Optimal Production Research Articles

Optimizing Production Well Geometry in the Utah FORGE Geothermal Project Using Machine Learning and Fluid Flow Modeling

This study addresses the critical challenge of optimizing well placement in Enhanced Geothermal Systems (EGS), specifically within the framework of the Utah FORGE geothermal project, as part of the 2023 Society of Petroleum Engineers (SPE) Geothermal Datathon. Effective well placement is essential for enhancing geothermal production efficiency and maximizing resource utilization. We employed a discrete fracture network (DFN) modeling approach, utilizing the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm from the Scikit-Learn library to analyze microseismic event location data. Through rigorous simulations conducted in the open-source GeoDT fluid flow simulator, we identified an optimal production well configuration characterized by a spacing of 400 m, an injection rate of 0.03 m³/s, and alignment parameters that significantly improve thermal recovery. The results indicate a projected net present value (NPV) of $75 million over a 20-year operational horizon, underscoring the economic potential of optimized well placement strategies. This study offers valuable insights for the operation of the FORGE geothermal site. More importantly, it exclusively utilizes open-source tools, enhancing accessibility and adaptability for the broader geothermal community.

Glycerol-silica/chitosan conjugated self-assembled nano-flower framework for Herstulla thompsoni delivery with effectiveness in natural settings: Optimization and pilot scale production

Hirsutulla thompsoni (HTS) is an entomopathogenic fungus (EPF), a secure and efficient substitute for synthetic insecticides. However, its susceptibility to degradation in conventional formulations limits its practical use for agricultural practices. In light of current setbacks, this work proposes using a glycerol-silica/chitosan nanoflower gel (NFG) as an efficient delivery system to enhance the efficacy of HTS. Inspired by glycerol-silica-chitosan conjugation, NFG self-assembles into flowers. The HTS-loaded nanoflower gel (HTS_NFG) features a flower-shaped morphology, an average size of 232 nm, and a zeta potential of +31.84mv. The laboratory-scale NFG is optimized with ingredients and process factors using multivariate principal component analysis (PCA), which progressed to pilot size 10 kg/shift. The notable foliage retention attributable to chitosan and lower contact angle was achievable on the hydrophobic leaf surface. The result of foliage retention and contact angle obtained showed a significant effect of NFG (p < 0.05). HTS_NFG was comparatively safer towards Chlorella spp. algae and Artemia salina, significant from other treatments (p < 0.05). Field efficacy evaluation demonstrated that the NFG was as effective as the reference sample against aphids. With its proven effectiveness, the NFG may be an aesthetic, sustainable, and feasible alternative for agro-production.

Antennal olfactory responses in the black soldier fly Hermetia illucens

The Black Soldier Fly (BSF) is considered as the “crown jewel” of the insect feed industry and circular economy, significantly contributing to the 2030 Sustainable Development Goals by reducing carbon dioxide emissions and enabling circular management of organic waste, animal manure, and plant residues. Despite their industrial importance, limited knowledge about adult BSF biology has hindered optimal mass production. In this context, the present paper aims to explore the olfactory capabilities of both male and female BSF in response to various odorants commonly associated with organic decomposition in substrates suitable for mate encounters and egg laying. This will be achieved by performing electroantennographic recordings and scanning electron microscopy (SEM) observations on the antennal sensilla. Our results demonstrate for the first time the supposed olfactory capabilities of BSF antennae and present a first dataset of substances emitted by decaying organic matter detected by both male and female flies. Additionally, the current EAG recordings allowed comparisons with molecular data previously obtained through in silico and in vitro methods, highlighting the need for caution and strongly supporting a multidisciplinary approach as the best tool for investigating insect chemical ecology. These findings advance our understanding of BSF chemical ecology, which is crucial for effective reproduction and could significantly optimize global breeding systems

Continuous bioethanol production from glucose-rich hydrolysate derived from wheat straw using a unique fed-batch cultivation method in a bioreactor

