bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Correlation between the Weight of Ovary, Number of Follicles, and Quality of Oocytes of Culling Female Bovine in Slaughterhouse
Authors: Chandramohan Koshini , Utama Suzanita , Lestari Tita Damayanti , Rimayanti  , Safitri Erma , Hestianah Eka Pramyrtha , Mulyati Sri , Damayanti Ratna , Khairullah Aswin Rafif , Hasib Abdullah 
Published: September 2024

The purpose of this research was to determine the correlation between the weight of the ovary, the number of follicles, and the quality of the oocytes from the culling female bovine obtained from the slaughterhouse. The variation may affect the potential of the ovary to produce follicles. Paired ovaries were obtained from female bovines. Follicle numbers were recorded and divided into three size categories (small: 3 mm, medium: < 3 mm-8 mm, and large: > 8 mm). Oocytes were aspirated and the number of oocytes was recorded and graded into four categories (grades A, B, C, and D). There was a positive correlation between the weight of the ovary and the number of follicles, which is 0.560 with the regression equation y = 3.52 + 0.501 x. There was a positive correlation between the number of follicles and the number of oocytes, which is 0.546 with the regression equation y =2.48 + 1.204 x. There was a positive correlation between the number of oocytes and the grade of oocytes, which is 0.520, with the regression equation y = 0.93 + 0.800 x. There was no correlation between the weight of the ovary and oocyte grade A, which is 0.013.
Case Report: Cryptocaryonosis in Indian Ocean Oriental Sweetlips (Plectorhinchus vittatus) Fish at the Closed System Quarantine of the Jakarta Aquarium and Safari
Authors: Mursalim, drh., M.Kes., Ph.D Muhammad Fadhlullah , Ramli Aqidatul Izza , Mustakdir Zulfikri , Suharto Rian Hari 
Published: September 2024

Cryptocaryon irritans, known as cryptocaryonosis disease infection in fish, is a significant problem for aquarists because they not only cause the disease but also lead to high mortality in the aquarium population. This case report aims to identify Cryptocaryon irritans infection in four Indian Ocean oriental sweetlips at the Jakarta Aquarium and Safari. Before they died, a total of four fish showed signs of weakness, scratching, excessive mucus, and pale gills. The diagnosis was confirmed through clinical assessment, physical examination, and microscopic analysis of skin scrape and gill clip samples, which revealed the presence of numerous trophonts (the young immature stages) of C. irritans. These findings underscore the importance of vigilant monitoring and prompt intervention to mitigate the impact of C. irritans, especially on marine aquarium fish populations.
A Case Report: Treatment of Anaplasmosis and Ectoparasitic Infestation in Mixed-Breed Golden Retriever Dog
Authors: Situmorang Fernando Jose Immanuel Clinton , Suartha I Nyoman , Jayanti Putu Devi 
Published: September 2024

Anaplasmosis is a disease in dogs caused by intracellular gram-negative bacteria belonging to the Anaplasmataceae family. A 6-month-old mixed-breed golden retriever was examined at the Laboratory of Veterinary Internal Medicine, Faculty of Veterinary Medicine, Udayana University, with complaints of itching, tick infestation, weakness, and decreased appetite. The clinical examination revealed pale mucous membranes in the mouth and eye conjunctiva, as well as an infestation of Rhipicephalus ticks on the skin. Routine hematological examination indicated the presence of anemia and thrombocytopenia. Blood smear examination confirmed the presence of Anaplasma sp. Treatment was provided in a causative and supportive manner. Causative therapy involved the administration of doxycycline at a dose of 10 mg/kg body weight orally for twenty-eight days, ivermectin at a dose of 0.2 mg/kg body weight injected subcutaneously every two weeks for four weeks. Supportive therapy included the daily administration of Fufang E'jiao Jiang ®(Dong E Ejiao Co, Ltd., Shandong, China) at 2 ml/day and Sangobion® (PT. Merck Tbk, Jakarta, Indonesia) at one tablet per day for fourteen days. Treatment with doxycycline, ivermectin, Fufang E'jiao Jiang® (Dong E Ejiao Co, Ltd., Shandong, China), and Sangobion® (PT. Merck Tbk, Jakarta, Indonesia) resulted in a positive outcome for the dog, with improved activity, hair growth, good appetite, and the absence of ticks.
Design of Religious Moderation Education in Muhammadiyah Middle School and Ma'arif NU Middle School Educational Institutions
Authors: Umam Khairul , Karim Abdul , Abidin Zainal 
Published: September 2024

