bluuebunny/crossref_metadata_2025 huggingface dataset:
Aesthetic sphere in philosophical and intellectual reflections of the XXth century
Authors:   Odessa National Polytechnical National University, Kovalova N. I. , Levchenko V. L. ,   Odessa National Polytechnical National University
Published: February 2020

The article is devoted to the consideration of the aesthetical and the philosophical in intellectual reflections of the twentieth century. The material for the study were conceptions of such characteristic figures of modernism and postmodernism as W. Benjamin and J.-F. Lyotard. The task of the work was the analysis of modern and postmodern discourses and identification of their intertwining and intercollision. Benjamin articulated main modernist tendencies in his writings. For him the sociological approach and the consideration of the subject of art and artistic activity in all manifestations were basic everywhere in analysis of art. Instead of these postmodern art reflects itself as an antisocial practice in the context of it by the "decline of metanorations", the decline of ideology, the rejection of the general theoretical position, Modernism cuts off idea of any connection with the past. The principle condition on creativity for modernists was innovation and originality. Benjamin demonstrates such a level of decadence of the moderating guidelines in relation to the tradition. But for him Interest in historicity, games with citations in his books and writings are closed him to postmodernist positions and directions. Postmodernism, in relation to the past, is based on the paradigmic guideline that "everything was already there," everything has already happened both as an event and in an interpretive sense.
La enseñanza de lenguas extranjeras y la Teoría de las Inteligencias Múltiples de Gardner. Reflexiones sobre la importancia de la emoción en el aprendizaje de lenguas extranjeras/Foreign language teaching and Gardner’s Theory of Multiple Intelligences. Afterthoughts on the importance of emotions in foreign language learning
Authors: Gabarrón Pérez Ángel
Published: February 2020

En el presente artículo se recoge una reflexión sobre la influencia de la Teoría de las Inteligencias Múltiples de Howard Gardner en la enseñanza de lenguas extranjeras a través de la revisión de literatura tradicional y contemporánea sobre el tema, estableciendo una retrospección que parte del “Nivel Umbral” (documento elaborado por expertos para el Consejo de Europa, que habría de ser la antesala del Marco Común Europeo de Referencia para las Lenguas (MCERL)), para continuar con las diferentes teorías pedagógicas que han influido en la enseñanza de lenguas durante las décadas de los 70 y 80, hasta llegar a la Teoría de las Inteligencias Múltiples.. En consecuencia, reflexionaremos sobre la forma en que cada individuo desarrolla en mayor o menor medida cada una de las inteligencias consideradas en la teoría de Gardner durante el proceso de enseñanza- aprendizaje de las lenguas extranjeras. Finalmente, teniendo en cuenta la importancia de la inteligencia emocional en el aprendizaje de una lengua, analizaremos el concepto del docente de lenguas como un “profesor emocional”, un gestor de sus propias emociones y de las emociones del discente, capaz de generar el escenario válido para el desarrollo de un proceso adecuado de enseñanza-aprendizaje de una lengua extranjera, y la importancia de las TIC en dicho proceso.
Utilización de las inteligencias múltiples como factor predictivo del gusto lector: análisis de viabilidad/Use of multiple intelligences as a predictive factor of the reader’s inclination: feasibility analysis
Authors: Lánchez-Perez Madelón , Merino-Soto César , López-Fernández Verónica
Published: February 2020

La teoría de las inteligencias múltiples, en conexión con el análisis del género literario preferente, podría ser la base del diseño de programas de intervención exitosos a la hora de fomentar el desarrollo del hábito lector en estudiantes de secundaria. El objetivo de este trabajo es: confirmar si existe relación significativa y positiva entre las inteligencias múltiples y el género literario preferente. La investigación se realizó con una muestra de 97 sujetos, de edades comprendidas entre los 12 y los 15 años. Se evaluaron las inteligencias múltiples y el género literario preferente, y se analizaron las correlaciones entre ambas variables. El cuestionario de género literario preferente fue diseñado ad hoc y sometido a un proceso de control de validez y fiabilidad. Los resultados muestran que: 1) se confirmó la validez y fiabilidad del cuestionario de género literario preferente, si bien algunos géneros obtuvieron un índice de confiabilidad débil; 2) se encontraron diversas relaciones significativas y positivas entre ambas variables siendo todas ellas de carácter débil, salvo la correlación entre el género fantasía y la inteligencia viso-espacial que resultó ser de carácter moderado. Se concluye que el empleo de la conexión entre las inteligencias múltiples y el género literario preferente ofrece diversas oportunidades a la hora de diseñar planes de intervención.
Agnes’ Self-Reflection in Ingmar Bergman’s Cries and Whispers
Authors: Solovyeva Maria
Published: February 2020

