Effects of CH_(4)/CO_(2) multi-component gas on components and properties of tight oil during CO_(2) utilization and storage: Physical experiment and composition numerical simulation

An essential technology of carbon capture, utilization and storage-enhanced oil recovery (CCUS-EOR) for tight oil reservoirs is CO_(2) huff-puff followed by associated produced gas reinjection. In this paper, the effects of multi-component gas on the properties and components of tight oil are studied. First, the core displacement experiments using the CH_(4)/CO_(2) multi-component gas are conducted to determine the oil displacement efficiency under different CO_(2) and CH_(4) ratios. Then, a viscometer and a liquid density balance are used to investigate the change characteristics of oil viscosity and density after multi-component gas displacement with different CO_(2) and CH_(4) ratios. In addition, a laboratory scale numerical model is established to validate the experimental results. Finally, a composition model of multi-stage fractured horizontal well in tight oil reservoir considering nano-confinement effects is established to investigate the effects of multi-component gas on the components of produced dead oil and formation crude oil. The experimental results show that the oil displacement efficiency of multi-component gas displacement is greater than that of single-component gas displacement. The CH_(4) decreases the viscosity and density of light oil, while CO_(2) decreases the viscosity but increases the density. And the numerical simulation results show that CO_(2) extracts more heavy components from the liquid phase into the vapor phase, while CH_(4) extracts more light components from the liquid phase into the vapor phase during cyclic gas injection. The multi-component gas can extract both the light components and the heavy components from oil, and the balanced production of each component can be achieved by using multi-component gas huff-puff.

Quantitative Detection Model of Pernicious Gases in Pig House Based on BP Neural Network

To find a neural network model suitable to identify the concentration of mixed pernicious gases in pig house, the quantitative detection model of pernicious gases in pig house was set up based on BP （ Back propagation） neural network. The BP neural network was trained separately by the three functions, trainbr, traingdm and trainlm, in order to identify the concentration of mixed pernicious gases composed of ammonia gas and hepatic gas. The neural network toolbox in MATLAB software was used to simulate the detection. The results showed that the neural network trained by trainbr function has high average identification accuracy and faster detection speed, and it is also insensitive to noise; therefore, it is suitable to identify the concentration of pemidous gases in pig house. These data provide a reference for intelligent monitoring of pemicious gases in pigsty.

Application of Mass Spectrometry (MS)-coupled Techniques in Pesticide Residue Detection

Pesticide residue detection is an important work to ensure the quality safety of agricultural products.In the process of agricultural production,in order to prevent and control agricultural diseases and pests,a certain amount of pesticides need to be used.However,if pesticides are used excessively,there will be certain pesticide residues in crops and related products.Therefore,it is necessary to do a good job in pesticide residue detection.The gas chromatography-mass spectrometry(GC-MS)and liquid chromatography-mass spectrometry(LC-MS)detection methods have good results and can effectively detect pesticide residues in related products.This paper reviewed and analyzed the application of GC-MS and LC-MS in pesticide residue detection,and proposed optimization measures based on practical experience,hoping to provide reference for relevant scholars.

Fretting Wear Behavior of Medium Carbon Steel Modified by Low Temperature Gas Multi-component Thermo-chemical Treatment

The introduction of surface engineering is expected to be an effective strategy against fretting damage. A large number of studies show that the low gas multi-component （such as carbon, nitrogen, sulphur and oxygen, etc） thermo-chemical treatment（LTGMTT） can overcome the brittleness of nitriding process, and upgrade the surface hardness and improve the wear resistance and fatigue properties of the work-pieces significantly. However, there are few reports on the anti-fretting properties of the LTGMTT modified layer up to now, which limits the applications of fretting. So this paper discusses the fretting wear behavior of modified layer on the surface of LZ50 （0.48%C） steel prepared by low temperature gas multi-component thermo-chemical treatment （LTGMTT） technology. The fretting wear tests of the modified layer flat specimens and its substrate （LZ50 steel） against 52100 steel balls with diameter of 40 mm are carried out under normal load of 150 N and displacement amplitudes varied from 2 μm to 40 μm. Characterization of the modified layer and dynamic analyses in combination with microscopic examinations were performed through the means of scanning electron microscope（SEM）, optical microscope（OM）, X-ray diffraction（XRD） and surface profilometer. The experimental results showed that the modified layer with a total thickness of 60 μm was consisted of three parts, i.e., loose layer, compound layer and diffusion layer. Compared with the substrate, the range of the mixed fretting regime（MFR） of the LTGMTT modified layer diminished, and the slip regime（SR） of the modified layer shifted to the direction of smaller displacement amplitude. The coefficient of friction（COF） of the modified layer was lower than that of the substrate in the initial stage. For the modified layer, the damage in partial slip regime（PSR） was very slight. The fretting wear mechanism of the modified layer both in MFR and SR was abrasive wear and delamination. The modified layer presented better wear resistance than the substrate in PSR and MFR; however, in SR, the wear resistance of the modified layer decreased with the increase of the displacement amplitudes. The experimental results can provide some experimental bases for promoting industrial application of LTGMTT modified layer in anti-fretting wear.

Predicting gas-bearing distribution using DNN based on multi-component seismic data: Quality evaluation using structural and fracture factors

The tight-fractured gas reservoir of the Upper Triassic Xujiahe Formation in the Western Sichuan Depression has low porosity and permeability. This study presents a DNN-based method for identifying gas-bearing strata in tight sandstone. First, multi-component composite seismic attributes are obtained.The strong nonlinear relationships between multi-component composite attributes and gas-bearing reservoirs can be constrained through a DNN. Therefore, we identify and predict the gas-bearing strata using a DNN. Then, sample data are fed into the DNN for training and testing. After optimized network parameters are determined by the performance curves and empirical formulas, the best deep learning gas-bearing prediction model is determined. The composite seismic attributes can then be fed into the model to extrapolate the hydrocarbon-bearing characteristics from known drilling areas to the entire region for predicting the gas reservoir distribution. Finally, we assess the proposed method in terms of the structure and fracture characteristics and predict favorable exploration areas for identifying gas reservoirs.