The present study provides solutions to the bioethanol industry’s main issues of the absence of production of maximum fermentable sugars from lignocellulosic biomass, the unsuitability of a single microorganism to convert the fermentable sugars (xylose and glucose) together to bioethanol, and the unavailability of fermentation technique to run the process unlimitedly with consistent yield and productivity. A novel fractional acid hydrolysis technology was demonstrated in this study, which produced more than 90% (w/w) of available glucose in wheat straw as glucose-rich hydrolysate (GRH). This hydrolysate was then made acid-free using a membrane-based acid separation unit to reuse the separated acid to make the hydrolysis process environmentally safe and chemically inexpensive. Thereafter, this acid-free GRH was fermented to bioethanol using a unique constant volume fed-batch fermentation technique under an optimum glucose-feeding strategy. Remarkably, this fermentation technique yielded optimal average bioethanol productivity (g/Lh), yield (g/g), and titer (g/L) of 7.147±0.533, 0.508±0.002, and 58.835±0.766; 5.722±0.529, 0.501±0.006, and 33.748±0.322, respectively, with more than 99% glucose utilization during ten fed-batch cycles of synthetic and GRH glucose. Notably, the high production of GRH from lignocellulosic biomass, acid separation and reuse, and continuous and consistent bioethanol production sets this study apart as a pioneering endeavor. Furthermore, the bioethanol profit of USD 0.019/kg biomass from the second batch onwards at a bioethanol selling price of USD 0.745/L suggests the feasibility of the current study for industrial-scale bioethanol production from lignocellulosic biomass.

Optimization of heterogeneous continuous flow hydrogenation using FTIR inline analysis: a comparative study of multi-objective Bayesian optimization and kinetic modeling

Heterogeneous continuous flow hydrogenation is important in the chemical industry, yet the simultaneous optimization of yield and productivity has historically been complex. This study introduces a heterogeneous continuous flow hydrogenation system specifically designed for preparing 2-amino-3-methylbenzoic acid (AMA), employing FTIR inline analysis coupled with an artificial neural network model for monitoring. We explored two distinct reaction optimization strategies: multi-objective Bayesian optimization (MOBO) and mechanism-based intrinsic kinetic modeling, executed in parallel to optimize reaction conditions. Remarkably, the MOBO approach achieved an optimal AMA yield (99%) and productivity (0.64 g/hour) within a limited number of iterations. In comparison, despite requiring extensive experimental data collection and equation fitting, the intrinsic kinetic modeling approach yielded a similar optimal result. Thus, while MOBO offers a more efficient route with fewer required experiments, kinetic modeling provides deeper insights into the optimization landscape but may be impacted by non-chemical kinetic phenomena and requires significant time and resources.

Modeling noisy learning in a dynamic oligopoly experiment

Estimating demand before production poses a significant challenge for many industries, including vaccine manufacturing, newspapers, and perishable foods. Both industry professionals and experimental subjects in laboratory settings often struggle to determine optimal production. This paper sheds light on the cognitive processes that explain individuals' inability to act optimally, using data from Nagel and Vriend (1999a,b). In their experiment, participants, acting as firms, set production levels without prior knowledge of the demand generated by own and competitors' advertising efforts. We first reexamine their two-step learning model, which involves directional learning for production levels and a hill-climbing algorithm for advertising, utilizing exogenous adjustment size distributions. We improve upon this model, inspired by the macroeconomic learning literature, with agents using constant gain learning for production decisions and hill climbing for advertising decisions with endogenous adjustments. We demonstrate that our model provides a better fit to the data than the original model by Nagel and Vriend (1999a) and yields superior out-of-sample forecasts, both for one-period-ahead predictions and simulated paths.

