bluuebunny/crossref_metadata_2025 huggingface dataset:
MANAJEMEN PROGRAM KAJIAN MASJID RAYA HUBBUL WATHAN ISLAMIC CENTER NUSA TENGGARA BARAT
Authors: Lalu Adam Zikrullah
Published: April 2024

This article examines Islamic programs at the Hubbul Wathan Islamic Center Mosque in Mataram, NTB, with a focus on looking at the implementation of management functions in each program held. In this article, there are several questions that are attempted to be answered, namely, what kind of and how is the management function implemented in every Islamic program at the Great Mosque of Hubbul Wathan Islamic Center, NTB? NTB Center.? This article is the result of field research and uses a qualitative approach. Regardless, the data in this article are sourced from primary and secondary data which are processed through observation, structured interviews, and documentation. The results of this study indicate that the implementation of the management function in every Islamic program at the Hubbul Wathan Islamic Center Islamic Center NTB Mosque has been well implemented. This matter is clearly seen in the process of implementing Islamic programs such as, among other things, planning before the study program, organizing tasks between related fields, carrying out tasks according to planning, and monitoring in the form of evaluating activities that have been carried out. Meanwhile, the background of the implementation of the management function of this activity is to facilitate and fulfill the community's needs regarding religious knowledge. However, even though the management functions have been well implemented, the local government's support for the implementation of Islamic studies programs appears to have not been maximized, particularly with regard to the accommodation of pilgrims
MANAJEMEN PONDOK PESANTREN AL-MADANI DALAM PENGEMBANGAN UMMAT DI DESA MAMBEN LAUK LENGKOK AL-KHAIRAT LOMBOK TIMUR
Authors: Rahmat Hidayat
Published: April 2024

This paper aims to investigate the role and position of the al-Madani Islamic boarding school, one of the Islamic boarding schools that has a positive trend in society through efforts to develop an understanding of community religion, especially in Mamben Lauk Village, Lengkok Al-Khairat, East Lombok. In this paper, the main focus of discussion is emphasized on the personal religious management programs that are offered and run. Several important issues that will be answered in this research are, what kind of maps are the religious programs offered by the Al-Madani Islamic boarding school?, Second, what is the management of religious programs at the Al-Madani Islamic boarding school? In general, the data in this paper were obtained through field research using a quantitative approach. Meanwhile, related information was obtained through in-depth interviews, observation, and documentation. The results of this study indicate that the religious programs of Al-Madani Islamic Boarding School have been very well planned and arranged in accordance with the three principles of management science, namely planning, organizing, actuating, controlling.
Perilaku Konsumtif dalam Belanja Online Memasuki Era 5.0 dalam Perspektif Manajemen dan Nilai-Nilai Islam
Authors: Agustina Latifah Agustina , Leni Leni Kirani , Moh. Ilham  , Novie Andriani Zakariya
Published: April 2024

The development of the era of society 5.0 has changed the way consumers interact and shop through media. Online shopping is a favorite of the community to meet needs. Among college students, online shopping has become a daily habit and necessity. This research focused on the consumptive behavior of UIN Sunan Ampel Surabaya students with a management perspective and Islamic values. The method used involves collecting qualitative data through observation, interviews, and documentation, with descriptive data analysis, a method used to analyze data by describing or describing the collected data. The results of this study show that UIN Sunan Ampel Surabaya students consider online shopping as an informative, stable price, and flexible way to shop. Although from the point of view of management and Islamic values, their behavior tends not to be in accordance with needs because it prioritizes wants.Keywords: Consumer Behavior, Online Shopping, Management, Islamic Values.
Dakwah Pada Masyarakat Multikultural
Authors: Fikri Hamdani Khaerul
Published: April 2024

Abstract: This article discusses the role of Islam as a missionary religion in encouraging active participation of its followers in missionary activities in Indonesia, a country rich in linguistic, ethnic, racial, and religious diversity. The close correlation between the progress or regression of the Islamic community and missionary activities creates the reality of a multicultural society in Indonesia. With a large and dispersed population across numerous islands, differences in religion, ethnicity, race, and language can have both positive and negative impacts, including the potential for conflict. The article focuses on a multicultural-based approach in the context of missionary activities, identifying the role of multiculturalism in society and highlighting appropriate missionary strategies. The two main questions addressed in this article are, first, what is the meaning of multiculturalism in society? And second, what are the suitable missionary strategies in the context of a multicultural society? Through this discussion, the article provides a profound understanding of the complex dynamics among missionary activities, Islam, and multicultural society in Indonesia. It demonstrates that successful missionary strategies have been implemented in multicultural communities and also offers valuable insights for readers interested in religious and multicultural issues.
Task-oriented training effect on promoting motor skills and daily physical activities in learners with musculoskeletal impairment
Authors: Baygaliev Adilbek , Butabayeva Laura , Autayeva Akbota , Eszhanov Zhaisan , Nishanbayeva Sabira
Published: April 2024

