bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Effect of Teaching PECS to a Child With Autism on Verbal Behaviour, Play, and Social Functioning
Authors: Jurgens Anneke , Anderson Angelika , Moore Dennis W. 
Published: June 2009

AbstractThe Picture Exchange Communication System (PECS) is a widely used intervention strategy designed to teach communication skills to children with developmental delays, including autism. The Picture Exchange Communication System incorporates the teaching of mand initiations that are thought to be pivotal response behaviours, and have been demonstrated to lead to generalised improvements in other nontargeted behaviours. The aim of the present study was to assess the acquisition of PECS with a 3-year-old boy with autism using the established PECS training program, and to evaluate concomitant changes in spoken language, social–communicative behaviours, and functional play. Results indicated that the participant rapidly acquired the criterion behaviours for Phases 1 to 3 of the PECS program. Although PECS exchanges were rarely observed in the generalisation settings, clear increases were evident in verbal mands and other initiations in both home and kindergarten generalisation settings. Increases in spoken vocabulary and in the length of comprehensible spoken utterances in free-play were observed as were gains in time spent in developmentally appropriate play. Implications of these results and directions for future research are discussed.
Designing a Simultaneous Water Alternating Gas Process for Optimizing Oil Recovery
Authors: Al-Ghanim Wafaa , Gharbi Ridha , Algharaib Meshal 
Published: June 2009

Abstract
Recently there has been an increasing interest in simultaneous water-alternating-gas (SWAG) in oil recovery operations. This method involves the simultaneous injection of water at the top of the reservoir formation and injecting gas at the bottom of the formation. The difference in water and gas densities will provide a sweeping mechanism in which water tends to sweep hydrocarbons downward and the gas tends to sweep the hydrocarbons upward. It is expected that the two displacement mechanisms will work on establishing a flood front, which will increase the sweep efficiency and thus the oil recovery. This study investigated the performance of SWAG in oil recovery operations.
A three-dimensional finite-difference black oil reservoir simulator has been used to determine the reservoir management strategies in order to optimize the oil recovery using SWAG injection technique. A specific strategy that was studied includes the use of horizontal injectors in conjunction with vertical producers. This well configuration has been shown to yield the best oil recovery compared to other well configurations. The management strategies involved studying different design parameters to maximize the recovery performance. Such parameters include; mobility ratio between oil and water phases, viscosity ratio between gas and oil phases, location of the water and the gas injectors, and injection rates of water and gas. Results showed the investigated parameters are critical in the success of the proposed injection SWAG scheme. The study provides the conditions under which this SWAG injection technique may yield higher recovery performance.
Utilization of the GRM (Geological Representative Models) to Integrate Different Types of Uncertainties in the Decision Making Process
Authors: Silveira Márcio A. , Costa Ana Paula A. , Zamora Gonzalo Javier A. 
Published: June 2009

AbstractDecision analysis applied to the development of petroleum fields must take into account the risk associated to several types of uncertainties. The combination of these uncertainties can be used to quantify the risk related to the decision process. The objective of this study was to evaluate the impact of the integration of different types of uncertainties, especially geological and economics on the complementary development project of an offshore field located 34 Km of Rio Grande do Norte coast in a water depth of 46 meters. It was applied a methodology, involving quantification of uncertainty and risk analysis (Costa, 2003), that proposes the use of models representing the geological uncertainties, called Geological Representative Models (GRM), to integrate with economic uncertainties (oil price, investment value, project start, etc.) and improved the decision making process of the project.In the risk methodology, many models are created and it is not viable to use all these models to integrate with other types of uncertainties. Therefore, some representative models are selected to continue the analysis. These models are selected based on the variation of net present value (NPV), oil production (Np), oil recovery (RF), water production (Wp), etc. The basic idea is to plot NPV (main objective function) against secondary objective-function (RF, Np, etc.) choosing models that are close to the values of P10, P50 and P90 that have significant variation in the other attributes. The adoption of this premise, which includes aspects of the amount and the speed of the recovery, is useful in sizing the later production facilities as well as in detailing the development plans and evaluating the flexibility of these plans. The adoption of this process as well as the use of an automated tool provided detailed information, contributing to the decision making process.
Innovated Simulation History Matching Approach Enabling Better Historical Performance Match and Embracing Uncertainty in Predictive Forecasting
Authors: Elrafie Emad , Agil Mohammed , Abbas Tariq , Idroos Boy , Colomar François-Michel 
Published: June 2009

