Dr. C. Özgen Karacan is a Research Petroleum Engineer with the USGS Geology, Energy & Minerals (GEM) Science Center in Reston, VA.
Dr. Karacan conducts research related to CO2-EOR, CO2 sequestration, reservoir engineering of petroleum system, and coal mine and abandoned mine methane resources. Before joining the USGS, Dr. Karacan worked for the National Institute for Occupational Safety and Health’s (NIOSH) Pittsburgh Mining Research Division for 13 years, where he managed research projects related to ventilation, and sources of gob gas and its control in coal mines.
Dr. Karacan is one of the Editors of International Journal of Coal Geology, and a Bureau member and vice chair of the United Nations Economic Commission for Europe’s (UNECE) Group of Experts on Coal Mine Methane. He holds associate professor of petroleum engineering accreditation in Turkey and an adjunct professor position at China University of Geosciences in Beijing (CUGB). Dr. Karacan won NIOSH Alice Hamilton Award in 2013 and 2016.
Dr. Karacan received his B.S., M.S., and Ph.D. degrees in petroleum and natural gas engineering from Middle East Technical University, in Ankara, Turkey and worked for the Pennsylvania State University between 1998 and 2003 as a research associate.
Professional Experience
2017-present: USGS, Geology, Energy & Minerals Science Center, Reston VA
2003-2017: CDC/NIOSH, Pittsburgh Mining Research Division, Pittsburgh PA
1998-2003: The Pennsylvania State University, University Park PA
1991-1998: Middle East Technical University, Ankara, Turkey
Education and Certifications
Ph.D. Petroleum and Natural Gas Engineering, Middle East Technical University, Ankara, Turkey, 1998
M.S. Petroleum and Natural Gas Engineering, Middle East Technical University, Ankara, Turkey, 1993
B.S. Petroleum and Natural Gas Engineering, Middle East Technical University, Ankara, Turkey, 1991
Science and Products
Assessing Emissions from Active and Abandoned Coal Mines
National assessment of carbon dioxide enhanced oil recovery and associated carbon dioxide retention resources - data release
Results from surveys to academic and industry and government geoscientists on the future of coal geoscientists
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
Merging machine learning and geostatistical approaches for spatial modeling of geoenergy resources
Merging machine learning and geostatistical approaches for spatial modeling of geoenergy resources
Predicting methane emissions and developing reduction strategies for a Central Appalachian Basin, USA, longwall mine through analysis and modeling of geology and degasification system performance
Assessment of resource potential from mine tailings using geostatistical modeling for compositions: A methodology and application to Katherine Mine site, Arizona, USA
Machine learning and data augmentation approach for identification of rare earth element potential in Indiana Coals, USA
National assessment of carbon dioxide enhanced oil recovery and associated carbon dioxide retention resources — Results
National assessment of carbon dioxide enhanced oil recovery and associated carbon dioxide retention resources — Summary
Multilayer perceptrons (MLPs)
Realizations
Insights on the characteristics and sources of gas from an underground coal mine using compositional data analysis
Single-well production history matching and geostatistical modeling as proxy to multi-well reservoir simulation for evaluating dynamic reservoir properties of coal seams
Science and Products
- Science
Assessing Emissions from Active and Abandoned Coal Mines
The gas emission zone liberates and accumulates significant amounts of coal mine methane as a by-product of active mining. In most active mines, coal mine methane is controlled by wellbores, called gob gas ventholes. Despite the presence of these wellbores, it is not possible to capture all of the methane generated within the gas emission zone. As a consequence, a large amount of gas migrates into... - 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 sResults from surveys to academic and industry and government geoscientists on the future of coal geoscientists
At recent technical conferences, many coal geoscientists in academia and government institutions as well as in industry organizations have expressed concern about the dwindling number of students and young staff members interested in careers in coal geoscience. To better understand what is driving these trends and to identify potential ways that the community can increase interest and participatio - Multimedia
- Publications
Filter Total Items: 30
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. WarwickMerging machine learning and geostatistical approaches for spatial modeling of geoenergy resources
Geostatistics is the most commonly used probabilistic approach for modeling earth systems, including quality parameters of various geoenergy resources. In geostatistics, estimates, either on a point or block support, are generated as a spatially-weighted average of surrounding samples. The optimal weights are determined through the stationary variogram model which accounts for the spatial structurAuthorsGamze Erdogan Erten, Oktay Erten, C. Özgen Karacan, Jeff Boisvert, Clayton V. DeutschMerging machine learning and geostatistical approaches for spatial modeling of geoenergy resources
Geostatistics is the most commonly used probabilistic approach for modeling earth systems, including quality parameters of various geoenergy resources. In geostatistics, estimates, either on a point or block support, are generated as a spatially-weighted average of surrounding samples. The optimal weights are determined through the stationary variogram model which accounts for the spatial structurAuthorsGamze Erdogan Erten, Oktay Erten, C. Özgen Karacan, Jeff Boisvert, Clayton V. DeutschPredicting methane emissions and developing reduction strategies for a Central Appalachian Basin, USA, longwall mine through analysis and modeling of geology and degasification system performance
Coal mine methane is a safety concern in active mines due to explosion risk and an environmental concern due to the greenhouse gas (GHG) properties of methane emissions to the atmosphere. Depending on the mine design and operation, structural and stratigraphic characteristics of the geology, and the properties of coal beds affected by mining, a significant amount of methane can be released duringAuthorsC. Özgen KaracanAssessment of resource potential from mine tailings using geostatistical modeling for compositions: A methodology and application to Katherine Mine site, Arizona, USA
The mining industry, in most cases, targets a specific valuable commodity that is present in small quantities within large volumes of extracted material. After milling and processing, most of the extracted material and the effluents are stored as waste (tailings) in impoundments, such as dams or waste dumps, or are backfilled into underground mines. In time, tailing materials may become an issue oAuthorsC. Özgen Karacan, Oktay Erten, Josep Antoni Martín-FernándezMachine learning and data augmentation approach for identification of rare earth element potential in Indiana Coals, USA
Rare earth elements and yttrium (REYs) are critical elements and valuable commodities due to their limited availability and high demand in a wide range of applications and especially in high-technology products. The increased demand and geopolitical pressures motivate the search for alternative sources of REYs, and coal, coal waste, and coal ash are considered as new sources for these critical eleAuthorsSnahamoy Chatterjee, Maria Mastalerz, Agnieszka Drobniak, C. Özgen KaracanNational 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. VarelaNational 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. VarelaMultilayer perceptrons (MLPs)
Artificial neural networks (ANNs) are adaptable systems that can solve problems that are difficult to describe with a mathematical relationship. They seek relationships between different types of datasets with their abilities to learn either with supervision or without. ANNs recognize patterns between input and output space and generalize solutions, in a way simulating the human brain’s learning eAuthorsC. Özgen KaracanRealizations
In statistics, a realization is an observed value of a random variable (Gubner 2006). In mathematical geology, the most important realizations are those in the form of maps of spatially correlated regionalized variables.Spatial description of random variables within complex domains and making certain decisions about those require complete knowledge of the attribute of interest at each point in spaAuthorsC. Özgen KaracanInsights 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. OleaSingle-well production history matching and geostatistical modeling as proxy to multi-well reservoir simulation for evaluating dynamic reservoir properties of coal seams
Reservoir properties of coal seams such as gas and water effective permeabilities and gas content, as well as spatial distributions thereof, affect the success of gas production and CO2-enhanced gas recovery (EGR) with simultaneous CO2 sequestration. These properties change during production and injection operations due to variations in reservoir pressure, matrix shrinkage/swelling, and water satuAuthorsC. Özgen Karacan