bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Genomewide Suppressor and Enhancer Analysis of cdc13-1 Reveals Varied Cellular Processes Influencing Telomere Capping in Saccharomyces cerevisiae
Authors: Addinall S G , Downey M , Yu M , Zubko M K , Dewar J , Leake A , Hallinan J , Shaw O , James K , Wilkinson D J , Wipat A , Durocher D , Lydall D 
Published: October 2008

Abstract
In Saccharomyces cerevisiae, Cdc13 binds telomeric DNA to recruit telomerase and to “cap” chromosome ends. In temperature-sensitive cdc13-1 mutants telomeric DNA is degraded and cell-cycle progression is inhibited. To identify novel proteins and pathways that cap telomeres, or that respond to uncapped telomeres, we combined cdc13-1 with the yeast gene deletion collection and used high-throughput spot-test assays to measure growth. We identified 369 gene deletions, in eight different phenotypic classes, that reproducibly demonstrated subtle genetic interactions with the cdc13-1 mutation. As expected, we identified DNA damage checkpoint, nonsense-mediated decay and telomerase components in our screen. However, we also identified genes affecting casein kinase II activity, cell polarity, mRNA degradation, mitochondrial function, phosphate transport, iron transport, protein degradation, and other functions. We also identified a number of genes of previously unknown function that we term RTC, for restriction of telomere capping, or MTC, for maintenance of telomere capping. It seems likely that many of the newly identified pathways/processes that affect growth of budding yeast cdc13-1 mutants will play evolutionarily conserved roles at telomeres. The high-throughput spot-testing approach that we describe is generally applicable and could aid in understanding other aspects of eukaryotic cell biology.
Recent Legal Developments in Carbon Sequestration
Authors: Flanery S. O. , McCarty S. C. 
Published: October 2008

Abstract
Carbon sequestration is the process of capturing carbon dioxide ("CO2") emissions, which would otherwise be released into the atmosphere, and permanently storing them in geologic formations. A number of technical and legal issues must be resolved before carbon sequestration can become a viable means to reduce carbon emissions. Recently the Interstate Oil and Gas Compact Commission ("IOGCC") set forth a model statute and model rules and regulations, and the United States Environmental Protection Agency ("EPA") set forth a proposed rule for CO2 injection that could resolve some of these issues and make large-scale carbon sequestration projects a reality. The IOGCC model treats CO2 as a resource and covers the areas of permitting, property ownership, storage operations, and long-term monitoring and liability. Certain parts of the IOGCC model rules were a basis for the EPA proposed rule governing carbon sequestration that was published for public comment on July 25, 2008. This EPA proposed rule creates a new class of underground injection wells regulated as part of the Underground Injection Control program under the Safe Drinking Water Act. Both the IOGCC model statute and the EPA proposed rule provide specific guidance on construction and permit application submittals tailored toward the long-term nature of carbon storage.
Carbon sequestration has also recently been addressed on a broader scale as a component of CO2 reduction in other federal proposals. The FutureGen project was recently modified by the Department of Energy ("DOE") from a $1.8 billion research and development facility to multiple operations that would utilize carbon sequestration technology in coal-fired power plants. Congress has been bombarded with proposed climate change legislation, such as the Lieberman-Warner bill that proposed a cap and trade program. All of the legislation provides methods for reducing emissions thereby increasing incentives to develop carbon sequestration. Also, carbon sequestration is being encouraged through the use of small-scale experimental projects set in motion by the DOE carbon sequestration partnerships.
New rules and regulations addressing the technical and legal aspects of sequestration must be adopted. Until this regulatory framework is available, development of sequestration projects most likely will be hindered or delayed.
Experimental Study of the Thermomechanical Behavior of the Petroleum Reservoir
Authors: Moustafa M. , Malek S. , Jianfu S. 
Published: October 2008

Abstract
This paper presents the findings of a laboratory investigation of the thermomechanical behaviour of anisotropic rock. The tests were performed on natural (Tournemire shale) using triaxial cells modified to control and to go to high temperature. The range of temperatures that were investigated is from 20° to 250°C (20, 100, 150, 200 and 250 C°), and the range of confining pressures is from 0 MPa to 20MPa (0, 5, 10, and 20 MPa). The influence of temperature on their mechanical behaviour was investigated for drained tests, and anisotropic elastic response and plastic deformation have been investigated. It seems that, the thermo-mechanical behaviour of the Tournemire shale is anisotropic and strongly depends on confining pressure and loading orientation at the applied temperature. Hydrostatic compressibility tests (in the perpendicular orientation θ =90°) allowed to present the thermal effect on the mechanical behaviour of this rock. In this range of temperatures, the deformability and strength of this rock were found to be strongly dependent of temperature.
Case Study: Evaluation of Regional Lithology for Carbon Dioxide Storage Using a Single Test Well in Southeastern Ohio
Authors: Meggyesy S. D. , Jagucki P. E. , Gerst J. , Place M. 
Published: October 2008

