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At least 91 records · Page 5Linked to original sources
USGS2015

Unconventional energy resources: 2015 review. Shale gas and liquids

Introduction As the source rocks from which petroleum is generated, organic-rich shales have always been considered an important component of petroleum systems. Over the last few years, it has been realized that in some mudrocks, sufficient hydrocarbons remain in place to allow for commercial development, although advanced drilling and completion technology is typically required to access hydrocarbons from these reservoirs. Tight oil reservoirs (also referred to as continuous oil accumulations) contain hydrocarbons migrated from source rocks that are geologically/stratigraphically interbedded with or occur immediately overlying/underlying them. Migration is minimal in charging these tight oil accumulations (Gaswirth and Marra 2014 ). Companies around the world are now successfully exploiting organic-rich shales and tight rocks for contained hydrocarbons, and the search for these types of unconventional petroleum reservoirs is growing. Unconventional reservoirs range in geologic age from Ordovician to Tertiary (Silverman et al. 2005 ; EIA 2013a ).

Natural Resources Research↗
USGS2016

Bitumen prices and structural changes in North American crude oil markets

In an earlier report, changes in bitumen prices at Hardesty, Alberta, Canada, were modeled as the responses to changes in monthly prices of Hardesty light/medium crude oil for the period 2000–2006 with a simple error correction econometric model. This note re-examines that price relationship for the period 2009–2014. Over the period 2006–2014, there was also rapid growth in North American light oil production from low-permeability carbonate, sandstone, and shale reservoirs. During that period, Canadian raw bitumen production grew by more than 12% per year and there was significant geographical diversification in its markets. Results of the statistical analysis showed that the change in the dynamic relationships between bitumen prices and Hardesty light oil prices probably reflected, in part, the maturation of bitumen markets and closer integration with North American light oil markets. The analysis also examines the dynamic relationships between bitumen prices and West Texas Intermediate and Brent international benchmark crude oil prices. Ideally, if bitumen prices are found to be closely related to a widely traded benchmark crude oil, the benchmark crude oil price forecasts could be used as a basis for predicting bitumen prices. However, neither of international benchmark crude oils tested had high explanatory power.

Natural Resources Research↗
USGS2016

Risk, liability, and economic issues with long-term CO 2 storage—A review

Given a scarcity of commercial-scale carbon capture and storage (CCS) projects, there is a great deal of uncertainty in the risks, liability, and their cost implications for geologic storage of carbon dioxide (CO 2 ). The probabilities of leakage and the risk of induced seismicity could be remote, but the volume of geologic CO 2 storage (GCS) projected to be necessary to have a significant impact on increasing CO 2 concentrations in the atmosphere is far greater than the volumes of CO 2 injected thus far. National-level estimates of the technically accessible CO 2 storage resource (TASR) onshore in the United States are on the order of thousands of gigatons of CO 2 storage capacity, but such estimates generally assume away any pressure management issues. Pressure buildup in the storage reservoir is expected to be a primary source of risk associated with CO 2 storage, and only a fraction of the theoretical TASR could be available unless the storage operator extracts the saltwater brines or other formation fluids that are already present in the geologic pore space targeted for CO 2 storage. Institutions, legislation, and processes to manage the risk, liability, and economic issues with CO 2 storage in the United States are beginning to emerge, but will need to progress further in order to allow a commercial-scale CO 2 storage industry to develop in the country. The combination of economic tradeoffs, property rights definitions, liability issues, and risk considerations suggests that CO 2 storage offshore of the United States may be more feasible than onshore, especially during the current (early) stages of industry development.

