Analysis Of Production Data Research Articles

Pseudoisotherm: A Revised Concept of Desorption Phenomena of Coalbed Gas Reservoirs Integrating Isotherm, Material Balance, and Pressure for Optimized Field Development

Summary Gas in the coal is found mainly in the form of adsorbed methane on the surface of micropores. Methane desorbs and diffuses from micropores to cleat systems; then, the cleat network delivers the gas to the wellbore. The Langmuir isotherm empirically explains this phenomenon, a plot between pressure and adsorbed gas content (GC). The isotherm is generated in a laboratory, indicating how a particular reservoir will desorb the gas from the coal surface with a reduction in pressure throughout the production stage from startup to abandonment. This study aims to validate the laboratory-derived isotherm after a few years of field production, impacting the revised development plan for infill wells. Assuming that the initially established isotherm is correct, the difference between the initial and current adsorbed gas volume should match closely with the produced gas volume. However, production analysis after 5 years indicates that the calculated produced gas volume is significantly higher than the observed, thus invalidating the fundamental material balance equation. This triggers the question: What is wrong with using the initially established adsorption isotherm in recovery calculations of depleted coal reservoirs, and how can it be corrected? This necessitates revision/review of isotherms to match current pressure and GC/gas in place (GIP = area × current GC × thickness × density). As explained before, for coalbed methane (CBM) reservoirs, GC, cumulative gas production, and current reservoir pressure are direct measurements and require a solid logic to change the parameters. On the other hand, a Langmuir isotherm is a laboratory-derived isotherm from a representative sample of coal with inherent uncertainties from sampling to measurement. Hence, the isotherm shape is modified based on production data analysis and associated material balance results. Considering all these empirical calculations, the laboratory isotherm is revised to satisfy both initial and current reservoir conditions. This solution is validated with hard field data in the form of new core holes drilled after 3 years of production. The pressure and GC measured in those core holes were plotted, which matched the pseudoisotherm, validating the new concept. Instead of using the laboratory-derived core-scale isotherm throughout field life, it is modified with respect to production data analysis and material balance to make it a field-scale isotherm. In the coalbed gas or CBM industry, a new name is coined as “pseudoisotherm” to differentiate it from laboratory-derived isotherm. This method can be used in other reservoirs to optimize field development through infill wells during the production stage and unlock the full potential of coal-gas reservoirs.

Gulf of Mexico Case Study Highlights Smart-Completion Application

_ This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 218794, “Multifaceted Smart Completion Application: A Gulf of Mexico Case Study,” by Jeffrey P. Manning, Ben J. Carter, SPE, and Leila Bannister, Occidental Petroleum, et al. The paper has not been peer reviewed. _ Reservoir heterogeneity, stacked pay systems, reservoir compartmentalization, and high temperature and pressure are common challenges seen in Gulf of Mexico (GOM) fields. The use of conventional completion design in vertical wells with commingled production from multiple zones has led to multiple operational challenges. In the complete paper, the authors explore the use of intelligent completions in deepwater GOM as a solution. Benefits of Intelligent Completions Intelligent completions allow collection, transmission, and validation of real-time, high-frequency data. This enables analysis of completion, production, and reservoir data while selected reservoir zones are controlled and monitored remotely in real time. Intelligent completions such as multiphase flowmeters, bottomhole pressure gauges, and cased-hole logging tools enable real-time data gathering and monitoring. Additionally, downhole flow-control systems, pinpoint stimulation, intelligent injection, and multizonal isolation technology are examples of intelligent completions that enable production optimization. This study concentrates on the application of downhole intelligent choke systems in wells that use radio frequency identification technology. Combining this technology with smart sensors or Global Positioning System technology enables sensor data to be transmitted wirelessly. Operations such as opening and closing of valves, indexing and release mechanisms, and a variety of other functions can be implemented using this technology. Multiple tools can be run at the same time without compromising the tool’s internal diameter. Each tool has a unique address; therefore, tags can be coded with data that identifies an individual tool to be actuated. Intelligent completions can be broadly categorized into the following: - Downhole flow-control systems: These are passive or active control systems to control flow from each zone. They are remotely controlled by hydraulic lines from the surface facility. - Permanent downhole sensors: These are discrete or distributed systems that monitor downhole parameters. - Permanent downhole chemical injection: These systems allow for treatment at different points in the wellbore and flowlines to prevent issues caused by corrosion, hydrates, asphaltenes, paraffin, and scaling. Case Study: Practical Use of Intelligent Completions in the GOM The operated field in the northern GOM has successfully used intelligent completions in multiple vertical producing wells to help significantly reduce operating costs associated with topsides water processing, mitigate the risk of sand production, and allow for better subsurface understanding using individual zone-flow tests (this synopsis concentrates on the first two of these three aspects). Intelligent completions enabled these operations without the use of an intervention vessel.

