Geology topics

C. Özgen Karacan

Publications and source records attributed to C. Özgen Karacan.

7 recordsLinked to original sources

USGS2026

Remote sensing enables basin-scale inventories of coal mine methane

Underground coal mines are important global sources of methane, but emission estimates are uncertain. We show that emission estimates for individual mines from aircraft remote-sensing surveys in the United States agree within 40% with direct measurements used for national emission reporting (IPCC Tier 3 estimate). Such direct measurements are unavailable in most countries, which rely on estimated emission factors (EFs) applied to coal-production rates. We find that EFs from IPCC Tier 1 and the Model for Calculating Coal Mine Methane (MC2M) methods overestimate U.S. emissions 3-fold due to incorrect dependence on mine depth. An IPCC Tier 2 method using measured basin-specific mine gas content agrees with direct emission measurements but does not account for gob well emissions and requires gas content data that are generally unavailable. We show that aircraft remote sensing for a small sample of mines can successfully estimate basin-specific EFs for ventilation shafts and gob wells, enabling estimates of basin- and national-scale emissions. We discuss how the method can be applied with satellite remote sensing to quantify coal emissions worldwide.

Alabama, Colorado, Kentucky, New Mexico, Ohio, Pen↗

USGS2026

Inference of pattern-based geological CO2 sequestration and oil recovery potential in a commingled main pay and residual oil zone CO2-EOR flood

Several detailed studies have shown that residual oil zones (ROZs) can present significant resources for additional hydrocarbon recovery as well as subsurface carbon dioxide (CO 2 ) sequestration via enhanced oil recovery by injecting CO 2 (CO 2 -EOR). Field development strategies included new wells drilled dedicated to main pay zones (MPZ) and ROZs, or existing wells in MPZs deepened to ROZs for commingled injection-production using different well patterns. The latter presented a challenge when discerning the injection and production from each of the zones, and for subsequent quantification of CO 2 sequestration and EOR potential from different patterns and from the field. In this paper, an innovative method for analyzing commingled injections and productions from MPZs and ROZs, with application to pattern-based data from four staggered line drive patterns in Wasson Field's Denver Unit, Texas, USA, was developed. Decline curve and ratio-trend methods were used as means of history-matching and forecasting. Cumulative production-time and cumulative production-rate data for oil, gas, and water, as well as water-oil ratio (WOR) and gas-oil ratio (GOR), were analyzed along with injection data for time intervals covering major injection events in MPZ, or MPZ and ROZ combined. A combined analysis enabled inference of allocation of fluids into different zones during WAG (water alternating gas) injection and thereby estimation of CO 2 storage, utilization, and retention in different zones as a function of total injection. Results show that ROZs generally present higher CO 2 sequestration potential compared to MPZs, and a comparable incremental oil recovery factor of ∼20%, on average. Results based on ratio analysis further show that while the WOR trend of the pattern production is mostly dominated and controlled by ROZ, GOR is controlled by both intervals. Although the method relying on decline curves and the approach used in zonal fluid allocations are subject to their limitations, this study presents a practical and innovative well-pattern-based method to infer and forecast CO 2 sequestration and oil recovery quantities and fluid ratios from MPZs and ROZs in commingled operations and highlight the added potential offered by ROZs.

Texas↗

USGS2026

Spatio-temporal modeling for assessing geoenergy resources: A workflow applied to gas in place variation in coal beds

