Oil And Gas Industry Research Articles

Study of the Safety–Economy–Environmental Protection Coordination of Beijing’s Natural Gas Industry Based on a Coupling Coordination Degree Model

Under the guidance of high-quality development goals, the energy industry should not only pay attention to the development level but also to the coordination effect among multiple elements. In the process of low-carbon development, natural gas plays an important transitional role as a clean fossil energy. In this study, by introducing the theoretical perspective of energy trilemma, a comprehensive measurement system of the three-dimensional development level of the regional natural gas industry was constructed. Then, in order to overcome the limitation that the coordination effect is weakened due to the concentration of function values, an improved coupling coordination model was established based on the redefined coupling degree distribution function. Next, based on actual data from Beijing from 2006 to 2022, the safety–economy–environmental protection development level of the natural gas industry was empirically analyzed, and the coupling coordination degree of multi-dimensional factors was deeply investigated. The empirical results reveal the following: (1) Beijing is one of the largest natural gas consumption markets in China, so the economy level of its natural gas industry was relatively high. However, the safety level and environmental protection level needed to be improved. This is mainly due to the scarce resource endowment, and the dependence of economic growth on fossil energy. (2) The coupling coordination degree showed a fluctuating upward trend. The coordination degree of safety and environmental protection was the best, mainly because they coexisted and promoted each other at the policy level. The coordination degree of safety and economy was also relatively high, mainly because supply security could provide resource support for market expansion and stabilize price levels. Meanwhile, a prosperous market would stimulate energy exploration and infrastructure extension. This study will help to provide a high-quality development plan for the natural gas industry for solving the regional energy trilemma.

Design of an industrial fan-powered cooler unit at the TEG inlet of a conventional natural gas dehydration plant

The natural gas industry faces significant challenges due to water vapor that is associated with natural gas, which results to issues like hydrate formation, blockages, corrosion of processing facilities and flow assurance related issues. To address this, the triethylene glycol (TEG) dehydration process is crucial for efficient water removal. A critical component of this process plant is the fan-powered cooler which regulates the temperature of lean TEG for optimum dehydration. This research integrates the conservation principle of mass and energy balance in the development of the fan-powered cooler design models and HYSYS simulation of the conventional dehydration plant in order to analyze the performance of the fan-powered cooler in terms of mass and energy balance during the dehydration process. Analysis of the results showed that the fan-powered cooler as a single input and single output unit gave the same value of 0.14221kg/s for mass flow rate at inlet and exit streams, but in terms of energy balance, the inlet and outlet temperature was 60.14370C and 48.88890C respectively, the temperature difference (reduction) showed that the lean temperature was reduced by the cooler before it was feed to the contactor in order to prevent loss of TEG during the dehydration process. This clearly showed why a cooler is configured at the TEG inlet to the contactor in a dehydration plant and improves the efficiency of dehydration process.

Experimental evaluation of yield stress-thixotropy of waste fly-ash added drilling fluid: in context with HPHT/geothermal well drilling

Proper transportation of cuttings to the surface, prevention of various well-controlled issues, stability of wellbore, formation damage minimization, etc. are very important issues that depend crucially on properly designed and maintained rheology of the drilling fluids. Search and selection of suitable drilling fluid additives that can favorably alter its rheology has always been a challenge for oilwell drilling industries. On the other hand, disposal of fly ash, which is a waste of thermal power industries is a big time issue to resolve considering these two important aspects, i.e., drilling fluid rheology investigation as well as suitable disposal outlet of fly ash, the present analysis was aimed to investigate the effective application of fly-ash (a waste of thermal power plants) as possible favorable rheology altering additives of water-based drilling fluids for wellbore drilling industries. Various drilling fluid samples based on fly ash were prepared and experimentally tested for their yield stress and thixotropic behavior. Rotational rheometer MCR-102 (Make: Anton-Paar) was used for the rheological analysis. The investigation compared different drilling fluid combinations based on fly ash and oil additives. Various time-dependent rheological aspects, i.e., thixotropic characteristics like thixotropic area, loss modulus, and damping coefficient were experimentally explored. Additionally, yield shear stress values were investigated by controlled shear stress tests with MCR-102. At the outset, the comprehensive thixotropic analysis concluded that nearly 10% of the fly ash addition would optimally be beneficial to sustain the favorable yield-thixotropy to water-based drilling fluids. It was also concluded that fly ash addition did not affect the chemical reactivity of the drilling fluid. All the samples exhibited the desired shear thinning behavior. The damping factor was greater than unity which implied the dissipative nature of all the drilling fluid samples, however presence of oil in the sample reduced it.