Natural Resources Research↗
USGS2016

Cost implications of uncertainty in CO 2 storage resource estimates: A review

Carbon capture from stationary sources and geologic storage of carbon dioxide (CO 2 ) is an important option to include in strategies to mitigate greenhouse gas emissions. However, the potential costs of commercial-scale CO 2 storage are not well constrained, stemming from the inherent uncertainty in storage resource estimates coupled with a lack of detailed estimates of the infrastructure needed to access those resources. Storage resource estimates are highly dependent on storage efficiency values or storage coefficients, which are calculated based on ranges of uncertain geological and physical reservoir parameters. If dynamic factors (such as variability in storage efficiencies, pressure interference, and acceptable injection rates over time), reservoir pressure limitations, boundaries on migration of CO 2 , consideration of closed or semi-closed saline reservoir systems, and other possible constraints on the technically accessible CO 2 storage resource (TASR) are accounted for, it is likely that only a fraction of the TASR could be available without incurring significant additional costs. Although storage resource estimates typically assume that any issues with pressure buildup due to CO 2 injection will be mitigated by reservoir pressure management, estimates of the costs of CO 2 storage generally do not include the costs of active pressure management. Production of saline waters (brines) could be essential to increasing the dynamic storage capacity of most reservoirs, but including the costs of this critical method of reservoir pressure management could increase current estimates of the costs of CO 2 storage by two times, or more. Even without considering the implications for reservoir pressure management, geologic uncertainty can significantly impact CO 2 storage capacities and costs, and contribute to uncertainty in carbon capture and storage (CCS) systems. Given the current state of available information and the scarcity of (data from) long-term commercial-scale CO 2 storage projects, decision makers may experience considerable difficulty in ascertaining the realistic potential, the likely costs, and the most beneficial pattern of deployment of CCS as an option to reduce CO 2 concentrations in the atmosphere.

Natural Resources Research↗
USGS2017

Spatiotemporal analysis of changes in lode mining claims around the McDermitt Caldera, northern Nevada and southern Oregon

Resource managers and agencies involved with planning for future federal land needs are required to complete an assessment of and forecast for future land use every ten years. Predicting mining activities on federal lands is difficult as current regulations do not require disclosure of exploration results. In these cases, historic mining claims may serve as a useful proxy for determining where mining-related activities may occur. We assess the utility of using a space–time cube (STC) and associated analyses to evaluate and characterize mining claim activities around the McDermitt Caldera in northern Nevada and southern Oregon. The most significant advantage of arranging the mining claim data into a STC is the ability to visualize and compare the data, which allows scientists to better understand patterns and results. Additional analyses of the STC (i.e., Trend, Emerging Hot Spot, Hot Spot, and Cluster and Outlier Analyses) provide extra insights into the data and may aid in predicting future mining claim activities.

Nevada, Oregon↗
USGS2017

Global trends in mineral commodities for advanced technologies

The U.S. Geological Survey National Minerals Information Center (NMIC) is the U.S. Government agency tasked with the collection, analysis, and dissemination of information on the production, consumption, import, export, and other measures of the flows of non-fuel mineral commodities of importance to the U.S. economy and national security. The NMIC and its agency predecessors have maintained a database of this information, collected and published annually, dating back to the beginning of the twentieth century. Time series analysis of annual information from the NMIC provides the opportunity to identify trends in the supply chains of the minerals and metals which are increasingly in demand for advanced technologies. The identification of trends in data for net import reliance, country concentration of production, global demand, price volatility, and other measures, when combined with world governance indicators, can be used to focus attention on individual mineral commodities where supply chain restrictions may develop. Specific examples for U.S. net import reliance, global tantalum primary mining, and mineral criticality screening are presented to illustrate the utility of time series analysis of trends in mineral commodity supply and demand, the types of data required, and the limitations of currently available information.

Natural Resources Research↗
USGS2017

Economics, helium, and the U.S. Federal Helium Reserve: Summary and outlook

In 2017, disruptions in the global supply of helium reminded consumers, distributors, and policy makers that the global helium supply chain lacks flexibility, and that attempts to increase production from the U.S. Federal Helium Reserve (the FHR) may not be able to compensate for the loss of one of the few major producers in the world. Issues with U.S. and global markets for helium include inelastic demand, economic availability of helium only as a byproduct, only 4–5 major producers, helium’s propensity to escape earth’s crust, an ongoing absence of storage facilities comparable to the FHR, and a lack of consequences for the venting of helium. The complex combination of these economic, physical, and regulatory issues is unique to helium, and determining helium’s practical availability goes far beyond estimating the technically accessible volume of underground resources. Although most of these issues have been analyzed since helium was recognized to be a valuable mineral commodity in the early 1900s, very few economic models have been developed that adequately consider the unique characteristics of helium and helium markets. In particular, there is a notable lack of recent empirical work to estimate the responsiveness of helium demand, supply, prices, and trade patterns to the ongoing drawdown and sale of helium reserves stored in the FHR. In general, existing models of helium either do not account for an oligopoly controlling supply, or they do not evaluate potential helium extraction and storage programs based on an intertemporal maximization of the value of the resource. Such models could be of very limited use to decision makers. This review found only one working paper with a helium market model that has incorporated both of these vital considerations. That and other economic studies along similar lines could be very useful in helping inform current helium policy discussions and decisions.

