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Ricardo A. Olea

Publications and source records attributed to Ricardo A. Olea.

At least 55 records · Page 3Linked to original sources
USGS2014

A synoptic examination of causes of land loss in southern Louisiana as related to the exploitation of subsurface geologic resources

During the last 80 years, Louisiana has been losing wetlands at an average rate of 62 km 2 /y (24 mi 2 /y) for an accumulated loss of approximately 4900 km 2 (1900 mi 2 ). The loss seems to be the combined result of natural and anthropogenic causes that are behind primarily land subsidence averaging about 10 mm/y (0.4 in/y) coinciding with a sea level rise now at 3 mm/y (0.1 in/y), both contributing to coastal inundation. Upon completing extensive review of often controversial and conflicting views only synoptically reported here, conclusions reached by applying Monte Carlo simulation include: (1) geodetic measurements are consistent with independently postulated causes of regional subsidence; (2) ranking of subsidence factors shows that the main contributor to the regional subsidence is adjustment to sediment load in the form of lithosphere flexure followed by normal faulting dipping basinward, which combined, account on average for 70% of the subsidence, with compaction accounting for another 23%; and (3) production of oil and gas plays a tertiary role. The literature supports the historical view that before experiencing engineering modifications across the catchment area, sedimentation from the Mississippi River system was able to build a prograding coastline by overcoming subsidence rates of similar magnitude with more generous sediment loads of coarser particle size. Sea level rise will become an increasingly dominant factor in land loss only if the acceleration predicted by simulation model scenarios materializes. Wetland losses most likely will continue for as long as there is no compensation to counterbalance the negative effects of land subsidence and sea level rise, with the latter determining the pace of future losses.

Louisiana↗
USGS2014

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), 1025–1044; Journal of Coastal Research, 30(6), 1330–1334.

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 because we use different observations and view those observations in a different context. The objective of this reply is to orient the reader, who then can decide which approach is more likely to be the correct analysis.

Journal of Coastal Research↗
USGS2014

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 ranges from 250 to 565 ft. Although stratigraphic complexities have been documented, a significant range in thickness most likely is because of tectonic thickening from folds and thrust faults. Outcrop studies in the Valley and Ridge and Appalachian Plateaus provinces illustrate the challenges of interpreting the relation of third-order faults, folds, and “disturbed” zones to the regional tectonic framework. Recent field work within the Valley and Ridge province determined that significant faulting and intraformational deformation are present within the Marcellus Shale at the outcrop scale. In an attempt to determine if this scale of deformation is detectable with conventional wireline logs, petrophysical properties (primarily mineralogy and porosity) were measured by interpretation of gamma-ray and bulk-density logs. The results of performing a statistical correlation of wireline logs from nine wells indicated that there are discontinuities within the Millboro Shale (undifferentiated Marcellus Shale and Mahantango Formation) where there are significant thickness differences between wells. Also, some intervals likely contain mineralogy that makes these zones more prone to layer-shortening cleavage duplexes. The Correlator program proved to be a useful tool in a region of contractional deformation.

