bluuebunny/crossref_metadata_2025_split huggingface dataset:
Oil Droplet Removal from Produced Water Using Nanoparticles and Their Magnetic Separation
Authors: Ko Saebom , Kim Eun Song , Park Siman , Daigle Hugh , Milner Thomas E. , Huh Chun , Bennetzen Martin V. , Geremia Giuliano A. 
Published: September 2016

Abstract
The removal of highly stable dispersed oil produced during oil recovery processes is very challenging, especially in offshore operations where the limited space does not allow use of equipment with long residence time for the required separation. Using magnetic nanoparticles (MNPs) to remove the dispersed oil from produced water is a promising way to overcome the difficulties that the current treatment technologies face, since the MNPs-attached oil droplets can be quickly and efficiently separated with application of an external magnetic field. The MNPs can be also regenerated and reused, minimizing the generation of hazardous waste. We investigated not only the optimal operating conditions, such as MNP concentration and salinity, but also the mechanisms of MNPs-oil attachment and magnetic separation.
We synthesized MNPs in the laboratory with a prescribed surface coating. The MNPs were superparamagnetic with an average individual particle size of ~10 nm. Crude oil content in separated water was reduced by as much as 99.9% using MNP concentrations as low as 0.04 wt% in 5 minutes after MNPs and oil were reacted.
The electrostatic attraction between negatively charged oil-in-water emulsions and positively charged MNPs controls the attachment of MNPs to the droplet surface; and the subsequent aggregation of the electrically neutral MNPs-attached oil droplets plays a critical role for accelerated and efficient magnetic separation. The particle aggregation occurred fast, generally within one minute. Thus, the total magnetic separation time was dramatically reduced to as short as 1 second, contrary to that of free, individual MNPs where it took about 36~72 hours, depending on the MNP concentrations.
Model calculations of magnetic separation velocity, accounting for the MNP magnetization and viscous drag, show that the velocity of free Amine functionalized MNPs (A-MNPs) increases about 1~3 orders of magnitude as the particles get closer to the magnet depending on the particle size. The smaller the particles, the greater the effect of the magnetic field on the velocity. A typical operating condition would be when the size of the MNPs-oil droplet aggregates is grown to be greater than 360 nm. Then, the total magnetic separation time will be approximately 5 minutes.
Wellbore Stability Analysis Based on Sensitivity and Uncertainty Analysis
Authors: Niño Fernando Antonio 
Published: September 2016

Abstract
A methodology based on sensitivity and uncertainty analysis is presented for performing a wellbore stability analysis in order to quantify model uncertainty and improve the predictions made. This methodology is applied to the safe mud window design for a study case.
A wellbore stability model is set up, as of constitutive equation and failure criteria selection. Based on available data, a stochastic approach is used to assess the uncertainty associated to input parameters, or otherwise other alternatives like expert opinion are utilized. Secondly, a sensitivity analysis is carried out by means of OAT and RSM methods displaying results on tornado and spider diagrams. Finally, an uncertainty analysis is performed using Monte Carlo simulations for quantifying uncertainty in model outputs and obtaining the required mud weight to drill successfully as a probability function.
Four approaches for assessing uncertainty in input data of wellbore stability models are presented. Sensitivity analyses showed maximum horizontal stress and cohesion as the most critical parameters in collapse pressure determination while minimum and maximum horizontal stresses were the major variables in fracture pressure evaluation. On other hand, vertical stress and Poisson ratio were considered as constants during the uncertainty evaluation due to their subtle impact in model results. Ultimately, an uncertainty analysis is presented via probabilistic graphs, which enables a better decision making since uncertainty in input data is considered and safe mud window is obtained as a probability function of drilling successfully.
The workflow proposed makes up a complete uncertainty study useful for developing wellbore stability analyses which optimizes the decision making in drilling process design. Aspects like evaluation of input data uncertainty and incorporation of sensitivity analyses are novel components for complementing the simulation Montecarlo as uncertainty analysis method and risk analysis tool.
Development of Software Application for Optimization of Primary Cementing Operations Using Visual Basic
Authors: Chaudhry Abdul Manan 
Published: September 2016