Predicting Natural Gas Production in Various Nations Using a Fractional Grey Bernoulli Approach

Accurate forecasting of natural gas production is crucial for economic stability, environmental sustainability, and market investment. This study presents an advanced forecasting method using the fractional grey Bernoulli model, which combines fractional accumulation and Bernoulli processes to enhance the predictive accuracy for nonlinear datasets. The model’s versatility and flexibility allow it to adapt to various data characteristics and complexities, thereby outperforming traditional grey models in forecasting performance. To optimize the model parameters, this study employs the Particle Swarm Optimization (PSO) algorithm, further improving the model’s effectiveness. Empirical analysis of natural gas production data from Brazil, Italy, and Qatar demonstrates that the model exhibits significant advantages in both fitting and forecasting capabilities. The findings indicate that the fractional grey Bernoulli model achieves high accuracy and reliability in predicting natural gas production in these countries, providing a robust framework for strategic energy planning and investment decision-making. With average forecast errors of 1.9113%, 4.0353%, and 1.8902% for natural gas production in Brazil, Italy, and Qatar respectively, this study underscores the model’s effectiveness in enhancing forecast reliability and minimizing risk, providing valuable insights for sustainable energy development.

Efficiency Assessment of the Production of Alternative Fuels of High Usable Quality within the Circular Economy: An Example from the Cement Sector

This article aims to present the mechanisms regulating the waste management system of one of the European countries that affect the cement industry. This publication analyses the possibility of using selected fractions of municipal and industrial waste as alternative fuels, including an analysis of ecological costs and benefits. The methodology includes the analysis of production data and the calculation of savings resulting from the use of alternative fuels. On this basis, ecological aspects were also indicated that should be taken into account when analyzing the profitability of the investment. Production data from an example Polish cement plant were used to analyze the research problem. Based on the guidelines of environmental standards and technical specifications, the parameters that PASr alternative fuels should meet were calculated in the company laboratory. This fuel type was then calculated in terms of emission intensity and production efficiency. The research results obtained in this paper study emphasize that the change in cement clinker production technology toward the use of waste raw materials and secondary fuels does not lead to an increase in heavy metal emissions to the extent that would justify qualifying cement as a material requiring systematic control of its harmful impacts on humans and the natural environment. The conclusions show that the use of alternative fuels reduces CO2 emissions and production costs, without negatively affecting the efficiency and production volume. The average energy requirement for the production of 1 ton of cement is approximately 3.3 GJ, which corresponds to 120 kg of coal with a calorific value of 27.5 MJ per kg. Energy costs account for 30–40% of the total cement production costs. Replacing alternative fuels with fossil fuels will help reduce energy costs, providing a competitive advantage for cement plants that use it as an energy source. The presented considerations can provide an answer to all interested parties, including representatives of the executive and legislative authorities, on what path the sector should follow to fit into the idea of sustainable building materials and the circular economy.

