bluuebunny/crossref_metadata_2025 huggingface dataset:
Maximizing Recovery in a Mature Rich Gas Condensate Field: Using Rate Transient Analysis to Identify Infill Opportunities
Authors: Al-Fazari I. , Govinda P. , Kalbani A.
Published: February 2025

Rate Transient Analysis (RTA) is a powerful technique in petroleum engineering that can be used to diagnose reservoir behavior, leading to better reservoir understanding and production optimization. In this study, RTA was used as a simple and agile analytical technique for the Field A reservoir. Field A is a rich tight gas condensate reservoir in a complex structure composed of six sub-units with varying geological characteristics located in Oman's north Field. The main purpose of this study was to understand the connected volume seen by existing wells and thereby identify sweet spots for future infills that would help maximize field recovery.

A clear and structured approach was followed in this study. First, the gap to top quartile was defined with an understanding of reservoir challenges and reservoir data uncertainties. Second, data were gathered to apply basic analytical techniques. Third, the analytical technique Blasingame was used to history match the connected pore volume. Fourth, a numerical technique was used to match the analytical approach, where the condensate banking effect was considered. Finally, the connected volume was estimated per well, and drainage areas were marked on a map to identify potentially undrained areas and infill opportunities.

Individual well RTA was performed for two blocks of the Field A reservoir, the East and West blocks, consisting of 31 wells in total. The effect of condensate dropout on the effective permeability-thickness (kh) of the reservoir was inferred from RTA. Well-level numerical models were generally able to match condensate-gas ratio decline trends and the effective kh reduction due to condensate banking. Changing skin was observed in many of the RTAs (initial negative skin gradually going towards 0), indicating gradual closure of hydraulic fractures. The study results indicate nine potential infill opportunities in both blocks of the Field A reservoir. The identified infill opportunities were ranked through economic evaluation, considering factors such as the cost of drilling and completing new wells, the expected increase in production rates, and the projected increase in reserves.

This study provides valuable insights for enhancing field performance and consequently improving field recovery. The study represents an agile approach in how field understanding, opportunities identification, and maturation can be developed quickly yet effectively using existing data and limited manpower in a limited time frame. RTA offers efficient analysis of changing reservoir and well conditions, surpassing limitations of traditional methods and dynamic simulation, providing a practical alternative for identifying infill opportunities and optimizing production strategies. The approach used can be replicated for other similar reservoirs, and the results have significant implications for the petroleum industry.
Enhancing Oil & Gas Recovery Using a Novel Nano Particle Technology
Authors: Ojukwu K. I.
Published: February 2025

Nanoparticle technology is increasingly prominent in the oil and gas industry, offering significant enhancements in both waterflood projects and hydraulic fracturing operations. The efficacy of nanoparticles hinges on various factors such as molecular composition, particle size, solvent base, and concentration. Typically, nanofluids consist of aqueous suspensions containing nonferrous metal nanoparticles, typically sized between 70-150 nanometers, dispersed in an anionic surfactant solution like sulfanole-akyl aryl sodium sulfonate. Anything smaller than this is rare to find in nanofluid applications.

In a recent application, smaller hydrophobic silicon dioxide particles (12-25nm) suspended in aqueous solution were deployed as part of stimulation fluid in multi-stage fracturing operations in multilateral oil producers within the Alberta Cadium and tight Montney formations. Initial Production (IP) results showed a remarkable improvement—up to 50% to 200% higher than nearby wells treated with different nanoproducts or traditional surfactants, with a significant reduction in water cut. Cumulative production comparisons revealed these wells recovered 25% more oil from the Montney formation within the first 10-12 months compared to offset parent wells treated conventionally, translating to a 3% increase in recovery factor.

Laboratory experiments corroborate that these very tiny silicon dioxide nanoparticles effectively fragment oil droplets in reservoir pores, mobilizing previously unrecoverable hydrocarbons. These nanoparticles also improve rock wettability and disperse effectively within formations to accelerate oil production. Overall, the operator realized a 400% return on investment with a mere 14-day payback period, underscoring the economic viability and transformative potential of nanoparticle technology in the oilfield.
Well Production Prediction Method Based on Multi-Factor Fusion Time Series Model
Authors: Zhang Yaqian , Li Xianjie , Cao Jinxin , Miao Chuanhui , Zhang Yuling , Zeng Shilin , Zhang Jian , Li Yiqiang , Liu Zheyu
Published: February 2025