Children frequently suffer from motor impairments   which hinder their development. Every movement requires stability therefore; musculoskeletal malfunction leads to poor movement. Task-oriented training is one of many methods and techniques used to promote motor skills and daily physical activities in children. The present   study's goal is to investigate how task-oriented training contributes to developing motor skills and daily physical activities in learners with cerebral palsy. The study employed a mixed- data collection strategy. The study included a total of 12 students with cerebral palsy. The promotion of a child's motor abilities and regular physical activity can be accomplished with the help of task-oriented training. The study's findings supported our hypothesis that   task-oriented training that has been devised and a series of exercises to increase range of motion (flexibility) led to positive dynamics in all groups of indicators regardless of the severity of the pathology.  The proposed program allowed children to increase muscle strength and range of motion in the joints. Thus, after the experimental work, the functional state of the musculoskeletal system improved   and qualitative and significant changes occurred in the independence of learners. It is suggested that teachers use task-oriented training when instructing school-age children who have this disorder.
Reducing stereotypical behaviors using augmented reality in children with autism spectrum disorder
Authors: Gaber Sherif Adel
Published: April 2024

Augmented reality (AR) has been shown to have a positive impact on children with autism spectrum disorder (ASD) because it can effectively simulate the real environment through interactive experiences created by the integration of digital elements with the outside world. This research aimed to verify the effectiveness of a training program based on AR for reducing stereotypical behavior (SB) in a sample of children with ASD. The study sample consisted of 16 male students with ASD who were enrolled in the Autism Institute in Al-Ahsa, Saudi Arabia, ranging from 8 to 13 years of age. The researcher also developed a training program and employed a quasi-experimental method in addition to research instruments including the Stereotypic Behavior Scale (SBS). The results of the analysis show statistically significant differences between the mean ranks of the participants in the three tests (pre-, post-  and follow-up) on the SBS (x2 = 30.471, p < 0.001)  which indicates the effectiveness of AR in reducing participants’ SB. Additionally, it demonstrates that the training impact lasts for two months after the end of the program. According to the research, AR-based software applications have the potential to improve children with ASD's socialization and interaction abilities. It is recommended to do additional research using larger sample sizes and controlled designs.
Elements affecting primary school teachers' digital competency in Vietnam’s northern mountainous areas
Authors: Nguyen Chuyen Thi Hong , Thu Huong Le Thi , Thuy Duong Lam , Thu Ha Nguyen Thi , Minh Thai Doan Thi
Published: April 2024

This study aims to identify the elements that contribute to the digital competencies of primary school teachers working in the mountainous region of Northern Vietnam and assess the significance of these factors. The research sample consisted of 260 primary school teachers from this region. Exploratory factor analysis (EFA) and multivariate regression methods are used. The results of this research indicate that seven characteristics have a substantial impact on the digital abilities of teachers: ability to incorporate digital technology into teaching,  conditions for digital transformation in teaching and learning activities are found to be influential, ability to create digital resources is highlighted as an important factor,  ability to select teaching content with opportunities for technology usage,  professional development needs of teachers,  school policy  and ability to select digital resources. These results offer education administrators a comprehensive understanding of the factors influencing primary teachers' digital competencies and  enable them to implement strategic changes and prioritize each element. Moreover, this study provides a valuable reference for future researchers seeking to explore new research directions in this field and analyze the correlation between factors to propose solutions to develop digital competencies of primary school teachers suitable to specific contexts and conditions.
INTEGRATION OF AN URBAN TRANSPORTATION SYSTEM AS AN ELEMENT OF MOBILITY PLANS
Authors: BYLINKO Leszek
Published: April 2024

In today’s urban mobility scene, the increasing number of private cars trying to travel through the city centers is one of the most onerous problems facing urban transport. Knowing about the impact that different transport demand management models can have on the efficiency of the urban transport system may be of key importance for developing solutions in this area. This knowledge is the main goal of the considerations undertaken. The observations presented in this article took place during the formation of a Sustainable Urban Mobility Plan (SUMP) for the Bielsko-Biała agglomeration. The author of the article is a member of the working group that prepared the SUMP project for the city. The study examined the effectiveness of mobility planning activities. The scope of these activities included collecting the data necessary to create a mobility plan, analyzing this data, building scenarios in the area of transport demand management, and designing the assessment of the adopted solutions. The article shows the procedure for creating a model of a SUMP for urban areas, which may be a prerequisite for municipal governments for effective applications for funding projects related to transport. The most important part of the analysis is the evaluation using integration indicators of selected key elements of the urban transport system of the Bielsko-Biała agglomeration in the area of transfer accessibility. Such research allows us to answer the question of whether the locations of new railway stops proposed under the agglomeration SUMP contribute to increasing the integration of the urban transport system. The current research implements one of the dimensions of mobility management projects. Related goals are, among other things, to achieve more effective integration of the urban transport system. The analyses were carried out by measuring selected properties of the transport network and a survey questionnaire.
VISUAL ATTENTION OF TRAM DRIVERS AS A STEP TOWARDS INCREASING SAFETY IN PUBLIC TRANSPORT: A COMPARATIVE EYE-TRACKING STUDY BETWEEN NOVICE AND EXPERT TRAM DRIVERS
Authors: WARCHOŁ-JAKUBOWSKA Anna , KREJTZ Krzysztof , SZCZECIŃSKI Patryk , WISIECKA Katarzyna , DUCHOWSKI Andrew T. , KREJTZ Izabela
Published: April 2024

