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Geology topics

Ricardo A. Olea

Publications and source records attributed to Ricardo A. Olea.

At least 19 recordsLinked to original sources

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 holes, and measured sections, was compiled from a previously released geologic database and reinterpreted to provide a more detailed geologic model for the Cherokee coal bed. The thickest part of the Cherokee coal bed lies along the crest of the Wamsutter arch, an east-west trending anticlinal feature that separates the Great Divide subbasin to north from the Washakie subbasin to the south. The Cherokee coal bed consists of several laterally persistent benches separated by partings that range in thickness from one inch to greater than 100 feet. A series of detailed geologic cross sections through the study area show both the structural geology and the distribution and areal extent of the individual coal benches of the Cherokee coal bed. Data generated from the geologic model were used in stochastic geostatistical analyses to estimate the remaining or in-place coal resources. Certain parameters, as described later in the text, were applied to calculate available coal resources for surface and underground mining. This study is part of an ongoing process by the U.S. Geological Survey (USGS) to transition from a distance-based approach to a probabilistic approach for determining uncertainty in coal resource assessment. This probabilistic approach uses quantitative statistical methods to determine the potential range of uncertainty in coal resource estimates, whereas the distance-based approach does not provide any mathematical method to determine the range of uncertainty. Using stochastic geostatistical methods, utilizing 100 realizations or gridding iterations of the data, in-place resources were calculated, with a 90 percent probability, to be 15.261 ± 0.464 billion short tons (bst). Available coal resources tonnages were calculated using separate sets of criteria for surface and underground mining methods, based on probable mining parameters. Tonnage values were calculated based on estimated coal densities determined from available coal quality data. Available coal resources that meet the parameters for surface mining methods were calculated, with a 90 percent probability, to be 0.813 ± 0.038 bst. Available coal resources that meet the parameters for underground mining methods were calculated, with a 90 percent probability, to be 2.393 ± 0.055 bst. The calculations were based on estimates of the resources that meet the parameters for the optimum mining of the thickest coal benches of the Cherokee coal bed. This is depicted in a series of cross sections through the study area that show projected underground mining horizons in the Cherokee coal bed, based on the thickest combinations of individual coal benches.

Wyoming

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

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 (CO 2 -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 CO 2 that could be stored (retained) as a result of CO 2 -EOR activities. The USGS assessment team evaluated more than 3,500 oil reservoirs that were miscible to injected CO 2 . The assessed reservoirs are in 185 previously defined USGS plays in 33 petroleum provinces of 7 national regions. The assessment team estimated that the technically recoverable oil associated with CO 2 -EOR ranges from approximately 25,000 million barrels (MMbbl) at the P 5 percentile to as much as 32,000 MMbbl at the P 95 percentile, with a mean of 29,000 MMbbl. The associated CO 2 retention ranges from approximately 7,400 million metric tons (Mt) at the P 5 percentile to as much as 9,500 Mt at the P 95 percentile, with a mean of 8,400 Mt. The West Texas and Eastern New Mexico region and the Gulf Coast region together contain 60 percent of the mean assessed CO 2 -EOR oil potential and 61 percent of the mean assessed CO 2 retention. Other regions with significant resource potential include the Midcontinent region and Rocky Mountains and Northern Great Plains region.

Continental United States

National assessment of carbon dioxide enhanced oil recovery and associated carbon dioxide retention resources — Summary

Introduction In 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 (CO 2 -EOR) technologies in amenable conventional oil reservoirs underlying the onshore and State waters areas of the conterminous United States. The assessment also includes estimates of the mass of CO 2 that could be stored (retained) in the assessed oil reservoirs following the application of the CO 2 -EOR process. The USGS assessment team evaluated more than 3,500 oil reservoirs that were miscible to injected CO 2 . The assessed reservoirs are in 185 previously defined USGS plays in 33 petroleum provinces of 7 national regions. The team estimated that the total technically recoverable oil resulting from the application of the CO 2 -EOR process ranges from approximately 25,000 million barrels (MMbbl) at the P 5 percentile to as much as 32,000 MMbbl at the P 95 percentile, with a mean of 29,000 MMbbl. The associated CO 2 retention ranges from approximately 7,400 million metric tons (Mt) at the P 5 percentile to as much as 9,500 Mt at the P 95 percentile, with a mean of 8,400 Mt. The results are summarized in this fact sheet and are provided in more detail in the companion data release and circular. The West Texas and Eastern New Mexico region (primarily its Permian Basin) and the Gulf Coast region together contain 60 percent of the mean assessed CO 2 -EOR oil potential and 61 percent of the mean assessed CO 2 retention. Other regions with significant resource potential include the Midcontinent region and the Rocky Mountains and Northern Great Plains region.