Production forecasting is a crucial issue in oilfield development, holding significant importance for evaluating geological potential and adjusting development schedule. However, due to complex geological conditions, seepage laws, and manual operations, traditional methods often struggle to achieve good results. This paper proposes a production forecasting method based on Multi-Factor LSTM combined with decline curve analysis. The production curve of an oil well is first fitted using a decline curve analysis, and then the difference between the actual production curve and the fitted production is taken as the input production data for the LSTM model. Considering operations such as daily production time, pump frequency changes, and choke size changes, this paper introduces these factors along with well production as input data within a time window to achieve higher production forecasting accuracy. The results indicate that the Multi-Factor LSTM combined with the decline curve analysis can effectively predict future well production. By introducing manual operations, the model can capture correlations between manual operations and oil production, demonstrating higher sensitivity to production fluctuations and achieving a model accuracy of 0.97. This represents an improvement of approximately 9% in R² compared to the Single-Factor LSTM model. Additionally, the introduction of the decline curve analysis complements the deficiency of machine learning methods in predicting long-term, monotonic decline trends. Compared to a standalone LSTM model, the proposed model better captures the long-term production decline due to natural energy depletion and reduced remaining oil reserves in the production sequence. The proposed oil well production forecasting method based on the time series model with multi-factor fusion exhibits good adaptability for oil well production forecasting, providing a new approach for rapid and accurate forecasting of field production and subsequent adjustment of production measures.
Enhancing Seismic 2D and 3D Data Conditioning by Leveraging Machine Learning
Authors: Kumar Sayani , Shekhar Sushant , Jeff Osabuohien Osahon , Salomia Gabriela , Hasan Hesham , Assaf Georges , Tran Dong , Maria Mihai Monica , Velikanov Ivan , Biniwale Shripad , Mustapha Hussein
Published: February 2025

Seismic interpretation is an essential factor in the success of field development projects because it allows geologists and engineers to better understand subsurface formations and identify potential resources; however, noisy seismic data, especially in regions with complex geological structures, frequently hinder this process. Such noise emerging from equipment limitations, environmental interference, and inherent geological complexities can obscure essential geological features, making accurate subsurface imaging challenging and reducing the effectiveness of traditional interpretation methods.

This paper presents a machine learning (ML) method to enhance the conditioning of 2D and 3D post-stack seismic data by targeting noise and migration artifacts. These issues are often responsible for compromising the quality of seismic data sets. The method this paper presents leverages convolutional neural networks (CNNs) to identify and correct spatial inconsistencies within the data. With minimal preprocessing, requiring only the conversion of data into a 3D NumPy array format, this approach simplifies the workflow while improving data clarity and accuracy. Early statistical analysis of outliers and data normalization provides the ML model with stable inputs, allowing it to iteratively train on raw data and infer the original signal patterns in an unsupervised manner without the need for labeled data sets.

The model outputs a conditioned version of the seismic data, significantly reducing noise while preserving critical geological features. The results demonstrate that ML seismic conditioning improves fault imaging, horizon continuity in areas with low signal-to-noise ratios (SNR), and localized smoothing without compromising resolution. Furthermore, the method presented in this paper retains signal fidelity and relative amplitude strengths, ensuring that geological interpretations remain accurate and reliable. By automating the traditional manual task of data conditioning, the proposed solution optimizes interpreter workflows, allowing them to focus on higher-level geological analysis and decision-making. This approach ultimately increases the accuracy of subsurface interpretations and resource exploration, improving the overall quality and efficiency of seismic interpretation projects.

In addition, for 2D seismic, traditional methods of denoising rely on expert judgement using tools such as f-x deconvolution. 2D CNNs offer an efficient alternative, especially when training data can be synthesized and leveraged in supervised learning. This method can help the CNN identify and remove noise while preserving pertinent subsurface structures. This paper presents a 2D CNN architecture containing a model trained with synthetic seismic data to improve SNR of field seismic data; hence, interpretation.
Combining Variation Diffusion Model and Multi-Source Experimental Data to Establish Digital Cores for Reservoir Exploration and Development
Authors: Zhu Dancheng , Wang Lian , Qu Jianhua , Zhang Liang , Deng Rui , Jing Feng
Published: February 2025

Digital core technology is emerging as a transformative force in the realm of reservoir engineering, offering unprecedented capabilities for conducting detailed and non-destructive analyses and experiments that were previously unimaginable. Traditional approaches to constructing digital cores, such as physical experiments and numerical reconstruction, have inherent limitations in terms of cost, time, and resource utilization. To overcome these obstacles, a groundbreaking intelligent digital core construction method called MSED-GDL which integrates multi-source experimental data with generative deep learning algorithms has been developed. This innovative method leverages the power of multi-source experimental data and generative deep learning algorithms to enable the rapid and efficient reconstruction of three-dimensional (3D) digital cores. By integrating sophisticated components such as the construction of a digital core autoencoder, the acquisition of multi-source experimental data through advanced fluid simulation techniques, and the application of variational diffusion models, MSED-GDL facilitates the swift and accurate reconstruction of 3D digital cores in a matter of seconds. To validate the efficacy of this method, an extensive dataset of 10 million digital core samples was generated and subjected to rigorous micro-scale fluid flow simulations, resulting in the acquisition of valuable multi-source experimental data, including porosity and permeability. The results demonstrated a high degree of consistency between the reconstructed digital cores and the original data in multiple key parameters, underscoring the statistical significance and robustness of the MSED-GDL method. This breakthrough in digital core technology holds profound implications for advancing our understanding of subsurface reservoir characteristics, optimizing exploration and development strategies, and enhancing resource utilization efficiency in the oil and gas industry.
Deepest 12-1/4" × 9-5/8" Section Drilled by Casing While Drilling (CWD) in Sanga-Sanga Block
Authors: Chairunnisa Z. E. , Wadjid Y. K. A , Kamil R. , Lubis T. A. , Wicaksono N. T. , Prasetyo D. E. , Saragih A. M. , Malik M. A.
Published: February 2025

In drilling the surface section of Sanga-Sanga Block, the main hazards are loss circulation and shallow gas where Casing While Drilling (CWD) is a secured solution. Services has been implemented for the past 5 years with over 97 runs with a recent success of reaching maximum depth ever drilled using CWD of 2256 ftMD from initially drilling 1657 ftMD wells in this field. The case study will describe the planning and execution of this well.