Abstract
Scientific software development is a multi-step process, involving good understanding of the mathematical model, development of an algorithm and subsequently its implementation as a computational code.
Using these methodologies an open source Cementing Operations software library has been coded. A software application "Cementing Operations Calculator" has been developed over this library, which efficiently provides solutions for primary cementing operations.
The software helps in selecting optimum parameters for primary cementing operations such as Displacement Volume, Lead Slurry Total Volume, Tail Slurry Total Volume, Lead Slurry Composition (quantity of cement & cement additives), Tail Slurry Composition (quantity of cement & cement additives), Lead Slurry Composition (Dead Volume), Tail Slurry Composition (Dead Volume) and finally the Chemicals required for performing the primary cementing operations job.
A number of geoscientific computational libraries are available in the public domain which have been initiated by various universities and developed and maintained by a large community of developers. Keeping in view the same trend, there is a need for developing open source libraries for petroleum engineering. Thus the aim of this research is to provide open source code which is publicly available to the others to enhance and incorporate new functionality. In addition the software tools are also publicly available which can be used by students and researchers for analysis of their data. The use of the software is demonstrated with real field data examples.
Adaptive Grid Refinement Improves Gas Injection Modeling
Authors: Gonzalez Karin G. 
Published: September 2016

Abstract
This paper introduces a new method to create adaptive mesh refinement and coarsening in compositional reservoir simulation. The methodology targets individual cells for refinement based on forecasted compositional fronts calculated using streamlines and the analytical convection-dispersive transport equation. Quadtree decomposition determines the optimal spatial discretization across the simulation grid using dynamic and static reservoir properties. Application of the new approach results in improved computational performance and better representation of complex fluid behavior.
Current dynamic gridding implementations have rigid schemes, posing two major limitations: cell refinement size is a pre-determined input value and compositional maps from the previous time step define the refinement region. This solution leads to suboptimal modeling due to time-lagging refinement and lack of grid adaptability in heterogeneous reservoirs and/or fast-moving compositional fronts. The new methodology overcomes these limitations by combining streamline and particle trajectory to forecast the injection front location and adapt grid sizes in advance.
Tracking compositional variations starts by calculating fluxes for all cells using the finite-difference solution. Next, Pollock's tracing method allows reducing the 3-dimensional model into a series of 1-dimensional streamlines, while the convection-dispersive equation forecasts future compositions, shape, and location of injection front along each streamline trajectory. Finally, quadtree decomposition analyzes the homogeneity of dynamic and/or static properties (e.g., composition, pressure, permeability, facies) to determine if a volume can be represented by a single gridblock or if it requires refinement to preserve spatial details. Grid discretization is dynamic over time, refining cells requiring high-resolution and/or coarsening those with low variation.
A mechanistic model with CO2 injection served to evaluate the methodology. The fluid was modeled with five pseudo-components and the Peng-Robison equation of state with volume translation to improve volumetric predictions. The new approach reduced the total number of cells required to model miscible injection by continuously creating adaptive grids that represent the advancement and shape of the injection front. Results showed a reduction in computational cost between 30-63% over a static fine grid without compromising the representation of compositional mixing phenomena and production forecast.
3-D Reconstruction of Porous Media and Rock Characterization
Authors: Naraghi Morteza Elahi 
Published: September 2016

Abstract
The transport and elastic properties of a rock are functions of the pore size distribution, geometry and morphology. Due to limited availability of 3-D micro-structure images of rocks, several attempts to theoretically model the behavior of rocks have been made. However, all such methods have limitations. In addition, 3-D micro-structure images of rocks, even if available, represent only a small volume of the rock, and the predictions of macroscale properties based on them are uncertain. In this study, a new stochastic method to reconstruct a 3-D model for the rock using only a 2-D section of the imaged rock sample is proposed. The proposed method is a combination of a multiple point statistics simulation, gradual deformation of images, and calculation of transport and elastic properties. The first step is to generate multiple independent realizations by performing multiple-point statistics based stochastic simulations. These simulations represent independent 2-D scans through the rock volume. Next, a succession of images is generated spanning two adjacent independent sections. These images are generated so as to gradually morph features from one section to those in the next independent section. These 2-D images are then stacked together to reconstruct the 3-D image.
After reconstruction, transport and elastic properties of the reconstructed image are computed. For a test case for which the measured rock properties are available, the results obtained using the reconstructed image reveal that the calculated properties are close to the measured values. Finally, we generated multiple realizations with different porosity values, where the shape of pores and grains are preserved. We studied the sensitivity of the elastic properties to the porosity of the samples. The results provide insights on the effect of cementation or increased overburden pressure on flow and mechanical properties of rocks.
Capturing Complex Reservoir Heterogeneity in a Field Under Water Injection – A Case Study of a Niger Delta Field
Authors: Nanaghan Karena O. 
Published: September 2016

