bluuebunny/crossref_metadata_2025_split huggingface dataset:
Technology Focus: Production Monitoring (March 2021)
Authors: Mata Carlos 
Published: April 2021

Last year, events accelerated several trends in the energy landscape. Oil and gas prices have remained low, and the industry is focusing more strongly on reducing costs and increasing operational efficiency. Reducing costs is not only about cutting costs today but also about reducing the life-cycle cost per barrel. Implementing innovative technologies that increase recovery requires a small investment but can bring large rewards.
Advances in sensor accuracy, computing power, and data analytics unlock innovative use cases for technology for mapping subsurface movements of fluids. Very different technologies provide independent insights into the displacement process in the reservoir—for example, distributed acoustic sensing (DAS) used for periodic 4D seismic, time-lapse borehole microgravity surveys for 4D reservoir fluid mapping, DNA analytics to map interwell connectivity and zonal contributions, and interpreting downhole gauge pressure fluctuations caused by tidal forces to map fluid fronts.
The aggregation of these uncorrelated insights helps geologists and reservoir engineers narrow down the number of possible realizations of the reservoir model, better map bypassed resources, and provide forecasts that are more realistic.
On the production side, well instrumentation continues to become more affordable over time. For example: distributed temperature sensing, DAS, and downhole gauge lines can be run in a single optoelectric cable, which reduces well complexity and instrumentation costs. Wells can be instrumented at surface for less than $5,000 using wireless technologies. Wireless downhole gauges also can be retrofitted in older completions. There are many ways to leverage technology for improving production and reservoir monitoring and unlocking potential.
The OnePetro online library offers a large collection of novel use cases for technology and algorithms applied to production and reservoir monitoring. The challenge now is to transform the way we work to realize the maximum value from such technology.
Laboratory Formation Damage Test Data Upscaled With Computational Fluid Dynamics
Authors: Feder Judy 
Published: April 2021

This article, written by JPT Technology Editor Judy Feder, contains highlights of paper SPE 199268, “Upscaling Laboratory Formation Damage Laboratory Test Data,” by Michael Byrne, SPE, Lesmana Djayapertapa, and Ken Watson, SPE, Lloyd’s Register, et al., prepared for the 2020 SPE International Conference and Exhibition on Formation Damage Control, Lafayette, Louisiana, 19-21 February. The paper has not been peer reviewed.
Through several case histories, the complete paper demonstrates applications of computational fluid dynamics (CFD) modeling to upscaling of laboratory-measured formation damage and reveals implications for well and completion design. The value of laboratory testing is quantified and interesting challenges to conventional wisdom are highlighted.
Introduction
Laboratory formation damage testing is often used to help select optimal drilling and completion fluids. Test procedures such as sand retention and return permeability represent an attempt to simulate near-wellbore conditions during well construction and production.
To determine what degree of permeability impairment is allowable, further interpretation that cannot be provided using classical nodal analysis or reservoir simulation methods is required. The complete paper describes the evolution of, and potential for, more-comprehensive upscaling and outlines the importance of consideration of full well geometry when designing and interpreting coreflood tests for formation damage. CFD simulations provide a means to upscale suitable laboratory test data to predict effect on well performance.
Methods
CFD simulations use a relatively simple, steady-state, static damage model that takes endpoint data from laboratory core tests and translates the data into parameters that are used for input into well geometry. Although this method has its merits and is a considerable advance on previous, more-simplistic upscaling attempts, it does not necessarily present the full picture of damage evolution in the near-wellbore. A transient model of damage with data again derived from laboratory coreflood data could reveal more about well cleanup and progressive damage removal.
Steady-State Modeling. No API recommended practice for return permeability testing exists. Laboratories have their own procedures that comply broadly with recommended procedures developed some time ago. Operators and consultants, too, have their own procedures, which they often ask laboratories to follow. Although no recommended practice exists, evaluation of drilling and completion fluids usually involves measurement of a base permeability and remeasurement of a return permeability—or several—after application of the test fluid or fluids. In many cases, the laboratory removes the external mud cake or trims a slice of the end of the plug to measure return permeability without mud cake (Fig. 1).
In-Situ Combustion Frontal Stability Analysis
Authors: Zhu Zhouyuan , Liu Yanni , Liu Canhua , Kovscek Anthony R. 
Published: April 2021