CWD is utilized in Sanga-Sanga Block to drill the surface section which was able to eliminate additional operation of drilling a pilot hole saving 85 hours drilling time and 285,699 USD. The cost savings of CWD compared to conventional drilling increases with deeper depths drilled. Therefore, the collaboration with the Operator and the CWD services provider during the planning and execution stage was the key to reach the maximum depth drillable in this field.

The latest well managed to drill deepest depth of up to 2256 ftMD for 9-5/8" × 12-1/4" hole size in 37.4 hours without any incident. This was achieved by optimizing the cutting structure using 3D bit drilling simulation software, as well as improving the hydraulics by constantly monitoring and adjusting the flowrate throughout the run done by collaboration by CWD field engineers, operator, and mud engineers on board. These adjustments managed to enhance efficiency and durability. The maximum depth achieved is 35% greater than the previous record.

This paper shows the continuous growth of CWD application which has proven to be a solution to overcoming losses, shallow gas hazards and many other drilling problems used in vertical depths up to beyond 1657 ftMD. The learnings from this case could initiate and be used as a reference for even deeper application of CWD technology in the Sanga Sanga Field or in other field applications.
Implementation of Artificial-Intelligence-Powered Tools in Data Processing for Well Time Estimation and Risk Analysis in Mexico and Ecuador Projects
Authors: Szlapa S. , Douy C. , Sesboue P. , Erives J. , Telles J. , Delgado A. A. Benavides , Paccha J. , Gori F. , Mani A. , Essmat N. , Azuara O.
Published: February 2025

The introduction of artificial intelligence (AI)-driven tools has revolutionized offset well analysis, particularly in estimating well time for conceptualization and planning phases. Previously labor-intensive manual processes for analyzing legacy data have been transformed into digital predictions of activities, operational sequences, key performance indicators (KPIs), and risk estimations through a web application. This system comprises AI engines that model specific aspects of well construction, working with a user interface that enables control over data and domain parameters. Engineers can develop well designs and, using existing designs as references, the application computes KPIs, forecasts operational sequences, assesses risks, and estimates well durations. By employing probability distributions for each input and iterating the process multiple times, the application generates histograms for each output upon simulation completion. Before AI tools, engineers faced the daunting task of manually analyzing extensive drilling reports, a process that could take weeks. The new web application streamlines this into a swift, efficient process, drastically reducing time and enhancing accuracy. Tested successfully in projects across Mexico and Ecuador, the application has shown significant improvements in efficiency and competitiveness. These AI-driven tools not only save time but also reduce costs and carbon emissions, exemplifying their transformative impact on the oil and gas industry.
Earth Model Building Strategies for Hybrid Survey of 3D Towed-Streamer and OBN – Case Study from Gulf of Thailand
Authors: Chen S. , Hassan A. , Ming W. L. , Busrijal R. , Abadi W. , Sriiamsaard W. , Suheri S. , Hartono A. , Arbi S. , Andria L.
Published: February 2025

Summary Extended Abstract

This paper discusses the processing of first 3D towed streamer and ocean-bottom node (OBN) survey acquired in shallow water areas within the Offshore Thailand. The objective is to obtain accurate velocities and seismic images at reservoir level while also capturing karst features around the basement. The very complex geology and poor resolution of the legacy image, create difficulties in mapping the low angle thrust fault and the karst feature in Permian carbonate section.
Influence of the Tan-Lu Strike-Slip Fault Zone on Depositional Facies Distribution within the Fault Terrace Zone of the Yellow River Estuary Depression, Southern Bohai Sea, Eastern China
Authors: Guan Dayong , Qian Geng , Yue Junpei , Pan Wenjing , Lu Weiyan
Published: February 2025

The Bohai area is China's largest offshore crude oil production base, with proven reserves of Paleogene clastic rocks accounting for less than 30%. This positions it as a crucial production field for the future. Currently, accurately predicting the spatial distribution of these Paleogene clastic rock reservoirs remains a significant challenge. Located in the southern Bohai Sea, the fault terrace zone of the Yellow River estuary depression is bounded by the Tan-Lu strike-slip fault zone, which traverses eastern China. Recent drilling has revealed considerable variations in the spatial distribution of Eocene sandstone within this zone. Accurately predicting the predominant depositional facies is crucial for assessing the potential of this area.