This paper presents an eye-tracking study capturing the dynamics of ambient and focal attention of tram drivers as an application of modern technology in improving their training. Twenty-three experts and twenty-four novices were invited to take part in the eye-tracking study. We explored the visual attention dynamics of tram drivers while they were watching tram-driving simulation videos. The tram driver’s view: The windshields and control panel were defined as areas of interest (AOIs). In line with expectations, experts were more focused than novices and maintained their concentration for a longer time than novice tram drivers. This difference was significant for regions crucial for monitoring the driving environment (the windshields AOIs). Monitoring drivers’ visual attention gives new insights into the process of gaining expertise in scanning the driving environment.
A HARDWARE PLATFORM FOR A MARITIME COLLISION AVOIDANCE SYSTEM
Authors: BROZOVIĆ Vladimir , KEZIĆ Danko , KRILE Srećko , BROZOVIĆ Filip
Published: April 2024

A maritime collision avoidance system built on a database is being developed. Different information important for navigation, like electronic charts, bathymetric data, sea current and forecast weather conditions, etc., as well as knowledge about weather and load-dependent maneuvering capabilities of the involved vessels, are entered into the database tables. When using the system in real-time, the targeted data must be found very quickly in the database. In parallel, for the prediction of ship courses and for the calculation of evasive courses, the system must be capable of solving very many calculations in the shortest possible time, and these calculations often use database tables. Fast communication for updating database tables with the latest data is equally important in such a system. This article briefly presents the hardware developed for the project. We designed such data models for the efficient application of the Postgres database, capable of real-time calculation.
A LANE TRACKING ALGORITHM FOR LOW-COMPUTATIONAL-POWER MICROCONTROLLER-CONTROLLED AUTONOMOUS VEHICLE MODELS
Authors: KOZŁOWSKI Maciej , CZEREPICKI Andrzej , DZIDO Piotr
Published: April 2024

At work, three tasks were presented: road lane detection and trajectory estimation, environment mapping, and the application of a neural network. All these tasks are based on the results of the lane detection method. The presented lane detection method stands out due to the execution of an interpolation transformation for all previously detected edge points. This transformation transfers these points to a “bird’s-eye” coordinate system and distributes them on a grid. Road lanes are identified by a lane feature filter based on the analysis of the distances between unique points. This allows lane views to be obtained in a coordinate system while preserving the distance condition. The road environment map is constructed from the obtained images using a probabilistic algorithm called Distributed Particle-SLAM (DP-SLAM). Based on the map result, a method for representing characteristic points describing the path of road lanes in each incoming camera image has been developed. These points are then used for training the neural network. The neural network solves a regression task for the coordinates of the points on the road lanes, enabling the identification of coefficients for parabolic fitting. Validation has been performed.
RISK BEHAVIORS AMONG DRIVERS: AN ASSESSMENT BASED ON RESEARCH
Authors: ODACHOWSKA-ROGALSKA Ewa , UCIŃSKA Monika , GĄSIOREK Kamila
Published: April 2024

The study was planned to analyze traffic behavior undertaken by drivers, including the emerging so-called awareness gaps. The study was conducted in Poland, and 211 drivers participated in it. The results show many important relationships that could form the basis for proposing effective social campaigns on road safety, including increasing the awareness of drivers as those who have a real impact on its improvement. The analyses confirm the existence of the awareness gap in the examined target group. They also show what kinds of behaviors are considered by drivers to be risky and what kinds of behaviors are aggressive. Moreover, they show the percentage of undesirable behaviors in road traffic and indicate which behaviors are considered by drivers to be the most threatening.
Sugar-Free Herbal Beverage Preferences: Customer Clustering Insights
Authors: Sudaryono Hasna Nadiyah Banafsaj , Widyastuti Hardiana , Sembiring Indra Refipal , Andrianto Mokhamad Syaefudin
Published: April 2024

Amidst the increased demand for public health products caused by the COVID-19 epidemic, Indonesia's herbal business has recognized opportunity for expansion, particularly in the area of sugar-free instant herbal beverages. The purpose of this study is to define customer profiles and identify the factors impacting customers' willingness to pay for such products using a dual technique of cluster analysis and Structural Equation Modeling - Partial Least Squares (SEM-PLS). The study identifies three unique client groups: teen students (Cluster 1), early adult workers (Cluster 2), and late adult workers (Cluster 3). Income, health consciousness, product quality, and price are factors that have a favorable and significant impact on willingness to pay across all clusters. Notably, in Cluster 3, willingness to pay is more influenced by product quality, health consciousness, and price. These findings are useful for the Indonesian herbal business, as they will guide targeted marketing tactics and product development efforts to efficiently serve to varied consumer demographics.
The “Blackpink's” Influence on Oreo Purchases in Indonesia: A Consumptive Behavior Study
Authors: Swastika Karin Regita , Evelina Tri Yulistyawati , Indrianti Titien
Published: April 2024