Continental United States

Assessment of carbon dioxide enhanced oil recovery and associated carbon dioxide retention resources of the United States

In 2020, the U.S. Geological Survey (USGS) completed a probabilistic assessment of the volume of technically recoverable oil resources that could be produced using current carbon dioxide enhanced oil recovery (CO2-EOR) technologies in amenable conventional oil reservoirs underlying onshore and State-owned offshore waters (herein after, onshore and State waters areas) of the conterminous United States. Our assessment also includes estimates of the mass of CO2 that could be stored (retained) in the assessed oil reservoirs following the application of the CO2-EOR process. The USGS assessment team evaluated more than 3,500 oil reservoirs that were amenable to miscible CO2 injection. The assessed reservoirs are located in 185 plays previously defined by a USGS National Oil and Gas Assessment in 33 petroleum provinces of seven national regions. The team estimated that the total technically recoverable oil resulting from the application of the CO2-EOR process ranges from approximately 25,000 million barrels (MMbbl) at the P5 probability percentile to as much as 32,000 MMbbl at the P95 probability percentile, with a mean of 29,000 MMbbl. The associated CO2 retention ranges from approximately 7,400 million metric tons (Mt) at the P5 percentile to as much as 9,500 Mt at the P95 percentile, with a mean of 8,400 Mt.

conterminous United States

Total alkali-silica diagram

The total alkali-silica (TAS) diagram is a scatterplot of the chemical concentrations of silica oxide (SiO 2 ) versus total alkali-sodium oxide (Na 2 O) plus potassium oxide (K 2 O) – in volcanic rocks.

Book chapter

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 its frequency of appearance. In simpler terms, for the purpose of this presentation, a random variable is a function that assigns to each of the outcomes of a random experiment a value with a certain probability. A random variable also goes by stochastic variable and aleatory variable. Random variables are usually annotated as Roman capital letters, such as X or Y .

Book chapter

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 Summary The 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 so marginally on distance to the nearest drill hole that, over time, it has become evident that Circular 891 is inadequate for modeling reliability and is limited by other shortcomings. The present publication describes the use of geostatistics as an approach allowing a more satisfactory performance than that which is achieved following Circular 891. Geostatistics takes advantage of partly random and partly organized fluctuations in attributes such as coal thickness, coal density, and elevation of the top of a coal bed, borrowing concepts and tools that have been standard features in statistics and risk analysis for decades. Considering that readers interested in this study may not have the background to go directly into the details of the methodology, we start by explaining geostatistical concepts and modeling techniques. The remainder of the publication is devoted to formulating the assessment methodology, applying it to data from the Fillmore Ranch coal bed in the Fort Union Formation in Wyoming, and explaining the computer software applied for performing calculations and displays. The assessment methodology has been designed to report three different forms of resources: coal in place, coal mineable by surface mining methods, and coal mineable by underground mining methods. These three types of resources are reported graphically by displaying both the magnitude and the reliability of total coal resources and resources at the cell scale. In the case of the Fillmore Ranch coal bed example, there is a 90-percent probability that the resources in place are 9.687 ± 0.383 billion short tons (bst), while the coal available for underground mining is 2.279 ± 0.160 bst, and that available for surface mining is only 0.240 ± 0.025 bst because of the steep dip to the west away from the outcrop. These magnitudes are derived from numerical probability distributions not following any specific form.

Wyoming

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 techniques such as principal component and cluster analysis. Considering that proportions of the different hydrocarbon molecules are relative parts of a laboratory sample, the data are compositional in nature, thus requiring the use of log-ratio approaches for adequate mathematical modeling. We apply both traditional and compositional modeling approaches to crude oil samples from an onshore area of about 50,000 square miles in southeast Texas. The data comprise 177 crude oil samples from producing oil fields that include key biomarkers, elemental, and isotopic values commonly used in source rock correlation studies. Our results indicate that compositional modeling has higher discriminating power and lower uncertainty than the traditional approach, allowing the identification of up to 16 clusters. Each cluster represents one oil family from a source rock organofacies ranging from Carboniferous to Paleogene. The families provide new insights into important petroleum systems in the Texas onshore region of the Gulf of Mexico sedimentary basin.

Texas

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 all values. Today, multiple software packages allow easy display of a frequency distribution.

