bluuebunny/crossref_metadata_2025_split huggingface dataset:
Security Ontology for Adaptive Mapping of Security Standards
Authors: Ramanauskaite Simona , Olifer Dmitrij , Olifer Dmitrij , Goranin Nikolaj , Goranin Nikolaj , Čenys Antanas , Čenys Antanas 
Published: September 2014

Adoption of security standards has the capability of improving the security level in an organization as well as to provide additional benefits and possibilities to the organization. However mapping of used standards has to be done when more than one security standard is employed in order to prevent redundant activities, not optimal resource management and unnecessary outlays. Employment of security ontology to map different standards can reduce the mapping complexity however the choice of security ontology is of high importance and there are no analyses on security ontology suitability for adaptive standards mapping. In this paper we analyze existing security ontologies by comparing their general properties, OntoMetric factors and ability to cover different security standards. As none of the analysed security ontologies were able to cover more than 1/3 of security standards, we proposed a new security ontology, which increased coverage of security standards compared to the existing ontologies and has a better branching and depth properties for ontology visualization purposes. During this research we mapped 4 security standards (ISO 27001, PCI DSS, ISSA 5173 and NISTIR 7621) to the new security ontology, therefore this ontology and mapping data can be used for adaptive mapping of any set of these security standards to optimize usage of multiple securitystandards in an organization.
Active Queue Management of TCP Flows with Self-scheduled Linear Parameter Varying Controllers
Authors: Kasnakoglu Cosku 
Published: September 2014

Control-theoretic approaches to Active Queue Management (AQM) are typically based on linearizations of fluid flow models around design conditions. These conditions depend on the Round Trip Time (RTT), and the AQM performance is known to degrade if RTT values during actual operation depart substantially from design values. To overcome this difficulty a self-scheduled LPV controller for AQM is considered in this paper, where the controller is modified in real-time based on RTT. Simulations show that the self-scheduled LPV controller has good performance for both constant and time-varying RTTs, and outperforms two other common control-theoretic approaches to AQM.
Improving the Efficiency of Image Clustering using Modified Non Euclidean Distance Measures in Data Mining
Authors: P Santhi , Bhaskaran V.Murali 
Published: September 2014

The Image is very important for the real world to transfer the messages from any source to destination. So, these images are converted in to useful information using data mining techniques. In existing all the research papers using kmeans and fuzzy k means with euclidean distance for image clustering. Here, each cluster needs its own centric for cluster calculation and the euclidean distance calculate the distance between the points. In clustering this process of distance calculation did not give efficient result. For make this in to efficient, this research paper proposes the non Euclidean distance measures for distance calculation. Here, the logical points are used to find the cluster. The result shows that image clustering based on the modified non Euclidean distance and the performance shows the efficiency of non euclidean distancemeasures.
Non-Negative Factorization for Clustering of Microarray Data
Authors: Morgos Lucian 
Published: September 2014

Typically, gene expression data are formed by thousands of genes associated to tens or hundreds of samples. Gene expression data comprise relevant (discriminant)information as well as irrelevant information often interpreted as noise. The irrelevant information usually affects the efficiency of discovering and grouping meaningful latent information correlated to biological significance, process closely related to data clustering. Class discovery through clustering may help in identifying latent features that reflect molecular signatures, ultimately leading to class forming. One solution for improving the class discovery efficiency is provided by data dimensionality reduction, where data is decomposed into lower dimensional factors, so that those factors approximate original data.
Reducing Cost and Deferred Production in Sucker Rod Pumping Well Subjected to Intermittent Steam Cycling Utilizing Steam ByPass Pump in PDVSA West
Authors: Argüello V. J. , Ramirez P.. , Jimenez B.. , Hernandez D.. , Nuñez S.. , Caldera N.. 
Published: September 2014

Abstract
The demand of heavy oil production is a challenge by the petroleum industry to develop, through new technology, and improved methods of pumping heavy oil producing wells. The "Steam ByPass" (SBP) pumps consists of a mechanical pump that operates in heavy oil-producing wells, subjected to cyclic steam stimulation (CSS), it allows the passage of steam without removing the pump from the well; additionally introduces enhancements and accessories to prevent the deposition of solids and damage to internal components during the injection phase that cause premature failure.
Actually in PDVSA West the process to cyclic steam injection with down hole pumping was carried out by annulus (casing - tubing) which could cause problems, such as: casing deterioration, lower quality steam, pumping premature failure (anchor, cage, and balls), loss or inefficiency of the steam cycles.
The high rate of failure of pumps, after the cyclic steam injection, it has originated the search for an alternative which increase or maximize the run life of pumps subjected CSS.
The evaluation of the "Steam ByPass" pump had been used in two (02) wells of Lagunillas field in PDVSA West and has obtained reduction of production deferred after CSS (in order to 100%), as well as reducing work over (almost two) during a regular process or to cause premature failure. These two tests has showed that the SBP pump overcoming the time average durability of pumps subjected to similarly process and demonstrated it is operational performance.
Improved Artificial Lift Design for Solvent Assisted SAGD Processes
Authors: Babayemi Babatunde , Wu Xingru , Sharma Suresh 
Published: September 2014

