Type Of Gas Research Articles

Analysis of Blackening Reaction of Zn–Mg–Al Alloy Coated Steel Prepared by Anodizing Process

The rising demand for black-treated steel faces challenges with conventional black painting due to issues like scratching and peeling, impacting corrosion resistance and aesthetics. This study explores an alternative method, anodic oxidation, to blacken the surfaces of galvanized or coated steel plates. Parameters like temperature, duration, current density, and gas type were varied during the blackening process. The investigation aimed to identify key factors influencing the blackening. Scanning electron microscopy observed the morphology, while energy-dispersive X-ray spectroscopy and glow discharge mass spectrometry analyzed the chemical composition distribution. X-ray diffraction and X-ray photoelectron spectroscopy conducted compound crystal structure analysis. Results indicate higher temperatures, longer durations, and higher current densities improve blackening through anodic oxidation. Increased magnesium proportion on the surface leads to roughness and porous magnesium oxide formation, enhancing light absorption and explaining the observed blackening effect.

Natural gas exploration potential and favorable targets of Permian Fengcheng Formation in the western Central Depression of Junggar Basin, NW China

Based on the organic geochemical data and the molecular and stable carbon isotopic compositions of natural gas of the Lower Permian Fengcheng Formation in the western Central Depression of Junggar Basin, combined with sedimentary environment analysis and hydrocarbon-generating simulation, the gas-generating potential of the Fengcheng source rock is evaluated, the distribution of large-scale effective source kitchen is described, the genetic types of natural gas are clarified, and four types of favorable exploration targets are selected. The results show that: (1) The Fengcheng Formation is a set of oil-prone source rocks, and the retained liquid hydrocarbon is conducive to late cracking into gas, with characteristics of high gas-generating potential and late accumulation; (2) The maximum thickness of Fengcheng source rock reaches 900 m. The source rock has entered the main gas-generating stage in Penyijingxi and Shawan sags, and the area with gas-generating intensity greater than 20×108 m3/km2 is approximately 6 500 km2. (3) Around the western Central Depression, highly mature oil-type gas with light carbon isotope composition was identified to be derived from the Fengcheng source rocks mainly, while the rest was coal-derived gas from the Carboniferous source rock; (4) Four types of favorable exploration targets with exploration potential were developed in the western Central Depression which are structural traps neighboring to the source, stratigraphic traps neighboring to the source, shale-gas type within the source, and structural traps within the source. Great attention should be paid to these targets.

Microbial treatment of waste crumb rubber: Reducing energy consumption and harmful emissions during asphalt production process

The emergence of crumb rubber modified asphalt (CRMA) has promoted the recycling utilization of waste tires and the improvement of asphalt performance. However, its unsatisfactory storage stability and high construction temperature have brought about excessive energy consumption and environmental challenges. In this study, the waste crumb rubber (CR) was bio-desulfurized by the synergy between two types bacteria for 7 days and 14 days, respectively. On this basis, bio-desulfurization crumb rubber modified asphalt (BCRMA) was prepared. The desulfurization effect of CR was characterized. Thermal storage stability and environmental performance of BCRMA were mainly investigated. The results showed that bio-desulfurization increased the number of pores, surface roughness and specific surface area of CR, and decreased the content of sulfur element. Bio-desulfurization of CR improved the insufficient thermal storage stability of rubberized asphalt and reduced the risk of system segregation. Bio-desulfurization CR has been proven to be a promising environmentally friendly material that can effectively lower the release concentration and release type of harmful flue gas from CRMA. This study makes the large-scale promotion and application of CRMA possible.

