计量经济分析 = Econometric analysis

Here we integrate spatial information on annual burnt area, fire frequency, fire seasonality, fire radiative power and fire size distributions to produce an integrated picture of fire regimes in southern Africa. The regional patterns are related to gradients of environmental and human controls of fire, and compared with findings from other grass-fuelled fire systems on the globe. The fire regime differs across a gradient of human land use intensity, and can be explained by the differential effect of humans on ignition frequencies and fire spread. Contrary to findings in the savannas of Australia, there is no obvious increase in fire size or fire intensity from the early to the late fire season in southern Africa, presumably because patterns of fire ignition are very different. Similarly, the importance of very large fires in driving the total annual area burnt is not obvious in southern Africa. These results point to the substantial effect that human activities can have on fire in a system with high rural population densities and active fire management. Not all aspects of a fire regime are equally impacted by people: fire-return time and fire radiative power show less response to human activities than fire size and annual burned area.

Southern African Fire Regimes as Revealed by Remote Sensing

Oil price volatility and oil-related events: An Internet concern study perspective

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Hydrochemical characterization and quality appraisal of groundwater from Pungar sub basin, Tamilnadu, India

See next page for additional authors Follow this and additional works at: http://ecommonsudaytonedu/phy_fac_pub Part of the Environmental Education Commons, Environmental Health and Protection Commons, Environmental Indicators and Impact Assessment Commons, Environmental Monitoring Commons, Natural Resource Economics Commons, Natural Resources and Conservation Commons, Natural Resources Management and Policy Commons, Oil, Gas, and Energy Commons, Other Environmental Sciences Commons, Sustainability Commons, and the Water Resource Management Commons

/pdf/renewable-energy-in-the-context-of-sustainable-development-3llzlruh2m.pdf

Renewable Energy in the Context of Sustainable Development

Modeling lost production from destroyed platforms in the 2004–2005 Gulf of Mexico hurricane seasons

The objective of a field development optimization process, or workflow, is to investigate various options and determine a course of action that will deliver the largest expected value from an asset. The analysis is often complicated by uncertainty in important inputs. Ideally, operators desire workflows and tools that integrate reservoir engineering and optimization principles in a fast-solving model that can be used to explore the full range of the uncertain inputs. This need is acute in the screening and concept selection stage where the primary objective is to determine the sensitivity of competing concepts to the sources of uncertainty. In these early stages, model results can be used to determine whether additional information should be collected, and to narrow down the number of competing options. The objective of this research is the development of a workflow and tool that integrates reservoir response surfaces within a project optimization model that contains facility and operational options, and to use this model to investigate the impacts of uncertainty on decision making. The integration of technical options is critical because a static view of capital investment and facility constraints causes a systematic undervaluation and can introduce error to development decisions. The new workflow and integrated reservoir-economic optimization tool developed in this research leverage methods and engineering work products that are already known to industry, for example, experimental design (ED) and response surface methods (RSMs). A demonstration is provided for a gas flood project using a stylized reservoir. Specifically, we investigate the selection of initial well configurations and injection capacities while simultaneously accounting for the options to update these decisions after production information is acquired in the early periods of production. The workflow is used to optimize the development of a gas flood. As a second step, the workflow is used to solve a value of information problem.

Development Optimization Using Reservoir Response Surfaces: Methods for Integrating Facility and Operational Options

This study examines the determinants of health, safety, and environmental (HS&E) incidence and reporting behavior in Gulf of Mexico offshore drilling. One objective is to determine statistically significant variables that influence the probability of HS&E incidence and reporting. Incidence modeling employs standard qualitative response models with binary and ordered dependent variables, and a Poisson specification. A second objective is to examine the impact of imperfect reporting on inferences. Unlike previous studies, models allowing for the possibility of imperfect reporting are specified and estimated. The results of this analysis provide strong evidence to support the hypothesis that aspects of well complexity and site complexity increase the likelihood of HS&E incidents in drilling. Equally important is evidence rejecting the hypothesis that broader oil company attributes influence HS&E incidence. An analysis of reporting behavior provides mixed support for the hypothesis that well-known fi...

Employing Detection Controlled Models in Health and Environmental Risk Assessment: A Case in Offshore Oil Drilling

Estimating the Cost of Errors in Estimates Used During Concept Selection

/pdf/gas-storage-facility-design-under-uncertainty-1nmtgishm6.pdf

Christopher J. Jablonowski

Papers

Modeling lost production from destroyed platforms in the 2004–2005 Gulf of Mexico hurricane seasons

Development Optimization Using Reservoir Response Surfaces: Methods for Integrating Facility and Operational Options

Employing Detection Controlled Models in Health and Environmental Risk Assessment: A Case in Offshore Oil Drilling

Estimating the Cost of Errors in Estimates Used During Concept Selection

Gas Storage Facility Design Under Uncertainty