Book chapter

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 magnitudes should be close to the respective population values. This paper proposes a resampling method that can compensate for preferential sampling of spatially correlated data without using declustering weights. The application of the method herein generates a dataset of median estimates of quantiles of multiple stratified resamples that is free of preferential sampling. The methodology is illustrated with two examples. The first one involves values actually measured in the field and has the advantage of representing a real scenario of spatial fluctuations and preferential sampling. A second dataset is synthetic and has the main benefit of a priori knowledge of the underlying spatial distribution, thus allowing a satisfactory evaluation of the results against the known baseline. Access to computer code is offered for practical application of the method.

Computers & Geosciences

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 that originates from the longwall face and caved zone, mixes with the ventilation air and travels through bleeder and return entries before being exhausted to atmosphere from air shafts. Although the gas associated with mining mostly focuses on methane, the gas is not pure methane but is a mixture (where both the components and their quantities vary depending on the sampling location). Understanding the evolution of the composition of the gas from source to different sampling and evaluation points in mines using proper statistical analysis and interpretation methods can lead to better designed degasification and ventilation systems and the selection of the most adequate utilization method for generating energy from the gas. In this work, we present the results of compositional data analysis (CoDa) of gases sampled at different locations in a longwall mine operating in Pennsylvanian coal-bearing strata in the Northern Appalachian coal basin. Sampling locations were from accessible parts of the bleeder entries, returns, bleeder evaluation points and shafts within the mine, and also from gob gas ventholes (GGV) and coal degasification boreholes drilled in the panel areas. In addition, desorbed gas samples from seams that are important for the mine were included in the analyses for comparison. The compositional data analysis showed that the gas composition shifts based on the sampling location, putting in-mine and pure coalbed gases on the opposite ends. Removal of air from the samples did not change this observation suggesting that oxygen is depleted especially for in-mine samples, which is due to oxidation. Results also suggested that desorbed gas samples may not represent the composition of the coal seam gas.

International Journal of Coal Geology

Units recovery methods in compositional data analysis

Compositional data carry relative information. Hence, their statistical analysis has to be performed on coordinates with respect to a log-ratio basis. Frequently, the modeler is required to back-transform the estimates obtained with the modeling to have them in the original units such as euros, kg or mg/liter. Approaches for recovering original units need to be formally introduced and its properties explored. Here, we formulate and analyze the properties of two procedures: a simple approach consisting of adding a residual part to the composition and an approach based on the use of an auxiliary variable. Both procedures are illustrated using a geochemical data set where the original units are recovered when spatial models are applied.

Natural Resources Research

Quantifying ecospace utilization and ecosystemengineering during the early Phanerozoic—The role of bioturbation and bioerosion

The Cambrian explosion (CE) and the great Ordovician biodiversification event (GOBE) are the two most important radiations in Paleozoic oceans. We quantify the role of bioturbation and bioerosion in ecospace utilization and ecosystem engineering using information from 1367 stratigraphic units. An increase in all diversity metrics is demonstrated for the Ediacaran-Cambrian transition, followed by a decrease in most values during the middle to late Cambrian, and by a more modest increase during the Ordovician. A marked increase in ichnodiversity and ichnodisparity of bioturbation is shown during the CE and of bioerosion during the GOBE. Innovations took place first in offshore settings and later expanded into marginal-marine, nearshore, deep-water, and carbonate environments. This study highlights the importance of the CE, despite its Ediacaran roots. Differences in infaunalization in offshore and shelf paleoenvironments favor the hypothesis of early Cambrian wedge-shaped oxygen minimum zones instead of a horizontally stratified ocean.

Science Advances

A probabilistic assessment methodology for carbon dioxide enhanced oil recovery and associated carbon dioxide retention