Analyzing Single-Valued Neutrosophic Fuzzy Graphs Through Matroid Perspectives

We hope to present this paper on the emergence of a novel category of matroids derived from single-valued neutrosophic (SVN) fuzzy-graphs. The findings of this study make a substantial contribution to both matroid theory and the field of neutrosophic systems. In this study, we aim to introduce the concept of SVN-matroids and conduct a thorough investigation into their fundamental properties. Additionally, we explore the essential requirements for establishing duality within the realm of matroids formed from neutrosophic fuzzy-networks. This investigation encompasses co-weak isomorphism, weak isomorphism, and isomorphism between two matroids. Furthermore, our research proposes the expansion of other graph products and the creation of a SVN-graph to utilize the Greedy and Kruskal algorithms for determining optimal productivity in an information flow of a single-source network within a SVN-network. The application of neutronosophic graph theory offers a paradigm for addressing optimization problems in chemical graph theory, such as identifying the maximal independent set and a minimum spanning tree. When faced with uncertainty, neutrosophic optimization provides more reliable solutions by considering the uncertainties associated with the objective function or constraints.

Performance Analysis of the 1 MW Rooftop Solar Power Generation System at the Karawang

Electric energy is crucial for development, with Indonesia's projected electricity demand reaching 120 GW by 2025. The National Energy Policy emphasizes the development of renewable energy, particularly Solar Power Plants (PLTS), which have rapidly advanced with increased efficiency and reduced production costs. PLTS has become an attractive option, especially in areas with high solar intensity, for applications such as home lighting and vaccine storage. The target PLTS capacity is 400 MW by 2024. Despite growing popularity, challenges such as high initial costs and efficiency in unstable weather conditions remain. Research shows that environmental factors and shading can affect PLTS performance. This study analyzes the performance of a 1 MW PLTS system at a ceramic factory in Karawang using Global Solar Atlas and PVsyst for simulation and comparison with field data. Simulation results indicate optimal power production &gt;90% with a performance ratio between 81.90% and 84.70%. The built PLTS shows a stable performance ratio above 79%, with power production differing by &lt;10% compared to PVsyst simulation, demonstrating system reliability in actual operational conditions. This research underscores the importance of environmental factors in PLTS design and operation to achieve maximum efficiency.

Conservation of local resources: The role of kepok banana blossom in supporting breast milk production

Optimal production of breast milk is essential to support the health and development of babies. One of the efforts that can be made to increase breast milk production is through the nutrition of breastfeeding mothers. This study aims to determine the effect of consumption of banana kepok blossoms on breast milk production. The study was conducted at PMB Midwife Fitri, Ciamis, using a pre-test and post-test design in an intervention group consisting of 15 breastfeeding mothers. The results showed that the consumption of banana kepok blossoms could significantly increase breast milk production, from an average of 54 mL before the intervention to 99 mL after the intervention. These findings provide an alternative to natural ingredients-based nutrition to support breast milk production in breastfeeding mothers.

Fusarium verticillioides pigment: production, response surface optimization, gamma irradiation and encapsulation studies

BackgroundNatural pigments are becoming more significant because of the rising cost of raw materials, pollution, and the complexity of synthetic pigments. Compared to synthetic pigments, natural pigments exhibit antimicrobial properties and is less allergic. Pigments from microbial sources could easily be obtained in an inexpensive culture media, produced in high yields, and microbes are capable of producing different colored pigments. Searching for new sources for natural pigments to replace synthetic ones in food applications has become an urgent necessity, but the instability of these compounds is sometimes considered one of the obstacles that reduce their application. Encapsulation provides an ideal solution for natural dye protection through a controlled release strategy. Thus, this study aims at isolation of several soil fungi and subsequent screening their pigment production ability. The chosen pigment-producing fungal strain underwent full identification. The produced pigment was extracted with ethyl acetate and estimated spectrophotometrically. As there is a necessity to obtain a high pigment yield for efficient industrial application, the best production medium was tested, optimum conditions for maximum dye production were also investigated through the response surface methodology, and gamma irradiation was also employed to enhance the fungal productivity. Encapsulation of the produced pigment into chitosan microsphere was tested. The pigment release under different pH conditions was also investigated.ResultsA new strain, Fusarium verticillioides AUMC 15934 was chosen and identified for a violet pigment production process. Out of four different media studied, the tested strain grew well on potato dextrose broth medium. Optimum conditions are initial medium pH 8, 25 °C-incubation temperature, and for 15-day incubation period under shaking state. Moreover, a 400 Gy irradiation dose enhanced the pigment production. Chitosan microsphere loaded by the pigment was successfully prepared and characterized by infrared spectroscopy and scanning electron microscopy.ConclusionThis irradiated Fusarium strain provides a more economically favorable source for production of a natural violet dye with an optimum productivity, enhanced yield, and improved properties (such as, enhanced stability, controlled release, and bioaccessibility) by encapsulation with chitosan for efficient application in food industry.

