bluuebunny/crossref_metadata_2025_split huggingface dataset:
Machine Learning Image Analysis for Asset Inspection
Authors: Hayward Nick , Portugal Marta 
Published: August 2019

Abstract
Total E&P UK Ltd and Merkle have undertaken a proof of concept project to investigate machine learning image analysis applied to image and video data from onshore and offshore sites, in preparation for the deployment of an autonomous asset inspection ground robot in 2019. The aim is to better understand the feasibility of these methods, and to demonstrate the benefits of robotic inspection with regard to improving safety and efficiency, enhancing data capture and reducing operational costs.
An object detection model was developed based on high-performance open source algorithms. Transfer learning was applied using a custom-built image library and the result is a model able to detect a range of different types of items in the industrial environment including mobile equipment, process equipment, infrastructure and personnel (with and without PPE). The object detection model is used to feed into object classification anomaly detection models to look at the state of selected pieces of identified equipment, such as whether a valve is open or closed, which can be placed in the context of the expected state of the process equipment by relating it to the digital twin for the asset. An additional object detection model was developed to operate as a gas leak detection system for infrared cameras.
The object detection model achieved good results and model performance was driven by the number and quality of images used for the training. An anomaly detection model designed to detect whether ball valves were open or closed delivered good results, with high accuracy and balanced false positive and false negative detection rates. The overall performance of the infrared gas detection model was restricted by the limited volume and variability of the training data, although the false positive detection rate was very low. A significant part of the machine learning was devoted to the development of a consistent labelled image library for oil and gas equipment, infrastructure and gas leaks. Image transformations were tested but boosting the number of images using transforms gave variable results. Additional training and testing data is needed to ensure that the models are as robust as possible, especially for the gas leak detection model. Once the models are productionised and in use, additional data can be used to periodically retrain the models for improved performance.
In addition to the machine learning algorithms, a fundamental aspect of the project is the development of the overall technical architecture, supporting the data science. This includes enabling the transfer of data from inspection robots or other connected camera devices into a data store in a cloud computing environment and returning the results to dashboard systems with different levels of detail depending on user requirements.
The Clair Ridge Project - A Safety Leadership Journey to Create a Strong Culture of Care
Authors: White Caroline , Houston Rob , Chapman Graeme , Gourlay Simon , Lang Kenneth 
Published: August 2019

Abstract
The Hook-up and Commissioning program for the BP operated Clair Ridge facility was conducted over a period of three years, starting with the accommodation platform in 2015/16, and then the Production and drilling platform over 2017 and 2018. The total topsides weight is 53,000 tonnes, and the field is located in the harsh waters of the Atlantic West of Shetland. Typically 750 persons were based offshore, but over the life of the program some 7000 individuals worked offshore at some point on the project. Recognizing the safety leadership challenges with such a major hook-up and changing workforce a huge amount of effort went into preparation and working with our contractors to onboard the workforce. Over the first months of the campaign the safety metrics were healthy and there was a good reporting culture, however an increase in incidents was seen, including one late in 2015 where a medical evacuation was required from the platform. The individual made a full recovery and returned to work however it caused the Operator and Contractor project leaders to reflect on their safety leadership and how they were working with and engaging with the workforce. It was a catalyst for change as the team was determined that no other serious incidents would happen during the project delivery.
In this paper we will share the Clair Ridge safety leadership journey and the steps taken by the operator, with the support and collaboration of the main contractors, to set a new approach to safety through the development of a genuine Culture of Care. This included: Building of trust and credibility between leadership and the workforceLeadership openness and transparency in communicationEmpowering front-line supervision to be safety leaders and giving them the skills and tools to do this well
As a result of the approach the Clair Ridge team is proud that, in the three years since the incident in 2015, over 9 million offshore workhours have been completed without any other Lost Time Incident, and a safe start-up was achieved with no process safety related incidents. Clair Ridge realised some of the highest participation in safety observations and near miss reporting across the Operator's global projects portfolio, a continual and significant reduction in all injuries and benefited from an excellent reporting culture.
A Culture of Care has been owned by all, and been recognised and commended by the contractor workforce and visitors to Clair Ridge.
ABB Subsea Power JIP - A Game Changer for Next Generation Subsea Processing
Authors: Vatland Svein , Ingebrigtsen Stian , Pretlove John , Nesheim Henning 
Published: August 2019