Abstract
The purpose of this project is to investigate the feasibility of carbon sequestration using information gathered from a single test well at a coal-fired power plant in the Appalachian Basin. The effort to date includes site selection, preliminary test design and implementation, and development of data objectives consistent with overall program goals. An iterative approach was implemented to enhance our understanding of the local and regional geologic conditions and limits at each stage. First steps included building a geologic model of injection and caprock formations based on regional well logs and other existing data as well as performing a 2-D surface seismic survey around the proposed well location. This information was then used to design the stratigraphic test well and data collection methodology. The test well was drilled in early 2007 and completed in January 2008. Wireline logs and rock samples collected during the drilling are being used to refine the geologic model and to develop plans for the injection tests scheduled for fall 2008. The site is one of the three locations selected for testing geologic storage of CO2 under the Midwestern Regional Carbon Sequestration Program (MRCSP) led by Battelle.
Information collected to date is being analyzed to indicate the potential for carbon sequestration in regional reservoirs. In general, the reservoirs are well-contained with good caprock. Drilling, logging, and collection and laboratory testing of sidewall cores have provided the data to design injection tests in up to three potential injection targets between approximately 5,000 and 8,000 feet below ground surface. Approximately 3,000 tons of supercritical-phase CO2 is planned to be injected in these formations. Targets include a Lower Silurian sandstone known regionally as a gas-producer; Silurian sequences consisting of interbedded layers of halite, anhydrite, limestone, and porosity-preserving dolomite; and a Lower Devonian sandstone. The upcoming injection tests will help to further refine local and regional injectivity and capacity in the target reservoirs; caprock integrity, and single-well monitoring techniques.
Field projects like this add to knowledge and understanding of how to select and characterize potential injection reservoirs, establish familiarity of the technology with the public and regulatory agencies, and aid in the selection of appropriate testing and monitoring techniques for each location.
Uncovering and Exploiting Existing Marcellus Shale Opportunities in the Appalachian Basin
Authors: Suhy T. E. 
Published: October 2008

Abstract
The developing interest in the Northeast Marcellus Shale play has led to a flood of lease acquisition activity not seen in many years. Competitive acreage positioning and rumors of huge delayed rentals, large signing bonuses, and generous buy-outs are reminiscent of the boom years in the early 1980's. Most of the potential affordable assets have already been locked up and the small or medium size operator has either been priced out or crowded out.
Those operators may not be as far behind the rush as they may fear. The nature of oil field culture has led to the Marcellus and other shale formations being ignored for years and viewed as more of a drilling nuisance than as a valuable play. As a result, it has been drilled to, drilled through, cased through and generally avoided for as long the Devonian Sands have been developed in the Appalachian Basin. In a few cases where shale stimulations were attempted, they were poorly designed and marginally effective which kept the interest very limited.
The oil field culture of past decades allowed many of these resources to remain hidden and underdeveloped. These assets can now be "Re-Discovered" through a variety of record resource reviews, re-drilling and re-completion techniques, spacing analysis, and general detective work.
This paper will explore a variety of techniques that both major and independent operators can use to take advantage of their existing underdeveloped assets.
A New Algorithm for Rachford-Rice for Multiphase Compositional Simulation
Authors: Okuno R. , Johns R. T. , Sepehrnoori K. 
Published: October 2008