SummaryBecause of complex chemical reactions and multiphase flow physics, the displacement front stability for in-situ combustion (ISC) enhanced oil recovery (EOR) processes are not well understood. In this work, theory and numerical simulation validation are presented to establish an analytical frontal stability criterion for ISC processes.First, the four influencing factors for ISC displacement stability are analyzed: viscous force, heat conduction, matrix permeability changes caused by coke deposition, and gravity. A thorough analysis of the different zones and displacement fronts in a typical ISC process is conducted, and the most unstable front with the strongest tendency for gravity override is identified. Second, analytical solutions for judging the frontal stability and gravity override are established. Third, numerical reservoir simulation is performed to study the frontal stability and gravity override to validate the analytical theory. Carefully selected numerical schemes, as well as spatial and temporal discretization, are used to ensure the accuracy of these simulations.The four major zones and three displacement fronts (combustion front, leading edge of steam plateau, and oil bank leading edge) are identified in a typical 1D ISC process. The most unstable front with the largest pressure gradient contrast is the leading edge of the steam plateau. Gravity override also first takes place here with large fluid density differences across the front. By establishing material and energy balances and solving the wavy perturbation of the steam front, an analytical equation for deciding the ISC flood front stability in a 2D horizontal plane is achieved. Furthermore, the analytical solution for ISC gravity override is established. In numerical simulations, we are able to obtain results with sufficient accuracy to capture unstable ISC displacements and show fingering behavior under different conditions. The matrix permeability reduction caused by coke deposition has minimal impact on frontal stability. The simulation results are successfully validated with the analytical work for conditions in which the ISC process is stable or unstable and also for the degree of ISC gravity override. This demonstrates the predictive capability of the analytical method.In summary, a theoretical framework to analyze whether the displacement front of an ISC process is stable or not has been established. Numerical simulations confirm its predictive capability. This serves as a new reservoir engineering tool to aid the implementation and design of practical ISC projects.
Preparation of fluorescent beads under C. elegans for fluorescence microscopy with adaptive optics
Authors: Lin Ruizhe , Kipreos Edward T. , Kner Peter 
Published: April 2021

Abstract
We describe a protocol for the preparation of a sample of fluorescent beads under C. elegans. This type of sample is useful for research into the use of adaptive optics to correct sample-induced optical aberrations in fluorescence microscopy.
Efﬁcacy and Safety of Nepa in Preventing Nausea and Vomiting Induced by Multiple-day Chemotherapy in Patients With Refractory/relapsed Aggressive Non-hodgkin’s Lymphoma Undergoing Stem Cell Mobilization Prior to Autologous Hematopoietic Stem Cell Transplantation
Authors: Renzo Nicola Di , Musso Maurizio , Scimè Rosanna , Cupri Alessandra , Perrone Tommasina , De Risi Clara , Pastore Domenico , Guarini Attilio , Mengarelli Andrea , Benedetti Fabio , Mazza Patrizio , Capria Saveria , Chiusolo Patrizia , Cupelli Luca , Federico Vincenzo , Bozzoli Valentina , Messa Anna Rita , Matera Rosella , Seripa Davide , Codega Paolo , Bonizzoni Erminio , Specchia Giorgina 
Published: April 2021