Virginia;West Virginia↗
USGS2014

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 the results of a study of the third of three coal deposits in which drilling density has been increased one order of magnitude in three stages. Applying geostatistical simulation, the densest dataset was used to check the results obtained by modeling the sparser drillings. We have come up with two summary displays of results based on the same simulations, which individually and combined provide a better assessment of uncertainty than traditional qualitative resource classifications: (a) a display of cell 90 percent confidence interval versus cumulative cell tonnage, and (b) a histogram of total resources. The first graph allows classification of data into any number of bins with dividers to be decided by the assessor on the basis of a discriminating variable that is statistically accepted as a measure of uncertainty, thereby improving the quality and flexibility of the modeling. The second display expands the scope of the modeling by providing a quantitative measure of uncertainty for total tonnage, which is a fundamental concern for stockholders, geologists, and decision makers. Our approach allows us to correctly model uncertainty issues not possible to predict with distance methods, such as (a) different levels of uncertainty for individual beds with the same pattern and density of drill holes, (b) different local degrees of reduction of uncertainty with drilling densification reflecting fluctuation in the complexity of the geology, (c) average reduction in uncertainty at a disproportionately lesser rate than the reduction in area per drill hole, (d) the proportional effect of higher uncertainty in areas of higher tonnages, despite a regular drilling pattern, (e) the possibility of a local increase in uncertainty despite drilling densification to reflect a more complex geology as the deposit is known in more detail, and (f) for exactly the same drilling pattern, tonnage per individual beds with different uncertainty than the aggregated tonnage. These results should be considered realistic improvements over distance methods used for quantitative classification of uncertainty in coal resource, such as U.S. Geological Survey Circular 891. 1 The approach should be a welcome addition to the toolkit of Competent Persons preparing public disclosures according to international mineral codes such as those promoted by the Combined Reserves International Reporting Standards Committee 2 and the Joint Ore Reserve Committee. 3 1 Wood, G.H., Jr., Kehn, T.M., Carter, M.D., and Culbertson, W.C., 1983, Coal resources classification system of the U.S. Geological Survey: U.S. Geological Survey Circular 891, 65 p. 2 CRIRSCO (Combined Reserves International Reporting Standards Committee), 2013, International reporting template for the public reporting of exploration results, mineral resources and mineral reserves: Accessed February 2014 at http://www.crirsco.com/crirsco_template_may2013.pdf. 3 JORC (Joint Ore Reserves Committee), 2012, Australasian code for reporting of exploration results, mineral resources and ore reserves: Accessed September 2014 at http://www.jorc.org/docs/jorc_code2012.pdf.

Wyoming↗
USGS2013

Time-lapse analysis of methane quantity in Mary Lee group of coal seams using filter-based multiple-point geostatistical simulation

Coal seam degasification and its success are important for controlling methane, and thus for the health and safety of coal miners. During the course of degasification, properties of coal seams change. Thus, the changes in coal reservoir conditions and in-place gas content as well as methane emission potential into mines should be evaluated by examining time-dependent changes and the presence of major heterogeneities and geological discontinuities in the field. In this work, time-lapsed reservoir and fluid storage properties of the New Castle coal seam, Mary Lee/Blue Creek seam, and Jagger seam of Black Warrior Basin, Alabama, were determined from gas and water production history matching and production forecasting of vertical degasification wellbores. These properties were combined with isotherm and other important data to compute gas-in-place (GIP) and its change with time at borehole locations. Time-lapsed training images (TIs) of GIP and GIP difference corresponding to each coal and date were generated by using these point-wise data and Voronoi decomposition on the TI grid, which included faults as discontinuities for expansion of Voronoi regions. Filter-based multiple-point geostatistical simulations, which were preferred in this study due to anisotropies and discontinuities in the area, were used to predict time-lapsed GIP distributions within the study area. Performed simulations were used for mapping spatial time-lapsed methane quantities as well as their uncertainties within the study area. The systematic approach presented in this paper is the first time in literature that history matching, TIs of GIPs and filter simulations are used for degasification performance evaluation and for assessing GIP for mining safety. Results from this study showed that using production history matching of coalbed methane wells to determine time-lapsed reservoir data could be used to compute spatial GIP and representative GIP TIs generated through Voronoi decomposition. Furthermore, performing filter simulations using point-wise data and TIs could be used to predict methane quantity in coal seams subjected to degasification. During the course of the study, it was shown that the material balance of gas produced by wellbores and the GIP reductions in coal seams predicted using filter simulations compared very well, showing the success of filter simulations for continuous variables in this case study. Quantitative results from filter simulations of GIP within the studied area briefly showed that GIP was reduced from an initial ∼73 Bcf (median) to ∼46 Bcf (2011), representing a 37 % decrease and varying spatially through degasification. It is forecasted that there will be an additional ∼2 Bcf reduction in methane quantity between 2011 and 2015. This study and presented results showed that the applied methodology and utilized techniques can be used to map GIP and its change within coal seams after degasification, which can further be used for ventilation design for methane control in coal mines.