Pengembangan Media Pop Up Book dalam Meningkatkan Budaya Literasi Program Pojok Baca di SMP Negeri 1 Berastagi

The research and development is titled “Development of Pop-Up Book Media in Enhancing Literacy Culture in the Reading Corner Program at SMP Negeri 1 Berastagi.”This development research aims to determine: (1) The design of pop-up book media; (2) The development of pop-up book media in enhancing student literacy; (3) The feasibility of pop-up book media in improving student literacy. This research is conducted using a Research and Development (R&D) model with the 4D model, which includes Define (definition), Design (design), Development (development), and Dissemination (dissemination). The subjects of this research are students of SMP Negeri 1 Berastagi, totaling 35 individuals. The instruments used in this research include questionnaires to assess the development, feasibility, and effectiveness of the media. Data analysis techniques include product data analysis, initial data analysis, and hypothesis testing.The results show that the pop-up book media received evaluations of 81% from media experts, 92% from material experts, and 65% from language experts. There was an average increase in student scores of 83%, indicating a significant change between pretest and posttest scores. The conclusion of the research is that the pop-up book media for drama content is suitable for use in literacy activities of the reading corner program. Recommendations for future research include being more meticulous in planning the development of pop-up book media, ensuring it aligns with the needs and characteristics of students.

Technology Focus: Data Analytics (October 2024)

In recent years, advancements in artificial intelligence, particularly the revolutionary applications of deep-learning-based computer vision and large language models, have significantly affected the oil and gas industry. These technological developments have underscored the growing importance and diversity of data analytics across various aspects of the industry’s daily operations. Maintaining this momentum, data analytics practitioners in the industry have reexamined existing workflows and realized the substantial benefits that artificial intelligence brings, including increased efficiency and expedited turnaround times. Organizations have allocated resources to develop a big-data-driven, multidisciplinary platform that leverages artificial intelligence and machine learning to enhance rapid and robust decision-making in asset management and risk mitigation. Integrated data-management platforms use both proprietary data and public domain data to streamline and automate processes that otherwise could be tedious and time-consuming. Successful case studies have been shared in the literature on topics such as candidate screening and production forecasting. A prominent area of focus garnering extensive attention is the integration of artificial intelligence and domain knowledge, exemplified by physics-informed machine learning. Several innovative workflows using proxy or surrogate models in conjunction with machine learning and deep learning have been published. These workflows demonstrate promising test cases that extract valuable insights from physics-based modeling results and provide production forecasts through a statistical approach. Undoubtedly, we can anticipate a surge in research and publications on this topic in the coming years, which will contribute significantly to reshaping our industry. As advancements in generative artificial intelligence and big data continue to accelerate, swiftly adapting and pivoting toward digital transformation will be essential in the emerging digital era. Recommended additional reading at OnePetro: www.onepetro.org. SPE 217665 Well Construction in the Era of Big Data: It’s Not Data Analytics, It’s Engineering With Data by G.S. Payette, ExxonMobil, et al. IPTC 24126 Deep-Learning-Based Long Short-Term Memory for Production Data Analysis of Hydraulically Fractured Wells by Fengyuan Zhang, China University of Petroleum-Beijing, et al. URTeC 3857064 Application of Data Analytics to Chemometric Analysis of Conventionally Produced Oil Samples From the Delaware Basin by Timothy Carpp, Texas A&M University, et al.

Mapping the SMEFT at high-energy colliders: from LEP and the (HL-)LHC to the FCC-ee

We present SMEFiT3.0, an updated global SMEFT analysis of Higgs, top quark, and diboson production data from the LHC complemented by electroweak precision observables (EWPOs) from LEP and SLD. We consider recent inclusive and differential measurements from the LHC Run II, alongside with a novel implementation of the EWPOs based on independent calculations of the relevant EFT contributions. We estimate the impact of HL-LHC measurements on the SMEFT parameter space when added on top of SMEFiT3.0, through dedicated projections extrapolating from Run II data. We quantify the significant constraints that measurements from two proposed high-energy circular e+e− colliders, the FCC-ee and the CEPC, would impose on both the SMEFT parameter space and on representative UV-complete models. Our analysis considers projections for the FCC-ee and the CEPC based on the latest running scenarios and includes Z-pole EWPOs, fermion-pair, Higgs, diboson, and top quark production, using optimal observables for both the W+W− and the tt¯\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ t\\overline{t} $$\\end{document} channels. The framework presented in this work may be extended to other future colliders and running scenarios, providing timely input to ongoing studies towards future high-energy particle physics facilities.