Mechanism of hot‐spot formation of emulsion explosives sensitized by hydrogen‐storage glass microballoons

AbstractIn order to investigate the primary factors influencing hot‐spot formation in emulsion explosives sensitized by hydrogen‐storage glass microballoons (GMBs), we conducted impact calculations on hydrogen‐storage GMBs. The calculations focused on tracking two main mechanisms: the brittle collapse of GMBs and the adiabatic compression of internal gas. Various parameters were considered, including loading pressures, initial porosities, gas types, and initial gas pressures. Our findings indicate that the contribution of brittle collapse to hot‐spot formation is negligible, while adiabatic compression emerges as the predominant intrinsic mechanism for hot‐spot ignition in GMB‐sensitized emulsion explosives. Moreover, we observed that the ignition time remains similar for low‐pressure nitrogen and high‐pressure hydrogen. The addition of hydrogen does not result in an increased number of hot‐spots; however, it elevates the energy of each individual hot‐spot, thereby enhancing power delivery. Optimal selection of GMB size is crucial for hot‐spot formation and hydrogen storage. GMBs that are excessively large are prone to shell breakage, while overly small GMBs have limited hydrogen storage capacity. GMBs within the size range of 20 μm to 100 μm are deemed more suitable for emulsion explosives.

Development and Validation of Low-Cost Indoor Air Quality Monitoring System for Swine Buildings.

The optimal indoor environment is associated with comfortable temperatures along with favorable indoor air quality. One of the air pollutants, particulate matter (PM), is potentially harmful to animals and humans. Most farms have monitoring systems to identify other hazardous gases rather than PM due to the sensor cost. In recent decades, the application of environmental monitoring systems based on Internet of Things (IoT) devices that incorporate low-cost sensors has elevated extensively. The current study develops a low-cost air quality monitoring system for swine buildings based on Raspberry Pi single-board computers along with a sensor array. The system collects data using 11 types of environmental variables along with temperature, humidity, CO2, light, pressure, and different types of gases, namely PM1, PM2.5, and PM10. The system is designed with a central web server that provides real-time data visualization and data availability through the Internet. It was tested in actual pig barns to ensure stability and functionality. In addition, there was a collocation test conducted by placing the system in two different pig barns to validate the sensor data. The Wilcoxon rank sum test demonstrates that there are no significant differences between the two sensor datasets, as all variables have a p-value greater than 0.05. However, except for carbon monoxide (CO), none of the variables exhibit correlation exceeding 0.5 with PM concentrations. Overall, a scalable, portable, non-complex, low-cost air quality monitoring system was successfully developed within a cost of USD 94.

Statistical Analysis of Bubble Parameters from a Model Bubble Column with and without Counter-Current Flow

Bubble columns are widely used in numerous industrial processes because of their advantages in operation, design, and maintenance compared to other multiphase reactor types. In contrast to their simple design, the generated flow conditions inside a bubble column reactor are quite complex, especially in continuous mode with counter-current liquid flow. For the design and optimization of such reactors, precise numerical simulations and modelling are needed. These simulations and models have to be validated with experimental data. For this reason, experiments were carried out in a laboratory-scale bubble column using shadow imaging and particle image velocimetry (PIV) techniques with and without counter-current liquid flow. In the experiments, two types of gases—relatively poorly soluble air and well-soluble CO2—were used and the bubbles were generated with three different capillary diameters. With changing gas and liquid flow rates, overall, 108 different flow conditions were investigated. In addition to the liquid flow fields captured by PIV, shadow imaging data were also statistically evaluated in the measurement volume and bubble parameters such as bubble diameter, velocity, aspect ratio, bubble motion direction, and inclination. The bubble slip velocity was calculated from the measured liquid and bubble velocities. The analysis of these parameters shows that the counter-current liquid flow has a noticeable influence on the bubble parameters, especially on the bubble velocity and motion direction. In the case of CO2 bubbles, remarkable bubble shrinkage was observed with counter-current liquid flow due to the enhanced mass transfer. The results obtained for bubble aspect ratio are compared to known correlations from the literature. The comprehensive and extensive bubble data obtained in this study will now be used as a source for the development of correlations needed in the validation of numerical simulations and models. The data are available from the authors on request.