The research methodology includes comprehensive studies on sedimentation influenced by structural dynamics, underpinned by source-to-sink system analysis. Specifically: (1) Analysis of paleontological stratigraphy and stratigraphic contacts subdivides the Eocene strata in this zone into six depositional cycles, characterized by clear lateral superposition relationships and episodic sedimentary features. (2) Structural evolution studies from the Paleocene to Eocene reveal that strata characteristics were shaped by the compressive actions of the Tan-Lu Fault Zone during the early Eocene to Paleocene, and by extensional influences during the mid to late Eocene. (3) Paleontological evidence indicates that under structural compression, the early Eocene strata predominantly developed on the western side of the fault terrace zone, while the central and eastern parts exhibited less development.

(4) During the mid to late Eocene, under tectonic extension, fracture channels functioning as sand transport pathways were extensively developed in the central to eastern parts. The primary direction of sand supply, influenced by extensional fractures in the source rock area, was oriented towards the eastern part of the fault terrace zone, rather than the central and western parts.

The study demonstrates that the differential tectonic activities of the Tan-Lu Fault Zone, characterized by initial compression followed by subsequent extension from the Paleogene to the Eocene, impact not only the stratigraphic distribution but also dictate the dominant depositional facies in the study area. Based on this insight, a targeted strategy for zonal and stratigraphic well placement within the fault terrace zone has been implemented, yielding promising exploration results.
Integration of an OGI Camera in a Legged Robot for a Fugitive Emission Monitoring
Authors: Campaci Renato , Moro Alberto , Borzone Tommaso , Favaretto Mauro , Vignali Andrea , Fassio Camilla , Corallo Nunzio , Garcia Fernando , Vandekerkhove Brecht , Lapijover Yoann , Aregger Severin , Shetti Sagar
Published: February 2025

OBJECTIVE/SCOPE

Methane emissions in Oil & Gas facilities are a significant concern due to methane's high global warming potential (GWP-100 of 28). Precise detection and quantification of methane emissions are essential for effective mitigation. Traditionally, methane monitoring is performed by operators using hand-held Optical Gas Imaging (OGI) cameras, which are used for hydrocarbon leak detection. However, this method exposes personnel to harsh environments, congested spaces, and potentially explosive atmospheres, and is prone to inefficiencies and errors, leading to unreliable emission estimates and undetected leaks.

Robotic platforms offer a promising solution for more frequent, reliable, and repeatable methane monitoring, reducing personnel exposure to unsafe environments. This paper presents an innovative solution involving a legged robot integrated with an OGI camera. The integration process included both hardware and software adaptations to ensure compatibility and operational efficiency. Field tests demonstrated the robot's ability to perform autonomous inspections and detect methane leaks effectively. This approach aims to enhance operator safety, enable early detection of greenhouse gases, and improve the efficiency of asset integrity management in Oil & Gas facilities.

METHODS, PROCEDURES, PROCESS

Eni and ANYbotics collaborated to integrate an OGI camera into the four-legged robot ANYmal D, developed by ANYbotics, to evaluate its potential for methane emissions monitoring. This robot is designed to perform autonomous missions in complex environments, such as Oil & Gas plants, even in the absence of GNSS signals. It has a good payload capacity and can climb stairs to reach monitoring targets. Additionally, the solution developed is potentially applicable to the ANYmal X robot, which is certified for operations in ATEX Zone 1.

RESULTS, OBSERVATIONS, CONCLUSIONS

The system successfully performed autonomous missions, detecting leaks with the OGI camera. Images were visible on the robot's control panel. Detection capability was not significantly affected by sky backgrounds, but warmer backgrounds provided better detection. The detection rate improved with GEM enabled, and closer focus allowed for the detection of lower flowrate leaks. Focus adjustments had to be done manually. The snapshot functionality missed frames due to the low write speed of the SD card. It is recommended to expose GEM settings in the workforce app and consider using an OGI camera with electromechanical focus.

NOVEL/ADDITIVE INFORMATION

This solution demonstrates the feasibility of using autonomous four-legged robots for methane monitoring in Oil & Gas plants, replacing human personnel. This approach aims to improve operator safety, achieve early detection of greenhouse gases, and enhance the efficiency of asset integrity management.
Reduced-Order Modeling for Fractured Reservoir Simulation by Use of Trajectory Piecewise Linearization
Authors: Gao Ming , Sun Wenyue , Xu Jianchun
Published: February 2025

Flow simulation for fractured reservoirs requires more computational cost than in conventional reservoirs, especially when fractures need to be explicitly characterized. Therefore, it is crucial to develop acceleration methods for subsurface flow simulation in fractured reservoirs. In this study, we use the embedded discrete fracture model (EDFM) for an accurate simulation of the flow behavior in fractured reservoirs and implement a reduced-order model (ROM) procedure as acceleration methods for this simulation. The procedure is based on proper orthogonal decomposition (POD) and trajectory piecewise linearization (TPWL). The POD method represents the states of the reservoir with a highly reduced set of bases, thus achieving the order reduction for linear solver in iteration. In order to achieve higher acceleration, the POD method is combined with TPWL, called the POD-TPWL method. POD-TPWL-based ROMs can directly obtain new solutions by linearizing solutions saved from previous simulation training without computing information such as Jacobin matrices. Therefore, this method can achieve more significant speed improvements. As variables in the fracture domain change more drastically than in the matrix domain, we improve settings such as the basis matrix in the POD-TPWL method so that we can accurately predict the variables in both domains and the production of the wells located in them. We tested the accuracy and robustness of the ROM with several test cases. The results show that the fractured system states maintain the required accuracy even when the schedules in the test case are significantly different from those in the training case. The speedup improvement using the POD-TPWL method is significant (depending on factors such as model size), and we achieved a 1155-fold speedup by applying the method to a 3D EDFM-based reservoir model.
Investigation on Dilation Mechanisms of Low-Permeability Sandstone Under Water Injection in Offshore Oil Field
Authors: Chen H. , Cao Y. , Yu J. , Ma Y. , Peng J. , Gao Y. , Li D.
Published: February 2025