<span lang="EN-US">This study aims to analyze the application of religious moderation education curriculum design in educational institutions, including Mandiri Berbagi and Mandiri Berubah Curriculum Models, collaborative and separate curriculum design, and hidden curriculum design in SMP Muhammadiyah 6 Wuluh and SMP 09 Ma'arif NU Ambulu in Jember. This study used a qualitative approach with the type of case study to describe and analyze the design of religious moderation education in educational institutions. Data collection was conducted by observing the activities of teachers and principals in designing a religious moderation education curriculum. At the same time, interviews were carried out with the principal, subject teacher, and the vice principal of curriculum involved in the design of religious moderation education. Data analysis follows the Miles, Huberman, and Saldana models, including data condensation, data presentation, and inference. Furthermore, the validity of the data was ensured using source and technical triangulation. The findings of this study revealed 1) the application of religious moderation education curriculum with Mandiri Berbagi and Mandiri Berubah Curriculum Models, 2) the design of moderation education curriculum with collaborative model of ISMUBARIS (Islam, to-Muhammadiyah, Arabic and Islamic Cultural History) and a separate model between religious education and the teachings of Nahdatul Ulama, and 3) hidden curriculum on all subjects with the message of Islam wasathiyah and moderate Islamic messages of an-Nahdiya. This research contributes to policymakers, such as the government, the Ministry of Education and Culture, the Ministry of Religion, and all educational institutions, such as junior high schools and MTs, in implementing religious moderation education for application in the curriculum and learning of Islam.</span>
Experimental and Numerical Investigation of Solids Transport in a Wellbore using Gauge Measurements Complemented with Fiber-Optic DTS
Authors: Shetty Rishikesh , Sharma Jyotsna , Tyagi Mayank , Santos Otto 
Published: September 2024

Summary
Solids detection and monitoring are critical for maintaining wellbore integrity and efficiency in hydrocarbon production. This study investigates the real-time detection and analysis of solids transport in a full-scale wellbore, using a combination of gauge measurements and fiber-optic distributed temperature sensor (DTS) data. The experiments are conducted in a 5163-ft deep wellbore filled with synthetic oil-based mud. The study involves monitoring the movement of solids-laden mud during circulation tests, with data collected from both downhole and surface pressure gauges as well as density measurements using a Coriolis meter. The experimental results were compared with numerical simulation predictions using an in-house program and commercial software, DrillSIMTM. The results show a good agreement between the experimental data, including the DTS measurements, and the numerical predictions, providing valuable insights into the dynamics of solids transport in multiphase flow systems under well-scale conditions. This underscores the potential for enhanced solids management and optimization through advanced monitoring techniques. Traditional methods face challenges in real-time detection and characterization, especially under complex flow conditions. The results of this study highlight the advantages of fiber-optic sensing technologies, such as DTS, which offer high-resolution spatial and temporal data, improved reliability under harsh conditions, and a comprehensive understanding of flow dynamics. By integrating traditional gauge measurements with fiber-optic sensor data and validated numerical models, this research provides a robust framework for optimizing solids management in oil and gas operations under a variety of field conditions.
AI-Driven Optimization of Refinery Configurations: A Novel Approach to Predicting Production Outputs and Capacities
Authors: Valliyatt Minas Poyil , Tharayil Sarafudheen M. , Razhi Abdulilah A. , AlQarni Shouq , AlThubaiti Leen 
Published: September 2024

Abstract
In the context of conceptualization and operation of refineries, achieving an optimal configuration emerges as a critical endeavor. Our proposed methodology transcends conventional approaches by seamlessly integrating domain expertise, empirical insights, and cutting-edge artificial intelligence (AI). Our approach holistically captures the intricate linkages between different refinery process facilities (also referred as process units or modules in later part of this paper) to make their best use in ever changing market conditions. Key aspects include robust predictive modeling for individual modules, meticulously considering feedstock availability, product demand, price information, process interdependencies and historical data. These predictions serve as foundational inputs during the conceptualization and planning stages, guiding optimal configuration decisions. Additionally, our rigorous cost modeling extends beyond capital costs to encompass financial parameters sufficient for shortlisting of configuration options for detailed economic evaluation. The machine learning models are evaluated based on the error metrices and has confirmed the models performs with in the acceptable tolerance ranges. Moreover, our integration of Large Language Models (LLMs) adeptly transforms complex refinery configurations into actionable insights expressed in business language. Decision-makers gain a holistic view, aligning technical choices with overarching organizational goals. Ultimately, this pioneering approach eases conceptualization process of new refineries and empowers operating refineries toward sustainable production and refinery-wide optimization.
Automating Drilling Practices to Compensate for Interactions Between Tool Joints and the Rotating Head
Authors: Eng David Forrest P. , Fischer Raymond , Waldner James , Eddy Aaron , Eng Sean Scotvold P. , Eng Cristian Tibrea P. , Fernandes Ashley 
Published: September 2024