This quantitative study investigates the influence of consumptive behavior and brand ambassadorship, specifically focusing on the case of Blackpink, on purchasing decisions for Oreo products among Indonesian consumers. Utilizing a deductive research approach, data was gathered through a survey employing a questionnaire administered to 100 Oreo consumers who are Blackpink fans, selected through purposive sampling. Statistical analysis, including t-tests and F-tests, was employed to test hypotheses concerning the impact of consumptive behavior and brand ambassadorship on purchasing decisions. Results indicate that both factors significantly affect consumer purchasing decisions, both individually and collectively. The findings suggest avenues for future research to explore additional variables, such as fanatical behavior influenced by idol brand ambassadors, and to compare the effects of various brand ambassadors over time, thereby offering valuable insights for marketing strategies.
Towards Improved Hospital Services: IS/IT Strategic Recommendations for Muhammadiyah Hospital Based on Cost and Prioritization Analysis
Authors: Ambarwati Rita , Bintang Pamungkas Moch. Ridho
Published: April 2024

This mixed-method study looks into the strategic priorities of information systems and technology (IS/IT) at Muhammadiyah Hospital in Sidoarjo, with a focus on long-term goals and alternative tactics. Using the Ward and Peppard approach, the research seeks to develop strategic suggestions and identify potential future application portfolios. The data was examined using cost-benefit analysis (CBA) and ranked using the Analytical Hierarchy Process. Furthermore, professional viewpoints were acquired through focus group discussions to evaluate IS/IT portfolio recommendations. The findings show that cost parameters play an important role in selecting developmental systems. The study emphasizes the need of using a multi-method approach in IS/IT strategic planning within healthcare, as well as the value of expert input in making good decisions. The findings provide a framework for Muhammadiyah Hospital to improve future services and go forward with key IS/IT projects.
Empowering MSME Employees: Quality of Work Life and Organizational Support
Authors: Izzatunissa  , Hidayah Nur
Published: April 2024

This quantitative study investigates the association between quality of life at work (QWL), perceived organizational support (POS), and employee performance in Kota Magelang's micro, little, and medium-sized firm (MSME) sector. Through a questionnaire issued to 210 MSME employees, with a 100% response rate, the research explores the impact of QWL on both employee performance and POS, as well as the mediating role of POS in the relationship between QWL and employee performance. The findings show a good relationship between QWL and staff performance, as well as a positive influence of QWL on the point of sale. Furthermore, the study emphasizes the mediating role of POS in the relationship between QWL and employee performance. These findings highlight the necessity of improving QWL and POS within MSMEs to support increased employee performance, hence contributing to the economic development of Magelang's City MSME sector.
Fiqh al-Bī'ah and the Concept of Green and Blue Economy for Achieving Sustainable Development in the Context of SDGs
Authors: Latifah Eny
Published: April 2024

This study aims to explore existing literature on Fiqh al-Bī’ah's role in the Green and Blue Economy concepts to achieve Sustainable Development, specifically examining implementation, principles, roles, and objectives aligned with Maqāṣid al-Sharī‘ah. The literature review identified two primary themes: first, the SDGs' foundational principles within the green and blue economy frameworks, and second, Fiqh al-Bī’ah's viewpoint on these economic models. The findings demonstrate the enactment of green and blue economies through SDGs Principles, incorporating people as principal agents in upholding and executing the green and blue economy to realize SDGs across multiple facets, including environmental, social, economic, and legal governance; Planet, which entails diverse measures to safeguard the earth from degradation in terrestrial, marine, and aerial realms; Prosperity, highlighting efforts towards achieving prosperity through economic, social, and technological initiatives; Peace, emphasizing endeavors towards establishing peace, justice, and an inclusive society free from fear and violence, alongside securing environmental safety; and Partnership, involving collaborative efforts in global development with both government and non-government entities to maintain and conserve the environment. Additionally, Fiqh al-Bī’ah in the Green Economy is characterized by safeguarding the body and soul, aligning worldly and afterlife goals, ensuring balanced production and consumption, preserving ecosystem equilibrium, upholding the dignity of all beings, and humans fulfilling their stewardship on earth. The Blue Economy includes Zero Waste, ecosystem protection, promoting environmental cleanliness and friendliness, resource utilization efficiency, and encouraging social inclusiveness and employment creation.
Entre o falar e o fazer: AÇÃO VERBAL e AÇAO MATERIAL como parâmetros contextuais
Authors: Farhat Theodoro C. , Gonçalves-Segundo Paulo Roberto
Published: April 2024