Abstract
Structural heterogeneity is one of the critical factors that can affect a reservoir's performance, properties and thus, its ultimate recovery. With the decline in oil price and continuous drive for cost optimisation, understanding the impact of such features on reservoir behaviour in terms of pressure communication, fluid movement, production and well placement becomes paramount.
In this research paper, the main study subject is a compartmentalised reservoir in a mature Niger Delta field undergoing water injection. Two blocks in the reservoir separated by a fault mapped from the seismic which was believed to be non-sealing as initial pressure data acquired from both blocks through aRepeat Formation Test(RFT) were similar; suggesting that these blocks were in hydraulic communication.
Production started from the western block in 2001, and after few years of production, a significant drop in reservoir pressure was observed. To arrest this pressure decline, water injection into the reservoir commenced in 2011. After four years of injection, a substantial increase in reservoir pressure was observed as confirmed from static bottom hole pressure surveys from existing wells in the block.
With the successful implementation of pressure maintenance and oil being swept updip structure as suggested by the history matched reservoir model, infill well opportunities were identified in the western and eastern parts of the A block. In order to properly land these wells, reduce production uncertainty and ensure its successful production, a pilot hole was drilled into these blocks to ascertain current fluid contacts and reservoir pressure. Information from the RFT was however surprising as reservoir pressure in the eastern block was found to be significantly depleted contrary to expectations; as similar pressure with the western block was expected since there was no producer in this block.
This paper describes how an integrated approach resulted in significant cost saving and how an analytical tool like the multi tank material balance methods was used to effectively characterise a complex reservoir under water injection and revise the field redevelopment plan.
An Extension of Johnson, Bossler and Neumann JBN Method for Calculating Relative Permeabilities
Authors: Abbas Mamudu 
Published: September 2016

Abstract
The Johnson, Bossler and Neumann (JBN) method is the industry standard for measuring relative permeabilities from field cores. Mitigating the numerical errors resulting from the numerical differentiation required by the method has been an area of interest over the years. There have been several modifications of this technique by many researchers in order to improve the results. Some of the researchers have used curve fitting and graphical approach. However, till date, the application of a numerical modeling technique to do the necessary numerical differentiation of the data required by the JBN method for improved results is yet to be established.
This paper presents the application of cubic spline numerical modeling technique (CSNMT) on JBN method. Production data from field cores were used. The JBN technique was initiated procedurally. The necessary numerical differentiation of the production data required by the JBN method was done with cubic spline numerical modeling technique (CSNMT). Tridiagonal system of equations was formed and resolved. Different and continuous equations (polynomials) were derived for the contiguous intervals and then differentiated accordingly. The procedure was then accomplished.
The technique shows good results which are close to those obtained when the numerical differentiation is done the traditional way, using an expression for an unequally spaced data gotten from the numerical differentiation of a second-order langrage interpolating polynomial for three data points. However, because of the oscillations induced and the difficulty in handling higher order polynomials numerically which leads to the use of second-order langrage interpolating polynomial instead of a polynomial of order one minus the number of the data points required, the results from the use of CSNMT are more reliable. In addition, the profiles of the production data are modeled in CSNMT. The reduction in the overall numerical error was reflected by the differences in the relative permeability values obtained by both approaches.
Hierarchical Geological Realism for Reliable Reservoir Predictions
Authors: Kuznetsova Alexandra 
Published: September 2016

Abstract
In the current oil price situation it is particularly important to improve the reliability of reservoir forecasts to make better field development decisions. The great challenge of reservoir modelling is to account for geological uncertainty to increase reliability of the predictions.
The aim of this paper is to explore and answer three important questions that tackle this challenge and affect reservoir predictions.
The first question is: to what extent does geological realism matter to reservoir predictions? To estimate the value of geological realism to reservoir predictions we introduce hierarchical geological realism into facies modelling. It allows us to account for geological realism at three different levels: 1) multiple possible geological concepts, 2) geological consistency of each geological concept, 3) geologically realistic relations of model parameters, such as: geobodies dimensions and facies proportions. Implementation of multiple possible geological concepts allows us to include interpretational uncertainty for more realistic predictions.
The second question is: how to maintain geological realism during model update? Automated history matching requires model updates to achieve a good match between observed and simulated data. Geological realism can easily be lost during a model perturbation whilst history matching. We aim to maintain geological realism through model the update process by using a metric space approach. Classification of models in the metric space provides geologically realistic differentiation between multiple possible geological concepts. The result of the classification allows us to predict a geologically realistic model description through the model update process.
Finally, we ask: can geological realism improve the reliability of the forecast? To answer this question we test the hierarchical approach in automated history matching on a West Coast of Africa reservoir. The results validate the choice of geological scenario and improve the reliability of the forecast.
Dynamic Hybrid Modelling Framework for Resources Management in Exporting Under-Developed and Developing Nations
Authors: Echendu Joseph C. 
Published: September 2016