Natural Resources Research↗
USGS2018

Statistical detection of flow regime changes in horizontal hydraulically fractured Bakken oil wells

The application of horizontal and hydraulically fractured wells for producing oil from low permeability formations has changed the face of the North American oil industry. One feature of the production profile of many such wells is a transition from transient linear oil flow to boundary-dominated flow. The identification of the time of this transition is important for the calibration of models that forecast the well’s future production and the expected ultimate recovery. It is preferable that such models generally use data from the boundary-dominated flow regime for parameter calibration. Accurate well production forecasts are needed for operational decisions, long-term planning, commercial transactions, regulatory proceedings, and asset valuation. Petroleum engineers frequently make the call on the transition point based on subjective visual interpretations of log–log plots for individual wells. This is time-consuming and is generally not repeatable by other analysts. This note evaluates statistical approaches that can serve as alternatives to the subjective visual interpretations. Specifically, the predictive performance of production models calibrated with boundary-dominated data based on transition dates calculated with constrained nonlinear least squares and Bayesian regressions was very close to that obtained using the visual method, suggesting that statistical approaches may indeed be constructed to replace less objective visual approaches without loss of accuracy.

Natural Resources Research↗
USGS2019

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↗
USGS2019

Growth drivers of Bakken oil well productivity

This paper identifies the drivers of the phenomenal growth in productivity in hydraulically fractured horizontal oil wells producing from the middle member of the Bakken Formation in North Dakota. The data show a strong underlying spatial component and somewhat weaker temporal component. Drivers of the spatial component are favorable reservoir conditions. The temporal component of well productivity growth is driven by increasing the number of fracture treatments and by increasing the volume of proppant and injection fluids used on a per fracture treatment basis. Random Forest, a non-parametric modeling procedure often applied in the context of machine learning, is used to identify the relative importance of geologic and well-completion factors that have driven the growth in Bakken well productivity. The findings of this study suggest that a significant part of the well productivity increases during the period from 2010 to 2015 have been the result of improved well-site selection. For the more recent period, that is from 2015 through 2017, part of the improved well productivity has resulted from substantial increases in the proppant and injection fluids used per stage and per well.

Montana, North Dakota, South Dakota↗
USGS2020

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↗
USGS2021

Assessing gas leakage potential into coal mines from shale gas well failures: Inference from field determination of strata permeability responses to longwall-induced deformations

This paper summarizes the changes in permeability at three boreholes located above an abutment pillar at a longwall coal mine in southwestern Pennsylvania. The motivation of this study was to better characterize the potential interaction between shale gas wells and the mine environment, through measurement of permeability changes in the coal mine overburden caused by mining-induced deformations. Measuring permeability changes around boreholes affected by longwall mining is an effective method to indicate changes in the fracture network above longwall abutment pillars and estimate the capacity for gas flow from shale gas wells to the mine environment. This study measured permeability through falling-head slug tests at different longwall face positions during the mining of two longwall panels on either side of the test abutment pillar where the test boreholes were located. Three test boreholes were drilled to different depths above the active mining level, and they had screened intervals to evaluate the response of different stratigraphic zones to mining-induced stresses. The results showed that the permeability around the slotted intervals of each borehole increased pre-mining to post-mining, and the permeability increased from mining of the first longwall panel to mining of the second one, adjacent to the pillar.