Optimalisasi Waktu Produksi Jamur Tiram Melalui Implementasi Sistem Penyiraman Berbasis IoT di UD Zaida Jamur Tiram

The optimization of oyster mushroom production time through the implementation of an Internet of Things (IoT)-based irrigation system at UD Zaida Jamur Tiram aims to enhance efficiency and production quality. This program integrates IoT technology to automate the irrigation process, allowing real-time control and monitoring of environmental conditions. Methods include the design and installation of an automatic irrigation system, technical training for operators, and performance evaluation through production data analysis. Results show a significant increase in time efficiency and consistency in oyster mushroom quality. The implementation of this IoT system is expected to support the sustainability and competitiveness of the oyster mushroom industry at UD Zaida.

Augmented Depletion Development Technology Assessed Across US Shale Plays

_ This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 217792, “Assessment of Augmented Depletion Development Technology Across US Shale Plays,” by Ahmed Merzoug, SPE, Texas A&M University, and Vibhas J. Pandey, SPE, ConocoPhillips. The paper has not been peer reviewed. _ The concept of augmented depletion development (ADD) was introduced to the industry through a pilot project conducted in the Bakken play in the US. These wells are openhole wells drilled within the fractured network of a pad. They are not fracture stimulated deliberately but do produce and contribute to the overall production of the lease. In this study, numerical modeling is used to understand the potential performance of these wells in several plays across the US. The learnings from this study can be used as a benchmark for operators that are planning on implementing such wells in their field development programs. Theoretical Basis of Study The concept of ADD can be modeled using a similar approach to the analytical solutions developed for flow into a multistage fractured horizontal well. In these wells, several regimes can be identified, such as transient linear flow and boundary-dominated flow. In previous work in the literature that proposed a method for analyzing production data of linear flow of fractured gas wells, fractures were assumed to have infinite dimensionless conductivity. Those researchers proposed a solution for a constant bottomhole-pressure liquid flow that is described in the present complete paper by a series of equations. For the case used by the present authors, a well spacing of 300 ft is assumed, implying that the perpendicular distance from the wellbore to a corresponding boundary is 150 ft, which is half the spacing between the fractured well and the ADD well (assuming each well drains half the fracture length). To elaborate further for better understanding of production, a plot of product of cumulative dimensionless rate and formation permeability (as a proxy for cumulative rate) while assuming all other properties behave the same shows that, with higher permeability, the recovery potential not only increases but also appears to accelerate. This supports the concept that, during the time of production of ADD wells, it is preferable to have higher permeabilities that can support faster production in zones that the primary wells may not drain effectively. The results of the analytical equation are for only one fracture but can be readily extended to multifractured horizontal wells using superposition methods. Methodology This study uses physics-based numerical modeling to simulate the performance of ADD wells in different plays. The numerical code simulates wellbore flow, hydraulic fracturing, geomechanics, and reservoir flow, all in the same package. The fracture and reservoir mesh are independent. The flow between the matrix and the reservoir is calculated using the 1D submesh approximation to reduce the computation expenses with higher accuracy. The hydraulic fracturing propagation algorithm uses a tip-tracking algorithm to allow the use of larger grid size without compromising accuracy in layered formations. The fracture conductivity is calculated with stress changes. The conductivity profile changes from a propped fracture into an unpropped fracture. The unpropped fracture conductivity is an underlying assumption used in this study. The collision between fractures initiated from different wells also is an assumption in this study.