Com o objetivo de fundamentar análises contextuais detalhadas, empiricamente testáveis e comparáveis, este artigo, amparado nos princípios da Linguística Sistêmico-Funcional, apresenta a descrição paradigmática de dois sistemas contextuais do parâmetro de campo: AÇÃO VERBAL e AÇÃO MATERIAL. Em primeiro lugar, localizamos tais sistemas, baseados nos trabalhos de Hasan (1999, 2014, 2020), em relação às dimensões globais de estratificação, instanciação e metafunção; depois, explicitamos as opções de cada sistema e suas potenciais inter-relações; discutimos, então, como se pode chegar a princípios realizacionais restritos a graus intermediários da escala de instanciação; depois, ilustramos como os subsistemas podem ser utilizados para descrever contextos de situação e, assim, possivelmente chegar a generalizações contextuais (no caso, o contexto global de um grupo de Facebook); por fim, fazemos considerações sobre como a proposta apresentada se relaciona com a descrição topológica de Matthiessen do parâmetro de campo, indicando convergências, divergências e complementaridades
Innovate, renovate, or transform? A critical and reflective look at english teaching in a brazilian public school amid covid-19 pandemic: a sociocultural and appraisal of emotions perspective
Authors: Barbosa Selma Maria Abdalla Dias , Bedran Patrícia Fabiana , Maia Regina Sousa , Marcano Mery Carolina Andrades
Published: April 2024

This study aimed to conduct a critical-reflexive analysis of discourse within English Language Teaching through the lens of Emotion-based Assessment Processes, focusing on an English teacher’s understanding of the terms innovation, renewal, and transformation inherent in the teaching and learning process, during the pandemic context of COVID-19 in Brazil. The research instruments used consisted of two online questionnaires with open-ended questions. This study was conducted from a sociocultural perspective, exploring the interactions between emotions and cognition, as described by Vygotsky (2001, 2010), Damásio (2004), Scherer (2005), Johnson (2009), and Pavlenko (2013). We adopted a qualitative ethnographic methodology within the frameworks of Transdisciplinary and Interdisciplinary Applied Linguistics, wherein we emphasize the construction of knowledge within a decolonial episteme concerning hegemonic power, as well as valuing the voices of the Global South with their cultural, economic, and social diversities. The research unveiled how emotions influence a teacher’s decision-making process. Furthermore, it underscored the importance of teachers incorporating innovation, transformation, and renewal into their teaching practices. This adaptability is crucial for addressing challenges imposed by external factors such as the pandemic or internal factors like resource limitations, enabling teachers to anticipate solutions for future problems.
O percurso de duas professoras em ações colaborativas para a inclusão de uma aluna autista na aula de língua estrangeira
Authors: Borges-Almeida Vanessa , Resende Cristiane
Published: April 2024

Este artigo apresenta resultados de uma investigação de natureza aplicada, abordagem qualitativa e fins exploratórios, e tem como objetivo descrever e discutir o percurso que uma professora regente e uma professora pesquisadora trilharam para chegar a ações colaborativas que promovessem a inclusão de uma aprendiz autista nas aulas de língua inglesa num centro de línguas público brasileiro. A discussão está pautada nas bases teóricas do paradigma reflexivo de Schön (1983) e nos estudos sobre colaboração docente (Oliveira, 2008; Dutra, 2014). Trata-se de uma pesquisa-ação colaborativa, cujos dados foram coletados por meio de entrevistas, observação participante, gravações de aula, notas de campo, análise documental, fotografias e gravações de encontros reflexivos entre as duas professoras. Os resultados observados foram a aquisição de conhecimentos sobre o transtorno do espectro autista e sobre estratégias para adaptações e acomodações para a inclusão, que exerceram um impacto positivo sobre as ações pedagógicas. Nesse processo de aprender a colaborar, as duas professoras tiveram de refletir para encontrar seus papéis necessários nos diferentes estágios da pesquisa
Enhancing Pressure Transient Analysis with Automatic Model Identification: A Machine Learning Approach
Authors: Nukala S. T. , Kumar A. , Rajput S. , Lopes V. S. , Wydiabhakti T. B.
Published: April 2024

Over its historical trajectory, Pressure Transient Analysis (PTA) has experienced a notable evolution, commencing with early techniques like straight-line analysis and type curve matching. The mid-20th century witnessed the introduction of pressure derivatives, enhancing the sophistication of reservoir behavior interpretation. Deconvolution methods took center stage in the late 20th century, offering intricate insights into wellbore and reservoir responses. In the contemporary era of PTA, log-log analysis has become the norm, featuring the plotting of pressure and its derivatives on logarithmic scales. Recent strides in the field concentrate on the integration of automation and machine learning to expedite PTA processes.

Our methodology enhances the Pressure Transient Analysis (PTA) process by leveraging a framework based on triplet loss. This architecture seamlessly integrates Convolutional Neural Network (CNN) layers, providing robust feature extraction capabilities for the automated analysis of pressure transient data. The model is trained using simulated experimental data generated through a systematic Design of Experiments (DOE) approach. This involves incorporating the ten most prevalent interpretation scenarios, encompassing well, reservoir, and boundary model types. For each model type, critical parameters such as permeability, horizontal well length, skin factor, and distance to the boundary are systematically sampled, resulting in the computation of 800 distinct pressure derivative responses.