Methodology for determining the heat distribution in disc brakes of mine hoisting machines

Purpose. To study the course of heat phenomena in disc brakes using modern computing systems in order to determine and substantiate the operating parameters for the hoisting machine components. Methodology. The research uses software packages, with the help of which a computational-theoretical apparatus is developed for heat mode modeling processes. In particular, the mentioned function is used in the SolidWorks Simulation software with the ability to evaluate the errors of the calculation results. Findings. In the course of the research, the dependence of the hoisting machine disc brake performance on the operating parameters of its components was determined. The research has led to a better understanding of the heat transfer processes in disc braking devices, as well as the ability to study the friction response of various materials and determine optimal parameters that help improve the performance of braking systems. The effectiveness has been proven of the proposed method for analyzing the heat distribution processes of the mine hoisting machine drum components under the influence of operating and emergency braking modes. Originality. For the first time, a methodology for calculating the heating temperature distribution along the brake rim plane during a safety stop has been developed and substantiated. A method has also been developed for determining the temperature field arising under steady-state heating conditions, which occur after repeated operating braking and cooling of the device. In this case, when using the formula for determining the temperature on the brake rim surface, the sample length, the relative velocity between the friction components and the heat flow distribution coefficient are taken into account. The brake disc geometric model developed in the SolidWorks software package makes it possible to study the temperature change on the device rim in real time. Practical value. The proposed design improvement based on the research results of heating processes should improve vehicle safety. The cost of braking systems is expected to be reduced through the use of optimal materials and production technologies. The software methods for modeling and analyzing the temperature influence on brake discs of the Mine Hoisting Machine (MHM) have been improved. Based on the research results, recommendations have been developed for the optimum braking process of machines in various operating conditions.

Energy and exergy analysis of a newly designed photovoltaic thermal system featuring ribs, petal array, and coiled twisted tapes: Experimental analysis

Photovoltaic systems suffer from electrical efficiency loss due to increases in surface temperature. To tackle this problem, Photovoltaic Thermal, consisting of photovoltaic and tube configurations attached to its back, is suggested. This study attempts to develop a new collector design in photovoltaic thermal systems. The new design features ribs and petal arrays on its inner and outer surfaces and a coiled twisted tape positioned inside it. The study also uses silicon carbide enhanced nanofluid (0.3 % and 6 % volume concentration) and phased changing material (1 % volume concentration) to boost the thermal efficiency further. Using an indoor solar simulator, the study investigates the effects of mass flow rate in the range of (0.1–0.85) kg/s, solar irradiances of (400–1000) W/m2, and coolant types of (water, 0.3 % and 0.6 % SiC enhanced nanofluid, water and nanophase changing materials, and 0.3 % and 0.6 % SiC enhanced nanofluid and nanophase changing materials). Besides revealing the relationship between all the parameters studied, the results report a maximum electrical energy efficiency of 11.2 %, thermal energy efficiency of 86.2 %, and total exergy efficiency of 15.3 %. The system reached optimal power production of 25.99 W using a photovoltaic module with a maximum power rate of 30 W.