Marketplace Data Analysis Using Web Scraping

The rapid development of the internet in fast communication has provided significant benefits for business people, allowing them to offer and sell product information boldly. One of the main advantages is the ability to search and find a variety of products easily through the internet. This convenience has led to the proliferation of many online stores in Indonesia, so that the need for applications that can help users search and combine product data from the internet arises. This study aims to develop a web application for product data analysis by utilizing web scraping techniques on the Tokopedia marketplace website, using the BeautifulSoup4 (Bs4) method. The web application is designed using the Streamlit module from Python. The results of this study are web applications that process data analysis taken from the Tokopedia website, which are classified based on certain criteria such as price range, highest and lowest ratings, highest and lowest sales, highest and lowest prices, percentage of location distribution, percentage of seller stores, and product recommendations.

Development of Marbel Sitasya Interactive Learning Media Based on Canva to Improve Science Learning Outcomes

Study This developing learning media interactive based Canva provided​ term Marble Sitasya To use overcome problem low results study science material solar system in class VI Wonotulus State Elementary School Regency Purworejo. Study This use Research and Development ( RnD ) method with Borg and Gall stages. The data analysis technique uses a feasibility test product, initial and final data analysis namely the t test and the N-Gain test. Based on results study show that learning media very worthy used. This proven with results evaluation appropriateness products by media experts and expert material obtained percentage by 76% and 90%. This media is also effectiv used in accordance with t test results on both the test stage is the scale test small and test scale great showing​ results sig value. (2-tailed) is 0.000 < 0.05, meaning Ho is rejected and Ha is accepted. Besides Therefore, the N-Gain test results are obtained amounted to 0.51 on the scale test small and fruitful amounted to 0.6082 on the scale test big with criteria currently. based on results study this stated that learning media interactive Marble Sitasya based canva very feasible and effective for increase results study participant educate on science content material solar system in class VI Wonotulus State Elementary School Regency Purworejo.

Pengembangan Media Flashcard untuk Meningkatkan Keterampilan Menulis Puisi Siswa Kelas VIII MTS Islamiyah Medan

This development research aims to find out: (1) the process of developing flashcard media to improve students' poetry writing skills. (2) the feasibility of flashcard media in improving students' poetry writing skills. (3) The effectiveness of flashcard media in improving students' poetry writing skills.This research was conducted using the research and development model (R&D) (Research and Development) This research uses the ADDIE development model with five stages, namely analysis, design, development, implementation, and evaluation. The subjects in this study are MTs Islamiyah Medan students totaling 28 students. The instrument of this study is to use a questionnaire to see the development, feasibility and effectiveness of the media developed. Data analysis techniques use product data analysis, preliminary data analysis, hypothesis testing. The results of the study show that flashcard media for writing poetry is very feasible to use with an average percentage of media experts 81.25% and material experts 97.5%. There was an increase in the average student score of 80.17%, so it was concluded that the average pretest and pottest scores experienced significant changes. Research conclusion: flashcard media for writing student poetry is suitable for use in poetry material learning activities by grade VIII students of MTS Islamiyah Medan. Further research suggestion: more thorough in planning the development of flashcard media, it should be developed according to the needs and characteristics of students.

OPTIMIZATION OF MIB-02 WELL BY CONVERTING THE ACTIVATION MODE USING PROSPER SOFTWARE

Mibale oil field considered a mature oil field, located offshore in the coastal basin of the DR Congo and discovered in 1973, has seen an evolution in its production since it began operation in 1976, starting from an initial rate of 10,000 BOPD with 3 producing wells to the current production of 5,905 BOPD from 14 wells. In 2021, the field had 393 MMstb of oil reserves in the reservoir. A thorough study of the production system was carried out, focusing on the five best producing wells, including well MIB-02. Despite traversing layers of the reservoir with high oil potential, the well is underperforming with a respective flow rate of 351 BOPD and a 60% WOR using an electric submersible pump. Following this low production, various studies were conducted, including the study on converting the activation method by proceeding with nodal analysis technique. The use of nodal analysis proved crucial in identifying the shortcomings of the production system, combining field history with analysis of production, well test, pressure, and completion data. The IPM Prosper software enabled a thorough analysis, revealing that MIB-02 had a production potential greater than its current performance. This performance was revealed after evaluation and interpretation of IPR, VLP curves and sensitivities of variables such as water cut and pressure at the first node. After interpreting these curves, the MIB-02 well had the production capacity of 4100.62 BOPD and 12463.9 BWPD. By converting the submersible electric pump activation mode to gas-lift and exploring various scenarios, production was improved with an oil flow rate of 1244.9 BOPD, water flow of 2539 BWPD, to a gas flow of 0.37346 MMscf/day and 67.1% water cut. Despite these improvements, excessive water production remains a challenge while also highlighting the complexity of the production system and the limitations of the analysis technique. Therefore, further studies can be envisaged by modeling and simulating the reservoir, considering well interventions and quantifying the remaining reserves today. This more comprehensive approach will enable a clearer vision and help decide the best optimization strategies for the Mibale field production system.