Abstract
ABB is running a joint project with Equinor, Total and Chevron to develop technologies for subsea power transmission, distribution and conversion. The output will form a critical part of future advanced subsea field developments. As such an undertaking has never been achieved before, it is a journey with considerable learnings to be shared not only upon completion (anticipated by the end of 2019) but also en route.
The paper will describe steps taken to build confidence along the way that the proposed solution will be fit for purpose when fully launched. Readers will gain insights into the key steps of this cutting-edge project. These include modifying prototypes of the equipment based on rounds of simulations, laboratory assessments (eg accelerated aging, vibration and shock testing) and water testing. Insight will be provided on tedious testing and qualification effort required to achieve the technology readiness level (TRL) required.
Readers will learn from the challenges experienced in this ground-breaking project and how they were overcome. Insight will be given into the overall challenge of both research/development and qualification of the novel technology developed in the JIP. Findings from testing, including extensive lab testing against industry standards, and the impact on subsequent development will be presented. The paper will eventually share results from extensive joint research work between the partners and ABB. The results are ground breaking and will by the end of the day introduce completely new opportunities for development of subsea fields.
As a first-of-kind-project, the results gained, and the subsequent technology developed will be of considerable interest to the industry. By the end of the day, the results from this project will be a key enabler for the subsea factory vision envisioned by the industry.
Work Orders - Value from Structureless Text in the Era of Digitisation
Authors: Salo Erik , McMillan David , Connor Richard 
Published: August 2019

Abstract
Free text and hand-written reports are losing ground to digitization fast, however many hours of effort are still lost across the industry to the manual creation and analysis of these data types. Work orders in particular contain valuable information from failure rates to asset health, but at the same time present operators with such analytical difficulties and lack of structure that many are missing out on the value completely. This research challenges the current mainstream practice of manual work order analysis by presenting a methodology fit for today’s context of efficiency and digitization.
A prototype text mining software for work order analysis was developed and tested in a user-oriented approach in cooperation with industrial partners. The final prototype combines classical machine learning methods, such as hierarchical clustering, with the operator’s expert knowledge obtained via an active learning approach. A novel distance metric in this context was adapted from information-theoretical research to improve clustering performance.
Using the prototype tool in a case study with real work order data, analytical effort for certain datasets was reduced by 90% - from two working weeks to a day. In addition, the active learning framework resulted in an approach that end users described as "practical" and "intuitive" during testing. An in-depth review was also conducted regarding the uncertainty of the results – a key factor for implementation in a decision-making context.
The outcomes of this work showcase the potential of machine learning to drive the digitization of not only new installations, but also older assets, where as a result the large amount of unstructured historical data becomes an advantage rather than a hindrance. User testing results encourage a wider uptake of machine learning solutions in the industry, and particularly a shift towards more accessible in-house analytical capabilities.
Categorising Risk for Drilling and Completions Using High-Resolution Acoustic LWD Image Logs
Authors: Basu Pramit , Morris Stephanie , Morris Stephen , Ritzmann Nicklas , Zheng Yan 
Published: August 2019

Abstract
In extended reach and horizontal wells, it is critical to maintain borehole quality and stability to ensure efficient drilling and for the running and installation of completions. Categorising the risk of borehole degradation is becoming an important aspect of the well planning process. The quality of the borehole is affected primarily by geomechanical or drilling practices, which can significantly impact the life cycle and completion expenditure/cost of a well. We show examples of how recently available, high-resolution, acoustic logging-while-drilling (LWD) borehole image logs have enabled detailed characterisation of borehole shape to the extent that we can visualise and analyse all contributors to borehole stability. LWD measurements also enable the use of time-lapse logging; comparing images from the first pass with repeated logging runs at later stages in drilling to look for degradation in conditions of the borehole shape. These data can be used for several new or existing applications that can be split into two main categories: 1. drilling hazards – degrading borehole shape profiles, identification of borehole breakout and washed-out sections and 2. completions hazards – cement volume calculations, identification of trajectory and small-scale irregularities that could impair liner placement. These applications use zonation to describe all ranges in borehole trajectory, borehole shape and image artefact features for coding of the well during or shortly after drilling. This scheme is then combined with a geomechanics-centric integrated risk management workflow which provides an improved well planning process by identifying potential drilling and geological risks in each of the planed well sections. Pre-drill risk identification combined with visual verification of the borehole condition enables quick decision making for drilling and potential de-risking of subsequent wireline logging and completions operations, thereby allowing safe, predictable operations with minimal NPT, from drilling to completions. The enabling technology of high-resolution LWD acoustic imaging has made possible the visualisation of borehole shape features in detail previously not possible in either water or oil-based mud systems.
Integrated Approach Toward Diagnosing Microbiologically Influenced Corrosion in the Petroleum Industry
Authors: Bruijnen Pieter , van Strien Willem , Doddema Sabine 
Published: August 2019