Optimization of microalgal-bacterial consortium flocculation through chitosan-diatomite composite materials: A sustainable approach to biomass harvesting

Chitosan-based flocculants are emerging as a promising technology for microalgae harvesting. However, the implementation of cost-effective and sustainable chitosan-inorganic composites within algal-bacterial symbiosis (ABS) systems for harvesting microalgal-bacterial consortiums (MBC) is still underdeveloped. This study addresses this gap by synthesizing and evaluating chitosan-diatomite composite materials (CTS/DTE), with a focus on their concentration impact on MBC flocculation. Optimal biomass production and flocculation performance were achieved at a CTS/DTE concentration of 60 mg/L during MBC co-culture. Comprehensive characterizations revealed that the largest particle size significantly contributed to superior flocculation efficiency. This efficacy was primarily attributed to the synergistic effects of net trapping and adsorption cross-linking, facilitated by the unique interaction between CTS and DTE. These interactions not only enhanced the bond between the flocculant and microalgal cells but also promoted the structural stabilization of the MBC flocs. Additionally, tryptophan-like proteins in the extracellular polymeric substances (EPS), as identified through three-dimensional fluorescence (EEM) analysis, were found to be the primary contributor to the hydrophobic properties of MBC flocs, significantly enhancing their adhesion and aggregation thermodynamics. Collectively, this research elucidates innovative strategies and provides both theoretical and practical insights for the efficient and cost-effective harvesting of MBC, underscoring the potential of CTS/DTE composites in enhancing the sustainability of ABS systems.

Simulation study of R1234ze and its mixed working medium in TEG‐ORC combined cycle

AbstractThermoelectric generation (TEG) and organic Rankine cycle (ORC) technologies both have their respective limitations in recovering waste heat from ships. However, the combination of TEG and ORC is an effective approach to achieve cascaded waste heat recovery and improve heat utilization efficiency. There has been some progress in research on waste heat recovery in maritime applications based on TEG‐ORC combined cycles. The selection of a working medium is a crucial element that directly influences the design and performance of the entire system, but there is limited research on the impact of different working fluids on combined cycle systems. In this study, a simulation model of a TEG‐ORC combined cycle system was established to examine its output potential using two different working fluids R1234ze and a mixture of R245fa/R1234ze. The results demonstrate that compared to employing the R1234ze working medium, the combined cycle system with the mixed working medium achieved a 13% increase in maximum output power, a 102% improvement in optimum thermal efficiency, and a 53% reduction in optimum power production cost. Additionally, the power output distribution in the system utilizing the mixed working fluid was more uniform compared to the system employing a single working medium. This confirms the great potential of using a mixed working fluid in a combined cycle system.

Electrothermal Conversion of Methane to Methanol at RoomTemperature with Phosphotungstic Acid.

Traditional methods for the aerobic oxidation of methane to methanol frequently require the use of noble metal catalysts or flammable H2-O2 mixtures. While electrochemical methods enhance safety and may avoid the use of noble metals, these processes suffer from low yields due to limited current density and/or low selectivity. Here, we design an electrothermal process to conduct aerobic oxidation of methane to methanol at room temperature using phosphotungstic acid (PTA) as a redox mediator. When electrochemically reduced, PTA activates methane with O2 to produce methanol selectively. The optimum productivity reaches 29.45 [[EQUATION]] with approximately 20.3% overall electron yield. Under continuous operation, we achieved 19.90 [[EQUATION]] catalytic activity, over 74.3% methanol selectivity, and 10 hours durability. This approach leverages reduced PTA to initiate thermal catalysis in solution phase, addressing slow methane oxidation kinetics and preventing overoxidations on electrode surfaces. The current density towards methanol production increased over 40 times compared with direct electrochemical processes. The in-situ generated hydroxyl radical, from the reaction of reduced PTA and oxygen, plays an important role in the methane conversion. This study demonstrates reduced polyoxotungstate as a viable platform to integrate thermo- and electrochemical methane oxidation at ambient conditions.