Superposition Rate: A Developed Approach for Analyzing Production Data in Tight Gas Reservoirs

The paper examines the application of various methods to analyze production data in which the superposition principle being one of them. This principle is divided into two main methods: Superposition rate and Superposition time. Both are designed to deal with multiple flow rates within production data. The Superposition time converts the production time into constant values and uses the final flow rate value. On the other hand Superposition rate consolidates multiple rates into a single flow rate during production time. This study focuses on analysis of production data using a developed method based on superposition-rate approach. This method converts variables such as flow rate and pressure into constant values, where each flow regime has its own technique by which superposition-rate is utilized. In addition, comparison between conventional and unconventional reservoirs is involved, particularly emphasizing the benefits and drawbacks of tight gas reservoirs.Various types of superposition methods with their functions were discussed. Among them, a workflow part includes a case study of a dominated flow regime used for a hydraulic fractured single well. The workflow part of this study includes a case study of hydraulically fractured well under a dominant flow regime. Results comparing multiple rates method with super position-rate method indicate that the latter has better accuracy with (R) coefficient of (0.96). Case study on fracture reservoir also shows further validated of superposition-rate by accurately estimating drainage volume.

The Production Analysis and Exploitation Scheme Design of a Special Offshore Heavy Oil Reservoir—First Offshore Artificial Island with Thermal Recovery

More and more offshore heavy oil resources are discovered and exploited as the focus of the oil and gas industry shifts from land to sea. However, unlike onshore heavy oil reservoirs, offshore heavy oil reservoirs not only have active edge and bottom water but also have different exploitation methods. In this paper, a typical special heavy oil reservoir in China was analyzed in detail, based on geology–reservoir–engineering integration technology. Firstly, it is identified as a self-sealing bottom water heavy oil reservoir by analyzing its geological characteristics and hydrocarbon accumulation mechanism. Secondly, the water cut is initially controlled by oil viscosity, but subsequently, by reservoir thickness through the analysis of oil and water production data. Thirdly, the bottom oil–water contact of the reservoir was re-corrected to build an accurate 3D geological model, based on the production history matching of a single well and the whole reservoir. Lastly, a scheme of thermal production coupled with cold production was proposed to exploit this special reservoir, and the parameters of steam, N2, and CO2 injection and production were optimized to predict oil production. This work can provide a valuable development model for the efficient exploitation of similar offshore special heavy oil reservoirs.

Intelligent smelting process, management system: Efficient and intelligent management strategy by incorporating large language model

In the steelmaking industry, enhancing production cost-effectiveness and operational efficiency requires the integration of intelligent systems to support production activities. Thus, effectively integrating various production modules is crucial to enable collaborative operations throughout the entire production chain, reducing management costs and complexities. This paper proposes, for the first time, the integration of Vision-Language Model (VLM) and Large Language Model (LLM) technologies in the steel manufacturing domain, creating a novel steelmaking process management system. The system facilitates data collection, analysis, visualization, and intelligent dialogue for the steelmaking process. The VLM module provides textual descriptions for slab defect detection, while LLM technology supports the analysis of production data and intelligent question-answering. The feasibility, superiority, and effectiveness of the system are demonstrated through production data and comparative experiments. The system has significantly lowered costs and enhanced operational understanding, marking a critical step toward intelligent and cost-effective management in the steelmaking domain.

