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At least 361 records · Page 20Linked to original sources
USGS2017

Summary of the analyses for recovery factors

Introduction In order to determine the hydrocarbon potential of oil reservoirs within the U.S. sedimentary basins for which the carbon dioxide enhanced oil recovery (CO 2- EOR) process has been considered suitable, the CO 2 Prophet model was chosen by the U.S. Geological Survey (USGS) to be the primary source for estimating recovery-factor values for individual reservoirs. The choice was made because of the model’s reliability and the ease with which it can be used to assess a large number of reservoirs. The other two approaches—the empirical decline curve analysis (DCA) method and a review of published literature on CO 2 -EOR projects—were deployed to verify the results of the CO 2 Prophet model. This chapter discusses the results from CO 2 Prophet (chapter B, by Emil D. Attanasi, this report) and compares them with results from decline curve analysis (chapter C, by Hossein Jahediesfanjani) and those reported in the literature for selected reservoirs with adequate data for analyses (chapter D, by Ricardo A. Olea). To estimate the technically recoverable hydrocarbon potential for oil reservoirs where CO 2 -EOR has been applied, two of the three approaches—CO 2 Prophet modeling and DCA—do not include analysis of economic factors, while the third approach—review of published literature—implicitly includes economics. For selected reservoirs, DCA has provided estimates of the technically recoverable hydrocarbon volumes, which, in combination with calculated amounts of original oil in place (OOIP), helped establish incremental CO 2 -EOR recovery factors for individual reservoirs. The review of published technical papers and reports has provided substantial information on recovery factors for 70 CO 2 -EOR projects that are either commercially profitable or classified as pilot tests. When comparing the results, it is important to bear in mind the differences and limitations of these three approaches.

Scientific Investigations Report↗
USGS2019

The Bouse Formation: A controversial Neogene archive of the evolving Colorado River: A scientific drilling workshop report (Feb. 28-March 3, 2019-Bluewater Resort, Parker, Arizona, USA

Neogene deposits of the lower Colorado River valley, especially the Miocene(?) and early Pliocene Bouse Formation, have been the focus of intense debate regarding the early paleoenvironmental history of this important continental-scale river system in southwestern North America and its integration with the proto-Gulf of California. Fine-grained units within these Neogene deposits also hold a promising archive of Pliocene paleoclimate history for this part of the world. Because the depocenter deposits of the Bouse Formation and the deposits that overlie and underlie it are poorly exposed and highly weathered, the formation is ripe for study through collection of drill cores. A workshop was held 28 February–3 March 2019 in Parker, AZ, USA, to discuss how scientific drilling might be employed to help resolve the Bouse controversies and improve our understanding of paleoclimate history in the region.

Arizona, California, Nevada↗
USGS1991

Is April to July runoff really decreasing in the Western United States?

Global warming has been the topic of a great deal of heated discussion and debate in recent years, both in the lay press and in scientific journals. The debate is about whether we are beginning to detect signs of a buildup of greenhouse gases on a global scale. A major part of the debate concerns the possible effects on climate and on the future availability of water resources. The ongoing drought in California has added impetus to the debate, serving notice of the serious consequences of any prolonged decrease in the availability of adequate water supplies. This paper has three primary objectives: (1) To evaluate the ramifications of using fractional runoff rather than total runoff to define trends in runoff; (2) to analyze additional streamflow data for the presence and extent of trends in annual and seasonal runoff volume for the conterminous Western United States; and (3) to examine the influence of the current California drought on indicators of trend.

Conference Paper↗
USGS2008

Climate change and coastal vulnerability assessment: Scenarios for integrated assessment

Coastal vulnerability assessments still focus mainly on sea-level rise, with less attention paid to other dimensions of climate change. The influence of non-climatic environmental change or socio-economic change is even less considered, and is often completely ignored. Given that the profound coastal changes of the twentieth century are likely to continue through the twenty-first century, this is a major omission, which may overstate the importance of climate change, and may also miss significant interactions of climate change with other non-climate drivers. To better support climate and coastal management policy development, more integrated assessments of climatic change in coastal areas are required, including the significant non-climatic changes. This paper explores the development of relevant climate and non-climate drivers, with an emphasis on the non-climate drivers. While these issues are applicable within any scenario framework, our ideas are illustrated using the widely used SRES scenarios, with both impacts and adaptation being considered. Importantly, scenario development is a process, and the assumptions that are made about future conditions concerning the coast need to be explicit, transparent and open to scientific debate concerning their realism and likelihood. These issues are generic across other sectors.