Summary
The microbiologically influenced-corrosion (MIC) -related problems encountered in the water-injection wells of the Rijn Oil Field, offshore the Netherlands, were assessed from multiple perspectives to determine the root cause of the corrosion and the declining injection performance. Various classical petroleum-engineering methods were combined with full-bore electromagnetic inspection and 3D laser scanning of tubing sections to analyze the injectivity and integrity problems on both well and reservoir scales. Quantitative evaluation of materials by scanning electron microscopy (QEMSCAN), a novel technique for quantitative analysis of minerals, was used to identify chemical components in the corrosion products and allowed us to reconstruct the electrochemical processes that had taken place on a micrometer scale. Molecular microbiological methods (MMMs) such as quantitative polymerase chain reaction (QPCR) and 16S next-generation sequencing (NGS) were applied to identify the entire microbial population in various samples.
Petroleum engineering, corrosion engineering, and microbiology were thus combined in a multiscale and multidisciplinary approach. This approach was followed successfully during the diagnostic process, resulting in verifiable hypotheses about the fundamental corrosion and plugging mechanisms in these water-injection wells. The results confirmed that the dominant corrosion process was MIC. Also, the presence of chloride contributed significantly to the corrosion process, possibly in combination with underdeposit corrosion (UDC). The full suite of analyses shed light on possible causes of the declining injectivity in the wells: There appeared to be a link between the formation of deposits and corrosion, strongly influenced by microbes. In this paper we demonstrate the importance of an integrated approach, which can lead to reliable diagnostics and successful mitigation against future corrosion and the declining performance of wells and pipes.
Predicting the Prognosis of Patients with Pneumocystis Pneumonia by the (1,3)-β-D-Glucan Test Change
Authors: Xu Jun , Yao Hui , Sun Feng 
Published: August 2019

Abstract
Background: To investigate the effects of the (1, 3)-β-D-glucan test (G test) to predict the outcomes of the patients with Pneumocystis pneumonia ( PCP ). Methods: The clinical data of PCP patients diagnosed from 2010 to 2018 in Peking Union Hospital collected. The imaging changes, the independent risk factors of death, changes of the G test and the patients’ outcomes were used as a receiver operating the characteristic (ROC) curves, and the area under the curve (AUC) calculated. Results: A total number of 104 patients enrolled in. The independent risk factors of death for PCP included pulmonary interstitial fibrosis (P=0.003), Cytomegalovirus co-infection (P=0.006), severe complication during treatment (P=0.001). The reduction of the G test was less than 9.13% of the initial G test (P=0.005), and the second imaging was not better than the first imaging (P=0.001). The efficiency of predicting the prognosis by the declined G test (AUC=0.740) is similar (P=0.893) to that of improving the imaging (AUC=0.731). The combination of the risk factors was the most effective predictor of the patients’ outcomes (AUC=0.938, CI 0.873 - 0.976, P < 0.001). Conclusion: The changes of G test can predict patient prognosis, and their efficiency is comparable to that of the changed imaging.
Liquid chromatography-high resolution mass spectrometry (LC-HRMS) analysis of Auxin Metabolites in Arabidopsis thaliana shoot tissues
Authors: Phapale Prasad , Alexandrov Theodore 
Published: August 2019

Abstract
Auxin metabolome affects almost every facet of plant development from hormone transport and biosynthesis to degradation. It also triggers several environmental responses. Measuring auxin biosynthesis can enable a better understanding of metabolism and hormonal activities during plant growth and developmental phases. Here we optimised a solid phase extraction (SPE) sample preparation and liquid chromatography-high resolution mass spectrometry \(LC-HRMS) method for profiling auxin metabolites in the tissues \(shoot and leaves) of the model plant system (Arabidopsis thaliana). We combined a sensitivity SPE sample preparation protocol with accurate LC-HRMS analysis to profile auxin metabolites in plant tissues.
Co-transcriptional quantification of RNA synthesis, RNA folding and RNA-protein interactions by "Systems NMR" approach.
Authors: Nikolaev Yaroslav , Ripin Nina , Soste Martin , Picotti Paola , Iber Dagmar , Allain Frédéric H.-T. 
Published: August 2019

Abstract
The protocol describes how to setup and analyse observation of a co-transcriptional RNA folding network by Systems NMR approach. While most experimental approaches can monitor only a single molecule class or reaction type at a time, Systems NMR permits single-sample dynamic quantification of entire “heterotypic” networks – involving different reaction and molecule types. It thus provides a deeper systems-level understanding of biological network dynamics by combining the dynamic resolution of biochemical assays and the multiplexing ability of “omics”. This particular protocol describes the reconstruction of an 8-reaction co-transcriptional network - with simultaneous monitoring of RNA, metabolite, and proteins in a single sample at the same time. From reactions side, the protocol simultaneously quantifies RNA transcription, RNA folding and RNA-protein interactions (observed both from RNA and from protein side) and few other auxiliary reactions. In addition to fundamental analyses of reaction constants under different conditions, the current applications of this particular reconstruction are: (1) map RNA-binding interfaces on proteins without having to purify/order the RNA; (2) monitor co-transcriptional RNA folding perturbations by proteins and small molecules; (3) monitor RNA-transcription-driven protein phase-separation with the possibility to observe multiple proteins at once, each with residue-level resolution. Not counting the protein and RNA template preparation times, the NMR measurement and data analysis parts take about 1 day each. This protocol accompanies Nikolaev et al, Nature Methods, 2019 (doi:XXX). The most up-to-date version of the protocol (including example code and data) is available at: github.com/systemsnmr/ivtnmr
A comparison between the stability fields of a Cl-rich scapolite and the end-member marialite
Authors: Almeida Kaléo M.F. , Jenkins David M. 
Published: August 2019