Natural Resources Research↗
USGS2021

Machine learning can assign geologic basin to produced water samples using major ion geochemistry

Understanding the geochemistry of waters produced during petroleum extraction is essential to informing the best treatment and reuse options, which can potentially be optimized for a given geologic basin. Here, we used the US Geological Survey’s National Produced Waters Geochemical Database (PWGD) to determine if major ion chemistry could be used to classify accurately a produced water sample to a given geologic basin based on similarities to a given training dataset. Two datasets were derived from the PWGD: one with seven features but more samples (PWGD7), and another with nine features but fewer samples (PWGD9). The seven-feature dataset, prior to randomly generating a training and testing (i.e., validation) dataset, had 58,541 samples, 20 basins, and was classified based on total dissolved solids (TDS), bicarbonate (HCO 3 ), Ca, Na, Cl, Mg, and sulfate (SO 4 ). The nine-feature dataset, prior to randomly splitting into a training and testing (i.e., validation) dataset, contained 33,271 samples, 19 basins, and was classified based on TDS, HCO 3 , Ca, Na, Cl, Mg, SO 4 , pH, and specific gravity. Three supervised machine learning algorithms—Random Forest, k-Nearest Neighbors, and Naïve Bayes—were used to develop multi-class classification models to predict a basin of origin for produced waters using major ion chemistry. After training, the models were tested on three different datasets: Validation7, Validation9, and one based on data absent from the PWGD. Prediction accuracies across the models ranged from 23.5 to 73.5% when tested on the two PWGD-based datasets. A model using the Random Forest algorithm predicted most accurately compared to all other models tested. The models generally predicted basin of origin more accurately on the PWGD7-based dataset than on the PWGD9-based dataset. An additional dataset, which contained data not in the PWGD, was used to test the most accurate model; results suggest that some basins may lack geochemical diversity or may not be well described, while others may be geochemically diverse or are well described. A compelling result of this work is that a produced water basin of origin can be determined using major ions alone and, therefore, deep basinal fluid compositions may not be as variable within a given basin as previously thought. Applications include predicting the geochemistry of produced fluid prior to drilling at different intervals and assigning historical produced water data to a producing basin.

Natural Resources Research↗
USGS2022

Decision analysis and CO2–Enhanced oil recovery development strategies

This paper analyzes the relationship between actual reservoir conditions and predicted measures of performance of carbon dioxide enhanced oil recovery (CO 2 –EOR) programs. It then shows how CO 2 –EOR operators might maximize the value of their projects by approaching implementation using a “flexible selective” pattern development strategy, where the CO 2 –EOR program patterns are selectively developed based on site-specific reservoir properties. It also analyzes performance measures and economic consequences of utilizing a continuous CO 2 injection strategy intended to maximize CO 2 retention for a defined time period. “Net CO 2 utilization,” calculated as difference between the volumes of CO 2 injected and CO 2 recovered in the production stream divided by the oil produced, is a standard measure of CO 2 –EOR carbon utilization, but it can be a misleading predictor of the actual CO 2 retained in the reservoir. Asset value can be added to a CO 2 –EOR project by recognizing effects of variations in reservoir parameter values and basing incremental development decisions on those data. For policy analysts, the consequences of ignoring geologic variability within a reservoir that is a candidate for CO 2 –EOR will likely be to substantially overestimate predicted adoption of CO 2 –EOR in response to economic incentives. This result holds true whether the CO 2 –EOR program objective is to maximize net value by maximizing oil production or maximize CO 2 storage with oil recovery.

Natural Resources Research↗
USGS2023

Applications of natural language processing to geoscience text data and prospectivity modelling

Geological maps are powerful models for visualizing the complex distribution of rock types through space and time. However, the descriptive information that forms the basis for a preferred map interpretation is typically stored in geological map databases as unstructured text data that are difficult to use in practice. Herein we apply natural language processing (NLP) to geoscientific text data from Canada, the U.S., and Australia to address that knowledge gap. First, rock descriptions, geological ages, lithostratigraphic and lithodemic information, and other long-form text data are translated to numerical vectors, i.e., a word embedding, using a geoscience language model. Network analysis of word associations, nearest neighbors, and principal component analysis are then used to extract meaningful semantic relationships between rock types. We further demonstrate using simple Naive Bayes classifiers and the area under receiver operating characteristics plots (AUC) how word vectors can be used to: (1) predict the locations of “pegmatitic” (AUC = 0.962) and “alkalic” (AUC = 0.938) rocks; (2) predict mineral potential for Mississippi-Valley-type (AUC = 0.868) and clastic-dominated (AUC = 0.809) Zn-Pb deposits; and (3) search geoscientific text data for analogues of the giant Mount Isa clastic-dominated Zn-Pb deposit using the cosine similarities between word vectors. This form of semantic search is a promising NLP approach for assessing mineral potential with limited training data. Overall, the results highlight how geoscience language models and NLP can be used to extract new knowledge from unstructured text data and reduce the mineral exploration search space for critical raw materials.