Early warning study of field station process safety based on VMD-CNN-LSTM-self-attention for natural gas load prediction

As a high-risk production unit, natural gas supply enterprises are increasingly recognizing the need to enhance production safety management. Traditional process warning methods, which rely on fixed alarm values, often fail to adequately account for dynamic changes in the production process. To address this issue, this study utilizes deep learning techniques to enhance the accuracy and reliability of natural gas load forecasting. By considering the benefits and feasibility of integrating multiple models, a VMD-CNN-LSTM-Self-Attention interval prediction method was innovatively proposed and developed. Empirical research was conducted using data from natural gas field station outgoing loads. The primary model constructed is a deep learning model for interval prediction of natural gas loads, which implements a graded alarm mechanism based on 85%, 90%, and 95% confidence intervals of real-time observations. This approach represents a novel strategy for enhancing enterprise safety production management. Experimental results demonstrate that the proposed method outperforms traditional warning models, reducing MAE, MAPE, MESE, and REMS by 1.13096 m3/h, 1.3504%, 7.6363 m3/h, 1.6743 m3/h, respectively, while improving R2 by 0.04698. These findings are expected to offer valuable insights for enhancing safe production management in the natural gas industry and provide new perspectives for the industry’s digital and intelligent transformation.

Prediction of the Natural Gas Compressibility Factor by using MLP and RBF Artificial Neural Networks

Abstract The compressibility factor indicates the deviation of the real natural gas from the ideal behavior. It is one of the most important parameters in the natural gas industry. In the present study, two different types of neural networks – multi-layer perceptron (MLP) and radial basis functions (RBF) – were used to predict the compressibility factor Z of natural gas. The pressure, temperature, and speed of sound (SoS) were chosen as input parameters for the artificial neural network (ANN) models. The training and testing of the MLP-ANN and RBF-ANN were carried out on the basis of 151 days of continuous measurements. Different variants of both types of neural networks were implemented and a comparative analysis of their modeling capabilities was performed. The models developed show a very high prediction accuracy, with the results obtained showing a certain advantage of the RBF-ANN. The comparative analysis was performed on the basis of standard performance indicators such as R2 , root mean square error (RMSE), mean square error (MSE), mean absolute error (MAE). The present study shows an intelligent method implemented in two different variants to determine the compressibility factor of natural gas without the need to use the equation of state.

The Crucial Role of Geothermal Fluids in Reducing the Water and Carbon Footprints of Lithium Mining in Salt Flats Worldwide

ABSTRACT Thermal waters, which often have a high Li concentration, can influence the formation of Li-rich brines in the salt flats. Several studies suggest that geothermal activity accelerates the leaching of Li-rich volcanic rocks in the catchment areas of the closed basins, contributing to higher Li concentrations in brines. Considering that there is no salt flat in Chile or other parts of the world that does not have a present-day (active) or palaeo-geothermal system, there is a need for a holistic geoscientific study of the salt flats to investigate the association between lithium enrichment of brine in the salt flats and geothermal systems present in the host closed basins. The expected results of such studies in different salt flats will help understand the role of geothermal systems in forming economic Li deposits that could be selectively mined sustainably. This is because thermal waters can also concentrate Li in specific horizons, allowing for selective extraction with minimal impact on freshwater aquifers. This would be possible because conductive heating by underlying thermal water could induce circulation (convective overturn) of basin brines within hydrologically connected horizons. Accordingly, this geothermally induced brine circulation may develop a heterogeneous subsurface Li distribution, where thermal waters could be instrumental in forming Li-enriched horizons in subsurface brine. Deciphering and modeling the latter will form a strong and tangible basis for developing environmentfriendly methods for Li mining that will have negligible influence on the groundwater and wetland ecosystems using drilling technologies prevalent in the hydrocarbon industry for extracting particular sedimentary horizons. Further, geothermal systems present in the closed hydrologcal basins could aid in reducing the environmental footprint of Li mining by providing thermal energy for extraction processes and electricity generation using low-enthalpy binary power plants. Considering the focus on direct extraction of Li (DLE) in Chile and neighboring countries, it is necesary to integrate it with geothermal following holistic geoscientific studies involving geological, geochemical and geophysical investigations, validated by exploratory drilling. This will help mitigate environmental challenges associated with current DLE technologies by using geothermal water in the extraction process and expertise from the geothermal industry in brine recharge.