The triplet loss framework adopts a self-supervised training strategy, where anchor, positive and negative pairs are dynamically generated from the simulated training dataset. The loss function encourages the network to reduce the distance between the anchor and positive examples while increasing the distance between the anchor and negative examples.

The experimental analysis revealed that the actual model class consistently ranked high among the top classes. The model exhibits an accuracy rate of 90% in providing the top-ranked model recommendations when evaluated on 100 samples derived from the 8 interpretation scenarios. Having prior knowledge about the most probable well test models at the top ranks diminishes the manual effort required for analysis.

This approach can expedite the identification of the pressure derivative response associated with specific combinations of well, reservoir, and boundary models, leading to the generation of models with reduced reliance on user interaction. The methodology streamlines the recognition of models for interpretation engineers, enabling faster integration with additional information from diverse sources like geophysics, geology, petrophysics, drilling, and production logging.
A Data-Driven Journey into Liquid Loading Detection and Prediction
Authors: Sinha Utkarsh , Chauhan Prithvi Singh , Zalavadia Hardikkumar , Adil Arsalan , Sankaran Sathish
Published: April 2024

Liquid loading is a persistent challenge encountered in onshore and offshore gas wells, particularly at low gas rates, where the accumulation of wellbore liquids leads to flow instabilities, operational disruptions, prolonged shut-ins leading to early well abandonment and reduced overall recovery. Typical liquid loading mitigation strategies such as velocity strings, well cycling, intermittent or permanent artificial lift, surfactants/soaps etc. involve additional cost and therefore, their operational success relies on selecting the right wells with proper understanding of expected critical rates at the right time. Models based on droplet, film or multiphase transient flow can be used to model liquid loading phenomenon. However, empirical correlations are used commonly to detect liquid loading, which often lack precision in field applications due to oversimplified assumptions regarding liquid behavior and flow regime consistency.

In this work, we introduce an innovative data-driven approach for liquid loading detection and prediction (LLDP) that harnesses high-frequency gas rate and tubing head pressure measurements to identify the onset of liquid loading and use it to correct critical rates computed by empirical methods. The LLDP methodology involves the computation of diagnostic statistical proxy features, enabling the characterization of flow instability arising from liquid loading. Upon detection, subsequent adjustment to gas rates via feedback control facilitate the determination of corrected critical rate by calibration of empirical correlations such as Turner and Coleman. This also allows us to predict when the reservoir energy will no longer be sufficient to lift the liquids combined with the corrected critical gas curve and estimate time to liquid loading.

Through extensive application across various unconventional and conventional gas fields, the LLDP method has consistently matched detected liquid loading events with manual field observations, eliminating biases and subjective interpretations. In a specific case study, the utilization of adjusted critical rates to optimize gas lift operations resulted in substantial cost savings by minimizing the need for buy-back gas. In another example, the detection of liquid loading and prediction helped optimize onshore gas well operations and field management practices.

This presentation highlights a rapid and systematic approach for the detection, quantification, and prediction of liquid loading, utilizing readily available field data without relying on assumptions. By accurately identifying critical gas rates and optimizing artificial lift configurations, the LLDP method offers a practical solution to the challenges posed by liquid loading in gas wells, ultimately enhancing operational efficiency and maximizing production.
A Real Time Cloud-Based Transient Modeling of Wellbore Fluids Enabling Safer Deep Transient Testing
Authors: Lopes Velerian Sanjao , Kumar Arvind , Nukala Poorna Venkata Sai Teja , Wydiabhakti Tety Benedicta
Published: April 2024

Wellbore dynamics is one of the key factors in reservoir testing, acting as a bridge between the reservoir and surface measurements. The objective of this research is to address the challenges encountered in well control and highlight the outcomes of employing wellbore dynamic simulation to enhance the safety of formation tester (FT) sampling and deep transient tests (DTT) conducted in wells, with a special emphasis on pre-job simulations multi-parameter sensitivity analysis. This effort is geared towards advancing our comprehension of the interaction between hydrocarbons and wellbore mud during and following FT pump-out operations. The most recent advancement in DTT technology allows for the pumping of a larger volume of hydrocarbons into the wellbore, when compared to the operation of a conventional formation tester. While conducting DTT, formation fluids pumped from the well are mixed with drilling mud from the surface through a circulation sub into the annulus. This mixture of fluids is then circulated out from the annulus to the surface during the flowing period. It is imperative to possess a thorough comprehension of these procedures to ensure well control safety. Consequently, the utilization of a dynamic multiphase flow simulator that considers the interactions between downhole pumped hydrocarbons and drilling fluids becomes crucial to enhance the accuracy of pressure simulations during the DTT operation. Given the paramount importance of safety in oil and gas operations, a cloud-based wellbore dynamics simulator enables precise quantification of drilling fluid adjustments, circulation rates, hydrocarbon composition, downhole pump rates, well depth, hole diameter, overbalance pressure, and pump duration for various FT design sequences. This allows for accurate forecasting of downhole well pressure and the distribution of free gas throughout the well, adjusting these parameters as needed. Subsequently, we will explore scenarios with kick potential and risk mitigation strategies. This paper showcases a total of 15 case studies (different hydrocarbon types and overbalance scenarios), where cloud-based wellbore fluid simulations were performed for different flow rate scenarios, and to predict the potential well control situations. A special emphasis was given to the near critical hydrocarbon fluids such as condensate, volatile oil, and wet gas.
Efficient and Sustainable Scale Removal: Unveiling the Power of Pressure Pulsing in Restoring Wellbore Accessibility
Authors: Aljauydi H. S. , Mehmood S. X. , Aljuaid B. M. , Abouakar A. H.
Published: April 2024