Abstract
Artificial lift design for heavy oil systems is a continual changing process in which evolving technological advancements coupled with constant learning experience has led to production capabilities that were not feasible in the past. There has been an increase in installation of temperature tolerant Electric Submersible pumps (ESP) with the primary aim of improving deliverability from mature heavy oil fields. Similarly, in the heavy oil industry, the desire to attain energy efficiency has birthed variations of the Steam Assisted Gravity Drainage (SAGD) process that use solvent additives in further reducing bitumen viscosity. The heavy oil emulsion formed in these systems exhibit rheological characteristics and outflow behaviors different to conventional SAGD systems. Tubing hydraulic performance, steam trap requirements and flow assurance behaviors associated with production from these systems are investigated in this work.
This paper presents dynamic multiphase simulations detailing fluid flow regimes, mass and heat transfer mechanisms and pressure/temperature changes as the reservoir fluid flows out of the reservoir, through an ESP and up the production tubing to the surface. The reservoir is a 3D fully coupled reservoir/wellbore model with properties similar to the Athabasca bitumen reservoir. The simulation was conducted considering all periods in the lifecycle of production i.e. pre and post ramp up. This research finds that a detailed understanding of fluid phase behavior and reservoir operating parameters during the different periods can dramatically improve operating efficiency and impact on ESP design.
Furthermore, results generated from this research can be used as a yardstick for SAGD production engineers in designing artificial lift systems for solvent assisted processes
Progressing Cavity Pump Sizing: Black Magic or Science?
Authors: Dunn Lonnie , Prakash Abhishek 
Published: September 2014

Abstract
Progressing cavity (PC) pumps deployed as an artificial lift method have seen their range of use expand from their heavy oil origins in Canada to a wide variety of different applications around the world. This expansion has been enabled by the development of new products to meet the different volume, lift and downhole fluid environment requirements. However the effect of the fluid environment on the PC pumps‘ stator elastomeric lining dimensions and properties and, in turn their impact on pump performance and life, introduces a critical application design consideration. This consideration is commonly referred to in the industry as pump sizing and encompasses the process of adjusting rotor dimensions to compensate for the impact of the downhole environment on the stator.
Pump sizing started as a trial and error approach based on pump functional testing. As the fluid environments began to have an increased impact on the stator elastomer, pump sizing came to be recognized as being important to ensuring pump success. Methods for measuring rotors and stators were improved and calculation and sizing methodologies developed. Pump test bench equipment and processes became more sophisticated and their accuracy and reliability improved. Methods for laboratory testing elastomer samples in well fluids were developed to quantify dimensional and mechanical property changes.
The second edition of the ISO 15136-1 International Standard for PC Pump Systems for Artificial Lift¹ provides guidelines for component measurement, pump testing and elastomer compatibility testing but does not address the use of this information for pump sizing. Consequently pump sizing is currently done differently across the industry with limited information being provided to end users. This often results in confusion and poor implementation and can detrimentally affect PC pump performance and runtimes. In extreme cases it has led to the characterization of PC pumps as being unsuitable for a particular application when the problem was primarily with the pump sizing. This paper provides an overview of the historical and current state of the different processes associated with PC pump sizing and shows how the newer processes can be applied in a systematic scientific manner to support the successful application of PC Pumps.
Evaluation and Optimization of Proppant Distribution in Multistage Fractured Horizontal Wells: A Simulation Approach
Authors: Bokane Atul , Jain Siddharth , Crespo Freddy 
Published: September 2014