Sustainability Science↗
USGS2021

Graph-based reinforcement learning for active learning in real time: An application in modeling river networks

Effective training of advanced ML models requires large amounts of labeled data, which is often scarce in scientific problems given the substantial human labor and material cost to collect labeled data. This poses a challenge on determining when and where we should deploy measuring instruments (e.g., in-situ sensors) to collect labeled data efficiently. This problem differs from traditional pool-based active learning settings in that the labeling decisions have to be made immediately after we observe the input data that come in a time series. In this paper, we develop a real-time active learning method that uses the spatial and temporal contextual information to select representative query samples in a reinforcement learning framework. To reduce the need for large training data, we further propose to transfer the policy learned from simulation data which is generated by existing physics-based models. We demonstrate the effectiveness of the proposed method by predicting streamflow and water temperature in the Delaware River Basin given a limited budget for collecting labeled data. We further study the spatial and temporal distribution of selected samples to verify the ability of this method in selecting informative samples over space and time.

Conference Paper↗
USGS2023

CONUS404: The NCAR-USGS 4-km long-term regional hydroclimate reanalysis over the CONUS

A unique, high-resolution, hydroclimate reanalysis, 40-plus-year (October 1979–September 2021), 4 km (named as CONUS404), has been created using the Weather Research and Forecasting Model by dynamically downscaling of the fifth-generation European Centre for Medium-Range Weather Forecasts (ECMWF) atmospheric reanalysis of the global climate dataset (ERA5) over the conterminous United States. The paper describes the approach for generating the dataset, provides an initial evaluation, including biases, and indicates how interested users can access the data. The motivation for creating this National Center for Atmospheric Research (NCAR)–U.S. Geological Survey (USGS) collaborative dataset is to provide research and end-user communities with a high-resolution, self-consistent, long-term, continental-scale hydroclimate dataset appropriate for forcing hydrological models and conducting hydroclimate scientific analyses over the conterminous United States. The data are archived and accessible on the USGS Black Pearl tape system and on the NCAR supercomputer Campaign storage system.

Continental United States↗
USGS2002

Basis and methods of NASA airborne topographic mapper lidar surveys for coastal studies

This paper provides an overview of the basic principles of airborne laser altimetry for surveys of coastal topography, and describes the methods used in the acquisition and processing of NASA Airborne Topographic Mapper (ATM) surveys that cover much of the conterminous US coastline. This form of remote sensing, also known as "topographic lidar", has undergone extremely rapid development during the last two decades, and has the potential to contribute within a wide range of coastal scientific investigations. Various airborne laser surveying (ALS) applications that are relevant to coastal studies are being pursued by researchers in a range of Earth science disciplines. Examples include the mapping of "bald earth" land surfaces below even moderately dense vegetation in studies of geologic framework and hydrology, and determination of the vegetation canopy structure, a key variable in mapping wildlife habitats. ALS has also proven to be an excellent method for the regional mapping of geomorphic change along barrier island beaches and other sandy coasts due to storms or long-term sedimentary processes. Coastal scientists are adopting ALS as a basic method in the study of an array of additional coastal topics. ALS can provide useful information in the analysis of shoreline change, the prediction and assessment of landslides along seacliffs and headlands, examination of subsidence causing coastal land loss, and in predicting storm surge and tsunami inundation.

Journal of Coastal Research↗
USGS2017

Predicted pH at the domestic and public supply drinking water depths, Central Valley, California