Abstract
The purpose of the simulation history match phase in a study is to achieve a simulation model calibrated to historical performance for predictive production forecasting while preserving reservoir understanding in terms of reservoir characterization and fluid flow mechanisms. The classical history match simulation approach involves running a number of history match simulation cases with modified simulation model variables to obtain only one of the many probable match models to the field data.
Undoubtedly, the conventional simulation history match approach does not normally handle the uncertainty of all model variables, nor the possibility to identify and carry forward a set of multiple equi-probable history match model scenarios to predictive forecasting. Furthermore, the conventional history match approach lacks a rigorous mechanism to ensure that the original reservoir characterization and understanding is preserved after achieving only one of the many probable history match models.
This paper presents an innovative history match approach as part of Saudi Aramco's integrated "Event Solution1" study workflow. This approach was developed to enable faster simulation history match under uncertainty, in terms of static and dynamic variables. The history matching process is performed with the aid of assisted history matching software 2 that tracks the match quality of hundreds of history match cases and analyzes the impact of each variable and its range of uncertainty on model match quality to historical field data. Finally, a proxy (statistical History Match solution surface including all uncertainty variables) is created that combines model learnings to provide directional guidance to a most likely history match model design. As the history match process progresses, history match variables are characterized into three distinct categories; (1) critical variables to history match, (2) non critical variables to history match but with significant impact on prediction, and (3) non critical variables to history match but with less impact on prediction. The impact of the variables on prediction is concluded by concurrently running prediction runs under uncertainty. The uncertainty range of the variables categorized in groups (1) and (3) are set to a single realizations or narrower range of uncertainty for each variable while group (2) variables are carried forward with a more restricted range of uncertainty (defined by history match quality analysis) setting the stage for prediction under uncertainty modeling.
This paper presents the application of an innovative history match approach that provides all project stakeholders with a shared understanding of critical and non critical uncertainties (static and dynamic) in history match as carried forward to prediction runs under uncertainty.
Optimised Combined Underground Gas Storage and Enhanced Oil Recovery
Authors: Yanze Yannick , de Kok Joop , Clemens Torsten 
Published: June 2009

Abstract
The Schoenkirchen Tief reservoir is located in the Vienna Basin. The reservoir contained 19 mn m3 oil originally in place. The current recovery factor after 46 years of production is 59 %. The field was produced by water injection. The wells, located at the crest of the high relief structure are exhibiting a high water cut.
2006-2008, a comprehensive study was performed to optimise the future development of the field. The study showed that this field can be used for high performance Underground Gas Storage. Due to gas/oil gravity drainage, oil will be mobilised and can be produced resulting in enhanced oil recovery.
The field development of this fractured dolomite reservoir can be optimised by using vertical dewatering wells. Completing the vertical wells far down in the structure results in minimising gas coning and fast build up of the working volume of gas. To reduce water handling costs, these water wells will produce the water out of the reservoir into a highly permeable aquifer located above the reservoir. This means, no water will be produced to surface.
The drainage of oil in the matrix of this dual-porosity dual-permeability reservoir model is lagging behind the downward movement of the gas/oil contact in the fractures in this high relief reservoir. Once the oil rim reached the original oil/water contact in the matrix, horizontal wells can be drilled to produce additional oil.
Processes which had to be considered in this field development are the fracture-matrix interaction, hysteresis and fluctuations of the oil rim in the fractures during the gas cycles.
Temperature Modeling and Analysis of Wells with Advanced Completion
Authors: Muradov K. M. , Davies D. R. 
Published: June 2009

AbstractAdvanced completions using technologies such as Inflow Control Devices or Interval Control Valves are successfully optimising oil and gas production. They are often accompanied by the installation of Distributed Temperature Sensors and Permanent Downhole Gauges, providing continuous, real-time monitoring of the downhole pressure and temperature. Interpretation of such data to locate influxes and to track zonal inflow performance is an important step towards a comprehensive well and field control strategy.Interpretation of these downhole measurements requires accurate modelling of the well's pressure and temperature. Modelling of the pressures associated with the production of wells with advanced completion has been available for sometime. However, the workflow required for temperature modelling is not yet complete. This paper discusses using available theoretical models and software tools to model the temperature distribution in wells with advanced completion. The strengths and weaknesses of the various approaches for data interpretation will be discussed.Several methods for the quantitative interpretation of downhole temperature measurements are proposed. The application of both currently available and novel theoretical models will be discussed. The workflow will be shown to be capable of providing both zonal flow rates and phase compositions.The interpretation and analysis techniques presented here form the basis of a well and/or field monitoring and production control workflow.
Zonal Rate Allocation in Intelligent Wells
Authors: Muradov K. M. , Davies D. R. 
Published: June 2009