Abstract
Multistage hydraulic fracturing has become the key technology for completion of horizontal and vertical wells. The perf and plug method is the most commonly used staging method. During each stage, multiple perforation clusters are used, attempting to create a separate transverse fracture at each cluster. How these clusters are placed can significantly affect both short- and long-term production performances. Simultaneous creation of multiple fractures is a cost-effective and time saving method for stimulating both vertical and horizontal wells. Multistage fracturing is an effective method in terms of completion efficiency; however, achieving even proppant distribution to each cluster is an intricate task that can be challenging within the industry.
Numerical simulations predict uneven proppant distribution of the fluid streams entering different perforation clusters. Field data indicates, in many cases, that some of the clusters do not contribute to production. This led to hypothesizing that actual proppant and fluid distribution along the stimulated clusters can differ from the assumed uniform distribution.
This paper presents an extensive optimization study and investigation of proppant transport in different perforation clusters within a single stage using computational fluid dynamics (CFD) techniques. Effects of proppant and fluid properties (e.g., variable mass flow rate, variable proppant and fluid densities, and viscosity of the fluid) were analyzed, while maintaining outside-casing parameters constant. Validation of empirical proppant transport CFD simulation results are compared to experimental test data.
The CFD results indicate that proppant transport can be accurately modeled when the effects of single particle settling, density driven flow, particle velocity profiles, and slurry rheology are all considered. Understanding the behavior of proppant and achieving more even proppant distribution among perforation clusters can help the industry. The investigation demonstrates that CFD is an effective tool for optimizing proppant distribution among perforation clusters and enhancing production.
Development of Specialized Plots for Production Data Analysis of Tight Reservoirs with Secondary Fractures
Authors: Ezulike O. D. , Dehghanpour H. 
Published: September 2014

Abstract
Many fractured horizontal wells are completed in tight oil/gas or shale gas reservoirs which have significant networks of interconnected secondary fractures (SF). However, the existing linear transient dual- and triple-porosity models do not properly account for SF. While the dual-porosity model assumes negligible SF, the linear sequential triple-porosity model assumes negligible fluid transfer between the rock matrix and hydraulic fractures. Hence, the application of these models for production data analysis of fractured horizontal wells could result in unreasonable reservoir/fracture parameter estimates and hydrocarbon forecast. For this reason, the quadrilinear flow model (QFM) was developed to account for matrix—hydraulic fracture communication. Although QFM properly accounts for the contribution of SF during reservoir depletion, reservoir parameter estimation from its type-curve matching procedure has a high degree of uncertainty. This paper proposes simplified QFM flow regime equations to reduce the uncertainty associated with reservoir parameter estimation.
This study carefully analyzes the general QFM solution by observing the flow regions from dimensionless rate and pressure type-curves. This solution is simplified by eliminating dimensionless parameters with negligible contribution to fluid depletion within the duration of each flow region. The resulting simplified equations are analytically inverted from Laplace space to time space. The simplification process 1) yields flow-region analysis equations for the specialized rate-normalized pressure and pressure derivative plots and 2) explains the possible physics behind the flow-regions.
The effect of secondary fracture networks on reservoir depletion can be investigated by applying QFM analysis equations on specialized rate-normalized pressure and pressure derivative production data plots. The choice of these plots is based on operational well constraints and observable flow regions. The analysis equations are applied to interpret production data of two multifractured horizontal wells completed in the Cardium and Bakken Formations. The results estimate effective half-length of hydraulic fractures, investigate the presence/absence of secondary fractures and propose a workflow for handling the uncertainty in reservoir parameter estimation when applying the specialized analysis equation plots.
Integration of Microseismic Data, Tracer Information, and Fracture Modeling into the Development of Fractured Horizontal Wells in the Slave Point Formation
Authors: Roney Dana , Quirk David , Ziarani Ali S. , Burke Lyle 
Published: September 2014

Abstract
The tight carbonate platform portion of the Slave Point has seen tremendous development over the last few years through application of multi-stage hydraulically fractured horizontal wells. Higher oil prices and depleting conventional resources have motivated operators to focus on this once by-passed resource. One of the primary engineering challenges is the optimization of the fracture size, geometry and conductivity along the length of a horizontal well. Tight reservoirs are marked by significant initial decline rates and many operators are now looking to a combination of fracture optimization and enhanced oil recovery (EOR) schemes to offset decline rates and increase the EUR. Understanding the performance and connectivity of the hydraulic fractures is a significant input to EOR design and performance.
In this study, sixteen stages of microseismic data collected from two wellbores were used to constrain fracture geometries. These geometries were then integrated with pumping operations, mini-frac / DFIT analysis, and log data to create a calibrated fracture model in a pseudo-3D fracture simulator. The objectives of the calibrated fracture model were to better understand the resultant fracture production performance as well as options to optimize fractures and improve hydrocarbon recovery.
Chemical tracers were included in each stage of the fracturing fluid (water). This allowed for fluid flow back to be analyzed in an attempt to understand which portions of the wellbore are more productive than others.
This paper presents a case study of the workflow to integrate the microseismic, fracturing, reservoir and tracer studies in order to optimize the understanding of the hydrocarbon production.
The Application of Discrete Fracture Network Modelling to the Optimization of Wells in Resource Plays
Authors: Emsley Simon , Chi Shihong , Rivas Jhon , Hallin Jim 
Published: September 2014