Electrothermal Conversion of Methane to Methanol at Room Temperature with Phosphotungstic Acid

Traditional methods for the aerobic oxidation of methane to methanol frequently require the use of noble metal catalysts or flammable H2‐O2 mixtures. While electrochemical methods enhance safety and may avoid the use of noble metals, these processes suffer from low yields due to limited current density and/or low selectivity. Here, we design an electrothermal process to conduct aerobic oxidation of methane to methanol at room temperature using phosphotungstic acid (PTA) as a redox mediator. When electrochemically reduced, PTA activates methane with O2 to produce methanol selectively. The optimum productivity reaches 29.45 [[EQUATION]] with approximately 20.3% overall electron yield. Under continuous operation, we achieved 19.90 [[EQUATION]] catalytic activity, over 74.3% methanol selectivity, and 10 hours durability. This approach leverages reduced PTA to initiate thermal catalysis in solution phase, addressing slow methane oxidation kinetics and preventing overoxidations on electrode surfaces. The current density towards methanol production increased over 40 times compared with direct electrochemical processes. The in‐situ generated hydroxyl radical, from the reaction of reduced PTA and oxygen, plays an important role in the methane conversion. This study demonstrates reduced polyoxotungstate as a viable platform to integrate thermo‐ and electrochemical methane oxidation at ambient conditions.

Production Physiology and Biochemical properties of Crude Thermophile Protease by Mild - Halophilic Bacillus thuringiensis aizawai HD 865

Objective: The current study aims to enrich the research library of Bacillus thuringensis, the most famous bacteria as a biopesticide, with a product that may enhance its ability as a biopesticide as well as its many other applications, namely the heat-tolerant alkaline protease. Methods: The strain Bacillus thuringiensis aizawai HD 865, obtained from HD Culture Collection was grown on a liquid growth medium of nutrient broth and yeast extract, and colonies were counted on agar plates. The zygote is then transferred to a skim milk environment to estimate the enzymatic activity under the different growth conditions of the growth environment (sodium chloride concentration, pH, aeration, fermentation duration), then testing the optimal conditions for enzymatic activity in the enzymatic reaction mixture (sodium chloride concentration, salinity resistance, optimum temperature, thermal stability, optimum pH and stability). Then analyze the data statistically. Results: Optimum alkaline protease medium production conditions were, 2 % NaCl, so Bacillus thuringiensis aizawai HD865 a mild - halophilic microorganism, aeration level 80%, pH 7 and 8 days of fermentation period. On the other hand, crude alkaline protease properties were found that, the optimum temperature for its activity was relatively high (70ºC), while heat-stabilities after 5 min of heating crude enzyme in boiling water bath then incubated for 15min on 30, 40, 50, 60, 70ºC, were 184.23, 178.07, 164.29, 165.51 and 121.46 Units, respectively; whereas the optimum pH was at pH 7.6 (151.76 Units) with tris buffer then at pH 9.6 with glycine - NaOH buffer; While pH stability was at pH 7.6 with tris buffer then at pH 8.4 with glycine - NaOH buffer. Thus, activities have decreased at different concentrations (0, 1, 2, 3, 4, 5 %) of sodium chloride in reaction mixture with enzyme activities (151.25, 137.35, 135.12, 135, 135.89, 114.38 Units) respectively, also decreased when rinse crude enzyme for 5 min in NaCl (0, 1, 2, 3, 4, 5 %), with (151.04, 175.57, 168.69, 154.61, 155.39 and 143.39 Units) respectively. Conclusion: Bacillus thuringiensis aizawai HD 865 strain is considered a low - salt tolerant strain, while the alkaline protease extracted from it is heat - resistant.