Abstract
PurposePrevention of chemotherapy-induced nausea and vomiting (CINV) is particularly challenging for patients receiving highly emetogenic preparative regimens before autologous stem cell transplantation (ASCT) due to the daily and continuous emetogenic stimulus of the multiple day chemotherapy (MD-CT). While studies have shown effective prevention of CINV during the conditioning phase with NK1 receptor antagonist (NK1RA)-containing regimens, there have been no studies evaluating antiemetic use with MD-CT administered for mobilization of hematopoietic stem cells prior to ASCT. MethodsThis multicenter, open-label, phase IIa study evaluated the efﬁcacy of every-other-day dosing of NEPA administered during MD-CT being given for mobilization of stem cells prior to ASCT in patients with relapsed-refractory aggressive non-Hodgkin’s lymphoma. Eighty-one patients participated. ResultsResponse rates were 77.8% for complete response (no emesis and no rescue use), 72.8% for complete control (complete response and no more than mild nausea), 86.4% for no emesis, and 82.7% for no rescue use during the overall phase (duration of MD-CT through 48 hours after). NEPA was well tolerated with no treatment-related adverse events reported. ConclusionNEPA, administered with a simplified every-other-day schedule, show to be very effective in preventing CINV in patients at high risk of CINV undergoing MD-CT for mobilization of hematopoietic stem cells prior to ASCT.
Predicting ground subsidence due to long term oil/gas production in a Niger Delta basin, Nigeria: implications for CO2 EOR and geosequestration
Authors: Abija Fidelis Ankwo , Abam Tamunoene. K. S. 
Published: April 2021

Abstract
Reservoir pressure depletion with production leading to porosity loss, compaction and surface subsidence are the effect of effective stress changes and the imposition of the overburden stress which was partly supported by the fluids on the rock grain skeleton. Ground subsidence is associated with environmental hazards, failure of operational facilities and damages to infrastructures amounting to huge economic losses. In this studies, subsidence has been assessed using the Geertsma nucleus of strain based on predicted reservoir pressure. Depletion was estimated as percentage pore pressure dissipation and dynamically derived geomechanical and petrophysical rock properties determined. Reservoir porosity vary from 15% – 32%, shale volume from 11.2% − 88%, bulk compressibility range from 2.52–2.53 x 10− 6 /mPa, and uniaxial compaction coefficient 1.15–1.8 x 10− 6/mPa. The vertical compaction in a typical reservoir interval with a thickness of 31.0m varies from 0.002mm to 0.05mm at 10% formation pressure depletion, − 0.005mm to 0.27mm at 50% formation pressure drawdown and 0.007 to 0.53mm at 99% production and reservoir pressure dissipation. surface subsidence would range from 0.045mm to 0.35mm at 10% pressure depletion, 0.058mm to 1.8mm at 50% pressure depletion and 0.045mm to -3.47mm at full reservoir pressure drawdown. At a distance of 92.45km from the Niger Delta coastline, subsidence in the oilfield can still spread to the coastline, the deformation causing damages to the environment, operational facilities and infrastructures that amount to huge economic losses to the operators and government. We recommend the use of CO2 in EOR to maximize production, mitigate subsidence through ground rebound and keep carbon securely sequestered.
Antibacterial potential of new active compounds with biological performances with drugs modeling of pharmacokinetics study as source of bacterial drugs manufacture process and preparations
Authors: ahmed waseem , Azmant Rafia , Qayyum Abdul , Khan Shah Masaud , Ahmed Rasheed , Naz Saima 
Published: April 2021

Abstract
Adhatoda vasica and Calotropis procera was popular plants for its traditional medicinal materials as treatment of many bacterial diseases and skin disorders the class of group of chemicals were present in these medical plants as used of various medicines the new bioactive compounds as sources of various medicines the currently study was aim to obtained the higher antibacterial resilient biomolecules were measured through several advanced analytical techniques. The results showed that methanolic extracts and supercritical fluid extraction methods were best for higher yield of new compounds measurement process, after extraction the four structural compounds b-Sitosteryl linoleate, Myristyl diglucoside, D-Triglucopyranoside and S-allylcysteine acid were isolated in herbal plants, while the complete HPLC-DAD analyzed process with accuracy ,precision inter and intraday process all four compounds were done. The new drug design with apply of compartmental modelling of pharmacokinetics were apply on these four compounds check their potential level and capacity of measurements. The cytotoxicity test was analyzed in both plants at three concentrations (1, 0.4 and 8) in which 0.4 % showed the higher activity of LD which was 8 % in Calotropis procera extracts. The best activity of LD was recorded in methanol extracts over other six solvents (Methanol, Ethyl acetate, Chloroform, Hexane, Aqueous, and Ascorbic acid). It was concluded that the both species may act as the best resources of medicines in future uses an efficient and precise combinatorial quantitative analysis method and provided insight into the chemical constituents and development of various antibacterial drugs and explore this medical plants
Using Transfer Learning for Diabetic Retinopathy Stages Classification
Authors: Houby Enas M.F. El 
Published: April 2021