AbstractIntelligent well system technology enables continuous downhole monitoring and zonal production control. Knowledge of zonal multiphase rates in real time gives the ability to flexibly respond to changes in the well and reservoir performance; leading to recovery optimization, etc. Frequently, only pressure and temperature data are measured downhole. Solution of the zonal flow rate calculation problem solely on the basis of these values is possible using mathematical optimization methods along with soft-sensing tools.This paper presents a method of automatic zonal rate allocation for intelligent wells based on measured downhole pressure and temperature data. A group of mathematical optimization algorithms is used for the rate allocation at a particular time. The inverse problem is solved by matching the calculated, downhole pressure and temperature values with those measured (possibly with limited accuracy) at certain positions.A further step illustrates the application of soft-sensing methods to data measured in real-time. The potential for system parameter calibration and influx detection will be discussed. The resulting, zonal flow rate allocation techniques are tested on synthetic and real data, which illustrates their use as the basis of a comprehensive workflow for the control of intelligent wells and fields.
Well Test Analysis in Tight Gas Reservoirs
Authors: Borges Jose Umberto A. , Jamiolahmady Mahmoud 
Published: June 2009

Abstract
The increasing global energy demand, rising energy prices and declining conventional gas reserves all call for increasing exploitation of gas reserves from unconventional sources, most notably gas trapped in tight formations. This study describes an investigation of some of the key issues related to well test interpretation in tight gas condensate formations, which are often overlooked or ignored.
A single-well radial model was constructed with measured rock and fluid properties using ECLIPSE300. This compositional simulator was used to generate synthetic pressure transient data which were subsequently interpreted in PanSystem welltesting package. The impact of test duration (drawdown, buildup), phases present (gas, condensate), type of fluid system (lean, rich) and reservoir heterogeneity (homogeneous, layered) were investigated. The results indicate that in the absence of wellbore storage effects, a short drawdown period ensures that a short buildup is sufficient to compute reservoir parameters from radial flow regime. For long drawdown periods, the subsequent buildup period can take months to reach infinite-acting radial flow. The time needed to dissipate layering effects (such as a high-perm streak) is frequently excessively long in tight reservoirs.
Also, a number of simulations with and without rate-dependent relative permeability curves were performed to investigate the positive impact of velocity (coupling effect) on two-phase skin due to condensate banking. The results reveal that the conventional two-phase pseudo-pressure function results in more difficult interpretations for obtaining reservoir parameters and is also unable to capture the positive coupling, which is more pronounced than negative inertia especially for richer fluid systems. Finally, the application of the probe radius concept yielded remarkably accurate reservoir pressure profiles versus distance as compared to those obtained by compositional simulations. This data could be used to calculate reasonably accurate rate-dependent relative permeability curves, thus improving long-term well deliverability predictions.
Modeling Mud-Filtrate Invasion Effects on Resistivity Logs to Estimate Permeability of Vuggy and Fractured Carbonate Formations
Authors: Miranda Luis Javier , Torres-Verdín Carlos , Lucia Jerry 
Published: June 2009

Abstract
We develop and validate a new method to diagnose and estimate secondary porosity and absolute permeability of fractured and vuggy carbonate formations based on the numerical simulation of the process of mud-filtrate invasion. The method includes the geological characterization of core laboratory data and their integration with well logs and fluid production measurements. We apply the new method to the interpretation of data acquired in a carbonate reservoir in the Barinas-Apure Basin in southwest Venezuela. The latter reservoir behaves as a triple-porosity petrophysical system which exhibits inter-crystalline, intra-crystalline, moldic, vuggy (connected and non-connected) and fractured porosity, all embedded in a tight matrix. Rock-core data and wellbore resistivity images indicate that vugs are the mayor component of secondary porosity while fractures and interconnected vugs account for most of the permeability.
The initial phase of our interpretation method consists of integrating core measurements with conventional and non-conventional well logs to calculate static and dynamic petrophysical properties via standard carbonate evaluation procedures. Starting with the calculated petrophysical properties, we simulate the process of invasion with both water- and oil-base muds. Resulting spatial distributions of water saturation and salt concentration in the near-borehole region give rise to spatial distributions of electrical resistivity which are used to numerically simulate laterolog and induction apparent resistivity logs. If the input values of porosity and permeability are not correct, the simulation of mud-filtrate invasion will result in a poor match of resistivity logs. In such cases, we update porosity and permeability until securing a good match between measurements and simulations. This procedure was tested on several key wells with and without core measurements, wellbore resistivity images, and well-testing measurements. We conclusively find that our final estimates of porosity and permeability are in good agreement with the properties of the global petrophysical system. Differences between porosity and permeability before and after simulation of the process of invasion are reliable indicators of presence and influence of vugs and/or fractures in the displacement of hydrocarbons by mud filtrate.
Innovative Data-Driven Permeability Prediction in a Heterogeneous Reservoir
Authors: Al-anazi Ammal , Gates Ian , Azaiez Jalel 
Published: June 2009