Technology Focus: Drilling Automation and Innovation (February 2025)

Everywhere you look these days, there is talk of how advances in big data, artificial intelligence (AI), and machine learning (ML) will revolutionize virtually every aspect of our lives. The thought of letting computer algorithms pore over mounds of data collected every day and spit out solutions to our biggest problems is certainly appealing. This month, we will look at how researchers in the drilling domain are using this potential to improve well construction. I would be remiss if I did not caution the reader to maintain some healthy perspective when looking at how other areas have been changed and assuming that a direct analog exists for drilling. Consider this: It is estimated that there are fewer than 100,000 wells drilled each year, meaning that more data is generated by traffic in a small city in a day than is produced by the entire global drilling industry each year. Suffice it to say, while AI and ML are powerful tools that will certainly effect change, one should not expect off-the-shelf solutions to simply be plug-and-play for revolutionizing drilling. Instead, it will be careful application of these tools combined with a strong grounding in the fundamental physics and engineering of the domain that will lead to meaningful progress. I urge readers to keep this in mind as they peruse the selection of papers for this month. Each takes a different approach to how problems are solved with data and algorithms, but they all share a common thread: There must be a solid foundation in domain knowledge to build a successful solution. Much like a sledgehammer, AI and ML are powerful tools, but they are not the right tool for every job. The key is knowing exactly when and how to use them in conjunction with everything else in the toolbox to achieve the maximum benefit. Recommended additional reading at OnePetro: www.onepetro.org. IPTC 24078 - Real-Time Detection of Stuck Pipe Using Hybrid AI/Physical-Prediction Models by Mohammed A. Malki, Saudi Aramco, et al. SPE 217953 - Drillstring Failures: Inevitable or Not? by G. Plessis, NOV, et al. SPE 220690 - Automating Drilling Practices To Compensate for Interactions Between Tool Joints and the Rotating Head by David Forrest, Precision Drilling, et al.

Optimizing the oil and natural gas industry: The role of ai and data analytics in ERP integration

Global energy requirements depend on the oil and natural gas industry which deals with efficiency issues and must meet both regulatory standards and environmental protection needs. Our research shows how adding artificial intelligence and data analysis tools into ERP systems solves industry problems. Enterprise resource planning systems powered by artificial intelligence make better supply chain decisions while helping businesses predict equipment maintenance needs leading to lower costs and more efficient operations. Research findings from case studies and industry data show that businesses reducing maintenance costs by 25% and improving logistics savings by 15% through AI-ERP implementation. While legacy systems, high costs and data security risks pose challenges the positive outcomes of merging AI with ERP systems prove greater in value. The research shows how these systems help energy companies operate more sustainably and emit less carbon in our modern energy environment. The sector will progress further as new developments like generative AI plus blockchain and edge computing enter the market. Companies need to train their teams, work with experts in the field and use clean technology solutions to stay ahead in today's changing market.

Future-Proofing Tech and Energy Organizations: The Strategic Role of Competence and Quality in Driving Innovation and Overcoming Failures

The Oil and Gas Industry (OGI) plays a vital role in sustaining a strong national economy, with its efficiency and competitiveness heavily shaped by the adoption of innovative technologies. Thus, the strategic role of competence and quality in driving innovation within the OGI is explored in this study. A quantitative approach is undertaken, and data is obtained from 260 middle- and senior-level executives spread across 15 registered and operational Oil and Gas (O&G) companies in the United Kingdom. To explore the relationship between innovation capabilities and performance outcomes, correlation, and Regression Analysis (RA) are undertaken. As per the findings, competence, particularly through structured feedback mechanisms and failure analysis, has a significant positive relationship with the quality of output performance. Also, in mitigating innovation failures and improving subsequent innovations, the structured feedback mechanisms are the most influential factors. As per the findings, developing innovation competencies enhances performance and sustainability in the O&G sector. Keywords: Innovation, Failures, Competitiveness, Quality, Oil and Gas industry.

Real options investments: Lessons from the US shale gas industry

AbstractUsing detailed project‐level investment data from the U.S. upstream natural gas industry, we examine the effect of the unexercised real options on individual firms’ real options investments. Drilling an unconventional well is a real options investment that is exercised by fracturing and completing the drilled well at an opportune time. We find a small negative but statistically significant effect of the number of unexercised options on real options investments. There is also a significant difference in the effect of unexercised real options on real options investment decisions of publicly traded and privately held firms.