Abstract
Purpose – Diabetes is a chronic disease, that leads to damage of many systems of the body. One of the dangerous complications of diabetes is diabetic retinopathy. Frequent inspection for diabetic retinopathy is essential to recognize patients at risk of visual impairment. The disease grade level must be tracked to manage its progress and to start the appropriate decision for treatment in time. Effective automated methods for the detection of diabetic retinopathy and the classification of its severity stage are necessary. It also helps to decrease the burden on ophthalmologists and reduce diagnostic contradictions among manual readers. Methods– In this research, a convolutional neural network (CNN) is used based on color retinal fundus images for the detection of diabetic retinopathy (DR) and classification of its stages. CNN can recognize sophisticated features on the retina and so provide an automatic diagnosis. The pre-trained CNN model Visual Geometry Group (VGG) is applied on DR data using a transfer learning approach to utilize the already learnt parameters based on 1,000,000 images of ImageNet with 1000 classes.Results – By conducting different experiments with different classes setting the built models achieved promising results. The best achieved accuracies for 2-ary, 3-ary, 4-ary, and 5-ary classification are 85.99, 80.5, 61.28, and 71, respectively.
Optimized MLCNN for Personalized News Recommendation Based on Social Media Harnessing Using Modified Genetic Algorithm
Authors: Manoharan Saravanapriya , senthilkumar radha , J Saktheewaran , A Kannan 
Published: April 2021

Abstract
Classification of label-specific users’ diversified interests is the most formidable task in personalized news recommendation systems (PNRS). To bring personalization to PNRS, many remarkable features have to be considered from their user profile to classify their interest. In this paper, 13, 346 features are considered per user to classify their interest for 15 labels using Multi-label Convolution Neural Network (MLCNN). The efficiency of MLCNN highly depends on its architecture through the tuning of its hyper parameters. Generally, researchers have manually designed a constant CNN architecture for each label and every label and verified the effectiveness, but this leads to additional complexity as well as large computational resources were consumed. Moreover, Designing the structure for all 15 labels leads to an increase in network structure exponentially with an increase in labels. Hence, in this paper, MLCNN architectures are optimized by implementing a novel approach Modified Genetic Algorithm (MGA) with the help of introducing four novel crossover operators to strengthen CNN performance for users interest classification. Further, for the recommendation process, the label-specific news articles were clustered from social media Facebook and Twitter feeds, and then most popular news articles were determined along with label-specific breaking news articles rendered from news feeds concerning users’ interest. The experimental result precisely proves that the proposed approach MGA attained an accuracy of 89.64%, 90.56%, 90.41%, and 91.79% for classifying users label specific interest and label-wise recommendation accuracy attained 93.3%, 90%, 90% from Twitter, Facebook, and also from Newsfeed respectively.
Conditional Survival After Surgical Resection of Appendiceal Tumors: a Population-based Study
Authors: Zhao Shutao , Lu Chang , Li Junan , Zhang Chao , Wang Xudong 
Published: April 2021