Investigation of SnO2-based Thick Film Gas Sensors through Optimization of Artificial Neural Networks Parameters for Hazardous Gas Detection

In the present study, a systematic approach for optimizing artificial neural network parameters for the detection of a greenhouse gas carbon di-oxide (CO2) through SnO2-based thick film gas sensors for a wide range of concentrations is presented. The un-doped and Pd-doped SnO2 thick film is used as the sensor. The approach includes dataset preparation, input and output variable selection, artificial neural network architecture selection, training, validation, hyperparameter tuning, and testing. The input variables were selected based on their relevance to the problem at hand, such as the concentrations of the gas. The output variables were the changes in resistance of the sensor in response to the corresponding input variables. The artificial neural network architecture was carefully chosen, considering factors like the number of layers, neurons per layer, activation functions, and learning rate. Using the prepared dataset, the artificial neural network was trained by adjusting the connection weights between neurons to minimize the disparity between actual and predicted sensor responses. After training, the accuracy of the artificial neural network and generalization ability were assessed using a separate dataset for validation. The approach in the presented study can be used for different types of gases, and can be utilized in various applications

Synthetic natural gas in the private heating sector in Germany: match or mismatch between production costs and consumer willingness to pay?

BackgroundThe residential heating sector in many European countries requires a fundamental transformation if it is to become climate neutral. Besides the introduction of efficiency measures and updating heating systems, scholars and practitioners consider replacing fossil fuels in existing heating systems a viable approach. Drop-in renewable gases such as biomethane and synthetic natural gas (SNG) cause considerably fewer carbon dioxide (CO2) emissions than natural gas and can be used in natural gas boilers, the dominant heating system in many European countries. To move the ongoing debate around e-fuels forward, this study reports on a Discrete Choice Experiment with 512 respondents in Germany that analyzed consumer preferences and willingness to pay (WTP) for SNG. I build on these insights by comparing WTP to the production costs, making evidence-based decision-making possible.ResultsThe results show that consumers prefer renewable gases over natural gas. Comparing the two types of renewable gases, SNG and biomethane, reveals that consumers clearly favor the latter despite the criticism it has come under in the last 10–15 years. Consumers show a surprisingly high WTP for increasing shares of SNG, with premia of 40 to almost 70% over a natural gas-based tariff. Comparing production costs to the WTP reveals that only tariffs with small shares of SNG (5% and 10%) can be offered at cost-covering prices.ConclusionsGiven the urgent need for a fundamental transition of the residential heating sector, marketers and policymakers should consider carefully whether it is worth channeling a rather unknown and expensive product like SNG into the voluntary market for heating gas, especially as biomethane is already established in the market and clearly a cheaper and more popular alternative.

Influence of Gas Type on Reactive Species Formation, Antimicrobial Activity, and Cytotoxicity of Plasma-Activated Water Produced in a Coaxial DBD Reactor

Influence of Gas Type on Reactive Species Formation, Antimicrobial Activity, and Cytotoxicity of Plasma-Activated Water Produced in a Coaxial DBD Reactor

Foam fractionation for the separation and enrichment of trace m-phenylenediamine and o-phenylenediamine in solution

In this study, a foam fractionation technique was developed for the separation and enrichment of the trace m-phenylenediamine (MPD) and o-phenylenediamine (OPD) in solution. Firstly, a self-designed foam fractionation device was assembled and built, followed by a comprehensive characterization on gas types, foam fractionation column parameters, and porous sieve plate material used in the apparatus. Subsequently, the most crucial parameters for the separation and enrichment, such as surfactant species, solution pH, electrolyte categories, and gas flow rate, were identified and optimized. The mechanisms of key processes during foam fractionation under the influence of these parameters were thoroughly discussed. Other influencing factors, such as surfactant concentration, foam collection time, and solution volume in the fractionation column, were optimized using response surface methodology (RSM). Under these optimal conditions, maximal enrichment ratios of 138.2 and 85.5 were achieved for MPD and OPD, respectively. Finally, foam fractionation coupled with high-performance liquid chromatography (HPLC) was employed to detect MPD and OPD in the solution. The results demonstrated limits of detection (LOD) of 1.5 × 10−2 μg/L and 1.5 μg/L for MPD and OPD, with relative standard deviation (RSD) values of 4.1 % and 3.9 %. When testing various actual samples, the recoveries were in the range from 92.0 % or greater in all cases. The method exhibited advantages of high sensitivity, precision, and accuracy, attributed to the high enrichment efficiency of foam fractionation. In conclusion, the foam fractionation method established in this study offers simplicity in apparatus, operational convenience, environmental friendliness (minimized use of organic solvents), and high enrichment efficiency. It proves valuable for the quantitative analysis of trace amounts of MPD and OPD in solution, presenting a novel approach for the detection of trace organic compounds in solutions.