This scientific investigations map is a product of the U.S. Geological Survey (USGS) National Water-Quality Assessment (NAWQA) project modeling and mapping team. The prediction grids depicted in this map are of continuous pH and are intended to provide an understanding of groundwater-quality conditions at the domestic and public supply drinking water zones in the groundwater of the Central Valley of California. The chemical quality of groundwater and the fate of many contaminants is often influenced by pH in all aquifers. These grids are of interest to water-resource managers, water-quality researchers, and groundwater modelers concerned with the occurrence of natural and anthropogenic contaminants related to pH. In this work, the median well depth categorized as domestic supply was 30 meters below land surface, and the median well depth categorized as public supply is 100 meters below land surface. Prediction grids were created using prediction modeling methods, specifically boosted regression trees (BRT) with a Gaussian error distribution within a statistical learning framework within the computing framework of R ( http://www.r-project.org/ ). The statistical learning framework seeks to maximize the predictive performance of machine learning methods through model tuning by cross validation. The response variable was measured pH from 1,337 wells and was compiled from two sources: USGS National Water Information System (NWIS) database (all data are publicly available from the USGS: http://waterdata.usgs.gov/ca/nwis/nwis ) and the California State Water Resources Control Board Division of Drinking Water (SWRCB-DDW) database (water quality data are publicly available from the SWRCB: http://www.waterboards.ca.gov/gama/geotracker_gama.shtml ). Only wells with measured pH and well depth data were selected, and for wells with multiple records, only the most recent sample in the period 1993–2014 was used. A total of 1,003 wells (training dataset) were used to train the BRT model, and 334 wells (hold-out dataset) were used to validate the prediction model. The training r-squared was 0.70, and the root-mean-square error (RMSE) in standard pH units was 0.26. The hold-out r-squared was 0.43, and RMSE in standard pH units was 0.37. Predictor variables consisting of more than 60 variables from 7 sources were assembled to develop a model that incorporates regional-scale soil properties, soil chemistry, land use, aquifer textures, and aquifer hydrology. Previously developed Central Valley model outputs of textures (Central Valley Textural Model, CVTM; Faunt and others, 2010) and MODFLOW-simulated vertical water fluxes and predicted depth to water table (Central Valley Hydrologic Model, CVHM; Faunt, 2009) were used to represent aquifer textures and groundwater hydraulics, respectively. In this work, wells were attributed to predictor variable values in ArcGIS using a 500-meter buffer. Faunt, C.C., ed., 2009, Groundwater availability in the Central Valley aquifer, California: U.S. Geological Survey Professional Paper 1776, 225 p., accessed at https://pubs.usgs.gov/pp/1766/ . Faunt, C.C., Belitz, K., and Hanson, R.T., 2010, Development of a three-dimensional model of sedimentary texture in valley-fill deposits of Central Valley, California, USA: Hydrogeology Journal, v. 18, no. 3, p. 625–649, https://doi.org/10.1007/s10040-009-0539-7 .

California↗
USGS2011

Making United States Integrated Ocean Observing System (U.S. IOOS) inclusive of marine biological resources

An important Data Management and Communication (DMAC) goal is to enable a multi-disciplinary view of the ocean environment by facilitating discovery and integration of data from various sources, projects and scientific domains. United States Integrated Ocean Observing System (U.S. IOOS) DMAC functional requirements are based upon guidelines for standardized data access services, data formats, metadata, controlled vocabularies, and other conventions. So far, the data integration effort has focused on geophysical U.S. IOOS core variables such as temperature, salinity, ocean currents, etc. The IOOS Biological Observations Project is addressing the DMAC requirements that pertain to biological observations standards and interoperability applicable to U.S. IOOS and to various observing systems. Biological observations are highly heterogeneous and the variety of formats, logical structures, and sampling methods create significant challenges. Here we describe an informatics framework for biological observing data (e.g. species presence/absence and abundance data) that will expand information content and reconcile standards for the representation and integration of these biological observations for users to maximize the value of these observing data. We further propose that the approach described can be applied to other datasets generated in scientific observing surveys and will provide a vehicle for wider dissemination of biological observing data. We propose to employ data definition conventions that are well understood in U.S. IOOS and to combine these with ratified terminologies, policies and guidelines.

Conference Paper↗
USGS2006

Linking the concept of scale to studies of biological diversity: evolving approaches and tools.

Although the concepts of scale and biological diversity independently have received rapidly increasing attention in the scientific literature since the 1980s, the rate at which the two concepts have been investigated jointly has grown much more slowly. We find that scale considerations have been incorporated explicitly into six broad areas of investigation related to biological diversity: (1) heterogeneity within and among ecosystems, (2) disturbance ecology, (3) conservation and restoration, (4) invasion biology, (5) importance of temporal scale for understanding processes, and (6) species responses to environmental heterogeneity. In addition to placing the papers of this Special Feature within the context of brief summaries of the expanding literature on these six topics, we provide an overview of tools useful for integrating scale considerations into studies of biological diversity. Such tools include hierarchical and structural-equation modelling, kriging, variable-width buffers, k -fold cross-validation, and cascading graph diagrams, among others. Finally, we address some of the major challenges and research frontiers that remain, and conclude with a look to the future.