The essay explores Ingmar Bergmans film Cries and Whispers (Viskningar och rop, 1972) from the perspective of the protagonists selfreflection as the main plot-constructing tool. The self-reflection of the main protagonist Agnes is presented by Bergman in a variety of forms which create, by mixing with each other, a polyphony of senses and images.
The author analyses those dramatic tools which make it possible to immerse a spectator into Agness inner feelings. Her diary is her conscious self-reflection and, therefore, becomes a cinematic instrument for a study of her psychology. Bergman explores the visual images of the main protagonists self-reflection and, logically, turns them into symbols. This is exemplified by the symbolic comparison of her mothers and her sisters images to a bouquet of magnificent white roses. And then, a close-up of a flower shows symbolically the true nature of Agness mother: the flower turns out to be an artificial one, revealing the hypocrisy of Agness externally beautiful mother. The protagonists conscious striving to understand herself is also revealed through the use of an analytical voice-over monologue accompanying a sequence of reminiscences about the mother.
The essay analyses the same sequence from the viewpoint of the objectorientation of Agness self-reflection. Within this sequence, self-reflection changes its object, becoming either introspective or extrospective. Agnes recomprehends herself either through the prism of herself or through the prism of the others. Quick alternation of these two types of self-reflection indicates the causal connection between Agness identity and her relationship with her mother. Significantly, the sequence's ending is the moment of the closest rapprochement between Agnes and her mother - that is, between two types of self-reflection.
A protagonist's self-reflection could be an effective tool of creating semantic resonance. An example of this is provided in the film's final sequence, in which Anna, the servant, reads the diary of the dead Agnes. This sequence is a reminiscence of those several minutes of Agness life when she was absolutely happy. It begins with Anna reading the diary and turns into the visualisation of a diary entry accompanied by the Annas voice-over on Agnes's behalf. This creates a triple resonance of the film's semantic content.
In the author's opinion, the above examples confirm that a characters selfreflection can become an effective dramatic tool for exploring a characters psychology and a technique of revealing the meanings in their polyphony.
Adaptation of Malt Barley (Hordeum Vulgare L.) Varieties in the highlands of North Gondar
Authors: Tahir Zeynu , Azanaw Asfaw
Published: February 2020

Study was initiated with the objectives to identify high yielder malt barley varieties. The trial has been conducted during 2014 main season and laid out on randomized complete block design with three replications. Analysis of variance was computed using SAS, 2002. At Dabat, result showed that highly significant difference among the varieties (p < 0.05) for all agronomic traits. At Debark and Wegera the analysis of variance indicated that highly significant to a significant difference among varieties  at p < 0.05 for days to heading, days to maturity, plant height, spike length, thousand seed weight and grain yield, and seed per spike. The combined analysis of variance showed that highly significant difference among varieties for days to heading, days to maturity, plant height, spike length, and grain yield. The location also contributed the significant effect for all yield components except biomass and grain yield. The interaction of location by genotype showed the highly significant difference on days to maturity and plant height. The average heading days ranged from 70-81 and the average maturity days were ranged from 127-136. Among the tested varieties, IBON-174/03 and SABINI exhibited highest grain yield. The overall combined analysis indicated that IBON-174/03 and SABINI were high yielder and well adapted at the tested sites. Therefore those varieties are recommended for production in the testes sites, and similar agro-ecologies.
Relación entre estrés percibido y calidad de sueño en enfermeras de turnos nocturno y rotativo
Authors: Peña-Rodríguez Iván-Alfredo , Nieto-Olarte Lina-Paola , Sánchez-Preciado Diana-Mayerli , Cortés-Lugo Rafael-Leonardo
Published: February 2020

Objetivo: determinar si existe relación entre el estrés percibido y la calidad de sueño en las enfermeras de los turnos nocturno y rotativo de la empresa social del Estado Hospital San Rafael de Facatativá. Metodología: estudio transversal con alcance correlacional donde se evaluó el estrés percibido y la calidad de sueño por medio de la escala de estrés percibido - versión 14 y el índice de calidad de sueño de Pittsburg -versión colombiana, respectivamente, en una muestra de 98 enfermeras que cumplieron con los criterios de inclusión. Resultados: se presentó una prevalencia del 72,45 % de estrés percibido y del 79,59 % de mala calidad de sueño; entre estas dos variables se halló una correlación baja (r = 0,258; p = 0,010). Se puede asegurar con un 95 % de confianza que mientras una variable aumenta, la otra también lo hace, queriendo decir que a mayor puntaje en la escala de estrés percibido, mayor puntaje en el índice de calidad de sueño de Pittsburgh, lo que sugiere que el nivel de estrés es un factor que tiene relación directamente proporcional con el sueño, es decir, entre mayor estrés, peor calidad de sueño. Conclusiones: se concluye que sí existe relación entre el estrés percibido y la calidad de sueño, lo cual evidencia, por un lado, que en las enfermeras a mayor estrés, peor calidad de sueño, y por otro, que a peor calidad de sueño, mayor estrés.
Vigilancia epidemiológica de ciclopía en el Hospital Universitario del Valle, Cali (Colombia) 2004-2008
Authors: Saldarriaga Wilmar
Published: February 2020