Rock dilation technology by water injection is an alternative and novel method for the reservoir stimulation of the sandstones in the oil fields west of the South China Sea. In this paper, triaxial compression and permeability experiments, physical simulation experiments, and numerical simulation were used to uncover the mechanisms of the dilation and permeability enhancement for the low-permeability sandstones. It was found that the strain softening occurs, and the permeability increases to 4 times when the volumetric strain is -12% under the effective confining pressure of 0.2 MPa. The strain softening and shear dilation tend to be more obvious under lower effective confining stress. Making the sandstone saturated can decrease the cohesion and increase the internal friction and dilation angles. As for tensile parting dilation, many microfracture networks take place, and the permeability increases by 2 orders of magnitude at most. The physical simulation revealed that the stepped-shape pore pressure preprocessing, low temperature, and cyclic oscillation with 0.5 min have a positive impact on the dilation effects. The numerical simulation of the old well showed a good fitting effect of BHPs and exhibited an effective dilation radius of around 12.83 m. For the new well, the BHPs and formation pore pressure were predicted, and the tensile-shear composite micro-fractures with a radius of about 40 m occur in the near-wellbore zone. This paper can provide a theoretical basis and technical support for the field operation.
Reservoir Prospectivity in Sentolo Formation Based on the Porosity and its Diagenesis: Analog Study
Authors: Assyifas A. A. , Dirgantoro M. F. , Giwangkara A. M. , Akmaluddin A.
Published: February 2025

The presence of a petroleum system in the South Central Java Basin represents a promising new hydrocarbon exploration environment. The existence of limestone in the Sentolo Formation can serve as a prospect reservoir rock. This paper will discuss the analysis of reservoir prospectivity levels in the Sentolo Formation based on the porosity and diagenetic process of analog outcrops, which is the most cost-feasible approach for initial exploration.

This research method consists of data acquisition, analysis, and synthesis. The data acquisition phase consisted of literature studies and field investigation. Field investigation included surface geological mapping, stratigraphic measurement, and lithological sampling. The following step is data analysis in the laboratory. Thin sections from five Sentolo Formation outcrop rock samples were examined using a petrographic image analysis method to determine the microfacies, diagenetic processes, and porosity. The last step is data synthesis, which mainly involves the integration and interpretation to determine the reservoir prospect of the Sentolo Formation based on outcrop data.

Limestone in the Sentolo Formation in the study area consists of Allochthonous Bioclastic Rudstone (01), Allochthonous Bioclastic Floatstone (02), and Packstone with Abundant Foraminifera (03). The depositional environments of 01 and 02 were in the open marine environment, and 03 was deposited on the slope. Based on porosity calculation, sample 01 has the highest porosity (21,89%), followed by 02 (17,8%) and 03 (16,9%), which are classified as good porosity (Koesoemadinata, 1980). The dominant types of porosity found are interparticle and vuggy porosity. The presence of vuggy and other secondary porosities implies the diagenetic processes. The observed diagenetic events in this study include marine, burial, dolomitization, and meteoric processes. The meteoric process is the primary diagenetic event responsible for the secondary porosity evolution in the study area. This event occurs in the early diagenetic process (Eogenetic stage). Comparisons are also made with the petroleum production system in the South Sumatera Basin, which bears characteristics similar to those of the South Central Java Basin. The porosity of the Baturaja carbonate reservoir rock in the South Sumatera Basin ranges from 5.4% to 11.6%, whereas the porosity in the study area reaches 7% to 21.89%.
Detailed Geomechanical Characterisation and Application of Shallow Shale Gas Reservoirs with Complex Tectonic and Multiple Fracture Systems
Authors: Zhang Muyang , Xian Chenggang , Huang Xiaoqing , Liu Yunyi , Liu Yang , Wang Jianjun , Liu Cheng , He Yong
Published: February 2025