PENGEMBANGAN MEDIA PEMBELAJARAN KARTU PINTAR BERBASIS VIDEO ANIMASI TIGA DIMENSI DENGAN PENGINTEGRASIAN KEARIFAN LOKAL UNTUK PENINGKATAN KOSAKATA BAHASA JAWA SISWA KELAS III SDN PETOMPON 01 SEMARANG

The use of Javanese vocabulary at SDN Petompon 01 Semarang was not optimal. This wasbecause children locked practice in speaking Javanese and also the use of learning media is stillminimal. Responding to this phenomenon, researchers developed smart card learning media basedon Three-Dimensional Animation Videos with the integration of local wisdom to fosterenthusiasm and increase the use of Javanese vocabulary in the school. The research was carriedout on 2 July - 24 August 2023 at SDN Pentompon 01 Semarang. This research used R&D(Research and Development) with a qualitative approach. The research population was allstudents in class IIIA at SDN Petompon 01 Semarang, totaling 16 students. Small group trialresearch sample testing was carried out in class IIIB using a purposive sampling technique bytaking 6 students based on class ranking, namely three students in the top rank, two students inthe middle rank, and one student in the bottom rank. Large group trials were carried out in ClassIIIA. The dependent variable of this research was increasing Javanese vocabulary, while theindependent variable is developing smart card learning media based on Three-DimensionalAnimation Videos with the integration of local wisdom. The data collection techniques used wereobservation, interviews, documentation, questionnaires and tests. The instruments used areobservation guidelines, interview guidelines, questionnaire sheets, and test questions. Productdata analysis techniques and initial data analysis consist of a normality test and homogeneity testas well as final data analysis consisting of the N-Gain Test and also the T-test. The researchresults showed that an average of 61 pretest results and posttest scores showed an increase in theaverage student score of 67.5333 with a percentage increase of 41% in the pretest results and 44%in the posttest results with details of 10 students who did not complete. and 6 students completedit so it can be concluded that three-dimensional animated video-based learning media is quitefeasible and effective for use in learning Javanese

Persistent Homology in Solar Production

Persistent homology, an algebraic topology-based mathematical framework, presents an innovative method for capturing and characterizing the inherent topological features present in time series datasets. The research aims to evaluate the efficacy of features derived from persistent homology in enhancing the accuracy and interpretability of classification models. This investigation contributes to the expanding convergence of topology and time series analysis, providing valuable insights into the potential of persistent homology for extracting information from temporal data. The study specifically focuses on the analysis of region-wise solar production data obtained from India for the year 2022. The examination of this data is conducted using R-Software, and the resulting topological properties are represented through persistent diagrams.

Novel methodology to couple decline curve analysis with CFD reservoir simulations for complex shale gas reservoirs

AbstractShale reservoirs are highly complex and are difficult to study using conventional reservoir simulation tools. This study introduces a novel methodology for estimating production from complex shale gas reservoirs by coupling decline curve analysis (DCA) with computational fluid dynamics (CFD) simulations. The proposed method uses exponential DCA to analyze production data from a dual porosity–permeability shale gas transport model. These complexities include fracture characteristics, geomechanical properties, nanopore confinement effects, and multiple flow mechanisms contributing to the total production performance. The shale gas transport model is validated through historical production data from Marcellus shale. The new methodology also tests fracture characteristics. It shows that increased porosity and permeability will increase the recoverable reserves but will have varying effects on the decline rate. The paper demonstrates the advantages of the proposed methodology over conventional reservoir simulation tools. It provides insights into the factors affecting shale gas production performance through the inclusion of the complexities of an unconventional shale gas reservoir. The paper provides a proof of concept on the particular reservoir of which the field data is provided—Barnett and Marcellus Shale.

Integrated Analysis of Two-Phase Production Data in Hydraulic Fractured Deep Shale Reservoirs: Coupling Multiple Fluid Transport Mechanisms

Integrated Analysis of Two-Phase Production Data in Hydraulic Fractured Deep Shale Reservoirs: Coupling Multiple Fluid Transport Mechanisms