Objetivos: determinar y analizar la prevalencia de ciclopía en el Hospital Universitario del Valle (HUV) y buscar en los casos los factores etiológicos descritos en la literatura.Metodología: el presente es un estudio de corte transversal analítico, ensamblado a partir del sistema de vigilancia epidemiológica de malformaciones congénitas en el HUV y bajo la metodología del Estudio Colaborativo Latinoamericano de Malformaciones Congénitas (ECLAMC), se detectaron los casos de ciclopía acontecidos entre diciembre de 2004 y abril de 2008, se obtuvo el número de nacimientos y se encontró la prevalencia de ciclopía en el HUV. Gracias a un formato de entrevista del ECLAMC, se buscaron en las pacientes los factores que según la literatura se asocian con la ocurrencia de ciclopía. Se tomó fotos de cada uno de los casos.Resultados: durante el período comprendido entre diciembre de 2004 y abril de 2008 se presentaron 18.224 nacimientos en el HUV. De éstos, 8 presentaron ciclopía con una prevalencia de 1 en 2.278 nacimientos (43,8 por 100.000). Todos los casos se clasificaron según Meyer como tipo I y 3 casos presentaron etmocefalea. Se encontró exposición a misoprostol, alcohol y marihuana en un caso; diabetes en otro, marihuana en otro; un caso presentó trisomia 13 y otro en que no se obtuvo cariotipo los hallazgos sugirieron trisomía 13.Conclusiones: La ciclopía en Cali y el Valle del Cauca es considerada un evento endémico. Por lo cual, se necesita un sistema de vigilancia epidemiológico de malformaciones congénitas, holoprosencefalia y ciclopía para Cali y el Valle del Cauca. Además, se necesitan estudios controlados sobre factores de riesgo individuales y colectivos.
Metódica MEIN para entrenar habilidades metacognitivas en niños de 4 a 6 años. Región Metropolitana de Chile.
Authors: Ilizástigui Del Portal Lourdes , Padilla Fernández Thiare , Martínez Sanguinetti Daniela , Fabré López Catalina
Published: February 2020

La metódica MEIN -metacognición infantil- es una herramienta psicoeducativa para el desarrollo, orientada a educadoras para entrenar habilidades cognitivas en las edades de 4 a 6 años con la finalidad de que los sujetos en edades más avanzadas puedan desarrollar metacognición. La Metódica MEIN hace posible entrenar de una manera peculiar, e interactiva, las habilidades cognitivas frente una actividad que a partir de la propia iniciativa del niño(a); el mediador intenciona, significa y lo/la acompaña para que sea capaz de idear la estrategia que empleará en el proceso de aprendizaje, y a partir de su apropiación transfiera a otros contextos, valorando el desempeño de su construcción. La metodología empleada fue cualitativa mediante un diseño de estudio de casos. El resultado fundamental del estudio demuestra que la Metódica MEIN es un recurso que facilita al educador orientar positivamente los procesos cognitivos en un espacio complejo de desarrollo para el entrenamiento temprano de habilidades metacognitivas. Al niño/niña le permite actuar libremente con independencia, facilitando la toma de conciencia.
Delmira Agustini: narraciones de vida y de muerte
Authors: Blixen Carina
Published: February 2020

Delmira Agustini (1886-1914) había publicado tres libros de poesía y ganado el reconocimiento de la crítica y el público cuando fue asesinada,el 6 de julio de 1914, por quien había sido su esposo. Este acontecimiento que ha tenido un lugar destacado en la crónica policial y en la historia literaria uruguaya, fue narrado por biografías y ficciones durante más de un siglo. Esta historiaha sido contada con algunas variantes que han reiterado un nudo de conflictos en torno a algunos protagonistas: Delmira, su madre, su novio-marido-amante-asesino, y ManueUgarte como el enamorado imposible. Sin embargo, la lectura de los manuscritos señala la relevancia de la figura de su padre: Santiago Agustini, casi una sombra en los relatos de la “tragedia”.Este trabajo intenta plantear la importancia de esta relación para comprender la producción poética de Delmira y abrir, desde esa perspectiva, la trama de relaciones emocionales e intelectuales que alimentaron vida y poesía.
Congratulations! Journal of Robotics and Mechatronics Best Paper Award 2019
Authors: Editorial Office
Published: February 2020

We are pleased to announce that the 12th Journal of Robotics and Mechatronics Best Paper Award (JRM Best Paper Award 2019) has been decided by the JRM editorial committee.

The following paper won the JRM Best Paper Award 2019, severely selected from among all 94 papers published in Vol.30 (2018). The Best Paper Award ceremony was held in Gakushi-Kaikan, Tokyo, Japan, on January 7, 2020, attended by the author and JRM editorial committee members who took part in the selection process. The award winner will also be announced on the JRM website and was given a certificate and a nearly US$1,000 honorarium.

JRM Best Paper Award 2019

Title: End-to-End Autonomous Mobile Robot Navigation with Model-Based System Support

Authors: Alexander Carballo, Shunya Seiya, Jacob Lambert, Hatem Darweesh, Patiphon Narksri, Luis Yoichi Morales, Naoki Akai, Eijiro Takeuchi, and Kazuya Takeda

J. Robot. Mechatron., Vol.30 No.4, pp. 563-583, August 2018
Global Excision of Severe Heterotopic Ossification of the Shoulder
Authors: Polfer Elizabeth M. , Nappo Kyle E. , Giuliani Jeffrey R. , Nesti Leon J.
Published: February 2020

Case:

A 21-year-old man sustained a closed glenohumeral fracture/dislocation as a pedestrian struck by a motor vehicle. He was treated nonoperatively and developed severe post-traumatic heterotopic ossification (HO) with near-complete shoulder ankylosis. We present our technique for safe surgical excision.