Satellite quantification of methane emissions from South American countries: a high-resolution inversion of TROPOMI and GOSAT observations

Abstract. We use 2021 TROPOMI and GOSAT satellite observations of atmospheric methane in an analytical inversion to quantify national methane emissions from South America at up to 25 km × 25 km resolution. From the inversion, we derive optimal posterior estimates of methane emissions, adjusting a combination of national anthropogenic emission inventories reported by individual countries to the United Nations Framework Convention on Climate Change (UNFCCC), the UNFCCC-based Global Fuel Exploitation Inventory (GFEIv2), and the Emissions Database for Global Atmospheric Research (EDGARv7) as prior estimates. We also evaluate two alternative wetland emission inventories (WetCHARTs and LPJ-wsl) as prior estimates. Our best posterior estimates for wetland emissions are consistent with previous inventories for the Amazon but lower for the Pantanal and higher for the Paraná. Our best posterior estimate of South American anthropogenic emissions is 48 (41–56) Tg a−1, where numbers in parentheses are the range from our inversion ensemble. This is 55 % higher than our prior estimate and is dominated by livestock (65 % of anthropogenic total). We find that TROPOMI and GOSAT observations can effectively optimize and separate national emissions by sector for 10 of the 13 countries and territories in the region, 7 of which account for 93 % of continental anthropogenic emissions: Brazil (19 (16–23) Tg a−1), Argentina (9.2 (7.9–11) Tg a−1), Venezuela (7.0 (5.5–9.9) Tg a−1), Colombia (5.0 (4.4–6.7) Tg a−1), Peru (2.4 (1.6–3.9) Tg a−1), Bolivia (0.96 (0.66–1.2) Tg a−1), and Paraguay (0.93 (0.88–1.0) Tg a−1). Our estimates align with the prior estimates for Brazil, Bolivia, and Paraguay but are significantly higher for other countries. Emissions in all countries are dominated by livestock (mainly enteric fermentation) except for oil–gas in Venezuela and landfills in Peru. Methane intensities from the oil–gas industry are high in Venezuela (33 %), Colombia (6.5 %), and Argentina (5.9 %). The livestock sector shows the largest difference between our top-down estimate and the UNFCCC prior estimates, and even countries using complex bottom-up methods report UNFCCC emissions significantly lower than our posterior estimate. These discrepancies could stem from underestimations in IPCC-recommended bottom-up calculations or uncertainties in the inversion from aggregation error and the prior spatial distribution of emissions.

Cross-Linked Poly(Styrene-Co-Divinylbenzene)-Coated Quartz and Kaolinite Proppants For Hydraulic Fracturing Applications

AbstractThe hydraulic fracturing operation, used as a production process in shale gas and coalbed methane reservoirs in the oil and natural gas industry, consists of fracturing fluid, proppant, and many other chemicals. This study successfully produced hydraulic fracturing proppants based on quartz and kaolinite minerals using divinyl benzene cross-linked styrene polymer with an in situ suspension polymerization method. Morphological analysis of the prepared proppants confirmed their spherical structure and the sphericity of quartz and kaolinite proppants were determined as 0.9. The polymer shells of the prepared proppants showed thermal resistance up to 375 °C and then decomposed between 375 °C and 575 °C. As a result of mechanical tests, quartz proppants showed a crush resistance of 14.08% under a load of 18,000 psi. Similarly, a crush resistance of 14.28% for kaolinite proppants was determined under a load of 15,000 psi. The apparent densities of quartz and kaolinite proppants were determined as 1.635 g/cm3 and 1.365 g/cm3, respectively. However, quartz proppants mostly display brittle breakage behavior, while kaolinite proppants are plastically deformed under the applied load.

Metal-Organic Framework with Polar Pore Surface Designed for Purification of Both Natural Gas and Ethylene.

