bluuebunny/crossref_metadata_2025_split huggingface dataset:
Correction Method for Well Testing Data Affected by Tide and its Application in South China Sea Offshore Oilfield
Authors: Yu Weiqiang , Mao Min , Zhao Hongxu , Zhang Guohao , Zhou Daoxi , Jiang Hongfeng , Lv Zuobin 
Published: February 2025

Abstract
During transient well testing of offshore oil and gas wells, pressure and pressure derivatives may be affected by tidal effects, resulting in periodic abnormal fluctuations that interfere with the interpretation of the model and reservoir parameters.
In this paper, tidal correction is carried out using fast Fourier transform method(FFT), optimization correction method based on tidal model driver(TMD) or measured tidal data. The FFT method is to transform abnormal pressure data into the frequency domain, identify and suppress tidal anomaly characteristics; The TMD optimization correction method calculates tidal signals and optimizes their fitting with original pressure to obtain data without tidal effects; Optimization correction method based on measured tidal data requires the use of the tidal table at the test well location or the tidal table in nearby port cities, to adjust the amplitude and delay time through optimization methods to achieve tidal removal.
Through research and practical well testing cases, it has been verified that the fast Fourier transform method, the optimization correction method based on tidal model driver or measured tidal data have their own characteristics when processing data from different sea areas or test conditions, we can choose one or a combination of multiple methods, which can effectively remove the influence of tides and accurately determine the radial flow characteristics and later characteristics on the pressure derivative curve.
This method can effectively diagnose the characteristics of tides, identify tidal components and suppress tidal effects by integrating multiple methods during the processing of raw pressure data, avoiding the ambiguity of results and computational complexity. Compared with previous studies, the method proposed in this article has better adaptability in removing tidal effects, especially when the build-up analysis period is short, it still has a very significant processing effect. It provides an effective means for correcting abnormal pressure data containing tidal effects.
Utilizing Machine Learning for Gas Lift Optimization: Reducing Interventions and Accelerating Production
Authors: Moelyono S. , Misra S. , Retnanto A. , Palviriyachote S. , Voneiff G. , Thompson A. 
Published: February 2025

Abstract
To optimize gas lift injection rate, production engineers need bottom-hole pressure (BHP) and updated reservoir pressure data for nodal analysis and gas lift performance curves. However, obtaining this traditionally involves well interventions, including an approximately 12-hour shut-in for BHP surveys, leading to production losses and delays. A data-driven approach is proposed in this study to help well intervention planning and accelerate the determination of the optimal gas lift injection rate by eliminating the need for a well intervention.
This approach involves prediction of well production performance, including gas lift injection and liquid production rates, based on surface measurement data such as wellhead pressure, gas lift injection pressure and subsurface data, like reservoir thickness, and information from surrounding wells with similar geological and reservoir properties. Machine Learning model is developed using these datasets, with surface parameters, well, PVT, and reservoir data as input features to predict the range of optimal gas lift injection rate and liquid production rate as output targets. Evaluation begins with classification to determine the necessity of gas lift injection, followed by regression analysis to establish the optimal range of gas lift injection rate and liquid production rate.
Logistic Regression can determine whether a well needs gas lift injection at F1 score of 0.97. For wells needing gas lift injection, Gradient Boosting regressor performs the best in predicting the range of optimal gas-lift injection rate of a well at a mean absolute percentage error (MAPE) of 0.04, while Random Forest regressor performs best in predicting the optimal liquid production rate, with a MAPE of 0.02. The predictive performance of the predictive methods drastically improved by creating new features, such as WOR (Water Oil Ratio) and oil rate divided by the product of wellhead pressure and gas lift injection pressure, derived from the raw data.
This proposed system benefits production engineers and field operations, offering a faster and more efficient method for optimizing gas lift injection rates, ultimately leading to enhanced oil production. It could save 27 hours compared to the traditional approach and generate recommendations in under an hour once the model is ready. Moreover, it helps prevent production losses.
Optimizing Fines Mitigation: Evaluating the Effect of Clay on Sand Agglomeration for Enhanced Sand Control
Authors: Kamat Dahlila , Saaid Ismail Mohd , Hassan N. A. , Chandrakant A. A. , Raggu A. D. 
Published: February 2025

Abstract
Fines migration in oil and gas fields is a significant problem that can lead to reduced production rates and potential equipment failure, resulting in significant monetary loss. While chemical sand control solutions have been used in the past, their effectiveness and ease of placement have been questioned, particularly in the context of mitigating fines production. This research aims to address this issue by exploring the potential of sand agglomeration as a new approach to fines mitigation. Specifically, the impact of clay content on sand agglomeration will be evaluated, with a focus on enhanced sand control. A series of tests as conducted to establish the performance of this new approach in reducing fines migration. By optimizing fines mitigation through sand agglomeration, this research seeks to provide a valuable contribution to the field of oil and gas production.
Compaction and Completion System Collapse Analyses for a Shallow Unconsolidated Reservoir, Offshore Peninsular Malaysia
Authors: Younessi A. , Chatterjee A. , Ghazali I. H. , Nordin N. F. 
Published: February 2025