Conclusions:

Excision led to improvements in motion and quality of life at 1 year postoperatively. Recommendations for successful HO excision around the shoulder include excision after at least 180 days, appropriate preoperative imaging to include cross-sectional imaging and a 3D model, intraoperative fluoroscopy, well-serviced instruments, preparation for iatrogenic fracture and/or neurovascular injury, meticulous hemostasis, postoperative HO prophylaxis, immediate postoperative therapy, and involvement of a multidisciplinary team.
Benthic Foraminifera Across the Cretaceous/Paleogene Boundary in the Eastern Tethys (Northern Alborz, Galanderud Section): Extinction Pattern and Paleoenvironmental Reconstruction
Authors: Rostami Masoud A. , Frontalini Fabrizio , Leckie R. Mark , Coccioni Rodolfo , Font Eric , Balmaki Behnaz
Published: February 2020

Extinction patterns, paleobathymetric inferences, and paleoenvironmental changes based on benthic foraminifera were investigated across the Cretaceous/Paleogene (K/Pg) boundary at the Galanderud section (Northern Alborz, Iran), which contains one of the most continuous and expanded K/Pg transitions in the eastern Tethys. On the basis of benthic foraminiferal taxa abundance and distribution, an outer neritic to uppermost bathyal paleo-depositional setting is inferred. In addition, benthic foraminiferal assemblages and planktic/benthic ratios do not indicate any major change in relative sea level during latest Maastrichtian-early Danian time.

Changes in benthic foraminiferal assemblages, morphotypes, diversity, heterogeneity, and benthic foraminiferal oxygen index, coupled with statistical analyses, define three intervals. In the first interval (uppermost Maastrichtian Plummerita hantkeninoides Zone), benthic foraminiferal assemblages are moderately to well preserved and highly diverse, with a combination of epibenthic and endobenthic taxa indicating stable, mesotrophic to weakly eutrophic, normal marine conditions. A major change in benthic foraminiferal assemblages at the K/Pg boundary defines a second interval (basal Danian Guembelitria cretacea and lower part of Parvularugoglobigerina eugubina Zones) that is marked by a decrease in the endobenthic morphogroups as well as a decrease in diversity, heterogeneity, genus and species richness. This second interval denotes highly oligotrophic conditions and a collapse in productivity and food availability due to the extinction of some primary producers, with the exception of the three chalk beds representing short-lived blooms of calcareous dinoflagellates. Benthic foraminifera do not show significant extinction at the end of the Cretaceous at this section with only about an 8% loss of species. Additionally, the abundance of some opportunistic species, including Cibicidoides pseudoacutus and Tappanina selmensis, may reflect instability in the benthic foraminiferal assemblages. The third interval (middle-upper part of the Pv. eugubina Zone) is characterized by the dominance of epibenthic morphogroups (up to 70% of the assemblages) with a partial recovery of endobenthic groups. The characteristics of the benthic foraminiferal assemblages indicate that the flux of food to the benthos had not fully recovered during the early Danian.
Los padres de familia y la sexualidad en la adolescencia
Authors: Balarezo López Gunther , Balarezo Galarreta José Manuel
Published: February 2020

Se hizo una revisión bibliográfica de la literatura publicada sobre sexualidad en la adolescencia, y se analizarony resumieron los aspectos más relevantes. La adolescencia es una etapa en que se hace frente a una serie de cambiosbiopsicosociales, en la cual el hogar debería ser el primer centro de aprendizaje de cuestiones relacionadas con lasexualidad; pero, en la realidad, esto no ocurre, debido a que los padres muchas veces no tienen los conocimientosadecuados. Como consecuencia, los adolescentes tienen mitos y tabúes al respecto y buscan respuestas a sus dudasen medios que no son los más apropiados
Factors Influencing the Efficiency of Miscible Displacement
Authors: Blackwell R.J. , Rayne J.R. , Terry W.M.
Published: February 2020

Published in Petroleum Transactions, AIME, Volume 217, 1959, pages 1–8.

This paper presents results of an experimental investigation of factors that control the efficiency with which oil is displaced from porous media by a miscible fluid. The study was made to elucidate the relevant processes both on microscopic level (within individual or between neighboring pore spaces) and on macroscopic level (within a large sand body).

Mixing of miscible fluids on the microscopic level was studied in sand-packed tubes. It was found that molecular diffusion is the dominant dispersion mechanism for reservoir conditions of rate, length and pore sizes. Macroscopic channeling was studied for various mobility ratios in reservoir models-scaled to relate viscous gravitational, and diffusional forces. The formation of channels was due to viscous fingering, gravity segregation and variations in permeability. With adverse mobility ratios, it was found for reservoirs of realistic widths that diffusion will not be effective in preventing the formation and growth of fingers, even in homogeneous sands. At sufficiently low rates channeling was eliminated by gravity segregation in tilted reservoirs. The dependence of recovery on mobility ratio, length-to-width ratio, flow rate and angle of dip is presented.