Diversity and Distributions↗
USGS2019

Status of three-dimensional geological mapping and modeling activities in the U.S. Geological Survey

The U.S. Geological Survey (USGS), created in 1879, is the national geological survey for the United States and the sole science agency within its cabinet-level bureau, the Department of the Interior. The USGS has a broad mission, including: serving the Nation by providing reliable scientific information to describe and understand the Earth; minimize loss of life and property from natural disasters; manage water, biological, energy, and mineral resources; and enhance and protect quality of life. USGS scientific activities are organized around major topics, or Mission Areas, aligned with distinct science themes; three-dimensional (3-D) modelling typically supports research and project work within a specific Mission Area. The vastness, diversity, and complexity of the geological landscape of the United States has resulted in the creation of 3-D geological framework models that are local or regional in scale; a National-scale 3-D model is only beginning to evolve. This paper summarizes 3-D geological modeling at the USGS and does not discuss 3-D modeling that is conducted by other Federal agencies, state geological surveys, academia, or industry within the U.S. This paper updates and expands upon a similar status report of USGS 3-D modeling activities of Jacobsen et al. (2011).

Report↗
USGS2006

Inversion of elastic impedance for unconsolidated sediments

Elastic properties of gas-hydrate-bearing sediments are important for quantifying gas hydrate amounts as well as discriminating the gas hydrate effect on velocity from free gas or pore pressure. This paper presents an elastic inversion method for estimating elastic properties of gas-hydrate-bearing sediments from angle stacks using sequential inversion of P-wave impedance from the zero-offset stack and S-wave impedance from the far-offset stack without assuming velocity ratio.

Scientific Investigations Report↗
USGS2020

An update of USGS bear-real-time earthquake shaking and impact products

We report on advancements in both hazard and consequence modeling that form the core of the U.S. Geological Survey’s (USGS) strategy to improve rapid earthquake shaking and loss estimates. Whereas our primary goal is to improve our operational capabilities of the USGS National Earthquake Information Center, the science, software, and datasets behind these systems continue to advance uses and studies of earthquake shaking and impact by the seismological, engineering, financial, and risk modeling communities. Several important updates to our integrated shaking and impact products are outlined and we introduce new earthquake information products that have recently been brought online, including rapid ground failure estimates and more spatially refined loss estimates domestically (in the U.S). We continue to compile, develop, and refine key openly available models and datasets that contribute to calibrating these systems and report on the collection and storage of new inventories. We also describe some of the basic operational considerations in the current generation of these shaking and loss-estimation systems. A key aspect of the product integration and development is leveraging earthquake-hazard and loss-modeling science done internally (within the USGS) and by external researchers and collaborators. Lastly, we outline new opportunities for further research and development by emphasizing scientific, data, and application gaps and challenges that must be solved in order to improve our shaking and impact information tools.

Conference Paper↗
USGS2022

Subsampling large-scale digital elevation models to expedite geospatial analyses in coastal regions

Large-area, high-resolution digital elevation models (DEMs) created from light detection and ranging (LIDAR) and/or multibeam echosounder data sets are commonly used in many scientific disciplines. These DEMs can span thousands of square kilometers, typically with a spatial resolution of 1 m or finer, and can be difficult to process and analyze without specialized computers and software. Such DEMs often can be subsampled to expedite analysis with negligible impact on results for large-scale geospatial analyses. Subsampling can be achieved by creating a grid of points that specify the locations from which to extract elevation values from the DEM. This paper presents a method that can be used to accurately perform subsampling of large-scale, high-resolution DEMs using GIS software. This subsampling method was applied to two LIDAR-derived DEMs encompassing 242 km 2 of the northern Florida Reef Tract as an example application and to test subsampling accuracy. Results indicate that subsampling 1-m-resolution DEMs using a 2-m-spaced grid results in no significant difference in mean elevation or other basic statistics for analyses performed over multiple spatial scales ranging from 1 km 2 to 242 km 2 .