Abstract
Background: This study aimed to evaluate the conditional survival (CS) of appendiceal tumors (ATs) after surgery.Methods: A total of 3,031 patients with ATs who underwent surgery were included in the Surveillance Epidemiology and End Results (SEER) database from 2004 to 2016. A multivariate Cox regression model was used to analyze the prognostic factors affecting overall survival (OS) and cancer-specific survival (CSS). CS was used to calculate the probability of survival for another 3 years after the patient had survived x years. The formulas were COS3 = OS (x + 3) /OS (x), and CCS3 = CSS (x + 3)/CSS (x).Results: The 1-year, 3-year, and 5-year OSs for all patients were 95.6%, 83.3%, and 73.9%, respectively, while the 1-year, 3-year, and 5-year CSSs were 97.0%, 87.1%, and 79.9%, respectively. Age, grade, histology, N stage, carcinoembryonic antigen (CEA), and radiation were independent prognostic factors for OS and CSS. For patients that survived for 1 year, 3 years, and 5 years, their COS3s were 81.7%, 83.9%, and 87.0%, respectively. The CCS3s were 85.5%, 88.3%, and 92.0% respectively. In patients with poor clinicopathological factors, COS3 and CCS3 increased significantly, and the survival gap between OS and COS3, CSS and CCS3 was more obvious.Conclusions: CS for appendiceal tumors were dynamic and increased over time, especially in patients with poor prognosis.
A Design Approach Of Mechanical Assemblies Based On MBSE And CAD Models Interoperability
Authors: Brahmi Rihab , Belhadj Imen , Hammadi Moncef , Aifaoui Nizar , Choley Jean-Yves 
Published: April 2021

Abstract
The technological development of the last decades have been able to push human to develop their needs, so a way to new demands were opened and this can lead to a complexity problem. Thereby, a good interoperability between the product design activities can lead to the possibility of ensuring a promising satisfaction to all requirements. However, the major problem is the enormous discontinuity between them. Indeed, each one treats the product from its point of view without recourse to the requirements defined by others. This paper is interested in the collaborative work that brings together the system engineer, who deals with the system from a global view, and the designer, who is a specialist in the detailed design, in order to validate requirements. A new methodology has been proposed to define the role of each one in the design process. This methodology focuses on the product development cycle from the analysis of needs to the validation phase. This obviously requires interoperability between the two domains of Model Based System Engineering (MBSE) and Computer Aided Design (CAD). Based on a pedal bicycle case study which is an industrial mechatronic product, the proposed methodology will be illustrated for validation and highlighting its advantages and limitations.
Atomistic mechanisms for frictional energy dissipation during continuous sliding
Authors: Krylov Sergei , Frenken Joost 
Published: April 2021

Abstract
From a first-principles-based analysis, atomistic mechanisms of frictional energy dissipation are established. For a rigid object moving continuously in the periodic surface potential landscape of a solid that has vibrational degrees of freedom, they can be viewed as (i) the continuous pumping of energy into the resonant modes, if these exist, and (ii) the destructive interference of the force contributions introduced by all excited phonon modes. We report a surprising, mutual compensation between these two basic effects, which leads to very regular oscillations of the dissipative force, with a period determined by half the period of the solid lattice, while the mean friction force experienced by the sliding object hardly depends on time and varies in a straightforward manner with the sliding velocity. These mechanisms act already in a purely dynamic system that includes independent, non-interacting phonon modes, and they manifest irreversibility as a kind of "dynamical stochastization". In contrast to wide-spread views, we show that transformation of mechanical energy into heat, that always takes place in real systems due to the coupling between phonon modes, can play only a minor role in the appearance of friction, if any. This insight into the microscopic mechanisms of energy dissipation opens a new, direct way towards true control over friction.
Segmentation of Biventricle in Cardiac Cine MRI via Nested Capsule Dense Network
Authors: Hu Yuhang , Zhang Yajuan , Zhang Hongyang , Shen Weihao , Zhou Shoujun , Guo Shijie , Wang Yuanquan 
Published: April 2021

Abstract
Cardiac magnetic resonance image (MRI) has been widely used in diagnosis of cardiovascular diseases because of its noninvasive nature and high image quality. The evaluation standard of physiological indexes in cardiac diagnosis is essentially the accuracy of segmentation of left ventricle (LV) and right ventricle (RV) in cardiac MRI. In this paper, we propose a novel Nested Capsule Dense Network (NCDN) structure based on the FC-DenseNet model and capsule convolution-capsule deconvolution. Different from the traditional symmetric single codec network structure such as U-net, NCDN uses multiple codecs instead of a single codec to achieve multi-resolution, which makes it possible to save more spatial information and improve the robustness of the model. The proposed model is tested on three datasets that includes York University Cardiac MRI dataset, Automated Cardiac Diagnosis Challenge (ACDC-2017), and local dataset. The results show that the proposed NCDN outperforms the state-of-the-art methods.