This study aims to investigate the safe and environmentally friendly application of pressure pulsing technique for effectively removing calcium sulphate scale (CSS) blockages in wellbores. The objective is to assess the ability of the pulsing tool to restore full wellbore accessibility while minimizing the carbon footprint.

The pressure pulsing tool utilized a combination of slickwater and gel to create a controlled water hammering effect, which facilitates the disruption of sand bridges, loosens particles, and clears blockages. Implemented with a four-port configuration, the tool expels fluids downward and outward, effectively eroding the CSS blockage through cavitation erosion. This process ensures a clean and accessible wellbore while promoting safety and reducing the carbon footprint.

The pressure pulsing technique successfully eliminated 41 feet of wellbore blockage, corresponding to the removal of 140 kg of accumulated CSS. This mechanical action, driven by cavitational erosion, proved crucial in the cleaning process. Further analysis revealed that the pulsing tool's optimized operational parameters led to increased penetration rates and improved removal efficiency. By employing the pressure pulsing technique, the study provides a safe, effective, and environmentally conscious solution for addressing CSS blockages, thereby enhancing well productivity and reducing the carbon footprint.

This study presents a pioneering approach using pressure pulsing technique to safely remove and clean CSS blockages in wellbores. By prioritizing safety and environmental consciousness, the application of this technique contributes to the reduction of potential hazards and the overall carbon footprint in the oil and gas industry. The findings provide valuable insights into improving operational practices and demonstrating the effectiveness of pressure pulsing as an eco-friendly solution for maintaining wellbore accessibility.
Carbon Sequestration in Mid Ocean Ridge Hydrothermal Systems
Authors: Croft Gregory D.
Published: April 2024

The objective of this paper is to explore a novel environment for carbon sequestration. Mid ocean ridge hydrothermal systems flow enormous volumes of water through vesicular porosity and natural fracture systems in basalt. Since the basic premise of carbon mineralization projects is to dissolve carbon dioxide in water and react the resulting carbonate ions with minerals in mafic or ultramafic igneous rock, the presence of so much natural flow through such rocks presents an opportunity. The proposed concept is to inject carbon dioxide in or near natural seawater intakes associated with these hydrothermal systems. Snæbjörnsdóttir and Gislason (2016) assessed the carbon dioxide sequestration potential in basalt offshore Iceland and concluded that up to 7000 GtCO2 could be stored offshore Iceland within its exclusive economic zone, so volumes of basalt are not a limiting factor.
Formation Evaluation and Behind Casing Opportunity Analysis Using Multi-Output Regression and Machine Learning Techniques
Authors: Hassani H. , Shahbazi A. , Fadhli M. Z. , Hamdi Z. , Hassan A. M. , Masoudi R. , Bataee M.
Published: April 2024

Generally, Behind Casing Opportunity (BCO) provides a good alternative to maximize brownfield production by enabling access to the remaining oil targets behind existing completion. Proper BCO maturation which includes minor reservoir unit analysis may offer a high return, low-risk item in terms of obtaining cheap oil at low cost. Unfortunately, a lack of proper resources such as possible manpower and budget constraints may pose a challenge for proper BCO analysis. A novel application of multioutput regression Random Forest algorithm to predict both BCO and fluid code for BCO determination marks a good start for further implementation of machine learning to tackle this problem. The multi-output model enables two or more variables to be predicted hence allowing uniformed prediction rules and time-saving alternatives. Exploratory data analysis (EDA) and required data preprocessing were carried out to provide excellent inputs for the algorithm. The algorithm produced two outputs of predicted BCO and fluid code with root mean squared error (RMSE) of 0.0933 and R2 of 0.9619. To properly support the logic of the model prediction, the log curve of both predicted values was plotted and the rationale behind the predicted result was observed. Besides, a good cross-plot correlation of both the predicted and actual value of the outputs also aided in further validating the result. The research potentially can help to further enhance BCO analysis by giving robust and very effective methods for both BCO and fluid detection. Furthermore, predicting fluid code helps for proper reservoir analysis hence providing a time-saving alternative for better drilling decisions.
Improving Production and Hydrocarbon Recovery from Viscous Oil Reservoirs in Ecuador While Minimizing the Carbon Intensity of Production Using AICD Technology
Authors: Konopczynski Michael , Grefa Martina , Castillo Martha , Villavicencio Angel , Solano Maurilio , Chanaga Arlen
Published: April 2024