In the Haiba Anticline Area, characterized by its shallow depth and significant tectonic stresses, a diverse spectrum of fracture systems is present. This paper explores the block complexity through 3D geomechanical modeling and verification. The study quantitatively characterizes the planar stress state and its heterogeneity. Based on data from multiple wells, the formation overpressure mechanism is judged, and a 3D pore pressure model is established. The equivalent mechanical models of different levels of fracture systems are established by numerical simulation experiments. Finally, the 3D geomechanical simulation is carried out through the Visage simulator on the Petrel platform, and the quality control is combined with the field information. The plane complex stress state is quantitatively characterized by Q index, and a new Stress Non-Uniformity index is introduced to quantitatively characterize the plane stress inhomogeneity of the block. By integrating the geomechanical model and key geomechanical characterization parameters, the stability of natural fractures under different stress conditions was evaluated, and the multi-stage and multi-cluster fracturing scheme was optimized. These findings are crucial for efficiently exploring and developing marine shallow shale gas in southern China.
Leveraging Artificial Intelligence to Revolutionize Rigless ESP Planning and Intervention Optimization
Authors: Zhao Mengpan , Li Qijun , Hong Yuandong , Zhang Li , Xue Fan , Dai Rui
Published: February 2025

The deployment of Electric Submersible Pumps (ESPs) is a critical process in artificial lift for oil and gas wells, traditionally requiring rig-based operations that are both costly and time-consuming. Rigless ESP interventions offer a promising alternative, providing substantial cost and safety advantages. However, selecting the appropriate system has historically been a complex and uncertain process, hindering broader application.

This paper highlights the advantages of Rigless ESP replacements over traditional rig-based methods, describe the applicability and limitations of different types of Rigless ESP technology and addresses the challenges associated with selecting the appropriate system. It also introduces the Rigless ESP Advisor, an innovative AI-powered software designed to streamline the planning and optimization of Rigless ESP interventions. The Rigless ESP Advisor combines analytical formulas and machine learning algorithms to analyze well data and recommend the optimal Rigless ESP system. Engineers input key downhole parameters and production forecasts into the software, which then rigorously analyzes the data to provide precise, evidence-based recommendations. The Advisor's machine learning model, trained on historical well performance data, ensures that each well receives the most suitable solution.

A case study was conducted on a high-producing well that recently experienced pump failure. The Rigless ESP Advisor recommended a 5.5'' Rigless WDESP (Wireline Deployed ESP) system based on the well's parameters and a 30-day production forecast. The recommended system was successfully implemented, with on-site operations confirming its reliable installation and retrieval.
History-Matching of Historical Pressures from Naturally Fractured Reservoirs
Authors: Kayode Babatope , Stephen Karl
Published: February 2025

In this study, we developed the equation for calculating equivalent dual-media pressure for comparison to historical pressure from Naturally Fractured Reservoirs (NFR) during history-matching. Dual-Porosity Dual-Permeability (DPDP) approach is the most popular approach used for modeling NFRs, however, commercial DPDP simulators calculate individual rather than the equivalent dual-media pressure, leading to uncertainties during history-matching.

Using the DPDP representation of NFRs, the compressibility equation was used to derive a mathematical model for deriving the equivalent dual-media pressure from the simulated matrix and fracture pressures. By applying the compressibility equation to each media, we obtained an expression containing both equivalent dual-media compressibility and pressure-change. Using the known dual-media pressure at the start of a time-step and the pressure-change during the time-step, we obtained the dual-media pressure at the end of the time-step. The resulting mathematical model is a storativity-weighted function of the simulated matrix and fracture pressures.

A synthetic dataset shows the relationship between the simulated individual media, and the derived dual-media pressures, under different scenarios. In reservoirs with low matrix permeability, and high fracture-to-matrix porosity and permeability ratios, large uncertainties may arise when the simulated matrix pressures are compared to historical pressure data. In an application example, using dual-media pressure instead of the simulated matrix pressure resulted in better history-matching of pressure prior to model's property modifications. The history-matching of pressure is a non-unique process, this study provides a new degree of freedom that can be explored during such a process in NFRs. Prior to modifying model properties to obtain a history-match, the dual-media pressure rather than the individual matrix pressure should be the basis of comparison to observed pressure data.

This study is the first to demonstrate the uncertainty associated with using simulated matrix pressure to history-match historical pressure in NFR. The findings could be incorporated into commercial simulators to improve the history-matching process, and ensure that model property modifications are not used as compensation for the mis-match between incomparable elements.

Statements and Declarations

The authors have no financial interests, ethical considerations or competing interests to declare relating to the contents of this work.
Benefícios do uso dos antidepressivos no tratamento da fibromialgia
Authors: Lima Laura Emanuella Dias de , Sampaio Moniky Ellen Sales , Guedes Brenda Luisa Belo , Goes Adriano Matheus de Sá , Oliveira Letícia Gomes de , Guimarães Márcia Cristina Monteiro , Diniz Isabela Guerreiro , Palmeira Maurício Koury
Published: February 2025