Abstract
Reservoir compaction has potential risks for casing or completion system collapse, which affects the integrity of wells, completion systems and surface facilities. This paper presents a case study demonstrating an integrated approach to evaluate such risks for a poorly consolidated reservoir located in offshore peninsular Malaysia. A poroelastic analytical approach is used to calculate the compaction associated with the reservoir depletion. The results of the reservoir compaction analysis are used to assess the likelihood of completion system collapse. For this purpose, an analytical approach is adopted to calculate the compressive and shear strains developed in the completion system. The maximum calculated vertical compaction for the worst-case is 0.45% at the maximum depletion, while the other cases are significantly lower. The compressive and shear strains developed in the completion systems are calculated at the maximum compaction calculated for the P10, P50 and P90 rock properties cases. All cases show the calculated compressive and shear strains are below the critical strain value of 0.50% for the studied field. The presented study reinforces the field development plan and prevents unforeseen costs and downtime throughout the life of the study field.
Successful Collaboration Between Surface and Subsurface Team to Reduce Carbon Emission Through a Holistic Approach by Alleviating Surface Constraint to Achieve Sustainable Low Carbon Future
Authors: Ravichandran T. , Yin Y. W. , Islamov R. , Bidin L. A. , Sidek S. , Subari I. 
Published: February 2025

Abstract
This paper discusses the result of successful surface optimization performed on a field with challenges associated with a high Gas-oil- ratio (GOR), excessive carbon emission and reduced field production efficiency. Total field gas production had already exceeded the limit of surface processing facilities in field B, which meant the Operator had to choke back production.
Surface optimization involved diverting the field A gas from High Pressure (HP) compressor to High High Pressure (HHP) compressor which located at field B 20km away to obtain additional ullage of 10MMscf/d. This configuration poses significant challenges in accurately determining backpressure impact to the well due to higher HHP suction pressure; field B surface facilities adequacy to process additional fluid from field A and deferment required to divert the flow from HP to HHP. In addition, field A is not equipped with well test facilities causing additional uncertainties to determine the production rate or impact of the diversion for each individual wells.
This paper evaluates the success of the HHP diversion in mitigating the high flaring challenges and improving the field's performance.
AI Automation in Civil Infrastructure Asset Management
Authors: Loh S. , Gautam A. 
Published: February 2025

This paper features the development path of automation solutions for civil infrastructure asset management for oil and gas facility. The scope covers the development, integration and scaling of ExxonMobil structural damage classification AI (Artificial Intelligence) into the Company's inspection, maintenance and equipment strategy work processes. Traditionally, civil infrastructures are challenged with large asset inventories and limited site resources to manage the asset program. This paper makes a strong case for fit for purpose digital and automation solutions to augment the existing engineering capabilities, resources and to optimize civil asset health.
The paper will present results in AI statistical performances, increase in inspection workflow productivity and improved line of sight to civil infrastructure risks. Recent deployment of AI in visual inspection workflows demonstrated ease of onboarding, training, and willingness of users to transition to new ways of working. Users such as site engineers and field inspectors have expressed high interest for business adoption and eagerness to participate in future AI incremental roll-out program given the value propositions. Adjacent AI enablers such as digital twin and asset integrity management solution teams have been interested to deepen the collaboration and integration, in light of AI's potential of expanding their respective digital technologies use cases.
This paper will examine several aspects of civil inspection work processes, technology enablement and people behaviors in order to successfully develop and implement AI capability in inspection. This is followed by a detailed discussion on AI development methodology and results from data science perspective.
Field Trials Review on Drilling Data Microchips Deployment, Recovery, and Data Retention
Authors: Tella Sherif A. , Alsheikh Abrar , Li Sanguo , Li Jibo , Zhan Guodong 
Published: February 2025