Introduction

Oil recovery by solvent flooding is finding increasing application in the field. while the process promises high recoveries from the region swept by solvent, under adverse conditions only a small fraction of the reservoir volume may be swept at the time solvent breaks through to the producing well. Further, the high cost of the solvent encourages its use only as a bank whose size must be kept at a minimum. Thus, two important questions arise:what fraction of the reservoir can be swept, practically, by solvent? andwhat is the minimum size solvent bank that can be used to carry out the displacement?

The answers to these questions require knowledge of both macroscopic channeling processes and microscopic mixing processes. The studies described here were carried out to gain this knowledge. Microscopic mechanisms which cause mixing will be discussed first, because an understanding of these mechanisms is necessary for proper interpretation of the experimental work on channeling described later.
Predictive Action Planning for Hole Cleaning Optimization and Stuck Pipe Prevention Using Digital Twinning and Reinforcement Learning
Authors: Saini Gurtej Singh , Ashok Pradeepkumar , van Oort Eric
Published: February 2020

Poor hole cleaning leads to problems such as pack-offs, stuck pipe incidents, and lost circulation events due to increased equivalent circulating density (ECD). Hole cleaning issues can be mitigated by using a digital twinning system that constantly monitors borehole condition with real-time data and process models, and suggests optimal actions. The solution space of possible actions, however, is very large causing computational hurdles for real time implementation. This paper describes a time-efficient digital twinning approach that uses reinforcement learning (RL) to simulate scenarios corresponding to multiple hole cleaning actions.

Digital twinning of cuttings transport in a wellbore requires the development of a system with multiple integrated physics and data-based models to quantitatively detect symptoms of impending issues early, and to take actions to mitigate these problems. First, the state of the borehole is quantified in terms of ECD, concentration of cuttings in flow, and cuttings bed height. Next, a solution space of all legal and feasible actions based on the current system state is obtained. Finally, the alternate action sequences are evaluated to suggest the most suitable path forward.

To classify the state of the borehole in terms of ECD, cuttings bed height and cuttings concentration in the flow stream, hydraulics and cuttings transport models were implemented, tested and validated against real field and experimental data. Based on the state of the system, allowable actions were evaluated in terms of some combination of hole cleaning parameters that can be controlled in near real-time, such as flow rate, rotary speed, mud density, mud rheology and the weight on bit for rate of penetration (ROP) control. To limit the size of the solution space, those actions that were unrealistic for implementation in real-time were discarded. Also, any actions that violated the limits of the available drilling margin were discarded. Finally, by defining immediate rewards associated with different states-action pairs based on their effect on the wellbore stability and hole condition, the concepts of Markov reward process (MRP) and scenario realizations were used to suggest the optimal action for a given state.

The predicted output of the algorithm for multiple operational scenarios was validated by comparing it with actions that a hole cleaning / extended reach drilling (ERD) expert would have taken when given similar scenarios. The automated process of identifying hole cleaning system states, generating multiple viable hole cleaning action sequences, and finally evaluating the probability of successful hole cleaning for multiple actions in real-time and deciding the best course of action, is a novel contribution of this work. It will benefit practitioners who struggle with hole cleaning / stuck pipe-related non-productive time and pave the way for hole cleaning automation.
How Realistic is the Calculated Cementing Displacement Efficiency?
Authors: K. Foroushan Hanieh , M. Ozbayoglu Evren , J. Gomes Paulo
Published: February 2020

Primary cementing is a crucial task in the completion of oil and gas wells, as it is potentially meant to provide zonal isolation, and prevent uncontrolled flows and environmental hazards. Much research has been conducted to find the key techniques for obtaining the maximum displacement efficiency during cementing operations. Yet, it appears that the industry could benefit from more investigations on the complications involved in displacement processes.

In this work, a methodology is proposed in an attempt to obtain qualitative and quantitative predictions of displacement efficiency. This method, which appears to complement previously existing methods, introduces a combined analysis of instability of the interface between the two fluids with an analytical solution of fluid displacement flow in eccentric annuli. The analytical solution enables the time-dependent calculation of interface location and provides a quantitative judgement on the volume fraction of the displaced fluid left in the annular space. On the other hand, the instability models provide an insight on the degree of cement contamination, and guidelines on how to minimize the amount of inter-mixing.

The proposed approach was implemented for several displacement cases and the results were evaluated by both Computational Fluid Dynamics (CFD) simulations and experimental tests. Instability of the interface in all the cases was studied and the analysis provided more in-depth understanding of the effect of different parameters on displacement efficiency. Considering that in the existing analytical models, including the one presented in this work, the interface between the two fluids is supposed to be sharp, the calculated volume fraction of displacing fluid can be not necessarily a proper representative of the real displacement efficiency. It was observed that there can exist cases where the volume fraction of the displacing fluid did not necessarily indicate an inefficient displacement, whereas the instability analysis suggested that the corresponding design had to be avoided. This was also validated by CFD simulations. Moreover, the instability model can provide more information about the critical values of design parameters and propose optimized designs for the improvement of displacement efficiency.