Alabama↗
USGS2013

Aggregation of carbon dioxide sequestration storage assessment units

The U.S. Geological Survey is currently conducting a national assessment of carbon dioxide (CO 2 ) storage resources, mandated by the Energy Independence and Security Act of 2007. Pre-emission capture and storage of CO 2 in subsurface saline formations is one potential method to reduce greenhouse gas emissions and the negative impact of global climate change. Like many large-scale resource assessments, the area under investigation is split into smaller, more manageable storage assessment units (SAUs), which must be aggregated with correctly propagated uncertainty to the basin, regional, and national scales. The aggregation methodology requires two types of data: marginal probability distributions of storage resource for each SAU, and a correlation matrix obtained by expert elicitation describing interdependencies between pairs of SAUs. Dependencies arise because geologic analogs, assessment methods, and assessors often overlap. The correlation matrix is used to induce rank correlation, using a Cholesky decomposition, among the empirical marginal distributions representing individually assessed SAUs. This manuscript presents a probabilistic aggregation method tailored to the correlations and dependencies inherent to a CO 2 storage assessment. Aggregation results must be presented at the basin, regional, and national scales. A single stage approach, in which one large correlation matrix is defined and subsets are used for different scales, is compared to a multiple stage approach, in which new correlation matrices are created to aggregate intermediate results. Although the single-stage approach requires determination of significantly more correlation coefficients, it captures geologic dependencies among similar units in different basins and it is less sensitive to fluctuations in low correlation coefficients than the multiple stage approach. Thus, subsets of one single-stage correlation matrix are used to aggregate to basin, regional, and national scales.

Stochastic Environmental Research and Risk Assessm↗
USGS2013

Direct estimation of diffuse gaseous emissions from coal fires: current methods and future directions

Coal fires occur in nature spontaneously, contribute to increases in greenhouse gases, and emit atmospheric toxicants. Increasing interest in quantifying coal fire emissions has resulted in the adaptation and development of specialized approaches and adoption of numerical modeling techniques. Overview of these methods for direct estimation of diffuse gas emissions from coal fires is presented in this paper. Here we take advantage of stochastic Gaussian simulation to interpolate CO 2 fluxes measured using a dynamic closed chamber at the Ruth Mullins coal fire in Perry County, Kentucky. This approach allows for preparing a map of diffuse gas emissions, one of the two primary ways that gases emanate from coal fires, and establishing the reliability of the study both locally and for the entire fire. Future research directions include continuous and automated sampling to improve quantification of gaseous coal fire emissions.

International Journal of Coal Geology↗
USGS2013

Using simulated maps to interpret the geochemistry, formation and quality of the Blue Gem Coal Bed, Kentucky, USA

This study presents geostatistical simulations of coal-quality parameters, major oxides and trace metals for an area covering roughly 812 km 2 of the Blue Gem coal bed in southeastern Kentucky, USA. The Blue Gem, characterized by low ash yield and low sulfur content, is an important economic resource. Past studies have characterized the Blue Gem's geochemistry, palynology and petrography and inferred a depositional setting of a planar peat deposit that transitioned to slightly domed later in its development. These studies have focused primarily on vertical geochemical trends within the coal bed. Simulated maps of chemical elements derived from 45 measured sample locations across the study area provide an opportunity to observe changes in the horizontal direction within the coal bed. As the Blue Gem coal bed shows significant vertical chemical trends, care was taken in this study to try to select samples from a single, middle portion of the coal. By revealing spatial distribution patterns of elements across the middle of the bed, associations between different components of the coal can be seen. The maps therefore help to provide a picture of the coal-forming peat bog at an instant in geologic time and allow interpretation of a depositional setting in the horizontal direction. Results from this middle portion of the coal suggest an association of SiO 2 with both K 2 O and TiO 2 in different parts of the study area. Further, a pocket in the southeast of the study area shows elevated concentrations of elements attributable to observed carbonate-phase minerals (MgO, CaO, Ba and Sr) as well as elements commonly associated with sulfide-phase minerals (Cu, Mo and Ni). Areas of relatively high ash yield are observed in the north and south of the mapped area, in contrast to the low ash yields seen towards the east. Additionally, we present joint probability maps where multiple coal-quality parameters are plotted simultaneously on one figure. This application allows researchers to investigate associations of more than two components in a straight-forward manner useful in guiding resource exploration.