Analytical assessment of hetero-/homogeneous combustion of magnesium particle: Fully explicit formulas for flame characteristics

In this study, by proposing a comprehensive multi-step model, the combustion of magnesium particles in O2-He, O2-Ar, and O2-N2 is scrutinized. In the current model, both the heterogeneous and homogeneous combustions are considered and the process is divided into four stages solid, liquid, and gas combustion and melting. Moreover, the diffusions of oxygen and unreacted magnesium to droplet and infinity together with surface exothermic reaction are considered. The governing equations are analytically solved and then, the formulas are extracted for combustion time and temperature, flame standoff distance, and evaporation rate as the functions of particle diameter, ambient temperature and pressure, oxygen mass fraction, type of inert gas, and Lewis numbers. For 120 µm particle and oxygen content of 0.05, time contributions of homogeneous and heterogeneous combustions are 85.8% and 14.2%, respectively. The burning time has drastic changes at ambient pressures below l atm, so that the burning time variations relative to the pressure in the environments less than 1 atm and greater than it are equal to 1200–1550 and 70–90 ms/atm, respectively. When the oxygen mass fraction is less than 0.29, combustion in helium-oxygen ends earlier than that in O2-Ar and O2-N2, but for the mass fraction greater than 0.35, it has the longest burning time.

Multiarray Gas Sensors Using Ternary Combined Ti3C2Tx MXene-Based Nanocomposites.

This paper reports chemiresistive multiarray gas sensors through the synthesized ternary nanocomposites, using a one-pot method to integrate two-dimensional MXene (Ti3C2Tx) with Ti-doped WO3 (Ti-WO3/Ti3C2Tx) and Ti3C2Tx with Pd-doped SnO2 (Pd-SnO2/Ti3C2Tx). The gas sensors based on Ti-WO3/Ti3C2Tx and Pd-SnO2/Ti3C2Tx exhibit exceptional sensitivity, particularly in detecting 70% at 1 ppm acetone and 91.1% at 1 ppm of H2S. Notably, our sensors demonstrate a remarkable sensing performance in the low-ppb range for acetone and H2S. Specifically, the Ti-WO3/Ti3C2Tx sensor demonstrates a detection limit of 0.035 ppb for acetone, and the Pd-SnO2/Ti3C2Tx sensor shows 0.116 ppb for H2S. Simultaneous measurements with Ti-WO3/Ti3C2Tx- and Pd-SnO2/Ti3C2Tx-based sensors enable the evaluation of both the concentration and type of unknown target gases, such as acetone or H2S. Furthermore, density functional theory calculations are performed to clarify the role of Ti and Pd doping in enhancing the performance of Ti-WO3/Ti3C2Tx and Pd-SnO2/Ti3C2Tx nanocomposites. Theoretical simulations contribute to a deeper understanding of the doping effects, providing essential insights into the mechanisms underlying the enhanced gas response of the gas sensors. Overall, this work provides valuable insights into the gas-sensing mechanisms and introduces a novel approach for high-performance multiarray gas sensing.