The present work provides a versatile tool that enables quantitative determination of displacement efficiency, along with an enhanced judgement on the amount of inter-fluid mixing and cement contamination. The novel approach of coupling the instability analysis with displacement flow calculation not only offers improvements on displacement designs, but also assists to avoid any undesirable outcomes caused by ineffective cement placement.
Data-Driven Optimization of Drilling Parameters
Authors: Asgharzadeh Shishavan Reza , Adam Derek , Banirazi Reza
Published: February 2020

A major challenge during drilling is to identify sub-formation change, enabling near-real-time adjustment of the drilling parameters to enhance performance. An algorithm that determines sub-formations and optimizes drilling parameters as formations change and then updates itself solves this problem. This paper presents case studies of wells in the New Mexico Delaware Basin with improved drilling performance, detailing the algorithm's design and ability to produce formation-specific drilling parameters.

The workflow leverages historical drilling and geological information from offset wells, statistical analysis, physics-based models, and 1 Hz drilling data to identify sub-formations and transition zones in active wells. Rock drillability is calculated and used to identify the formation change via the algorithm. Simultaneously, optimal drilling parameters for the formation are generated, using an approach that relies on mechanical specific energy (MSE).

The workflow was successfully applied to a significant population of wells in multiple fields. Analyzing the results, the main observations were as follows: reduced cumulative MSE and average drilling time, improved consistency, and expedited learning curve. These achievements to a large extent are due to improved downhole dynamics and the reduction of input variability due to the statistical analysis of the algorithm. In addition, self-learning capabilities are built into the algorithm, which can improve its own performance with the addition of offset data during field development.

In general, three variables have major effects on drilling performance: surface controls, downhole equipment, and geology. Among these variables, geology is the most uncertain and yet crucial to success, as changes in rock type can significantly affect drilling performance. The power of the algorithm comes from the fact that it quantifies geological effects along with the effects of surface controls and BHA to significantly improve performance. This enables the algorithm to determine the formations that affect drilling operations and suggest the optimum drilling parameters for that formation zone.

This work combines real-time and historical drilling and geological data to identify the sub-formation changes and proposes the optimized drilling parameters. As observed in the case studies, this can lead to a significant improvement in drilling performance, near-real-time optimization of the drilling parameters, and minimizing non-productive time due to sudden changes in formation type.
Dynamics Vibration Prediction and Comparison with Downhole Data Measurements in Unconventional Wells
Authors: Mahjoub Mohamed , Nguyen Khac-Long , Menand Stéphane , Tran Quang-Thinh , Andrianoely Marie-Ange , Manin Lionel , Dufour Régis , Isbell Matt
Published: February 2020

During drilling operations, high drillstring vibrations may originate from various sources, namely, the bit-rock interaction, drillstring-wellbore contacts, stick-slip phenomena, fluid-structure interaction, and mass unbalances. Excessive vibrations may induce drilling equipment failures (fatigue, cracking, washouts, and ruptures), which can be costly and catastrophic. Therefore, it is crucial to accurately model the drillstring dynamics in order to help drilling engineers make better decisions and avoid harmful vibrational effects.

This paper proposes a numerical model developed in the time domain to estimate the drillstring lateral, axial, and torsional dynamics. It is based on the finite element method coupled with the Craig-Bampton reduction method (Craig and Bampton 1968) to reduce computation time. The drillstring-wellbore contact forces are automatically determined and may occur on both tool-joints and drill pipe bodies, and the drilling fluid is accounted for by its inertial and frictional effects.

The efficiency, accuracy, and predictive capacities of the model are assessed by comparing the computational results to downhole measurements for a case study of a non-conventional well. A good agreement for both lateral and torsional vibrations is obtained. The numerical results are used for a more detailed analysis on the lateral and torsional vibrations of the system. The evolution of lateral acceleration, from a forward to backward whirling tendency on the system, can then be assessed with the use of a spectral analysis.

The novelty of this dynamics model is that it can portray a realistic geometry of a drilling assembly in 3D curved wells with the fluid presence and gives a complete study of the coupling phenomena between the axial, torsional, and lateral vibrations. The use of this novel dynamics model along with downhole data acquisition and wired pipe technology is one of the essential steps towards drilling automation to provide a better mitigation of drillstring vibrations.
The Development and Application of Real-Time Deep Learning Models to Drive Directional Drilling Efficiency
Authors: Cao Dingzhou , Hender Don , Ariabod Sam , James Chris , Ben Yuxing , Lee Micheal
Published: February 2020

This paper provides the technical details to develop a real-time deep learning model to detect and estimate the duration of downlinking sequences of Rotary Steerable Systems (RSS) based on a single measurement (standpipe pressure, SPP). Further analytics are derived based on the downlink recognition results together with other real-time log data (ROP, RPM, Torque, etc.) to drive directional drilling efficiency.

