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USGS2023

Merging 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 structure of the samples. Recently, efficient modeling workflows using various machine learning algorithms (MLAs) have been expanded to the spatial context for modeling geological heterogeneity. The flexible use of MLAs as a spatial estimation tool stems mainly from the fact that unlike kriging, they do not require any variogram, nor do they depend strongly on a prior stationarity assumption (i.e., second order stationarity). This study evaluates the performance of two MLAs (ensemble super learner and elliptical radial basis neural network), ordinary kriging, and hybrid spatial modeling approaches using ordinary intrinsic collocated cokriging. The aforementioned modeling techniques are compared for estimating resources for four coal variables (wash yield, ash yield, calorific value and thickness) as an example. The results suggest that MLAs, when implemented alone, do not outperform ordinary kriging, but the estimation accuracy of the final model, measured by the root mean squared error tends to subtly improve (

Virginia↗

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↗

USGS1981

Potential hydrologic effects of developing coal and other geo-energy resources of Oregon; a review

Southwestern Oregon has several hundred million tons of good-quality minable coal. Because of the dip of the coal beds, the only economical method of mining would be by underground methods. In addition, minor occurrences of low-quality coal have been noted at more than 20 sites in both western and northeastern Oregon. About 2 million acres are now under lease for petroleum and gas exploration across the State. Natural gas was discovered in northwestern Oregon in 1979, and current production is about 17 million cubic feet per day from five wells. Thirteen Known Geothermal Resource Areas in several parts of the State cover 432,000 acres, and more than 420,000 acres are under lease for geothermal exploration. No hydrologic impacts have been noted from exploration and production of coal or other geoenergy resources in Oregon. (USGS)

Open-File Report↗

USGS2023

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 these viable fields that also contain ROZs have extended carbon dioxide enhanced oil recovery (CO 2 -EOR) to below the MPZ to commercially recover oil from the associated ROZ. Increased interest in ROZs is also due to the application of anthropogenic CO 2 for oil recovery, leading to the subsurface sequestration of CO 2 , which can be part of the current net-zero carbon oil and climate change objectives. Several detailed studies of selected formations in the Permian Basin of the United States have shown that ROZs can be as common as traditional conventional oil reservoir traps, suggesting significant resources for potential additional hydrocarbon recovery and subsurface CO 2 sequestration via CO 2 -EOR. However, applications of CO 2 -EOR to ROZs have been limited despite the estimation of significant oil resources considered recoverable through CO 2 -EOR, and the benefit of concurrent geologic CO 2 storage that would help offset carbon emissions from the produced oil. The combination of insufficient economic incentives and technical reasons related to data scarcity, such as lack of penetration of wells and well logs, for locating ROZs has limited development of their resource potential when compared to known fields. This paper presents a probabilistic methodology for identifying and evaluating ROZ resources for CO 2 -EOR and CO 2 sequestration potential with the use of public and proprietary data sources. The methodology was developed during a pilot study that focused on the ROZ in the San Andres Formation of a nine-county area in the Permian Basin in West Texas. The pilot study estimated a mean oil in place of 25 × 10 9 barrels (bbl) of oil and a mean potential incremental oil recovery and CO 2 utilization of 2.6 × 10 9 bbl and 28.2 Tcf (1.46 × 10 9 tons), respectively, with 1 hydrocarbon pore volume (HCPV) of injection using the water alternating gas (WAG) method. The results of this pilot study are consistent with reported volumes in the literature for a similar area in the Permian Basin. The pilot study demonstrated that this methodology could be used to identify and assess the recoverable oil and coincident CO 2 storage volumes of ROZs in other formations and regions.

Texas↗

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↗

USGS2023

Structural discontinuities and their control on hydrothermal systems in the Great Basin, USA

Faults are important controls on hydrothermal circulation worldwide. More specifically, structural discontinuities, i.e. locations where faults interact and intersect, host many hydrothermal systems. In the Great Basin, western USA, an extensive characterization effort demonstrated that hydrothermal systems are controlled by one (or more) of eight types of structural discontinuities. Presumably, specific attributes of these structural settings control the generation and maintenance of permeability and porosity, and therefore localize hydrothermal processes. Herein, I examine representative examples of the eight structural settings that host hydrothermal systems in the Great Basin. For each setting, I use a boundary element method to model fault slip on the major faults and track the distribution of stress and strain in the surrounding crust. Results demonstrate that the largest magnitude and most localized stress and strain effects occur in the structural settings that host the largest number of hydrothermal systems; fault stepovers and fault terminations. Structural settings that are common in areas of strike-slip faulting also show localized stress and strain effects. The modelling presented provides process-based explanations for the empirical and conceptual results of regional characterization of Great Basin hydrothermal systems.

Great Basin↗