Abstract
Flash calculations for use in compositional simulation are more difficult and time-consuming as the number of equilibrium phases increase beyond two. Because of its complexity many simulators do not even attempt to incorporate three or more hydrocarbon phases even though such cases are important in many low-temperature gas floods, or for high temperatures where hydrocarbons can partition into water. Multiphase flash algorithms typically use successive substitution (SS) followed by Newton's method. For NP-phase flash calculations, (NP-1) Rachford-Rice (RR) equations are solved in every iteration step in SS, and depending on the choice of independent variables, in Newton's method. Solution of RR equations determines both compositions and amounts of phases for a fixed overall composition and set of K-values. A robust algorithm for RR is critical to obtain convergence in multiphase compositional simulation, and has not been satisfactorily developed unlike the traditional two-phase flash. In this paper, we develop a robust and efficient algorithm for RR equations for multiphase compositional simulation.
We focus primarily on systems with three equilibrium hydrocarbon phases, although other applications are possible. We derive a function, whose gradient vector consists of RR equations. This correct solution to the RR equations is formulated as a minimization of the non-monotonic convex function using the independent variables of (NP-1) phase mole fractions. The key to obtaining a robust algorithm is that we specify non-negative constraints for the resulting equilibrium phase compositions, which are described by a very small region with no poles. The minimization uses Newton's direction with a line search technique to exhibit super-linear convergence. We show a case in which a previously developed method cannot converge while our algorithm rapidly converges in a few iterations. We implement the algorithm both in a stand-alone flash code and in UTCOMP, a multiphase compositional simulator, and show that the algorithm is guaranteed to converge when a multiphase region exists as indicated by stability analysis.
Optimized Design of Cyclic Pressure Pulsing in a Depleted, Naturally Fractured Reservoir
Authors: Artun E. , Ertekin T. , Watson R. , Miller B. 
Published: October 2008

Abstract
Gas cyclic pressure pulsing is an effective IOR method specifically for naturally fractured reservoirs. Due to the computational cost of simulating a large number of scenarios, it is an arduous task to determine the optimum operational conditions for the process. In this study, a practical screening and optimization workflow is utilized to determine the most optimum operating conditions for cyclic pressure pulsing applications with N2 and CO2 in a fully-depleted reservoir. Two huff ‘n’ puff design schemes with variable and constant injection volumes are implemented in a compositional, dual-porosity reservoir simulation model. A set of representative design scenarios is created and run using this model. Then, the collected performance indicators are fed into the neural network for training and two neural network-based proxies are developed: 1) A forward proxy to predict the corresponding performance indicators once given the design scenarios, 2) An inverse proxy to predict the corresponding design scenarios once given a set of desired performance characteristics. Finally, the genetic algorithm is used to search for the best design scenario that would maximize the efficiency of the process for a given time of operation. To evaluate the objective function, the forward proxy is used for computational efficiency. The methodology is tested with a single-well reservoir model of the Big Andy Field which is a depleted, naturally fractured reservoir in Eastern Kentucky with stripper-well production. Predictive capability and accuracy of developed networks are checked by comparing simulation outputs with network outputs. It is observed that networks are able to accurately predict the performance indicators including the peak rate, time to reach the peak rate, cycle flow rates, incremental oil production, and gas-oil-ratio. The proposed methodology is practical and computationally efficient in structuring more effective decisions towards the optimum design of the process.
Water Quality: Is it Important for Cement?
Authors: Rowan T. M. , Stone M. L. 
Published: October 2008

Abstract
In this paper, the relationship between cement mix water quality and cement quality are investigated. Water quality will be tested for chlorides, calcium and magnesium, pH, and alkalinity. Full API analysis will be used to compare the effects that different concentrations of the aforementioned components have on cement properties.
Each component previously mentioned will be measured out at specific concentrations in the water. The water will then be used to mix a cement slurry according to API Specification 10. After the slurry is blended, a battery of tests will be run including thickening time, viscosity, compressive strength, free water and fluid loss. Each parameter will then be compared to the results of the cement slurry that was mixed using distilled or de-ionized water. We will also look at the effects of all the "additives" included in the water sample used to mix the cement and any change they have made to the properties of each blend.
This is mainly a study for quality control purposes. We are taking a look at what the limits for specific elements are and what their influence is on certain cement properties. These analyses will help us determine if slurry being considered is suitable for any particular job proposal. This will also enhance our quality control measures and improve our stance on customer satisfaction, which is always our main goal.
Cooperative Optimization-Based Dimensionality Reduction for Advanced Data Mining and Visualization
Authors: Chen D. , Hamid S. , Dix M. , Quirein J. , Jacobson L. , Hollingsworth M. 
Published: October 2008