This paper describes an integrated workflow used to evaluate the potential improvement in oil production and hydrocarbon recovery with the implementation of AICD completions in these fields, the completion designs and implementation, and post installation well performance. This paper summarizes the technical learnings from this project. In addition, the paper describes the potential reduction in carbon intensity of the produced crude by significant reduction in the energy used to lift, process and dispose of produced water.
Optimizing Injection Well Trajectory to Maximize Storage Security and Minimize Geomechanical Risk
Authors: Li Y. , ONeal R. , Whitezell M. , Kovscek A. R.
Published: April 2024

The objective is to demonstrate an optimal well design for a potential geological carbon storage (GCS) project. CO2 plume shape, size, and pressure response in the subsurface are design variables. The chosen well trajectory improves injectivity while minimizing formation pressure buildup. The CO2 plume shape and migration are controlled within a complex dipping storage formation. In order to achieve the goals, we designed a toolbox (pyCMG) to standardize the well design optimization process that is applicable to different carbon storage assets. This toolbox is helpful to maximize storage security and minimize geomechanical risk. We developed a numerical model of transport within a storage formation fully coupled with geomechanical deformation to represent a prospective GCS site in Kern County, California. It honors a pre-defined injection scheme with injection rates that ramp up and then decline for a total of 12.3 Mt of CO2 injection in 18 years. The peak injection rate is greater than 1 Mt/yr whereas the post injection period is 100 years. The pyCMG toolbox allows efficient computations for hundreds of cases. It is useful to understand potential outcomes and optimize the well trajectory to fulfill plume and pressure buildup constraints while satisfying the target inject amount.

We propose to develop a long, deviated injection well to best address the injectivity and plume migration challenges for this heterogeneous, dipping formation. The well design optimization successfully reduces the pressure build-up by 54% over the base design while only increasing the areal extent of the plume by 8.4%. We quantified the carbon dioxide plume shape and size at the land surface. The plume grows rapidly at the beginning due to injection, it increases slightly after shut-in due to slow up-dip migration driven by buoyancy, and becomes stationary within the post-injection monitoring period. The optimal injector design balances the optimization goals of CO2 plume size, pressure increase in storage formation, and pressure build-up at fault. The optimal well is robust under uncertainties from injection schemes and geological model realizations. The best injector is capable to enlarge the total storage amount with an average of annual injection rates greater than 1 Mt/yr. Rock deformation due to the pressure buildup is also computed. The maximum land uplift is predicted to be 2.1 cm during the year of the peak annual injection rate. Land surface uplift strongly correlates with the subsurface pressure response.
Predicting Future Heat Outputs from Enhanced Geothermal System Utilizing Machine Learning Approach
Authors: Nath Fatick , Romero Nora A Garcia , Cabezudo Eleazar , Sutradhar Shaon , Cisneros Erik , Portillo Orlando , Gindic Ronen
Published: April 2024

The Earth is a vast energy reservoir. The U.S. Department of Energy estimates that harnessing just 0.1% of the Earth's geothermal energy can power humanity for 2 million years. The energy sector has shown a significant interest in geothermal energy owing to its advancements in renewable energy, environmental friendliness, and widespread accessibility. An improved geothermal system (EGS) efficiently extracts heat from deep hot dry rock (HDR). However, EGS is battling to ensure safe drilling and appropriate fracturing to extract heat potential. Essential aspects to evaluate are deformation and fracture face damage during induced fracturing in order to extract heat energy from HDR, due to its heterogeneities. This study examines and predicts future heat outputs from EGS utilizing machine learning.

The UTAH FORGE well, 16B (78)-32, provided the well logs and petrophysical characteristics. The single-well data was divided into three categories: training, testing, and validation, with a 70:20:10 ratio. The model was built using eleven well-log variables in total, including anisotropy in heat, density, porosity, Poisson ratio, compressional and shear travel times, and SP and GR. Machine Learning model (ML), Decision Tree (DT) and Random Forest (RF) model were constructed, and an optimization technique was employed to ascertain the hyperparameters of the ideal model for heat production prediction.

The pair plot indicates that there is no discernible noise present in the recorded data, and the correlation matrix illustrates a perfect correlation (unity) between temperature and depth. The machine learning model exhibited outstanding performance in forecasting the future temperature of the geothermal reservoir. Both Random Forest (RF) and Decision Tree (DT) models displayed exceptional accuracy, achieving R2 scores exceeding 98% with RMSE values below 3%. Particularly, the Random Forest model surpassed traditional approaches, achieving an accuracy of approximately 99.7%. These results suggest that these models remain capable of generating reliable and useful projections.