The advancement of high-value CH4 purification technology within the natural gas industry is paramount for industrial processes. Herein, we constructed ZJNU-402, a new porous material characterized by permanent porosity, as an effective adsorbent for separating C3H8/CH4 and C2H6/CH4 mixtures. The findings reveal an outstanding C3H8 adsorption capacity of 68 cm3 g-1 and a moderate C2H6 adsorption rate of 42 cm3 g-1, with a notably lower CH4 adsorption rate of 11 cm3 g-1. Noteworthy is the exceptional selectivity of ZJNU-402 for C3H8/CH4 and C2H6/CH4, standing at 375 and 31, respectively, surpassing many previously documented high-performance adsorbents and breaking the traditional trade-off between adsorption capacity and separation selectivity. Adsorption heat calculations show that compared with CH4 molecules, C3H8 and C2H6 molecules form stronger bonds with the skeleton, resulting in excellent separation performance. In addition, the breakthrough experiment of ZJNU-402 can also completely separate the ternary component C3H8/C2H6/CH4 mixture to obtain 99.95 % high-purity methane. At the same time, ZJNU-402 also has excellent structural stability, excellent recyclability, and low isosteric adsorption heat. Consequently, ZJNU-402 exhibits substantial potential for augmenting the efficacy of natural gas enrichment processes.

Design and realization of compressor data abnormality safety monitoring and inducement traceability expert system.

Centrifugal compressors are widely used in the oil and natural gas industry for gas compression, reinjection, and transportation. Fault diagnosis and identification of centrifugal compressors are crucial. To promptly monitor abnormal changes in compressor data and trace the causes leading to these data anomalies, this paper proposes a security monitoring and root cause tracing method for compressor data anomalies. Additionally, it presents an intelligent system design method for fault tracing in compressors and localization of faults from different sources. This method starts from petrochemical big data and consists of three parts: fault dynamic knowledge graph construction, instrument data sliding fault-tolerant filtering, and the fusion and reasoning of fault dynamic knowledge graph and instrument data variation monitoring. The results show that this method effectively overcomes the problems of false alarms and missed alarms based on fixed threshold alarm methods, and achieves 100% classification of two types of faults: non starting of the drive machine and low oil pressure by constructing a PCA (Principal Component Analysis)-SPE (Square Prediction Error)-CNN (Convolutional Neural Network) classifier. Combined with dynamic knowledge graph and NLP (Natural Language Processing) inference, it achieves good diagnostic results.

Assessing the potential of geothermal energy in Cambrian complexes for renewable energy transition in Lithuania

Several depleted Cambrian oil fields in Lithuania, with water-cuts reaching 99 %, present promising opportunities for geothermal energy utilization. This study focused on Lithuania’s Cambrian reservoir complex, which has the highest water production rates. The study aimed to explore the advantages of horizontal wells, a technology not previously employed for geothermal production in Lithuania, over traditional vertical wells. To optimize field development, various scenarios were evaluated using mechanistic models, with insights subsequently applied to real field conditions. The results from the mechanistic model demonstrated that horizontal wells outperform vertical wells in both water production and power generation. Furthermore, increasing fracture intensity was shown to enhance water output and power generation by operating the wells at pressures above fracture propagation, facilitating re-injection. However, the study also emphasized the importance of thorough reservoir characterization and modeling to account for geological complexities and improve production outcomes. In conclusion, the research underscores that horizontal wells offer several advantages over vertical wells for geothermal energy production. These include increased water production, higher power generation, reduced drilling costs, and enhanced operational efficiency. These benefits align with technological advancements observed in the hydrocarbon industry, making horizontal wells a viable solution for maximizing geothermal energy potential in Lithuania’s depleted oil and gas fields.

SCENARIO PLANNING FOR PT BANGGAI LNG'S BUSINESS STRATEGY TO FACE FUTURE LNG INDUSTRY CHALLENGES

Abstract- The liquefied natural gas (LNG) industry is undergoing significant transformation due to fluctuating global demand, the transition to renewable energy, and evolving regulations. PT Banggai LNG (PT BLNG), a key player in Indonesia, leverages its strategic location and advanced infrastructure to meet domestic and international demand. However, PT BLNG faces market volatility, intense competition, and increasingly complex environmental regulations. This research employs scenario planning to help PT BLNG develop business strategies to address challenges in the LNG industry, utilizing PESTEL analysis, Porter’s Five Forces, VRIO framework, and SWOT analysis. These analyses highlight regulatory pressures, competition, limited resources, and regional demand opportunities. Four strategic scenarios were developed: “Stable but Limited Growth,” “Emerging Markets,” “Challenging Markets,” and “Profitable but Constrained Markets.” Proposed strategies include cost optimization, infrastructure development, and market diversification. With early warning signals, a five-year roadmap, and the four strategic scenarios, PT BLNG is expected to adapt to uncertainties, align with global energy trends, and sustain its long-term competitiveness in the LNG industry in Indonesia and the surrounding region. Keywords: Business Strategy; Liquefied Natural Gas; Scenario Planning