Abstract
The drilling and completion of wells in resource plays has tended to be based on drilling a pre-determined number of wells with uniformly spaced laterals drilled on pre-defined azimuths. The development of resource plays is now incorporating geophysics. Workflows have been developed that make 3D seismic data relevant to unconventional resource optimisation and to improve the economics of exploration and development. This can be achieved by constructing models, incorporating data sets derived from the seismic volumes and wireline data and then forward modelling and subsequently optimising well placement and hydraulic fracture design.
The workflow described here starts with a 3D surface-seismic multi-component data set and goes through to hydraulic fracture simulation and potential well optimization achieved through the construction of a discrete fracture network (DFN) model. The data sets are derived from azimuthal velocity analysis and anisotropic parameter calculations; seismic attribute analysis, interpretation and inversion provide a rich data source to develop a model, driven by deterministic data.
Three theoretical wells were included in the model, the location of one indicated that it was drilled into the intersection of two faults which could have been avoided. The other two were forward modelled, simulating hydraulic fracturing; this showed that in areas of high fracture density there was a larger number of stimulated fractures and predicted micro-seismicity, suggesting the reactivation of pre-existing fault and fractures. In areas with lower fracture densities, additional fractures were generated suggesting that hydraulic fracturing would result in the generation of new tensile fractures.
The modelling provided an enhanced understanding of the reservoir, providing greater insight than would be obtained from co-rendering. Importantly, the model tested different well positions, stage spacings and drilling azimuths. In this case study the locations and azimuths of the laterals were changed with differences in the stage-to-stage stimulated volume of between 3 and 30%. This was particularly the case for the central stages of the modelled wells and this has clear financial implications in the development of the resource in terms of drilling costs, completions and production.
Using High-Grading and Portfolio Tools to Allocate Resources among Shale Play Opportunities
Authors: Chorn Larry , Serice John , Del Rosario-Davis Suzanne 
Published: September 2014

Abstract
Portfolio theory requires the decision maker to associate a project's reward potential with its risk profile to characterize its contribution to an investment program. Reward and risk must be quantified in a manner that enables comparison across the set of investment alternatives to ensure that the capital allocation process is optimized. This quantification becomes difficult when the opportunity set contains very different investments, such as an offshore oil field, an oil sands project expansion, and a refinery upgrade. The risk components are different for each, and the rewards have different time horizons. Nevertheless, the risks and rewards for these types of investment opportunities are clear and can be modeled using historical information and experience.
Many companies have added shale plays to their investment portfolio, mixing one or more shale plays into an opportunity set. The risk and rewards of shale plays are gradually being understood. However, the ability to predict the economic performance in terms of production rate and reserve addition is not a science. Controllable and uncontrollable risks impact the expected reward. Controllable risks are quantifiable; however, uncontrollable risks, critical shale properties' distribution within the play and their effect on production, remain unpredictable before appraisal drilling.
Evaluating shale play investments as part of a portfolio requires quantifying both types of risk. Uncontrollable risks require new methods and insights to understand and quantify. Key shale property distribution prediction, coupling well logs with geostatistics, enables the quantification of uncontrollable risks in a shale play investment. The method quantifies relations between key shale properties and well performance to improve predrilling production forecasts. This paper addresses the method's application within and between shale plays to optimize capital allocations. This enables senior management to deliver production growth, cash flow, net present value (NPV), and reserve replacement, within capital constraints, from a portfolio comprising shale assets.
Advances in Understanding Liquid Flow in Gas Shales
Authors: Ghanbari Ebrahim , Xu Mingxiang , Dehghanpour Hassan , Bearinger Doug 
Published: September 2014

Abstract
Understanding water uptake of gas shales is critical for designing fracturing and treatment fluids. Previous imbibition experiments on unconfined gas shales have led to several key observations. The water uptake of dry shales is higher than their oil uptake. Furthermore, water imbibition results in sample expansion and microfracture induction. This study provides additional experimental data to understand the effects of rock fabric, complex pore network, and clay swelling on imbibition behavior.
We systematically measure the imbibition rates of fresh water, brine and oil into the confined and unconfined rock samples and crushed packs from different shale members of the Horn River Basin. We also measure the ion diffusion rate from shale into water during imbibition experiments. The results show that confining the shale samples decreases the water imbibition rate of samples tested parallel to the bedding. However, it has a negligible effect on water uptake of samples tested perpendicular to the bedding and on ion diffusion rates. The comparative study suggests that, for both confined and unconfined samples, water uptake is higher than oil uptake. The liquid imbibition and ion diffusion rates along the bedding are higher than those against the bedding. Surprisingly, the crushed samples show a completely different behavior. The oil uptake of crushed packs is higher than their water uptake. The data suggest that the connected pore network of the intact samples is water wet while the majority of rock including poorly connected pores is oil wet. This argument is backed by complete spreading of oil on fresh break surfaces of the rock.