Real-time RSS downlink recognition is treated as an image segmentation problem. The Deep Learning (DL) models were created using the dynamic U-Net concept and materialized with a pre-trained ResNet-34 as the underlying architecture. Transfer learning was used due to the limited number of training samples (≪ 100 downlinks per onshore well) to help with speed and accuracy. The SPP time series data was segmented based on stand of pipe drilled (one image per stand). This "image" was then fed into the model for downlink recognition. To further increase the accuracy, a second opinion mechanism was applied when the models were tested and deployed into the Real-Time Drilling (RTD) system. Using a dual model approach greatly reduced the number of false positives due to non-downlink pressure fluctuations causing "noise". The patterns of SPP and its rate of change (delta SPP) are quite different. They both have pros and cons for identifying the downlink, thus two independent models were built based on these two signals. The DL model A is trained based on the original SPP signal and the DL model B is trained based on delta SPP. A downlink is confirmed only when both models show positive results.

Data of 10 onshore wells (2 rigs) drilled with RSS were segmented (8165 images in total) and labeled. There were 671 images with 795 downlinks and 7980 images without downlink. The five-fold cross-validation technique was used to identify the best model(s). The F1 score of blind test result was .991 (accuracy was ~99.82%, see Table 2). The relative error of duration estimation is 2.49%. The current rig fleet within the RTD system has a mix of drilling tool configurations - RSS and mud motors. To further validate the models’ robustness regarding drilling tools, additional tests were conducted using mud motor wells’ datasets from 21 rigs (25431 images without downlink). There were 3 false negatives from this extended test set, which resulted in a ~99.93% accuracy for the aggregated 31 wells dataset. These results suggest that the models are accurate, reliable and robust.

The real-time DL solution presented in this paper enables operators to analyze RSS performance during and between downlinking events. This would allow drilling engineers and rig supervisors to make faster, more reliable data-driven decisions to optimize performance and directional control of the well path.
Auto-Suggestive Real-Time Classification of Driller Memos into Activity Codes Using Natural Language Processing
Authors: Ucherek Jared , Lawal Tesleem , Prinz Matthew , Li Lisa , Ashok Pradeepkumar , van Oort Eric , Gobert Tatiana , Mejia Juan
Published: February 2020

Activity codes recorded by drillers are very useful for quantifying invisible lost time (ILT). However, classifying more than 100 activity codes accurately and consistently across various rig operations becomes infeasible for human operators. We propose an auto-suggestive system that guides the drillers to the correct codes based on memos they enter into the system. This aims to both eliminate manual classification errors and improve memo entry.

The method for extracting activity codes from memos can be broken into the following steps. The first step consists of filtering unnecessary text and vectorizing the memos. The vectors are then re-weighted using the term frequency-inverse document frequency (TFIDF) statistical measure. Next, data resampling helps to create a uniform set of labels for the training data, because there are quite a few important activity codes that appear infrequently with respect to others. Finally, a classifier is trained. It is shown that the finalized model can be used as a real-time auto-suggestive mechanism during the drillers’ data input process. Moreover, its use for cleaning up historical datasets is also explored.

This method was implemented on a large historical dataset consisting of 150 wells, and ILT analysis was performed with the original dataset and with the auto-classified dataset. Comparing these results clearly showed that performing analysis on a dataset that has not been properly classified can lead to incorrect and misleading conclusions. Also, this method did not require a manual re-labeling of the dataset for model training. This makes the algorithm readily applicable for any end-user, irrespective of the number of activity codes used. Various classifiers including logistic regression, support vector machine, random forests, naïve Bayes, and multi-layered perceptron were implemented and tested. Given comparable performances, we conclude that a simple and interpretable logistic regression model is best for real-time classification. Tests were also performed to see how many typed words in a memo would be needed before the correct activity code was identified. The results are detailed in this paper.

This is the first body of work that has taken drillers’ memos and converted them into activity codes, without the need for a human-classified training dataset. The real-time classifier is very powerful in ensuring clean data at the source and will be particularly useful when implemented on reporting systems for classifying rig activities by IADC activity codes. We further demonstrate the use of the classifier for cleansing historical datasets such that ILT analysis can be done more accurately.
Borehole Stability in Shale: Beyond Mud Weight
Authors: Araujo Ewerton , Kisinger Darren , Vidal Daniel , Cresap Barry
Published: February 2020

Several wells in the Gulf of Mexico were analyzed to understand the source of shale instability during drilling and wireline operations. In spite of the mud weight being above the borehole collapse pressure, the wells still exhibited signs of shale instability. As such, it was evident that another mechanism was playing a role in the failure of the shales. This study investigated the drilling fluid properties that are known to affect shale stability. One fundamental property investigated was the water phase salinity, as shales can act as osmotic membranes, allowing fluid diffusion through the porous space while restricting the movement of salt ions. This establishment of an osmotic pressure can either preserve or destroy the mechanical integrity of the shale.