Abstract
For many years, downhole data transfer has faced challenges due to limited communication bandwidths, resulting in delays in logging data acquisition and difficulties in capturing high-frequency drilling dynamics measurements. There is an urgent requirement to improve the capacity and speed of downhole data communication significantly. However, maintaining safe and optimal drilling conditions requires knowledge of downhole parameters. Hence, cost-effective drilling data microchips that collect real-time downhole data readings during drilling are necessary for precisely predicting wellbore property fluctuations, local overheating, and guiding the drilling trajectory in the wellbore. On the other hand, conventional alternative solutions use less than 10% of the acquired data in real time. Microchips often consist of an on-chip battery, sensors, secondary memory, and a system-on-a-chip (SoC). However, the data microchips may be exposed to random stresses throughout the drilling and releasing operations into the well annulus, which could lead to the failure of interconnects and other components, resulting in damage, loss of stored data, and a low recovery rate when the data microchips are released. This article reports one of the phases of a project and this phase describes the design and development of lab-qualified data microchips as a solution to high-resolution, near real-time, downhole data storage and transmission. The article also describes the results of field trials in five different well sections while drilling to evaluate and assess the physical recovery rate and integrity of data retention. A total of 134 lab-qualified data microchips (DM) were deployed in five well sections, achieving an overall physical recovery rate of 76.12% and a digital recovery rate of 89.22%. The third trial faced issues, recording the lowest physical recovery at 37.5%, yet had a perfect digital recovery. The 4th and 5th trials excelled, with recovery rates of 95.83% and 100%, respectively. A total of 11 DMs were damaged, which signifies that a considerable proportion of the deployed DMs were recovered successfully and most of them contained usable data. This report will present the design and development of data microchips considering the packaging, micromemory circuit, and communication protocol for data read/write. In addition, this report will discuss the testing methods, and the outcomes of the field trials conducted in five different well sections.
Innovative Strategies for Push-The-Bit Drilling Automation: Mitigating Vibrations and Maximizing Steering Efficiency in Challenging Norwegian Continental Shelf Formations and Large Hole Sizes
Authors: Rakhmangulov Farit , Aliyev Sanan 
Published: February 2025

Abstract
Drilling with Push-the-Bit Rotary Steerable Systems (RSS) encounters challenges in larger hole sizes. Operator demands for high inclination and Dogleg Severity (DLS) in these diameters heighten complexities. Key challenges involve achieving desired angles and DLS in unconsolidated formations, overcoming gravity forces at over 50° inclination, and managing vibrations causing equipment failures in formations with interfacial severity. Deploying RSS with an autonomous drilling platform ensures efficient, and accurate wellbore delivery on the Norwegian continental shelf (NCS).
To handle downhole data and multiple wells efficiently, a Data Lake Approach was adopted. This involved leveraging a corporate Data Lake to amalgamate databases from diverse datasets into a unified model, simplifying data visualization in Business Intelligence (BI) tools. Automation of the data collection saves time for drilling analysis, eliminates the need for manual data collection, preparation. Furthermore, the correct automation setup and utilization of a web-based dashboard address a key customer objective - increasing Rate of Penetration (ROP) by automatically adjusting the rotary steerable system's steering force and toolface to match the demanded DLS and wellpath.
Ten drilling runs, utilizing hybrid bits with Push-the-Bit RSS as well as Tungsten Carbide Insert (TCI), and Milled Tooth roller cone bits, were analyzed. All bit types demonstrated excellent performance in vibrations and steering, outperforming PDC (Polycrystalline Diamond Compact) bits. Similar issues were noted with Point-the-Bit RSS. Recent runs with hybrid bits yielded optimal results: low Stick-Slip and Whirl vibrations, highest DLS, achieved higher inclination angles in large hole sizes, and stable steering efficiency, even in unconsolidated sand formations. The hybrid bits notably minimized the right-hand walk tendency associated with PDC bits.
Over ten runs on the NCS, data indicates improved ROP, well placement, and borehole quality through drilling automation and BI tools. The digital twin continuously learns, and updates based on historical steering actions and real-time data calibration, allowing user input. Different modes can be selected for drilling efficiency based on operational constraints, objectives, and field knowledge, incorporating attitude and position control while managing projection horizon, build rate boundaries, and walk rate.
The proposed approach provides a novel perspective on drilling with Push-The-Bit RSS in larger borehole diameters, expanding the boundaries of drilling, especially in Extended Reach Drilling (ERD) wells. Furthermore, this methodology emphasizes the potential of automated drilling and automated data analytics, contributing to effective decision-making in future well planning and resulting in substantial reductions in operational and HSE risks.
Unveiling the Evolution and Facies Distribution of a Miocene Carbonate Platform in Central Luconia, Offshore Malaysia
Authors: Henglai P. , Fongngern R. , Uttareun R. , Sa-nguanphon S. , Soontornnateepat T. , Srisuriyon J. 
Published: February 2025