Abstract
Most reserves growth models have focused on mature fields in developed nations. Consequently, the direct application of such models to under-developed and developing nations with perceived maturing fields becomes challenging as the fundamental assumption in existing model formulations do not apply and are violated. The resultant resource management policies thus fail to meet the yearnings and aspirations of many under-developed and/or developing petroleum-dependent economies.
This work bridges this gap using the formulation of a hybrid model that captures the peculiarity of under-developed and developing nations with attendant maturing field, towards their resources management. The modelling framework entails a hybrid of discovery-process, econometrics, and discounted cash flow approaches. However, for the purpose of this paper, policy application of the latter is the focus.
Discounted Cash Flow (DCF) model framework adopted in this paper; is used to evaluate and investigate the impacts of volatility of oil price on oil and gas development economics using conventional, linear and logarithmic scales' fiscal policy schemes. Economic performance indicators such as Internal Rate of Return (IRR), Profitability Index (PI), and Take statistics are incorporated to evaluate investment performance. Sensitivity simulation approach is also incorporated to investigate its impact on decision variables. The overall aim is mitigating associated economic and technical risks in the highly risky and capital intensive oil and gas industry during low oil price regime.
This paper recommends that resources utilization emphasis should be geared towards value addition by providing incentives that encourages more investment domestically, thereby opening up opportunities for its citizenry. Paradoxically, incentivizing and delaying gratification that encourages investments tend to yield approximate economic performance metrics as perceived regressive fiscal terms that would not encourage upstream E&P investments, ceteris paribus.
Analysis of Production Rates of a Gas Well Using Computational Fluid Dynamics and Rate-Dependent Pseudo-Skin Factor
Authors: Molina Oscar 
Published: September 2016

Abstract
This paper investigates the impact of high-rate production on well performance of a cased-hole gas well with a fracpack type of completion. We modeled fluid dynamics in the near wellbore region, where the most drastic changes in pressure, velocity and temperature are expected to occur, using a computational fluid dynamics approach.
Fluid flow modeling was based on Navier-Stokes equations coupled with Forchheimer equation, which enabled us to study inertial and turbulence effects in regions where velocity suddenly increases and then decreases in the same way in a relatively small length scale. In addition, gas properties were incorporated into the momentum balance equation via the Soave-Redlich-Kwong equation of state. Simulations were pressure-driven at steady-state and isothermal conditions so that external pressure was kept constant and pressure at the wellbore was varied to generate the well performance curve for the simulation model.
The concept of rate-dependent pseudo-skin factor was then introduced as a tool to assess the level of nonlinearity caused by inertial and turbulence kinetic energy losses at different pressure drawdowns. Analysis of simulation results showed that rate-dependent pseudo-skin went from a negative value at low rates to positive at medium-to-high producing rates. This is because inertial and turbulence effects were negligible at low superficial velocity, hence negative skin factor of completion prevailed, while the opposite happens at high superficial velocity. Therefore, we hypothesize that optimum operating condition of a well is at the maximum possible flow rate at which inertial and turbulence kinetic energy losses are minimum; we found this condition coincides with the well flowing condition at which the rate-dependent pseudo-skin is zero.
The Triple Aim and its Implications on the Management of Chronic Rhinosinusitis
Authors: Barry Jonnae Y. , McCrary Hilary C. , Kent Sean , Saleh Ahlam A. , Chang Eugene H. , Chiu Alexander G. 
Published: September 2016

Introduction Accountable care organizations (ACO) and alternative payment models are a sign of the change in reimbursement from fee-for-service to value-based reimbursement. The focus of health care under ACOs is represented by the Triple Aim: to improve the experience of health care, improve the health of populations, and reduce the per capita costs. Individuals with chronic rhinosinusitis (CRS) are heavy consumers of health care services. Results of recent studies have indicated that there is the potential for improved outcomes and cost savings from early surgical intervention. Adhering to the principles of the Triple Aim may signal a paradigm shift in regard to timing of intervention for CRS in certain patients. Methods A scoping review was performed to analyze the current literature related to management of CRS and the impact on cost, population health outcomes, and the patient's experience of health care. Results A growing body of literature indicates that, in appropriately selected patients, when compared with medical management, endoscopic sinus surgery has the potential to improve patient outcomes and reduce the long-term cost burden of CRS. Conclusion With the advent of ACOs, a paradigm shift in the treatment of CRS is inevitable to better conform to the goals of the Triple Aim. Future treatment algorithms will need to account for the heterogeneity within CRS and seek to identify appropriate timing and interventions for patients on an individual basis if the value of health care is to be improved.