The analysis compared the water phase salinity (WPS) and mud weight (MW) of several wells, in the context of geomechanics, to understand their relationship with the actual borehole stability condition. In one particular case, the data revealed the impact of mud salinity on shale stability, where three different boreholes penetrated the same shale: the original hole (OH) and two sidetracks. In the OH, there was no indication of shale instability during the eight days the hole was exposed, no cavings were reported, and the caliper log showed an in-gauge hole. The first sidetrack (ST1) was completely different where the salinity level was reduced by 7% while the MW remained the same as the OH. During the first ten days of shale exposure in ST1, there was no significant indication of shale sloughing. However, after ten days, it was challenging to maintain a stable wellbore, which led to a stuck pipe event, and an unsuccessful attempt to regain wellbore stability by raising the MW. In the second sidetrack (ST2), the salinity concentration and MW were the same as in the OH, and after fourteen days of exposure to the mud system, there were no signs of instability. The caliper from ST2 confirmed that an in-gauge hole was maintained the entire time of drilling and wireline operations.

These observations were used to calibrate a borehole stability model, which was used to plan a subsequent infill well in the field drilled at a higher inclination and with a long open hole section through the same shales. The model successfully predicted the optimum combination of MW and WPS to maintain a stable wellbore throughout drilling and wireline operations. The results show that a scientifically-driven modeling approach based on offset wellbore observations and appropriate model selection and calibration can result in a significant improvement in drilling operational uptime by minimizing shale instability.
Building a General and Sustainable Machine Learning Solution in a Real-Time Drilling System
Authors: Ben Yuxing , Han Weilu , James Chris , Cao Dingzhou
Published: February 2020

One of the core components of a real-time drilling analytics system is online rig state classification. We have deployed a rig state classification algorithm which leverages machine learning on a real-time drilling system. With new data continuously flowing through the machine-learning-based algorithm, monitoring performance and accuracy is a time-consuming proposition. Traditionally, misclassified results have been reviewed and corrected offline, manually. This paper will present a general and sustainable machine learning solution to address this challenge.

A convolutional neural network (CNN) model was deployed to classify rig states in a real-time drilling analytics system. After observing wells with misclassified results, the time-series data was aggregated and corrected offline. With this new, corrected data set, the original model was retrained including both the new labeled data and the original data set used to develop the model. In parallel, an offline model based on semantic segmentation and batch data aggregation was developed to continuously monitor the performance of the online model. Finally, a post-processing procedure was implemented to improve the results which were identified as inaccurate.

After studying drilling time series data from over 40 wells with over 30 million timestamps across three US onshore basins, several problems were identified that led to lower than expected CNN model inference accuracy. Those include: data integrity, data quality (unit of measure), model uncertainty, and sample distribution shift. After these issues were addressed, a new ML model was developed which had an accuracy of over 99% and f1 score of 0.99-1. The offline model, based on semantic segmentation, had better accuracy than the online model, resulting from batch data processing across entire drilling intervals. The post-processing procedure, based on domain knowledge, was applied to the data mislabeled by the online CNN model. The combination of the three techniques has led to a highly-reliable prediction which forms the foundation of drilling analytics across the entire rig fleet.

This paper presents a multi-layered approach to developing and monitoring a ML based rig state inference system for real-time drilling analytics. With rig states forming the foundation of drilling analytics, a reliable, accurate, scalable solution is required to minimize manual effort required to clean and classify data prior to analysis. The authors are not aware of any real-time drilling applications of CNN-based inference or semantic-segmentation-based post-processing to classify and monitor time-series rig state prediction.
Achieving Automated Directional Drilling Across us Onshore Basins
Authors: Coffey Scott , Groover Austin
Published: February 2020

As automated directional drilling matures, it is increasingly accepted by operators as a technology to improve drilling performance. The maturation of one service provider's slide automation technology was driven largely by development and experience in one US onshore basin. This approach produced a system that was robust and configurable – but configured initially for basin-specific challenges. This paper describes how automated directional drilling practices from different basins are captured to drive performance improvements and collapse the learning curve in each subsequent deployment.

The implementation of this technology beyond the development basin was guided by an understanding of directional drilling best practices and challenges in each new area. Basin-specific factors like wellbore geometry and trajectory, formation tendency, and BHA objectives were assessed and codified to drive adjustments to the automation configuration. Engineering studies of offset wells preceded initial deployments in each new basin to identify necessary adjustments; changes were iteratively implemented and monitored via novel KPIs, such as pre-slide flat time, steering control precision, and performance consistency, alongside other industry-standard metrics.

Results from deployments in multiple US onshore basins areas show that because of variations in drilling practices, basin-specific configurations are a critical part of delivering high-performance automated directional drilling. A key early finding was the importance of identifying similar and dissimilar practices between basins so that adjustments to the system's logic were focused on high-impact activities, while minimizing startup time. Furthermore, as parameters and equipment change within a basin, it is necessary to continuously monitor and revise the slide automation system to accommodate these changes. One case study is presented to show how differences in manual slide performance between basins drive changes to the automated steering system's behavior. Another case study is presented that outlines the relationship between different BHA equipment and the automation configuration.