Kentucky↗
USGS2013

Sequential Gaussian co-simulation of rate decline parameters of longwall gob gas ventholes

Gob gas ventholes (GGVs) are used to control methane inflows into a longwall mining operation by capturing the gas within the overlying fractured strata before it enters the work environment. Using geostatistical co-simulation techniques, this paper maps the parameters of their rate decline behaviors across the study area, a longwall mine in the Northern Appalachian basin. Geostatistical gas-in-place (GIP) simulations were performed, using data from 64 exploration boreholes, and GIP data were mapped within the fractured zone of the study area. In addition, methane flowrates monitored from 10 GGVs were analyzed using decline curve analyses (DCA) techniques to determine parameters of decline rates. Surface elevation showed the most influence on methane production from GGVs and thus was used to investigate its relation with DCA parameters using correlation techniques on normal-scored data. Geostatistical analysis was pursued using sequential Gaussian co-simulation with surface elevation as the secondary variable and with DCA parameters as the primary variables. The primary DCA variables were effective percentage decline rate, rate at production start, rate at the beginning of forecast period, and production end duration. Co-simulation results were presented to visualize decline parameters at an area-wide scale. Wells located at lower elevations, i.e., at the bottom of valleys, tend to perform better in terms of their rate declines compared to those at higher elevations. These results were used to calculate drainage radii of GGVs using GIP realizations. The calculated drainage radii are close to ones predicted by pressure transient tests.

Pennsylvania↗
USGS2013

National assessment of geologic carbon dioxide storage resources: methodology implementation

In response to the 2007 Energy Independence and Security Act, the U.S. Geological Survey (USGS) conducted a national assessment of potential geologic storage resources for carbon dioxide (CO2). Storage of CO2 in subsurface saline formations is one important method to reduce greenhouse gas emissions and curb global climate change. This report provides updates and implementation details of the assessment methodology of Brennan and others (2010, http://pubs.usgs.gov/of/2010/1127/) and describes the probabilistic model used to calculate potential storage resources in subsurface saline formations.

Open-File Report↗
USGS2012

Geostatistical population-mixture approach to unconventional-resource assessment with an application to the Woodford Gas Shale, Arkoma Basin, eastern Oklahoma

Evaluation of resources such as tight sands and gas shales requires the formulation of assessment models that are different from those used for the inference of conventional resources. Formulations in present use are based in classical statistics that ignore the partly organized and partly random geographical variation of attributes related to the occurrence of hydrocarbons. This paper is the third in a series of methodological tests aimed at enhancing the assessment of unconventional resources through more-effective use of implicit and explicit information contained in the data, more-accurate evaluation of resources, and more-informative display of results. Reprocessing of estimated-ultimate-recovery (EUR) data at the Woodford gas shale in Oklahoma shows that subdivision of the play into areas as homogeneous as possible can produce results comparable to those obtained using several variables correlated to local productivity.

Oklahoma↗
USGS2012

VARBOOT: A spatial bootstrap program for semivariogram uncertainty assessment

In applied geostatistics, the semivariogram is commonly estimated from experimental data, producing an empirical semivariogram for a specified number of discrete lags. In a second stage, a model defined by a few parameters is fitted to the empirical semivariogram. As the experimental data are usually few and sparsely located, there is considerable uncertainty about the calculated semivariogram values (uncertainty of the empirical semivariogram) and about the parameters of any model fitted to them (uncertainty of the estimated model parameters). In this paper, the uncertainty in the modeling of the empirical semivariogram is numerically assessed by the generalized bootstrap, which is an extension of the classic bootstrap procedure modified for spatially correlated data. A computer program is described and provided for the assessment of those uncertainties. In particular, the program provides for the empirical semivariogram: the standard errors, the bootstrap percentile confidence intervals, the complete variance–covariance matrix, standard deviation correlation matrix. A public domain, natural dataset is used to illustrate the performance of the program. A promising result is that, for any distance, the median of the bootstrap distribution for the empirical semivariogram approximates more closely the underlying semivariogram than the estimate derived from the empirical sample.

Computers & Geosciences↗
USGS2011

On the use of the beta distribution in probabilistic resource assessments

The triangular distribution is a popular choice when it comes to modeling bounded continuous random variables. Its wide acceptance derives mostly from its simple analytic properties and the ease with which modelers can specify its three parameters through the extremes and the mode. On the negative side, hardly any real process follows a triangular distribution, which from the outset puts at a disadvantage any model employing triangular distributions. At a time when numerical techniques such as the Monte Carlo method are displacing analytic approaches in stochastic resource assessments, easy specification remains the most attractive characteristic of the triangular distribution. The beta distribution is another continuous distribution defined within a finite interval offering wider flexibility in style of variation, thus allowing consideration of models in which the random variables closely follow the observed or expected styles of variation. Despite its more complex definition, generation of values following a beta distribution is as straightforward as generating values following a triangular distribution, leaving the selection of parameters as the main impediment to practically considering beta distributions. This contribution intends to promote the acceptance of the beta distribution by explaining its properties and offering several suggestions to facilitate the specification of its two shape parameters. In general, given the same distributional parameters, use of the beta distributions in stochastic modeling may yield significantly different results, yet better estimates, than the triangular distribution.