Journal of Coastal Research↗
USGS2016

Assessing the socioeconomic impact and value of open geospatial information

The production and accessibility of geospatial information including Earth observation is changing greatly both technically and in terms of human participation. Advances in technology have changed the way that geospatial data are produced and accessed, resulting in more efficient processes and greater accessibility than ever before. Improved technology has also created opportunities for increased participation in the gathering and interpretation of data through crowdsourcing and citizen science efforts. Increased accessibility has resulted in greater participation in the use of data as prices for Government-produced data have fallen and barriers to access have been reduced. The increase in participation in the production and in the use of data, defined as data democracy for this workshop, are having great impacts on economics and more generally on society. There is also a strong drive by governments around the world, as shown by the G8 Declaration in June 2013, to make public sector information and scientific data more widely accessible. These are respectively termed “open data” and “open research data.” This report summarizes discussion at the Workshop on Assessing the Impact and Value of Open Geospatial Information held at George Washington University in Washington, D.C. in October 2014. Workshop participants examined the consequences of expanding data democracy with a focus on its socioeconomic impacts. Evaluations were presented of state-of-the-art methods to assess these socioeconomic impacts, which included position papers and remarks by discussants. The workshop included discussions about the following topics: (1) increased and expanded information sources; (2) societal impacts, including approaches to economics assessments; (3) constraints to open access, including the demands for return on investment, specifications of intellectual property rights, and privacy issues; and (4) learning from the experiences of other data-rich domains, such as environmental management, internet businesses, health, and transportation. The workshop was a working meeting with strong participant engagement, leading to recommendations for action. The meeting included five topic-driven sessions and keynote presentations. Precirculated position papers for each panel session facilitated preparation and remarks by discussants. After the position papers are updated following the discussants’ remarks, it is planned to submit them for publication. The workshop included 68 participants coming from international organizations, the U.S. public and private sectors, nongovernmental organizations, and academia. Participants included policy makers and analysts, financial analysts, economists, information scientists, geospatial practitioners, and other discipline experts.

Open-File Report↗
USGS1995

Geoscience research databases for coastal Alabama ecosystem management

Effective management of complex coastal ecosystems necessitates access to scientific knowledge that can be acquired through a multidisciplinary approach involving Federal and State scientists that take advantage of agency expertise and resources for the benefit of all participants working toward a set of common research and management goals. Cooperative geostatic investigations have led toward building databases of fundamental scientific knowledge that can be utilized to manage coastal Alabama's natural and future development. These databases have been used to assess the occurrence and economic potential of hard mineral resources in the Alabama EFZ, and to support oil spill contingency planning and environmental analysis for coastal Alabama.

Conference Paper↗
USGS2006

Revisiting Frazier's subdeltas: enhancing datasets with dimensionality, better to understand geologic systems

Scientific knowledge from the past century is commonly represented by two-dimensional figures and graphs, as presented in manuscripts and maps. Using today's computer technology, this information can be extracted and projected into three- and four-dimensional perspectives. Computer models can be applied to datasets to provide additional insight into complex spatial and temporal systems. This process can be demonstrated by applying digitizing and modeling techniques to valuable information within widely used publications. The seminal paper by D. Frazier, published in 1967, identified 16 separate delta lobes formed by the Mississippi River during the past 6,000 yrs. The paper includes stratigraphic descriptions through geologic cross-sections, and provides distribution and chronologies of the delta lobes. The data from Frazier's publication are extensively referenced in the literature. Additional information can be extracted from the data through computer modeling. Digitizing and geo-rectifying Frazier's geologic cross-sections produce a three-dimensional perspective of the delta lobes. Adding the chronological data included in the report provides the fourth-dimension of the delta cycles, which can be visualized through computer-generated animation. Supplemental information can be added to the model, such as post-abandonment subsidence of the delta-lobe surface. Analyzing the regional, net surface-elevation balance between delta progradations and land subsidence is computationally intensive. By visualizing this process during the past 4,500 yrs through multi-dimensional animation, the importance of sediment compaction in influencing both the shape and direction of subsequent delta progradations becomes apparent. Visualization enhances a classic dataset, and can be further refined using additional data, as well as provide a guide for identifying future areas of study.

Gulf Coast Association of Geological Societies Tra↗
USGS2015

Dune management challenges on developed coasts

From October 26-28, 2015, nearly 100 members of the coastal management and research communities met in Kitty Hawk, NC, USA to bridge the apparent gap between the coastal dune research of scientists and engineers and the needs of coastal management practitioners. The workshop aimed to identify the challenges involved in building and managing dunes on developed coasts, assess the extent to which scientific knowledge can be applied to the management community, and identify approaches to provide means to bridge the gap between needs and potential solutions.

Conference Paper↗