Abstract
Dimensionality reduction in advanced data mining is often a non-linear problem, and the method used to resolve the dimensionality reduction will typically include:
Definition of the objective function to preserve essential information of the original data Specification of the algorithm to optimize the sample mapping from a high-dimensional (HD) space to a low-dimensional (LD) space Determination of the transformation scheme that can be applied to unseen new data.
In practice, a data-driven approach that maximizes the sample pair distance match of the original data and the transformed data is usually used. But, the sample mapping optimization and new data transformation are often determined in diverse domains.
This paper provides a hybrid method to determine the appropriate data transformation from an original HD space to an output LD space, usually 2D or 3D space, with minimal information loss. This method is fundamentally a cooperative optimization algorithm combining more than one computational intelligence paradigm. Basically, given the problem data in a HD space, the proposed method first applies evolutionary computation (EC) to determine the LD output values, and then, performs particle swarm optimization (PSO) to refine the results. The data conversion scheme is implemented by a neural network ensemble using the EC-PSO-derived LD outputs as training targets. This method has better capability to tackle problems of local minima and to produce robust conversion of the new data. To make the preserved information essential to the user, multi-objective fitting for advanced data exploration is embedded into this method.
In this paper, both the theoretical background of the developed method and the procedures applied to high-dimensional data visualization, feature extraction, and cluster analyses are discussed. Two case studies with simulated and field data to demonstrate potential applications in reservoir characterization and predictive modeling are also presented. The results strongly justify using a cooperative optimization approach to improve data mapping (especially in handling large data sets), and suggest that the method shows promise as being an effective standard procedure to help automate high-dimensional data processing.
Determination of Relative Permeability and Capillary Pressure Curves Using an Automated History-Matching Approach
Authors: Basbug B. , Karpyn Z. T. 
Published: October 2008

Abstract
The efficiency of hydrocarbon recovery from oil and gas reservoirs is mainly controlled by our ability to understand and define fluid transport properties, such as relative permeability and capillary pressure. This study focuses on the development and implementation of a numerical model of multiphase flow in a fractured core sample by establishing a proper physical framework that describes the capillary pressure-relative permeability characteristics. An automated history matching approach is proposed to determine relative permeability and capillary pressure curves consistent with a core flood reservoir model performance. The automated history matching approach relies on a commercial reservoir simulator coupled with an optimization protocol. A large-scale ‘Trust Region Method’ that minimizes the objective function is implemented for the adjustment of parameters controlling the relative permeability and capillary pressure curves. The objective function is defined as the non-linear least square representation of the difference between estimated and obtained fluid saturation distributions from a core flood reservoir model. The results indicate that the proposed approach successfully predicts relative permeability and capillary pressure curves of a fractured core sample which provides a foundation for field-scale history matching with simultaneous estimation of transport properties.
The Effect of Carbonic Acid on Well Cements as Identified through Lab and Field Studies
Authors: Duguid A. 
Published: October 2008

Abstract
In the United States carbon capture and storage as a means of emissions mitigation is moving towards commercial implementation. In anticipation of large numbers of CCS sites coming online it is important to understand wells as potential leakage pathways and identify existing technologies that can measure and monitor the integrity of wells that are exposed to CO2. Well integrity is important because wells and the annuli and pathways that may exist within them can act as leakage pathways for CO2 back to the surface or as conduits for leakage between formations. Studies related to the integrity of wells have been conducted on well cements created in both the laboratory and in the field. This paper will discuss recent laboratory and field work, the differences between the results of the two types of experiments, and how the results of the two are not contradictory but are due to differing conditions between the lab and the field. This paper will also discuss how the results of field measurements can be used to identify the types and combinations of tools that may be used to detect wellbore integrity problems in future.
Development and Testing of an Expert System for Coalbed Methane Reservoirs Using Artificial Neural Networks
Authors: Srinivasan K. , Ertekin T. 
Published: October 2008

Abstract
Reservoir simulators are effectively used in predicting the production performances of oil and gas reservoirs within a good level of accuracy. However, during initial stages of exploitation, our knowledge on most of the reservoir properties and production parameters involve a good degree of uncertainty. In such cases, expert systems can be effective as a screening tool by mimicking the performance of a reservoir simulator at a lower cost and reduced personnel and machine time. The expert system described in this paper is a tool which can be used to predict the performance of a coalbed methane reservoir similar to its numerical counterparts.
The proposed expert system has been trained with the help of an extensive data base and has the capability of providing gas and water production profiles for a period of about ten years for a given coalbed methane reservoir. Other outputs include cumulative gas and water production, peak gas flow rate expected, time to achieve a peak rate and abandonment time. This study also involves the development of an inverse expert system which has the capability of identifying the optimum production strategies for a desired production scenario from a coalbed reservoir. Conventional reservoir simulators cannot suggest an optimized design strategy that can help achieve a certain desired production performance from a coal seam unless a large number of scenarios are studied. The inverse model can tackle this optimization problem quite effectively.