Objetivo: Realizar uma análise crítica acerca dos benefícios do uso de antidepressivos no tratamento da fibromialgia. Métodos: Trata-se de uma revisão integrativa de literatura, utilizando de uma abordagem comparativa qualiquantitativa. A seleção dos artigos ocorreu por meio das bases de dados: PubMed e Cochrane library, utilizando os descritores patients AND fibromyalgia OR fibromyositis fibromyalgia syndrome AND antidepressive agents OR antidepressant drugs AND therapeutics OR treatment AND efficacy, e, posteriormente, foram adicionados ao gerenciador de referências bibliográficas Rayyan para avaliação de inclusão, exclusão e extração dos dados mais relevantes dos artigos. Resultados: Dentre os artigos avaliados a maioria revelou a eficácia dos antidepressivos, tanto individualmente, quanto combinados, na diminuição da dor na fibromialgia; A minoria concluiu que não houveram diferenças significativas na comparação dos índices de dor no começo e no final do estudo. Em suma, os estudos explicitaram as indicações da Sociedade Brasileira de Reumatologia para o tratamento da dor na fibromialgia. Considerações finais: Infere-se que o uso de antidepressivos oferece benefícios no tratamento da fibromialgia e que sua utilização individualmente supera possíveis efeitos colaterais. Porém, foi observada a necessidade de estudos que avaliem a eficácia a longo prazo dos antidepressivos para a fibromialgia.
Avaliação do estresse percebido em estudantes universitários
Authors: Silva Mariana Exel , Araújo Sabrina Vitória Conceição de Miranda , Lessi Giovanna Camparis
Published: February 2025

Objetivo: Avaliar o nível de estresse percebido em estudantes universitários. Métodos: O presente trabalho trata de um estudo transversal. Foram incluídos indivíduos de ambos os sexos maiores de 18 anos, acadêmicos de ensino superior a partir do segundo semestre letivo, não importando o curso ou turno. Os voluntários responderam ao questionário PSS-10 (Escala de Estresse Percebido de 10 itens). Foi realizada análise descritiva dos dados e para a comparação da pontuação do questionário foi empregando o Teste-t para amostras independentes, sendo considerado p ≤ 0,005. Resultados: Participaram do estudo 144 voluntários, sendo 102 (70,1%) do sexo feminino e 42 (29,9%) do sexo masculino. A média da idade dos participantes foi 23,13 anos (± 4,86). A média da pontuação PSS-10 foi 22,38 (± 2,96). Conclusão: De acordo com os resultados desse estudo, foi evidenciado um alto nível de estresse entre os estudantes universitários. Fatores como gênero, prática de atividade física, presença de distúrbios psiquiátricos, tabagismo e jornada de trabalho não demonstraram ter influência significativa na incidência do estresse dessa população.
On the issue of eyeball dislocation
Authors:   Ufa Research Institute, Ufa, Russia, Babushkin A.E. , Orenburkina O.I. ,   All-Russian Center for Eye and Plastic Surger y of the Bashkir State Medical University of the Ministr y of Health of Russia, Ufa, Russia, Israfilova G.Z. ,   Ufa Research Institute, Ufa, Russia
Published: February 2025

This review article presents material on eyeball dislocation, which is a rare occurrence in ophthalmic emergency practice, causing severe stress in patients. Diagnosing a dislocated eyeball is not difficult, since it is visible to the naked eye. The main goal of treatment of traumatic and spontaneous dislocation of the eyeball should be the earliest possible reposition of the dislocated eye in order to preserve visual functions and appropriate medication, incl. for the treatment of possible complications.

Uncomplicated spontaneous dislocation of the eyeball is usually not difficult to eliminate and in most cases does not require surgical intervention. In some cases, there is still a need for lateral tarsorrhaphy, an alternative to which is orbital decompression (especially indicated for patients with exophthalmos). It is important to prevent recurrences of eyeball dislocation by outpatient monitoring of such patients, identification and treatment of the underlying, provoking disease.

Key words: eye dislocation, eyeball prolapse, early reposition, orbital decompression
УЧАСТИЕ ИНСТИТУЦИОНАЛЬНЫХ ИНВЕСТОРОВ В КЛИМАТИЧЕСКОМ ФИНАНСИРОВАНИИ: МЕЖДУНАРОДНЫЙ ОПЫТ И ПЕРСПЕКТИВЫ
Authors: Ершов Д.Н.
Published: February 2025

Статья представляет собой первую часть исследования роли институциональных инвесторов в климатическом финансировании. На примере Германии показано современное состояние климатического финансирования в промышленно развитых странах как эффективного инструмента привлечения финансовых ресурсов для противодействия неблагоприятным изменениям климата и их последствиям. Особое внимание уделено роли институциональных инвесторов и механизмам стимулирования их участия в климатическом финансировании.