A comparative study of machine learning models for identifying noxious gases through thermal fingerprint measurements and MOS sensors

Recently, there has been a notable surge of interest in developing swift and precise gas detection and categorization tools through artificial intelligence. This work specifically focuses on designing a simple sensor array configuration and empirically compares various machine-learning models for identifying multiple gases. The study employs eight metal oxide semiconductor sensors, each operating independently based on the thermal fingerprint principle. These sensors are utilized to gather data on responses to different toxic gases, and a range of traditional machine learning classifiers are trained and assessed using this dataset. The classifiers undergo investigation across various train/test dataset split ratios and different principal component analysis dimensionalities. Average accuracy metrics are employed over the entire testing dataset to evaluate model performance. The results demonstrated the challenge of selectively detecting each gas type solely through conventional analyses with the gas response data of the proposed sensor array. Nevertheless, the utilization of machine learning models has exhibited promising outcomes in augmenting gas identification and classification. The findings reveal a consistent improvement in testing accuracy for the Gradient Boosting model, which achieves an outstanding accuracy rate, with instances of reaching 100% accuracy in the training dataset when three or more principal components are considered. This study highlights the potential of the proposed straightforward sensor array and presents effective recognition algorithms applicable to creating electronic noses for gas-sensing applications.

Cushion Gas Consideration for Underground Hydrogen Storage

Due to the increasing world population and environmental considerations, there has been a tremendous interest in alternative energy sources. Hydrogen plays a major role as an energy carrier due to its environmentally benign nature. The combustion of hydrogen releases water vapor while it also has a vast industrial application in aerospace, pharmaceutical, and metallurgical industries. Although promising, hydrogen faces storage challenges. Underground hydrogen storage (UHS) presents a promising method of safely storing hydrogen. The selection of the appropriate cushion gas for UHS is a critical aspect of ensuring the safety, efficiency, and reliability of the storage system. Cushion gas plays a pivotal role in maintaining the necessary pressure within the storage reservoir, thereby enabling consistent injection and withdrawal rates of hydrogen. One of the key functions of the cushion gas is to act as a buffer, ensuring that the storage pressure remains within the desired range despite fluctuations in hydrogen demand or supply. This is achieved by alternately expanding and compressing the cushion gas during the injection and withdrawal cycles, thereby effectively regulating the overall pressure dynamics within the storage facility. Furthermore, the choice of cushion gas can have significant implications on the performance and long-term stability of the UHS system. Factors such as compatibility with hydrogen, cost-effectiveness, availability, and environmental impact must be carefully considered when selecting the most suitable cushion gas. The present study provides a comprehensive review of different types of cushion gases commonly used in UHS, including nitrogen, methane, and carbon dioxide. By examining the advantages, limitations, and practical considerations associated with each option, the study aims to offer valuable insights into optimizing the performance and reliability of UHS systems. Ultimately, the successful implementation of UHS hinges not only on technological innovation but also on strategic decisions regarding cushion gas selection and management. By addressing these challenges proactively, stakeholders can unlock the full potential of hydrogen as a clean and sustainable energy carrier, thereby contributing to the global transition towards a low-carbon future.

Noble gas characteristics of microbial gas in the Qaidam Basin, China: Implications for helium enrichment processes

Helium is a critical, strategic and nonrenewable resource with limited reserves and unstable supplies. However, the helium sources and migration processes in petroliferous basins remain unclear. The Qaidam Basin features multiple reservoir layers, multiple genetic types of natural gas, and varying helium concentrations, providing an ideal natural laboratory for understanding the helium enrichment processes. Here, we present the original noble gas isotopic compositions and major gas components of 11 microbial gas samples from three gas layers in the Sebei No.1 gas field, eastern Qaidam Basin, China. The helium isotopic ratios range from 0.007 to 0.057 Ra, reflecting a predominantly crustal source. The Quaternary Sebei microbial gas features much lower helium concentration (0.0003–0.001%), 21Ne/22Ne ratio (0.031–0.034), and 40Ar/36Ar ratio (292–380) than thermogenic natural gases in the Qaidam Basin. The middle gas layer (II) of the Sebei gas field features higher 21Ne/22Ne and 40Ar/36Ar ratios than the top and bottom gas layers, displaying positive correlations with higher 4He groundwater concentrations before degassing, as calculated from 4He/20Ne ratios and 20Ne concentrations in air-saturated water. However, the correlations between the 4He contents in natural gas and the 21Ne/22Ne and 40Ar/36Ar ratios are unclear, suggesting that 4He dissolves into the groundwater system before degassing into a gas reservoir and that the variations in the 4He concentration in the gas phase are caused by the different levels of hydrocarbon dilution. Quantitative calculations of helium production revealed an external helium flux from the crustal basement except for the in-situ production from sedimentary strata even in this broadly-defined self-generating and self-preserving natural gas system. The helium resources in the Qaidam Basin are mainly distributed in tectonically active zones with uplifted pre-Jurassic basement rocks (providing sufficient helium sources), ancient groundwater systems (accumulating more helium) and suitable hydrocarbon production (acting as a carrier gas but diluting helium as slightly as possible).