The U.S. Energy Independence and Security Act of 2007 authorized the U.S. Geological Survey (USGS) to conduct a national assessment of the potential volume of hydrocarbons recoverable by injection of carbon dioxide (CO 2 ) into known oil reservoirs with historical production. The implementation of CO 2 enhanced oil recovery (CO 2 -EOR) techniques could increase the U.S. recoverable hydrocarbon resource base. Use of anthropogenic CO 2 in the CO 2 -EOR process could reduce the amount of CO 2 released to the atmosphere by allowing a percentage of the injected CO 2 to remain in reservoir pore space once occupied by produced oil and water or by CO 2 dissolution in oil and water in the reservoir. The USGS has developed a new methodology for the national assessment of technically recoverable oil resources that may be produced by using current CO 2 -EOR technologies. The methodology relies on a proprietary reservoir-level database, the comprehensive resource database (CRD). The CRD incorporates commercially available geologic and engineering data, and USGS-defined play averages or province averages of reservoir data were used to populate incomplete records. Values from the CRD are used to estimate the original oil in place ( OOIP ) for each reservoir. The inputs are reviewed by USGS geologists, particularly when play or province averages have been used. Monte Carlo simulation is used to produce a numerical probability distribution for the OOIP for each reservoir, with the mean defined as the value of the OOIP in the CRD. A reservoir model (CO 2 Prophet, developed for the U.S. Department of Energy by Texaco, Inc.) is used to determine the incremental recovery factors for oil during the CO 2 -EOR process, on an individual reservoir basis. The model is also used to estimate the volume of CO 2 remaining in the reservoir after the CO 2 -EOR process is complete. Empirical decline curve analysis and comparison with data from published papers and reports on CO 2 -EOR projects are utilized to substantiate the simulation results. Numerical distributions of recovery factors are prepared for variations in the reservoir lithology (clastic or carbonate). The distribution of incremental oil is computed by multiplying the appropriate probability distribution of recovery factors by the individual reservoir distribution of the OOIP . A way to estimate the CO 2 remaining in the reservoir after the completion of the CO 2 -EOR process is also included in the methodology. Assessment results will be aggregated to play, petroleum province, regional, and national scales. This assessment methodology has been tested on the Horseshoe Atoll, Upper Pennsylvanian-Wolfcampian play in the Permian Basin Province in Texas; the play consists of 27 reservoirs having at least 2 billion barrels of OOIP that are amenable to the CO 2 -EOR process. The play was selected as a test case because CO 2 -EOR production data and published reports are available for several reservoirs within the play. Preliminary estimates of oil recoverable by implementation of miscible CO 2 -EOR are comparable to those reported in the literature and obtained by reservoir decline curve analysis.

Scientific Investigations Report

Assessment of coal resources and reserves in the Little Snake River coal field and Red Desert assessment area, Greater Green River Basin, Wyoming

The assessment of the Little Snake River coal field and Red Desert area covers approximately 2,300 square miles in the eastern portion of the Greater Green River Basin in south-central Wyoming. Coal-bearing formations are present throughout the Eocene, Paleocene, and Cretaceous strata in the assessment area. Paleogene-age coal beds are present in the Eocene Wasatch Formation and Paleocene Fort Union Formation. Cretaceous-age coal beds are present in the Lance, Almond, and Allen Ridge Formations. Utilizing over 4,000 data points, 55 individual coal beds were identified in the assessment area. Coal resources were calculated using geologic models generated from these data points, using criteria for minimum thickness and areal extent. The geologic modeling criteria indicated that 33 of the 55 individual coal beds had sufficient thickness and areal extent to be economically significant. Calculated original coal resources within the assessment area were approximately 73.2 billion short tons (BST). After excluding coal resources lost due to land use and technical restrictions, recoverable coal resources were approximately 19.37 BST, including 2.14 BST of coal resources that could be extracted using surface mining methods and 17.23 BST of coal resources that could be extracted using underground mining methods. Due to mining costs and projected low potential sales value of the coal resources, only approximately 167 million short tons (MST) can be classified as reserves, which is less than 1 percent of the recoverable coal resources

Wyoming

Assessment experimental semivariogram uncertainty in the presence of a polynomial drift

The semivariogram, which measures the spatial variability between experimental data, is generally used as a structural input in all two-point geostatistical procedures. However, in most geoscience applications, experimental semivariograms are usually computed from a limited number of sparsely spaced measurements, which results in uncertainty associated with the semivariance values estimated for a specified number of lags. More importantly, considering a spatial variable modelled by a nonstationary random field, uncertainty is not only in the experimental semivariogram of the residuals, but also in the coefficients of the drift model estimated from the available experimental data. Therefore, when assessing the reliability of an experimental semivariogram (or estimated semivariances) in the nonstationary case, both aforementioned uncertainties should be taken into account. The aim of this paper is to extend the “Generalised Bootstrap” procedure to the nonstationary model by propagating the uncertainty associated with the estimated drift coefficients into the uncertainty in the experimental semivariogram of the residuals. The proposed methodology is demonstrated in a case study using abundant geophysical measurements characterised by a nonstationary random function. Two scenarios are evaluated in the case study: (1) it is assumed that the drift coefficients can be estimated without any uncertainty, and (2) uncertainty of the drift coefficients is taken into account. We have explained the methodology that allows to assess the uncertainty of the semivariogram lag estimates in the presence of the drift in the mean. Considering the second scenario, uncertainty is obviously larger than the case where uncertainty of the drift in the mean is ignored. This evaluation should be considered in applications where the data is often rather limited, such as subsurface hydrology (i.e. porosity, transmissivity), soil science (i.e. heavy metal content, soil moisture) and mining (i.e. scoping or pre-feasibility stage of the project). In fact, modern geostatistics should provide not only the semivariogram estimates but also estimation of its uncertainty.

Natural Resources Research