Abstract
The evolution and facies distribution of relatively small carbonate platforms, approximately 30 km2, are not well documented, even though they are common in ancient and modern carbonate systems. This study investigates platform evolution and facies distribution of a Miocene carbonate platform in Central Luconia, offshore Malaysia. An integrated approach, including core-described lithofacies, well-log correlation, and seismic analysis, allowed for mapping depositional facies and platform evolution through time. The platform was divided into five stratigraphic zones (1 [top], 2 Upper, 2 Lower, 3 Upper, 3 Lower [bottom]) separated by low porosity intervals. Five depositional facies groups were recognized in core samples: (1) bioclastic wacke-packstone facies deposited in a platform interior, (2) bioclastic packstone facies deposited in backreef environments, (3) coral boundstone facies deposited at the reef margin, (4) interbedded shale and carbonate facies deposited on the slope, and (5) argillaceous carbonate facies deposited across the platform as flooding layers. Well D penetrated almost the entire platform, and facies in that well changed upward from mainly bioclastic wacke-packstone at the bottom to mainly bioclastic packstone in the middle to coral boundstone near the top before being covered by interbedded shale and carbonate. Six seismic facies characterizations were generated and combined with well data to map the five facies groups through time. The platform shows repeated backstepping of facies at flooding layers followed by aggradation of facies belts up to exposure surfaces, resulting in a long-term backstepping of depositional environments until the platform drowned. Sr-isotopes dating near the top of this platform yielded an age of approximately 12 Ma.
ПРОЕКТИРОВАНИЕ СТРАТЕГИИ ТЕХНОЛОГИЧНОГО РАЗВИТИЯ ПРОВИНЦИАЛЬНОГО РЕГИОНА
Authors: Белокур О.С. , Цветкова Г.С. 
Published: February 2025

Обоснована актуальность фокусированного развития социально-экономической системы провинциального региона. На основе корреляционного анализа, расчёта коэффициентов локализации и производительности труда определены ключевые приоритеты и отрасли специализации провинциального региона, способные выступить драйверами технологичного развития. Разработана модель стратегии технологичного развития региона на основе стейкхолдер-анализа и концепции сбалансированных показателей.
Introduction. The speed of creation of new products, technologies, and markets, and active transformation of business processes and marketing communications make it possible to develop new strategic guidelines for Russian regions. In these conditions, the problem of developing effective strategies for Russian provincial regions with limited resource and economic potential is acute. The goal of the study is to design the key elements of the technological development strategy for Mari El Republic, including strategic guidelines, supporting industries, and the interests of stakeholders. The analysis of the structure of the region's economy based on the localization and labor productivity indicators confirmed the existence of objective opportunities for choosing a strategy for technological development of Mari El Republic. Results. The model of regional strategy of technological development includes a description of the management object, the center as a control element, the subjects of the strategy, the mechanism, and the results of the strategy. The features of the strategy subjects are given on the basis of stakeholder analysis. The description of the strategy implementation algorithm was carried out on the basis of a system of balanced indicators, construction of a strategic map in the following projections - "personnel", "internal processes", "markets and consumers", "finance". Conclusion. The main result of the study is a model of implementation of a technological scenario in the region. The model shows the cause-and-effect relationship between the resources and the results of the region’s development, as well as it highlights the most significant components which define the success of the implementation of the technological development strategy.
РОЛЬ И ЗНАЧЕНИЕ НАУЧНОГО ПРЕДВИДЕНИЯ В СОВРЕМЕННОЙ ЭКОНОМИКЕ
Authors: Холодова М.А. 
Published: February 2025

В статье рассматривается роль и значение научного предвидения в современной экономике. Представлена трактовка ключевых элементов научного предвидения, среди которых планирование и прогнозирование. Обосновано, что основу стратегического планирования в условиях усиления неопределённости внешней среды и стремительных технологических изменений составляет долгосрочное прогнозирование.
Introduction. Today particular attention is paid to the problems of scientific prediction from top to bottom due to quick changes in the external environment such as economy globalization processes, qualitative changes in its structure, rapid spread of innovations, change of technological and economic orders. The goal of the study is to ground the role of economic prediction in modern economy, define the primary importance of the system of scientific prediction in the context of quick changes of the external environment, characterized by the change of technological and economic orders. Results. The critical overview of scientific sources showed that under prediction it was understood a scientifically grounded presentation of development of the future,based on the knowledge about the laws of nature, society and thought. The interpretation of the notion “planning” and “forecasting”, which are the successive steps of prediction of behavior of the studied object in the long run, was considered. In practice, an optimal long-term forecasting shall be based on at least three forecasts: «standard», «specific», and «conservative». At that, the development and ground of the “specific forecast” is obligatory as it is supposed to study the full potential,necessary for sustainable economic growth, aimed at implementing the strategic priorities. Modern system of scientific prediction includes aset of interrelated elements (hypotheses, concepts, forecasts, plans, programs, and economic orientation), and it is named the “strategic planning”. It is demonstrated that the forecasting constituent of the strategic planning system shall be of system and variative nature, shall be institutionalized, and shall be the imperative for contouring of the scientific and technological and economic policy. A simulation nature of the system of strategic planning of economy in Russia is justified. The author concluded that the system approach for elaborating and grounding of long-term forecasts in socio-economic development of national economy contributed to the development of a methodology of strategic planning.