Gas Sensors Based on Semiconductor Metal Oxides Fabricated by Electrospinning: A Review.

Electrospinning has revolutionized the field of semiconductor metal oxide (SMO) gas sensors, which are pivotal for gas detection. SMOs are known for their high sensitivity, rapid responsiveness, and exceptional selectivity towards various types of gases. When synthesized via electrospinning, they gain unmatched advantages. These include high porosity, large specific surface areas, adjustable morphologies and compositions, and diverse structural designs, improving gas-sensing performance. This review explores the application of variously structured and composed SMOs prepared by electrospinning in gas sensors. It highlights strategies to augment gas-sensing performance, such as noble metal modification and doping with transition metals, rare earth elements, and metal cations, all contributing to heightened sensitivity and selectivity. We also look at the fabrication of composite SMOs with polymers or carbon nanofibers, which addresses the challenge of high operating temperatures. Furthermore, this review discusses the advantages of hierarchical and core-shell structures. The use of spinel and perovskite structures is also explored for their unique chemical compositions and crystal structure. These structures are useful for high sensitivity and selectivity towards specific gases. These methodologies emphasize the critical role of innovative material integration and structural design in achieving high-performance gas sensors, pointing toward future research directions in this rapidly evolving field.

Experimental study of emission characteristics for fully premixed combustion of dimethyl ether and hydrogen based on flame ions

The detection of flame ion current is a promising approach in fully premixed combustion. However, how to control the excess air coefficient (α) by ion current still needs an effective method. For this reason, the application of natural gas (12T), hydrogen-doped 12T (12T-H) and dimethyl ether (DME) in fully premixed combustion is experimentally studied in this paper. The emission characteristics of NOx, CO and CO2 from fully premixed condensing gas boilers (FPCGB) were analyzed. The detection voltage generated by the flame ion current is used to monitor the NOx emissions of different gas types. A novel combustion control method based on flame ion current is proposed. The results show that hydrogen addition can reduce NOx, CO and CO2 emissions of 12T. The highest NOx emission is observed at a hydrogen volume ratio (HVR) of 15 % in the experiment. The detection voltage gradually decreases with increasing HVR. The CO2 of DME is always lower than 12T. When α exceeds 1.21, 1.31 and 1.12, respectively, DME exhibits higher values in NOx, CO and detection voltage compared to that of 12T. In addition, two combustion characteristic values are identified and proposed for combustion feedback control. The peak voltage (Up) can be used as a parameter to identify the type of gas. The emission voltage (Ue) can be used to determine whether the NOx emission concentration exceeds the 40 ppm threshold.

Effect of the pyrolysis conditions and type of feedstock on nanobiochars obtained as a result of ball milling