The ability to estimate spatio-temporal changes in hydrocarbon reservoir properties and energy resources within pore volumes is essential for optimizing production, reservoir management, geologic energy storage, and safety in underground mining operations. In coal seams, predicting remaining methane gas-in-place (GIP) is critical for quantifying producible gas and improving mine safety and productivity through effective ventilation planning. Although such changes are commonly evaluated using physics-based numerical simulation models, these approaches often require extensive data, calibration effort, and time. This study presents a spatio-temporal geostatistical modeling approach that bridges the gap between purely spatial models and full numerical simulations. The method is applied to a case study of coal seam degasification in the Mary Lee coal group, Black Warrior Basin, Alabama, USA, to estimate GIP evolution over time within a selected mining district. The analysis uses published data from prior natural gas production history-matching of degasification using vertical wells. Empirical spatial and temporal statistics were calculated for reservoir pressure and water saturation, and spatio-temporal variogram models were fitted to experimental variograms. These models provided the structural basis for spatio-temporal kriging, integrated with spatial estimates of time-invariant parameters (porosity, density, and thickness) to estimate GIP. This approach enabled estimation of GIP changes over time, including periods without data. Boxplots of GIP estimates indicated systematic depletion and decreasing spatial variability, reflecting the impacts of degasification. Comparison with cumulative gas production from empirical well records showed approximately 85% agreement based on a relative similarity metric. Spatio-temporal GIP estimates were also used to estimate methane emissions to longwall ventilation systems and compared with reported emissions from the U.S. EPA Greenhouse Gas Reporting Program, showing similar distributions (≈80%) given data limitations. Overall, this integrated modeling approach provides time-dependent GIP estimates with broader implications for resource assessment applications.

Alabama↗

USGS2025

Estimated ultimate recovery (EUR) Prediction for Eagle Ford Shale using integrated datasets and artificial neural networks

The estimated ultimate recovery (EUR) is an important parameter for forecasting oil and gas production and informing decisions regarding field development strategies. In this study, we combined site-specific geologic, completion, and operational parameters with the predictive capabilities of machine learning (ML) models to predict EURs of the wells for the Eagle Ford Marl Continuous Oil Assessment Unit. We developed an extensive dataset of wells that have produced from the lower and upper Eagle Ford Shale intervals and reduced the model complexity using principal component analysis. We tested the ML models and estimated the sensitivities of ML-predicted EURs to changes in the values of different input variables. The results of applying the optimized ML model to the Eagle Ford suggest that the approach developed in this study could be promising. The ML estimates of the EURs fit the DCA-based values with an R 2 ~ 0.9 and a mean absolute error of ~36 × 10 3 bbl. In the lower Eagle Ford Shale, the EUR estimates were found to be most sensitive to changes in porosity, net thickness of the interval, clay volume, and the API gravity of the oil; and that in the upper Eagle Ford Shale they were most sensitive to changes in the total organic carbon and water saturation, which suggests that it could be important to consider these parameters in assessing these intervals or close analogs.

Louisiana, Mississippi, Texas↗

USGS2025

Temporal and spatial comparison of coal mine ventilation methane emissions and mitigation quantified using PRISMA satellite data and on-site measurements

Emission monitoring at the facility level (bottom-up, BU) is key for accurate reporting of coal mine methane (CMM) emissions. Recent advances in aerial and satellite observations (top-down, TD) indicate that these methods have the potential to support CMM emissions monitoring and reporting of, as well as track the effectiveness of, mitigation actions. That said, studies have shown discrepancies between BU and TD estimations. Performing TD monitoring with concurrent BU measurements at the same mines may help address the observed discrepancies and improve quantification methods to narrow the gap between BU and TD data. This paper presents a comparison of concurrent BU-TD methane emission fluxes monitored from two ventilation shafts at a southwestern Virginia, USA, longwall mine to complement the existing body of studies on satellite-based monitoring of coal mines by incorporating continuous ground-based monitoring with concurrent TD monitoring of methane emission fluxes to address the gap and provide valuable insights into temporal emission patterns. The shafts were monitored on multiple dates between 2020 and 2023. BU monitoring was performed at the exhaust fans, while TD quantifications used PRISMA hyperspectral satellite data and two different wind reanalysis datasets (i.e., GEOS-FP and ERA5). This mine also offered a unique opportunity for BU-TD comparisons before and after ventilation air methane (VAM) oxidizer operation, which was installed at one of the shafts in 2022. The results showed that TD-estimated mean fluxes were generally lower than BU data, which were attributed to quantification difficulties associated with the low albedo caused by heavy vegetation and the terrain of the area. However, despite the discrepancies in mean emissions, both the interquartile range and the data range of the distributions generally overlapped, and the estimates correctly showed the emission trends.