Abstract
The use of managed pressure drilling (MPD) equipment on North America land rigs has become more common over the past several years. Standard and heavy weight drill pipe tool joints require more weight to pass through the rotating head than the pipe bodies. The negative impacts of this phenomena on both rate of penetration (ROP) and downhole dynamics have been previously studied and published. Various methods of manually adjusting AutoDriller setpoints have been presented as industry best practices. This paper presents the automation of industry best practices through the rig's process control system. Implementation and scaling across a rig fleet will also be discussed.
Using a patented process (Scotvold et al. 2020), an application was developed to run on the rig's process control system, where AutoDriller setpoints are automatically adjusted as the tool joints pass through the rotating head on each stand. Different methods of AutoDriller control can be utilized to achieve the intended result. Design of the application to minimize human error when configuring for specific pipe will be a focus, as well as challenges encountered with this in the past.
Numerous examples, methods, and control methods such as manually adding weight across tool joints, using ROP as a control method, and automating the process with different logic will be compared. Analysis of these scenarios will demonstrate the value of consistency by removing as much human intervention and setup from the operation as possible.
This paper presents the full automation of industry best practices that have historically been conducted through repetitive manual tasks. In addition, there is a strong focus on improving system autonomy going forward to minimize the level of human intervention and setup that is required for optimal performance while drilling with MPD equipment. Ease of scalability for automating this process will also be discussed as it was a major consideration when developing the application.
Novel Method for Automated Advanced Mud Gas Extraction Efficiency Correction (EEC) Characterization in Near Real Time
Authors: Ritzmann N. , Mueller T. , Erdmann S. , Says I. 
Published: September 2024

Abstract
Advanced mud gas logging is progressing to a more established service throughout the industry over the last two decades. It is more and more recognized as a highly valuable addition to standard and advanced downhole logging data and can be used to a certain extent as a continuous formation fluid composition log often comparing well with pressure volume temperature (PVT) fluid sample analysis. Compared to basic mud gas data, the process involves several correction layers starting from a booster dilution and contamination over to recycled gas correction until the final layer of the extraction efficiency correction (EEC). For this last step a new, fast, and online methodology has been developed and will be presented here together with comparison results between PVT data and corresponding, fully corrected, mud gas data. Mud gas is extracted from drilling mud at surface and measured with gas chromatographs, focusing on the hydrocarbon compounds up to C8s. The boiling point and the interaction of the components is different for each one of them and can be to a certain extent correlated to the number of carbons in the molecule. To derive PVT like quantification, up to normal pentane it is critical to accurately determine the extraction efficiency for each component and to be able to respond in case of fluid changes. Therefore, a fully automatic method is presented that determines the EEC on live mud samples in less than 10 minutes any time a significant change to the mud system is made. The method isolates a fixed volume of mud inside the equipment's extraction chamber and derives the correction coefficients by the integral of concentration extracted compared to a reference integral from before the test was started. This simple and fast method enables the methodology to quickly respond to necessary changes.
Several case studies from water as well as oil-based mud demonstrate the applicability of the newly introduced method and unlock the full potential of advanced mud gas data up to normal-pentane.
Minimizing Greenhouse Gas Footprint of Enhanced Oil Recovery Operations Through Optimizing Injected Fluid Composition
Authors: Olofinnika O. A. , Selveindran A. , Okoroafor E. R. 
Published: September 2024

Abstract
Most oil and gas fields face the dual challenge of optimizing recovery and minimizing CO2 and greenhouse gas footprint from depleting fields. Although tertiary recovery strategies including CO2 and produced gas injection are adopted, the cost and miscibility uncertainty associated with pure CO2 and produced gas streams remains a challenge. Therefore, this paper assesses the impact of pure and blended compositions of produced gas and CO2 in simultaneously improving the oil recovery efficiency and minimizing the GHG footprint of petroleum development projects.
We performed an experimental coreflood of a single-stage water alternating gas flood using CO2. Carbonate cores and crude oil with properties typical to a Permian field were studied. X-ray computed tomography (CT) before and after gas injection enabled investigations of fluid retention at the core scale. A sample field model was applied to investigate the impact of injected fluid composition on field-scale GHG reduction and oil recovery.
We observed increased CO2 storage in the optimal produced gas and CO2 blend compared to pure CO2 injection. We benchmarked the GHG emissions and oil recovery across differing injected gas compositions at the end of the WAG flood against a base case of waterflooding only. Our results revealed lower emissions and high recovery by switching to an optimal injection composition. The results suggest optimal compositions of produced gases and CO2 exist with a capacity to further improve the oil recovery and storage efficiency of CO2 while minimizing the overall GHG footprint of oil and gas operations.
We demonstrate experimentally how alteration of injected fluid composition can simultaneously increase oil recovery, reduce GHG emissions, and increase CO2 storage capacity. Adoption of this work has the potential to mitigate the flaring of produced gases and costs associated with pure CO2 injection while ensuring low carbon footprint operations in the oil and gas sector.
Machine-Learning Workflow for Fracture Geometry Characterization Using High-Resolution Distributed Strain Sensing During Well Production
Authors: Ma Wei , Wu Kan , Jin Ge 
Published: September 2024