Currently, the production of nanobiochar (n-BC) using ball milling is a promising and cost-effective method. Studies concerning the physicochemical properties of bulk biochar (b-BC) in relation to pyrolysis temperature, various feedstocks or types of carrier gas have been thoroughly investigated. However, there is a lack of information on how the mentioned conditions determine the properties of the obtained n-BCs. In this study, b-BCs produced from different feedstocks (willow (WL), sewage sludge (SSL), rice husk (RH) and oilseed rape (OSR)), temperatures (450–750 °C) and carrier gases (N2 or CO2) were ball-milled to produce n-BCs. The specific surface area (SBET), elemental composition (C, H, N, O), morphology (SEM), functional groups (FT-IR), and crystalline and amorphous nature of the carbon (RAMAN) were determined. The size of n-BCs depended on the feedstock used (particles ranged from 30 to 87.9 nm). The type of feedstock mostly determined the properties of n-BCs. The most visible differences between n-BCs and b-BCs were observed for surface properties and C content. For all n-BCs, an SBET increase was observed after ball milling, which may enhance the adsorption potential of biochar. The most intense SBET changes were noted for WL-derived n-BCs obtained at 450 °C (increase from 7.2 to 146.3 m2/g) and at 750 °C (increase from 3.9 to 160.8 m2/g) and for RH-derived n-BCs produced at 550 °C (increase from 3.7 to 158.6 m2/g). The C content decreased for n-BCs produced from plant biomass (WL, RH and OSR) and increased (from 20 to 28%) for n-BCs derived from sewage sludge (SSL). Other physicochemical properties mainly depended on the feedstock used for biochar production.

Analysis of The Influence Between Mining, Agriculture and Processed Product Exports on Indonesia's Sales Development in International Trade in the Time Frame 2019-2022

Exports are one of the international trade activities that provide benefits to Indonesia, including capital transactions, employment, and foreign exchange reserves. There are 2 types of exports, namely oil and gas and non-oil and gas exports. The value of non-oil and gas exports tends to be higher than oil and gas exports. So this research focuses on three non-oil and gas sectors, which consist of mining, agriculture, and processing industry (processed products). The purpose of this study is to determine the effect of mining, agriculture, and processed product exports on Indonesia's sales in international trade in the 2019-2022 timeframe. This research uses a quantitative approach, and a multiple linear regression analysis model with the IBM SPSS 22 application. The research data comes from the Central Bureau of Statistics, the Ministry of Trade, and related agencies. The variables used include 3 independent variables and 1 dependent variable. The independent variables are mining exports (X1) with the commodities used are coal, copper, lignite, iron and steel, agricultural exports (X2), and exports of processed products (X3), and Indonesia's sales as the dependent variable (Y). Based on the results of the study, partially shows that mining exports, and processed products have a significant positive effect on Indonesian sales. While agricultural exports (X2) have no effect on Indonesian sales (Y).

Mechanistic analysis of acid gas storage and oil recovery in naturally fractured reservoirs using single matrix block approach

AbstractThe objective of this study is to assess the storage of acid gas, containing CO2 and H2S, in a depleted naturally fractured reservoir (NFR) using single matrix block (SMB) approach. The acid gas dissolution in oil is considered by Peng‐Robinson equation of state and compositional simulation. The PHREEQC package is used to determine acid gas solubility in formation brine. Three types of acid gases with different compositions are used for this study and their swelling behavior and miscibility in relation to the reservoir oil are analyzed. An SMB model, with a matrix block surrounded by fractures, is constructed, and validated for simulation of a real experiment. The simulation is conducted for synthetic and real reservoir fluids when the oil is in its residual saturation. A sensitivity analysis is performed to study the effects of key parameters, such as acid gas composition, reservoir pressure, permeability, porosity and matrix height on the storage capacity and oil recovery factor. The matrix has a volume of 27 m3 and about half of acid gas storage is achieved in the first 5 years while the simulations are run for 30 years. The results show that up to 90% of remained oil is recoverable, and more than 0.67 kmol of acid gas per cubic meter of matrix is stored whether matrix contains a real oil or a synthetic one. Higher storage is achieved for higher matrix porosities and heights and large H2S proportion in acid gas. In all cases about 10% of acid gas is trapped in water and the remaining 90% is dissolved in oil. The mineral trapping was more active in CO2‐rich acid gases. While about 10 kg of the matrix rock was dissolved in the acidic brine when the acid gas contained H2S, the amount of the dissolved minerals in acidic brine resulted from the injection of CO2‐rich acid gas was more than 16 kg. Finally, this study gives a comparative analysis of the storage performance of acid gas mixture and pure CO2. © 2024 Society of Chemical Industry and John Wiley & Sons, Ltd.