Natural Resources Research↗
USGS2023

Reconnaissance survey for potential energy storage and carbon dioxide storage resources of petroleum reservoirs in western Europe

Energy producers and utilities use oil and gas reservoirs for gas storage to meet peak seasonal demand or to supplement intermittent energy production. These reservoirs are also suitable for the long-term storage of carbon dioxide (CO 2 ), a greenhouse gas. This study reports on a reconnaissance analysis of the potential magnitude of storage resources in 9424 known oil and gas reservoirs from 24 countries within highly industrialized western Europe. To standardize the storage resources of the oil and gas reservoirs, their volumetric capacity is expressed in terms of metric tons (mass) of CO 2 . Estimates of recoverable oil and gas at the surface are converted to subsurface volumes and then converted to the equivalent mass of CO 2 at reservoir conditions. The results indicate 36.7 gigatons of CO 2 could be stored, with oil reservoirs accounting for 32% of that total and natural gas reservoirs comprising the remaining 68%. About four-fifths of the reservoir storage resource is offshore, with about three-fourths of that offshore resource at water depths of 200 m or less. Most countries do not have the reservoir storage resources to store 15 years of CO 2 at 2017 emission levels. With few exceptions the bulk of the storage is offshore for countries that do have at least 15 years of storage. The expansion of natural gas storage for strategic purposes in abandoned onshore gas reservoirs is not expected to seriously impact CO 2 storage. The contribution of this analysis is the description of the spatial distribution of potential storage and physical accessibility.

Natural Resources Research↗
USGS2024

How quickly do oil and gas wells “Water Out”? Quantifying and contrasting water production trends

Water production from petroleum (oil and natural gas) wells is a topic of increasing environmental and economic importance, yet quantification efforts have been limited to date, and patterns between and within petroleum plays are largely unscrutinized. Additionally, classification of reservoirs as “unconventional” (also known as “continuous”) carries scientific and regulatory importance, but in some cases the distinction from "conventional" wells is unclear. Using water, oil, and gas production data, we calculated a set of quantitative metrics that elucidate trends in the water-to-petroleum ratio over the life of each producing well. The percent growth of the water-to-petroleum ratio quantifies the degree to which a well “waters out” over time; values calculated for 153,900 wells in 18 oil and gas plays show generally much higher values for conventional wells than for continuous/unconventional wells. Analysis of the percent growth along with the slope and median metrics reveals greater variation between conventional plays and between continuous (unconventional) plays than previously recognized. Further, an example from the Bakken Formation in the Williston Basin, USA, illustrates that, within a single play, the metrics provide insight into spatial variation of water production trends, as influenced by geology and reservoir characteristics. By quantifying the variability of water production trends within individual plays and between plays, including differences between conventional and continuous (unconventional) plays, these results provide a more nuanced view of water production from oil and gas wells than has previously been possible and they illustrate the degree to which water management considerations vary spatially and temporally.

Natural Resources Research↗
USGS2019

Selecting ecological models using multi-objective optimization

Choices in ecological research and natural resource management require balancing multiple, often competing objectives. Examples include maximizing species persistence in a wildlife conservation context, while minimizing cost, or balancing opposing stakeholder objectives when managing wildlife populations. Multiple-objective optimization (MOO) provides a unifying framework for solving multiple objective problems. Model selection is a critical component of ecological inference and prediction and requires balancing the competing objectives of model fit and model complexity. The tradeoff between model fit and model complexity provides a basis for describing the model-selection problem within the MOO framework. We discuss MOO and two strategies for solving the MOO problem; modeling preferences pre-optimization and post-optimization. Most conventional model selection methods can be formulated as solutions of MOO problems via specification of pre-optimization preferences. We reconcile model selection within the MOO framework. We also consider model selection using post-optimization specification of preferences. That is, by first identifying Pareto optimal solutions, and then selecting among them. We demonstrate concepts with an ecological application of model selection using avian species richness data in the continental United States.

Ecological Modelling↗