AbstractRayleigh Frequency Shift Distributed Strain Sensing (RFS-DSS) has emerged as a crucial technique for characterizing fracture geometry in unconventional reservoirs by measuring strain responses along optical fibers. Several numerical modeling studies have been conducted to relate the RFS-DSS strain data to the fracture geometry and then to estimate the production performance. However, the issue of solution non-uniqueness remains unaddressed. Multiple combinations of fracture properties can potentially generate identical strain responses, introducing significant uncertainty in interpretation. The objective of this paper is to develop an integrated artificial intelligence (AI) assisted workflow to calibrate uncertain parameters and automatically history match field-measured strain responses and then estimate the well production performance.The workflow is summarized as follows: First, the uncertain parameters and objectives are identified for this study. Uncertainty analysis is then conducted to investigate the impact of these parameters on strain change objectives. Initial numerical cases are generated using the Latin Hypercube Sampling (LHS) method. These cases are subsequently simulated using a coupled fluid flow and geomechanics simulator during production. Next, four strain change objectives, peak value, minimum strain, strain area, and strain width, are calculated, and efficient machine learning models are constructed as proxies for the simulator. Different machine learning models are developed for predicting the strain change objectives: Neural Network (NN) models for peak value, minimum strain, and strain area, and XGBoost for strain width. The Markov Chain Monte Carlo (MCMC) algorithm is implemented in conjunction with these proxy models to identify appropriate candidate samples from the posterior distributions. The P50 solution is then derived after rigorous history matching. Our AI-driven workflow demonstrates remarkable computational efficiency, capable of proposing 50,000 samples and generating comprehensive posterior distributions in less than 20 minutes.Validation of the workflow using synthetic cases reveals that the P50 solutions of fracture geometry derived from the posteriors show excellent agreement with the true fracture geometry. The four strain change objectives calculated using the P50 solutions align closely with the true values of the strain change objectives. The results of this study demonstrate the accuracy and robustness of this workflow for predicting strain change objectives and automatically history-matching field-measured strain changes. Furthermore, for field applications, after history matching the measured strain using this workflow to obtain the fracture geometry, we can then estimate production profiles for various completion designs, providing valuable guidance for optimizing completion design and evaluating production performance.
Management as a Technical Discipline in Energy
Authors: Capello Maria Angela , Howes C. Susan , Kirkham Peter , Calleberg Amanda , Nandurdikar Neeraj , Swami Gautam 
Published: September 2024

Abstract
Management is a technical discipline that requires a solid knowledge base and a constant learning approach. Management Practitioners need to master various domains such as Asset and Portfolio Management, Risk Management and Decision-Making, Strategic Planning and Management, Energy Economics, Professionalism, Training, and Education to support an efficient decision-making process, and quantify the risks involved. This paper explores how the practice of management has evolved in the Oil and Gas sector, and the relevance of creating standards or guidelines to guide its practitioners.
The term "Management" is usually associated with people skills, whereas the methodologies of technical disciplines of management are well-known in the energy sector. Our paper focuses on five of the 29 technical sub-disciplines of the SPE taxonomy (Society of Petroleum Engineers [SPE], n.d.) of Management, showing their evolution through time and the progress of related roles in the industry. We highlight challenges and opportunities for the creation of systems and technical approaches. The technical sub-disciplines analyzed in this article are:
Portfolio analysis, management, and optimization Risk, uncertainty, and risk assessment Benchmarking and performance indicators Future of energy/oil and gas Personnel competence
The summary and analysis of the five Management disciplines addressed in this paper produced two deliverables: 1) an evolution timeline that shows how data analytics, changes in economics frameworks, and environmental considerations catapulted management workflows to a systematic approach in the decision-making for all the technical disciplines analyzed, and 2) a list of opportunities and challenges for the creation of guidelines for Management in the energy sector.
The ATCE Centennial Celebration provides a unique opportunity to share knowledge and experience in technical managerial workflows and practices, in looking back and forecasting the future, benefiting the Management technical discipline.
The conclusions highlight the importance of advancing Management disciplines in the technical realm. The examples exemplify the importance for management practitioners of keeping their technical skills updated. Our paper aims to raise awareness about the current practices of Management in oil and gas, how they have evolved, and what are the main future challenges and opportunities in the creation of certifications, best practices, guidelines, and standards in Management. We want to inspire students and young professionals to initiate their path into management early on in their careers.