Introduction. Climate financing is among the most pressing and debated issues in the modern international financial system due to the growing threat of climate change and the need to respond to its impacts and finance the climate change mitigation and adaptation projects. The scale of financing and the urgency of making decisions necessitate the attraction of all possible sources of financing: public and private resources and the funds managed by institutional investors (banks, investment funds, management companies, insurance companies, etc.). Today there is some experience in using various financial mechanisms for mitigating the consequences and preventing further climate change and creating the conditions for participation of institutional investors. The study and generalization of this experience as well as the existing problems and prospects for further development is an urgent task for Russia in the formation of its own state climate policy. The research is aimedat analyzing the history and current state of climate finance in industrialized countries using the example of Germany. Particular attention is paid to the participation of institutional investors and mechanisms to stimulate their participation in climate finance. Methods. Analytical, historical, statistical, systemic-structural, and cause-and-effect methods were used in the research. All data were taken from open information sources. The data from specialized organizations dealing with climate finance issues were also used. Results. The history of climate finance development and international climate agreements is analyzed and briefly presented. The approaches and practices used in Germany for the development of climate finance and the attraction of institutional investors are analyzed. The mechanisms of climate projects financing within the country and abroad as well as problematic issues and prospects for further development of climate change are offered. Conclusion. Germany is making the significant efforts to support climate finance but they are not systemic. The practical experience of recent years indicates the inadequacy of using only market oriented mechanisms. The growing scale and the level of complexity of the tasks in resisting the negative climate change and its consequences requires more active support from the state, including stimulation of institutional investors for more active participation in climate finance.
РЕГУЛИРОВАНИЕ ПРОЦЕССА ФОРМИРОВАНИЯ РЫНКА ВЫСОКОКАЧЕСТВЕННОГО ПРОДОВОЛЬСТВИЯ В РЕГИОНЕ
Authors: Тумаланов Н.В. , Урусова И.Н.
Published: February 2025

Рассматриваются условия и закономерности функционирования рынка высококачественных продуктов с целью определения возможностей региональных производителей успешного выхода на данный рынок. Обоснована необходимость государственного регулирования и поддержки производителей продовольствия высокого качества, совершенствования институтов его регулирования. В процессе исследования применялись методы анализа: отраслевой конкурентной среды, ресурсов и способностей фирм, жизненного цикла товара, SWOT-анализ.

Introduction. The considered problem is of current relevance as the food quality is worsening year by year. It does not satisfy the consumer confidence. Moreover, some food becomes even dangerous. This is to say that the level of food security of population is decreasing. The process of food industry development is disturbed. The government body does not always take the trend and regularities for prime quality product in the policy. The goal of the research is to reveal the conditions and regularities of forming and functioning of the market in order to ground the necessity in its organizing by a state and to define the opportunities of regional manufacturers to enter the market with success. Different kinds of analyses (branch analysis, analysis of competitive environment, analysis of resources and capabilities of firms, product life cycle analysis, SWOT- analysis) were used in the research. Results.A reasonable rendering of some regularities of market functioning of the considered products, and conditions for creation of the market for them is given. The conditions that allow to get the marketshare and favourably compete in the market are revealed. The need in state regulation and support of high quality food manufacturers, enhancement of the institutes for regulation of this market is grounded. The obtained results are of theoretical importance, they enrich the competitive theory and the concept of market organization. The practical importanceis the opportunity to use the obtained results in implementing the strategy of food and processing industry development in a region and developing the competitive relations in this market.
ДИВЕРСИФИКАЦИЯ ПРЕДПРИЯТИЙ ОПК: СТРАТЕГИЧЕСКИЕ ОРИЕНТИРЫ И ПРАКТИКА
Authors: Юрин П.О. , Двоеглазов В.В.
Published: February 2025

Проведён анализ выполнения государственных программ, направленных на поддержку и развитие оборонно-промышленного комплекса Российской Федерации. Определены направления проектов по диверсификации предприятий оборонно-промышленного комплекса. Обобщён опыт производства продукции гражданского назначения, на основании которого сделаны выводы, характеризующие возможности диверсификации. Проведён системный анализ комплекса, на основании которого разработаны рекомендации для развития организаций отрасли. Сформированы направления приоритетов по повышению эффективности оборонно-промышленного комплекса.

Introduction. The relevance of military-industrial complex (MIC) diversification is caused by a drop in consumer demand, which is a consequence of decrease in the state defense order. In this context, the Government of the Russian Federation sets the task of increasing the share of manufacture of high-tech civilian and dual-use products at the defense industry enterprises. However, defense industry organizations face difficulties in choosing the lines of manufacture development. The goal of the research is to study the economic activity of the military-industrial complex and determine strategic development orienting points Results. Practical aspects of diversification were considered on the basis of electronic and radio-electronic industry of defense industry enterprises. According to the Ministry of Industry and Trade, 425 enterprises and organizations operate in electronic, radio and communications industry, and 371 of them participate in the implementation of the state defense order. The authors studied the successful experience of diversification of manufacturers of high-tech products (AO "Angstrem", Federal State Unitary Enterprise "Academician Pilyugin Center", OAO NPP "TEMP" named after F. Korotkov", AO NPO "Orion"). These are the difficulties that defense industry enterprises face with when diversifying: lack of skills and experience when promoting in highly competitive open markets; high risks when developing new markets with large investments; regular work to reduce the cost of manufacture of civilian products. The tasks set by the Government of the Russian Federation for the defense industry enterprises are carried out despite the difficulties described above. Conclusion. The SWOT analysis of the development of electronic industry in the military-industrial complex showed that the defense industry enterprises have established the manufacture of military products using the unique technological expertise, the commercialization of which in the civilian market is uncertain, since there is no experience of their application. Favorable conditions for defense industry enterprises to promote products in the civil sector were established. They are subsidies and support in Russian and foreign markets, directed action of federal programs and national projects.