in the periodic table. Coal constituents are conventionally grouped into four components (proximate analysis): fixed carbon, ash, inherent moisture, and volatile matter. These four parts, customarily measured as weight losses and expressed as percentages, share all properties and statistical challenges of compo
Authors
Ricardo A. Olea, James A. Luppens
Stochastic reservoir simulation for the modeling of uncertainty in coal seam degasification
Coal seam degasification improves coal mine safety by reducing the gas content of coal seams and also by generating added value as an energy source. Coal seam reservoir simulation is one of the most effective ways to help with these two main objectives. As in all modeling and simulation studies, how the reservoir is defined and whether observed productions can be predicted are important considerat
Authors
C. Özgen Karacan, Ricardo A. Olea
Cokriging of compositional balances including a dimension reduction and retrieval of original units
Compositional data constitutes a special class of quantitative measurements involving parts of a whole. The sample space has an algebraic-geometric structure different from that of real-valued data. A subcomposition is a subset of all possible parts. When compositional data values include geographical locations, they are also regionalized variables. In the Earth sciences, geochemical analyses are
Authors
V. Pawlowsky-Glahn, J. J. Egozcue, Ricardo A. Olea, E Pardo-Igúzquiza
Robust and resistant semivariogram modelling using a generalized bootstrap
The bootstrap is a computer-intensive resampling method for estimatingthe uncertainty of complex statistical models. We expand on anapplication of the bootstrap for inferring semivariogram parameters andtheir uncertainty. The model fitted to the median of the bootstrap distributionof the experimental semivariogram is proposed as an estimator ofthe semivariogram. The proposed application is not res
Authors
Ricardo A. Olea, E. Pardo-Iguzquiza, P. A. Dowd
Modeling uncertainty in coal resource assessments, with an application to a central area of the Gillette coal field, Wyoming
Standards for the public disclosure of mineral resources and reserves do not require the use of any specific methodology when it comes to estimating the reliability of the resources. Unbeknownst to most intended recipients of resource appraisals, such freedom commonly results in subjective opinions or estimations based on suboptimal approaches, such as use of distance methods. This report presents
Authors
Ricardo A. Olea, James A. Luppens
Reply to: Turner, R.E., 2014. Discussion of: Olea, R.A. and Coleman, J.L., Jr., 2014. A synoptic examination of causes of land loss in southern Louisiana as related to the exploitation of subsurface geologic resources, Journal of Coastal Research, 30(5),
To a large extent, geology is a science of solving inverse problems based on some data and scientific principles. Solutions to these types of problems are not unique, especially when using different data, invoking different principles, or both. It is not surprising that the discussant and we have reached different conclusions on the same specific issue of land loss along the coast of Louisiana bec
Authors
Ricardo A. Olea, James L. Coleman
Characterization of the Marcellus Shale based on computer-assisted correlation of wireline logs in Virginia and West Virginia
The Middle Devonian Marcellus Shale in the Appalachian basin extends from central Ohio on the west to eastern New York on the east, and from north-central New York on the north to northern Tennessee on the south. Its thickness ranges from 0 feet (ft) where it pinches out to the west to as much as 700 ft in its eastern extent. Within the Broadtop synclinorium, the thickness of the Marcellus Shale r
Authors
Catherine B. Enomoto, Ricardo A. Olea, James L. Coleman
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.
*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