Virginia↗

USGS2025

Waning greenhouse gas emissions from U.S. Federal lease coal production by the mid-21st century

This study presents estimates of future years (2024–2051) United States Federal lease coal production and the resulting greenhouse gas (GHG) emissions from the combustion, transport, and mining of that fuel. Results from the coal production estimate indicate a decline in production from Federal leases; with known production of 240 million short tons (mtn) in 2023 and a projected decline to 34.0 mtn by 2051, which represents a reduction to 14.2% of the 2023 value. In parallel with this projection, total GHG emissions are estimated to decrease from 402.2 million metric tons of carbon dioxide equivalent (MMT CO 2 eq.) in 2024 to 55.0 MMT CO 2 eq. in 2051, a decline to 13.7% of 2024 emissions estimates. The reductions in coal production and emissions are mainly the result of planned coal combustion power plant closures, with major projected closures in 2037 and 2048. However, GHG emissions estimates for future years can be uncertain as they rely heavily on coal production estimates from operators' public business plans and other publicly available resources. Forward looking plans of this type are subject to significant changes if economic and political factors deviate from current information. Results suggest that average GHG emissions over the time series breakout to 95% end point combustion, 3.7% transportation combustion emissions, and 1.3% fugitive emissions, although there is uncertainty associated with these figures. Uncertainty stemming from production projections, sector distributions, and emissions factors on the future emissions estimates increases with time, ranging from −28% to +48% within the 2024–2051 timeframe.

Alabama, Colorado, Montana, North Dakota, Utah, Wy↗

USGS2025

Performance analysis of oil recovery and CO2 retention in a greenfield residual oil zone: CO2-EOR in Tall Cotton Field (Permian Basin, West Texas, USA)

Residual oil zones (ROZs) can offer significant oil resources via enhanced oil recovery (EOR) as well as subsurface carbon dioxide (CO 2 ) retention during injection. If injected CO 2 is anthropogenic, the ROZs can offer a substantial geologic storage potential. The ROZs below the oil/water contact (OWC) of main pay zones (MPZ) in conventional reservoirs or brownfields, are more commonly developed for CO 2 injection and oil production and reported in the literature. However, CO 2 -EOR in greenfield ROZs, reservoirs without a MPZ present, have rarely been developed for CO 2 -EOR operation. The Tall Cotton Field of West Texas, Permian Basin, which started production in 2015 (Phase 1) and expanded in 2017 (Phase 2) from the San Andres Limestone, is one of the first examples of greenfield ROZs developed for EOR by injecting CO 2 . This paper analyses EOR and CO 2 retention performance of Tall Cotton Field using allocated injection and production data from inverted 5-spot well patterns of Phase-1 and -2 developments. Production and injection data allocated to each of the 28 identified patterns (nine 20-acre patterns for Phase-1, three 20-acre and sixteen 10-acre patterns for Phase-2) were analyzed for historical and forecasted oil recovery using ratio-trend decline analysis, and for CO 2 retention performance of the patterns. The allocated data were further used to calculate injected reservoir pore volume and void replacement ratios (VRR) for the analysis period. Quantitative results indicated that oil recovery factors of the 5-spot patterns varied between 4–10 %, and 5–30 % between the end of injection and the forecast periods, respectively. Storage of CO 2 , on the other hand, increased to a mean value of ∼7130 MMscf per pattern in Phase-1 and to a mean storage of 3700 MMscf per pattern in Phase-2 until the end of injection, followed by a decline after the end of injection and into the forecast period. Resulting CO 2 utilization factors ∼6–50 Mscf/bbl were estimated at the end of injection. Overall, presented results suggested that developing greenfield ROZs for CO 2 -EOR can be as promising as brownfield ROZs and mature MPZs for EOR and underground storage of injected CO 2 . For Tall Cotton Field, results suggest that Phase-2 patterns generally outperformed Phase-1 for oil recovery factors, while Phase-1 performed better in CO 2 retention performance metrics. This is the first study in the literature that reports a detailed CO 2 -EOR performance analysis of a greenfield ROZ in the Permian Basin, which can potentially allow for comparison with MPZs and brownfield ROZs.

Texas↗