Abstract
In complex reservoirs where heterogeneity of properties and errors associated with sampling yield uncertain measurements of geological properties, e.g. porosity and permeability, conventional techniques such as empirical and nonlinear regression methods attempt to estimate values of these properties with low or no error. Conversely, artificial intelligence asserts that the error contains useful information that complements conventional techniques. For example, fuzzy logic methods to predict permeability at uncored wells provide uncertainty measures based on secondary variables such gamma ray, neutron porosity, sonic porosity, bulk density, formation resistivity, and core-based permeability. Fuzzy logic provides tools for uncertainty modeling and improved permeability estimation.
Here, a two-stage fuzzy ranking algorithm is integrated in the fuzzy predictive model to improve generalization capability and transparency of the model through selecting inputs best suited to predict permeability. Fuzzy curve and surface analysis is used to rapidly and automatically identify information-rich well logs and filter out data dependencies. Subtractive clustering algorithm generates membership functions and isolates clusters of data. The Takagi-Sugeno-Kang fuzzy rule-based system (TSK) is constructed from a subset of logs and core measurements. The antecedent fuzzy sets are obtained by projecting the mean and variance onto input data axes. The consequent functions consist of a set of linear equations. To tune antecedent and consequent membership function parameters, an Adaptive Network based fuzzy inference systems (ANFIS) is used.
The proposed methodology is initially validates using the standard Box & Jenkins’ gas furnace data to predict C02 concentration and compared to a multilinear regression technique. Generalization capability has increased through using the most significant inputs during modeling gas furnace data. The methodology was also demonstrated by predicting permeability from well log data of a heterogeneous sandstone reservoir located in the Middle East. The fuzzy model was compared to conventional linear and multilinear regression models to show its applicability and superiority in heterogeneous systems. Unlike conventional methods, the proposed fuzzy technique does not require any prior knowledge of the reservoir and relationships between permeability and input variables. In addition, the technique accounts for uncertainty that exists in log data. The result is an efficient interpretation expert system that can be continuously conditioned as new data becomes available.
Enhanced Mass Transfer of CO2 into Water: Experiment and Modeling
Authors: Farajzadeh Rouhollah , Zitha Pacelli L. J. , Bruining Hans 
Published: June 2009

Abstract
Global warming has increased interest in quantification of the dissolution of CO2 in (sub)-surface water. CO2 is present above the surface water. Dissolution of CO2 into water (or oil) causes a density increase, with respect to pure water (or oil). This density effect causes natural convection, which enhances the mass transfer rate across the interface. This article describes a series of experiments performed in a cylindrical PVT-cell at a pressure range of pi=10-50 bar, where a fixed volume of CO2 gas was brought into contact with a column of distilled water. The results show that the mass transfer rate across the interface is much faster than predicted by Fickian diffusion. This mass transfer rate increases with increasing initial gas pressure and in the long term it is controlled by diffusion.
A theoretical interpretation of the observed effects has been proposed, based on diffusion and natural convection phenomena. The CO2 concentration at the interface is estimated from the gas pressure using Henry's solubility law, in which the coefficient varies with both pressure and temperature. Good agreement between the experiments and the theoretical results has been obtained.
Successful Multistage Hydraulic Fracturing Treatments Using a Seawater-Based Polymer-Free Fluid System Executed From a Supply Vessel; Lebada Vest Field, Black Sea Offshore Romania
Authors: Bukovac Tomislav , Belhaouas Rafik , Perez Daniel , Dragomir Alexandru , Ghita Viorel , Webel Carlos 
Published: June 2009

Abstract
Offshore operations are extremely expensive because of the operational environment and the necessary infrastructure. In this environment, emphasis is placed on high-efficiency operations based on specially tailored solutions combining available resources with new technologies. This results in a significant impact on operational efficiency by lowering costs and ultimately increasing hydrocarbon production.
To introduce greater efficiencies in offshore operations, a horizontal openhole candidate well was selected to be equipped with a permanent completion system that would enable multiple fracturing treatments. Later, it was determined that by using a novel viscoelastic polymer-free surfactant-based fluid, the entire operation could be performed in a single operation, adding additional savings to the process and improving efficiency.
Interpreted openhole images and advanced sonic logs were used to determine the optimum completion configuration and to select favorable fracture initiation points and treatment designs.
Because a specialized fracturing vessel tailored for operations in the Black Sea was not available, a supply vessel was used. The vessel had all required fracturing equipment rigged up and secured on decks.
To enable sufficient fracturing fluid volume for placing three propped fracturing treatments in a single pumping operation, a polymer-free fracturing fluid was formulated and mixed with seawater continuously.
This novel multistage fracturing system was introduced in Europe for the first time. Results indicate a sustained increased production. Because of this success, additional wells are scheduled to be stimulated using same approach in the following months.