Estimation of the reduction in produced water discharges through the application of relative permeability modifier treatments

The management of produced water is a significant environmental challenge, particularly considering the goal to achieve 'Water Neutrality' by 2045, which requires the entire elimination of discharges into water bodies. In Colombia, discharged water currently accounts for over 30% of total water production, approximately 80 million m3, which adversely affect various ecosystems. Moreover, the economic implications are substantial, as each barrel of produced water represents a significant quantity of unextracted oil, impacting the fields’ profitability. To address this issue, various stimulation methods have been used to mitigate water production. This study is intended to assess the efficacy of these techniques in reducing water production and improving environmental management. The Universidad Industrial de Santander, through its specialized services to the hydrocarbon industry, has conducted numerous assessments of relative permeability modifier (RPM) treatments across diverse scenarios and conditions. These evaluations have revealed high reduction in water permeabilities of up to 90%, effectively curbing water contributions from producer wells. This approach not only yields tangible benefits for companies by averting treatment costs, but also translates into environmental benefits through reduced water discharge. In this study, we leverage this expertise to assess the potential impact of RPM treatments on water production. By analyzing changes in relative permeability curves via reservoir simulation, we aim to estimate the prospective decrease in water production and, consequently, the reduction in oil industry discharges in Colombia prior to a widespread implementation of this technique.

Strategic asset management in LNG Plants: A holistic approach to long-term planning, rejuvenation, and sustainability

The liquefied natural gas (LNG) industry plays a vital role in the global energy landscape, balancing growing energy demands with the imperative of reducing environmental impacts. However, the sector faces significant challenges, including aging infrastructure, the need for operational efficiency, and adherence to sustainability goals. This paper explores the role of strategic asset management (SAM) as a holistic solution for optimizing LNG plant operations. It introduces a comprehensive framework that integrates organizational, financial, and technical strategies, emphasizing long-term planning, rejuvenation, and sustainability. Key strategies, such as predictive maintenance, digital twins, and risk-based inspection methods, are discussed for their effectiveness in extending asset lifecycles and minimizing downtime. Furthermore, the paper underscores the importance of environmental, social, and governance (ESG) factors, renewable energy integration, and resilience planning in addressing climate risks and market volatility. Concluding with actionable recommendations, this paper provides a roadmap for stakeholders to adopt SAM practices, ensuring sustainable, resilient, and competitive LNG operations. Keywords: Liquefied Natural Gas, Strategic Asset Management, Sustainability, Predictive Maintenance, Digital Twin Technology, Resilience Planning.

INFORMATION AND SOFTWARE OF VIRTUAL REALITY TRAINING APPLICATION «NATURAL GAS DRYER PLANT»

Abstract. Traditional training methods for natural gas dehydration plant operators have several limitations. Theoretical training may need to provide more insight into real-world working conditions, while practical training can be dangerous or require significant financial investment. Virtual reality (VR) technology offers a potential solution to this challenge by enabling the replication of the natural gas dehydration plant experience in a safe, immersive digital environment. This research project has developed a software application that simulates the operation of a natural gas dehydration plant using VR technology. The article describes the world background and possible alternatives for the project's hardware and software implementation. Finally, the virtual environment was created using the Unity game engine, which incorporates Open VR and VRTK plugins to enable user interaction and navigation. The application allows users to explore the plant freely, interact with equipment and tools, perform standard operating procedures, and respond to emergency scenarios. The project has several scenarios controlled by the tutor that need to be solved by the student. All scenarios involve visual effects to increase immersion. A multi-user mode and voice chat functionality have also been implemented to facilitate collaborative learning. The development of this VR training application addresses the need for practical, hands-on learning in the natural gas industry, where actual equipment can be prohibitively expensive or hazardous. By providing a realistic, interactive virtual environment, the application aims to enhance the skills and understanding of natural gas dehydration plant operators, improving safety and operational efficiency. The application was developed on request and in close cooperation with the Department of Chemical Engineering at Sumy State University. The findings from this research can serve as a basis for further development of VR applications in various industrial and educational domains.

Additive Manufacturing in the Oil Gas Industry: Strategies for Managing Powder Waste in Multi Jet Fusion Printing (MJF)

Additive Manufacturing in the Oil Gas Industry: Strategies for Managing Powder Waste in Multi Jet Fusion Printing (MJF)