Optimization of coupling phase-change materials and thermal screens in façade-integrated hybrid photovoltaic collectors for optimal energy production and thermal comfort in buildings

The operation of building-integrated photovoltaic (BIPV) systems gives rise to a significant proportion of the solar radiation absorbed by the cells being unable to be converted into electricity. This phenomenon consequently increases the temperature. This temperature increase impacts the cells' electrical efficiency, leading to a reduction in their performance and accelerating their degradation. The combination of phase-change materials with insulating fluid blades, situated behind photovoltaic cells, represents a passive cooling solution that optimizes the performance of hybrid photovoltaic systems when incorporated into facades. The present study assesses a system that incorporates paraffin as a PCM and an argon layer in a PV-PCM-argon layer physical model (PVT/ArPCM), in comparison with a PV-PCM system (PVT/PCM), to enhance the thermoelectric performance of photovoltaic systems mounted on façades while ensuring optimal thermal comfort within buildings. The discrete heat transfer equations were solved using the Thomas algorithm and the iterative Gauss-Seidel method in conjunction with the implicit finite difference method. The findings illustrate that the electrical efficiency experienced only a slight increase, estimated at 0.01%, while there was a notable enhancement in the indoor thermal comfort experienced by occupants, with a 65% improvement observed due to the incorporation of an argon-filled thermal screen. The incorporation of an argon layer led to a minor reduction in temperature of 0.01°C in the photovoltaic cells, resulting in a minimal improvement of 0.014% in electrical power production. The phase-changing material incorporated into PVT/ArPCM demonstrated superior thermal management capabilities in comparison to the same material employed in PVT/PCM.

Boosted photothermal-assisted photocatalytic H2 production by dual heat source-based S-scheme heterojunction

With advances in catalytic research, improvement of catalytic efficiency by using photothermal synergies to strengthen the reaction mechanisms has been focused. In this work, a novel photothermal-assisted photocatalytic H2 production system was constructed by loading Co3O4 nanoparticles on surface of black carbon nitride (BCN) nanosheets, served as the dual thermal source to enhance photothermal effect for synergistically assisting in photocatalytic H2 evolution with optimal H2 production rate reached 3.7 mmol g−1 h−1, significantly higher than that of pure carbon nitride (CN) and BCN. Moreover, the S-scheme heterojunction is also formed between Co3O4 and BCN, leading to the optimization of the charge transfer path, which further promotes the improvement of photothermal-assisted photocatalytic H2 production activity. This study provides the design idea of coupling the multi-heat source effect with the heterojunction electron transport for constructing an efficient photothermal-assisted hydrogen production system.

Development of Machine Learning-Based Production Forecasting for Offshore Gas Fields Using a Dynamic Material Balance Equation

Offshore oil and gas fields pose significant challenges due to their lower accessibility compared to onshore fields. To enhance operational efficiency in these deep-sea environments, it is essential to design optimal fluid production conditions that ensure equipment durability and flow safety. This study aims to develop a smart operational solution that integrates data from three offshore gas fields with a dynamic material balance equation (DMBE) method. By combining the material balance equation and inflow performance relation (IPR), we establish a reservoir flow analysis model linked to an AI-trained production pipe and subsea pipeline flow analysis model. We simulate time-dependent changes in reservoir production capacity using DMBE and IPR. Additionally, we utilize SLB’s PIPESIM software to create a vertical flow performance (VFP) table under various conditions. Machine learning techniques train this VFP table to analyze pipeline flow characteristics and parameter correlations, ultimately developing a model to predict bottomhole pressure (BHP) for specific production conditions. Our research employs three methods to select the deep learning model, ultimately opting for a multilayer perceptron (MLP) combined with regression. The trained model’s predictions show an average error rate of within 1.5% when compared with existing commercial simulators, demonstrating high accuracy. This research is expected to enable efficient production management and risk forecasting for each well, thus increasing revenue, minimizing operational costs, and contributing to stable plant operations and predictive maintenance of equipment.