Natural Resources Research↗
USGS2011

Building on crossvalidation for increasing the quality of geostatistical modeling

The random function is a mathematical model commonly used in the assessment of uncertainty associated with a spatially correlated attribute that has been partially sampled. There are multiple algorithms for modeling such random functions, all sharing the requirement of specifying various parameters that have critical influence on the results. The importance of finding ways to compare the methods and setting parameters to obtain results that better model uncertainty has increased as these algorithms have grown in number and complexity. Crossvalidation has been used in spatial statistics, mostly in kriging, for the analysis of mean square errors. An appeal of this approach is its ability to work with the same empirical sample available for running the algorithms. This paper goes beyond checking estimates by formulating a function sensitive to conditional bias. Under ideal conditions, such function turns into a straight line, which can be used as a reference for preparing measures of performance. Applied to kriging, deviations from the ideal line provide sensitivity to the semivariogram lacking in crossvalidation of kriging errors and are more sensitive to conditional bias than analyses of errors. In terms of stochastic simulation, in addition to finding better parameters, the deviations allow comparison of the realizations resulting from the applications of different methods. Examples show improvements of about 30% in the deviations and approximately 10% in the square root of mean square errors between reasonable starting modelling and the solutions according to the new criteria.

Stochastic Environmental Research and Risk Assessm↗
USGS2011

Late quaternary climate variations reflected in Baltic Sea sediments

Late Pleistocene to Holocene climate change of the Atlantic and the northern European realm is reflected by the facies of sediments in the Baltic Sea. The sedimentary sequence have been subdivided into zones reflecting the main postglacial stages of the Baltic Sea basin development according to sediment echosounder profiling and investigating sediment cores from the central Baltic. The changes in the environment of Baltic Sea bottom water is displayed by sediment physical, geochemical, and microfossil proxies. These proxies mark the main shift in the sedimentary facies of the Baltic Basin at 8.14 cal. years BP, from a freshwater to a brackish/marine environment due to the Littorina transgression of marine water masses from the North Sea. The downhole physical facies variation from the Eastern Gotland can be correlated basinwide. Thickness maps of the freshwater and the brackish sediments ascribe the general change in the hydrographic circulation from a coast-to-basin to a basin-to-basin system along with the Littorina transgression. Variations in the salinity of the brackish Littorina Baltic Basin are attributed to changes in the North Atlantic Oscillation (NAO) ascribing the wind forces driving the inflow of marine water into the Baltic Basin. Time series analysis of facies variation reveals distinct periodicities of 900 and 1,500 years. These periods can be compared with data from North Atlantic marine sediments and Greenland ice cores identifying global climate change effects in Baltic Basin sediments.

Book chapter↗
USGS2011

Methodology for quantifying uncertainty in coal assessments with an application to a Texas lignite deposit

A common practice for characterizing uncertainty in coal resource assessments has been the itemization of tonnage at the mining unit level and the classification of such units according to distance to drilling holes. Distance criteria, such as those used in U.S. Geological Survey Circular 891, are still widely used for public disclosure. A major deficiency of distance methods is that they do not provide a quantitative measure of uncertainty. Additionally, relying on distance between data points alone does not take into consideration other factors known to have an influence on uncertainty, such as spatial correlation, type of probability distribution followed by the data, geological discontinuities, and boundary of the deposit. Several geostatistical methods have been combined to formulate a quantitative characterization for appraising uncertainty. Drill hole datasets ranging from widespread exploration drilling to detailed development drilling from a lignite deposit in Texas were used to illustrate the modeling. The results show that distance to the nearest drill hole is almost completely unrelated to uncertainty, which confirms the inadequacy of characterizing uncertainty based solely on a simple classification of resources by distance classes. The more complex statistical methods used in this study quantify uncertainty and show good agreement between confidence intervals in the uncertainty predictions and data from additional drilling.

International Journal of Coal Geology↗