AbstractScapolites are pervasive rock-forming aluminosilicates that are found in metamorphic, igneous, and hydrothermal environments; nonetheless, the stability field of Cl-rich scapolite is not well constrained. This experimental study investigated two reactions involving Cl-rich scapolite. First, the anhydrous reaction 1 of plagioclase + halite + calcite to form scapolite [modeled as: 3 plagioclase (Ab80An20) + 0.8 NaCl + 0.2 CaCO3 = scapolite (Ma80Me20)] was investigated to determine the effect of the Ca-rich meionite (Me = Ca4Al6Si6O24CO3) component on the Na end-member marialite (Ma = Na4Al3Si9O24Cl). Second, the effect of water on this reaction was investigated using the hydrothermally equivalent reaction 2, H2O + scapolite (Ma80Me20) = 3 plagioclase (Ab80An20) + CaCO3 + liquid, where the liquid is assumed to be a saline-rich hydrous-silicate melt. Experiments were conducted with synthetic phases over the range of 500–1030 °C and 0.4–2.0 GPa. For reaction 1, intermediate composition scapolite shows a wide thermal stability and is stable relative to plagioclase + halite + calcite at temperatures above 750 °C at 0.4 GPa and 760 °C at 2.0 GPa. For reaction 2, intermediate scapolite appears to be quite tolerant of water; it forms at a minimum bulk salinity [XNaCl = molar ratio of NaCl/(NaCl+H2O)] of the brine of approximately 0.2 XNaCl at 830 and 680 °C at pressures of 2.0 and 1.5 GPa, respectively. Based on the study done by Almeida and Jenkins (2017), pure marialite is very intolerant of water when compared to intermediate composition scapolite. Compositional changes in the scapolite and plagioclase were characterized by X-ray diffraction and electron microprobe analysis and found to shift from the nominal bulk compositions to the observed compositions of Ma85Me15 for scapolite and to Ab91An09 for plagioclase. These results were used to model the phase equilibria along the marialitemeionite join in temperature-composition space. This study demonstrates that a small change in the scapolite composition from end-member marialite to Ma85Me15 expands the stability field of marialite significantly, presumably due to the high entropy of mixing in scapolite, as well as increases its tolerance to water. This supports the much more common presence of intermediate scapolites in hydrothermal settings than either end-member meionite or marialite as is widely reported in the literature.
Narrativas de actores educativos acerca del rol de las emociones en el conflicto escolar. El caso de estudiantes y docentes de grado noveno del Colegio Agustín Parra
Authors: Sarmiento Segura Lyda Constanza 
Published: August 2019

El presente trabajo busca la interpretación del rol que desempeñan las emociones en los conflictos que se presentan en el escenario escolar, desde las narraciones de los estudiantes y docentes del grado noveno de educación básica. Para ello se identifican las situaciones que generan conflicto en el escenario escolar, se analiza el papel que tienen las emociones en la generación y en la superación de los conflictos que se presentan en el escenario escolar y se estudian las narraciones que hacen los actores educativos de la forma como las emociones intervienen en las situaciones de conflicto. El enfoque de la investigación es cualitativo, basado en la narrativa que surge durante las entrevistas. De acuerdo con los resultados se concluyó que las emociones conducen a la generación de conflictos en la medida en que las personas desconocen la forma en que pueden manejarlas, por lo que acuden a manifestaciones violentas como alternativa para expresar su rechazo por lo que están sintiendo. Existen además otras emociones que pueden contribuir a que un conflicto sencillo se agrave, como son las que se generan por la presión de los observadores, incluyendo el orgullo, la ira y la vergüenza. Ante las anteriores conclusiones, de acuerdo con las narrativas de los actores educativos, las emociones tienen un papel determinante no solo en la generación del conflicto escolar sino también en su resolución pacífica. Se requiere que los docentes estén mejor preparados no solo para manejar con liderazgo las situaciones de conflicto que se les presenten, sino para resolver ellos mismos sus propios conflictos, dado que su ejemplo también es determinante de la conducta de los jóvenes.