Wide dynamic detection range of methane gas based on enhanced cavity absorption spectroscopy

Integrated cavity output spectroscopy(ICOS) is an effective technique in trace gase detection.The strong absorption due to the long optical path of this method makes it challenging in the application scenes that have large gas concentration fluctuation,especially when the gas concentration is high.In this paper,we demonstrate an extension of the dynamic range of ICOS by using a detuned laser combined with an off-axis integrating cavity.With this,we improve the upper limit of the dynamic detection range from 0.1%(1000 ppm) to 20% of the gas concentration.This method provides a way of using ICOS in the applications with unpredictable gas concentrations such as gas leak detection,ocean acidification,carbon sequestration,etc.

Preparation of polythiophene/WO_3 organic-inorganic hybrids and their gas sensing properties for NO_2 detection at low temperature

Polythiophene/WO3（PTP/WO3）organic-inorganic hybrids were synthesized by an in situ chemical oxidative polymerization method,and char- acterized by X-ray diffraction（XRD）,transmission electron microscopy（TEM）and thermo-gravimetric analysis（TGA）.The Polythiophene/ WO3 hybrids have higher thermal stability than pure polythiophene,which is beneficial to potential application as chemical sensors.Gas sensing measurements demonstrate that the gas sensor based on the Polythiophene/WO3 hybrids has high response and good selectivity for de- tecting NO2 of ppm level at low temperature.Both the operating temperature and PTP contents have an influence on the response of PTP/WO3 hybrids to NO2.The 10 wt%PTP/WO3 hybrid showed the highest response at low operating temperature of 70-C.It is expected that the PTP/WO3 hybrids can be potentially used as gas sensor material for detecting the low concentration of NO2 at low temperature.

Gas concentration monitoring system for small and medium-sized coal mines based on gas-sensing detection and single-chip control

This paper is aimed at the actual conditions of disaster caused by gas in small and medium-sized coal mines. A new gas concentration monitoring system for coal mines is developed on the basis of gas-sensing detection and single-chip control. The monitoring system uses the tin oxide as the main material of N-type semiconductor gas sensors, be- cause it has good sensitive characteristics for the flammable and explosive gas （ such as methane, carbon monoxide）. The QM-N5-semiconductor gas sensor is adopted to detect the output values of the resistance under the different gas con- centrations. The system, designedly, takes the AT89C51 digital chip as the core of the circuit processing hardware structure to analyze and judge the input values of the resistance, and then achieve the control and alarm for going beyond the limit of gas concentration. The gas concentration monitoring system has man）, advantages including simple in struc- ture, fast response time, stable performance and low cost. Thus, it can be widely used to monitor gas concentration and provide early wamings in small and medium-sized coal mines.

Real-Time Tunable Gas Sensing Platform Based on SnO_(2) Nanoparticles Activated by Blue Micro-Light-Emitting Diodes

Micro-light-emitting diodes(μLEDs)have gained significant interest as an activation source for gas sensors owing to their advantages,including room temperature operation and low power consumption.However,despite these benefits,challenges still exist such as a limited range of detectable gases and slow response.In this study,we present a blueμLED-integrated light-activated gas sensor array based on SnO_(2)nanoparticles(NPs)that exhibit excellent sensitivity,tunable selectivity,and rapid detection with micro-watt level power consumption.The optimal power forμLED is observed at the highest gas response,supported by finite-difference time-domain simulation.Additionally,we first report the visible light-activated selective detection of reducing gases using noble metal-decorated SnO_(2)NPs.The noble metals induce catalytic interaction with reducing gases,clearly distinguishing NH3,H2,and C2H5OH.Real-time gas monitoring based on a fully hardwareimplemented light-activated sensing array was demonstrated,opening up new avenues for advancements in light-activated electronic nose technologies.

Application of multi-component joint inversion in oil and gas exploration:A case study of reservoir and gas saturation prediction of the Xujiahe formation in the PLN area of the central Sichuan Basin

Multi-component seismic exploration is an important technique in the utilization of P-waves and converted S-waves for oil and gas exploration.It has unique advantages in the structural imaging of gas zones,reservoir prediction,lithology,and gas-water identifi cation,and the development direction and degree of fractures.Multi-component joint inversion is one of the most important steps in multi-component exploration.In this paper,starting from the basic principle of multi-component joint inversion,the diff erences between the method and single P-wave inversion are introduced.Next,the technique is applied to the PLN area of the Sichuan Basin,and the P-wave impedance,S-wave impedance,and density are obtained based on multi-component joint inversion.Through the velocity and lithology,porosity,and gas saturation fi tting formulas,prediction results are calculated,and the results are analyzed.Finally,multi-component joint inversion and single P-wave inversion are compared in eff ective reservoir prediction.The results show that multi-component joint inversion increases the constraints on the inversion conditions,reduces the multi-solution of a single P-wave inversion,and is more objective and reliable for the identification of reservoirs,effectively improving the accuracy of oil and gas reservoir prediction and development.

MOF/Polymer-Integrated Multi-Hotspot Mid-Infrared Nanoantennas for Sensitive Detection of CO_(2) Gas

Metal-organic frameworks(MOFs)have been extensively used for gas sorption,storage and separation owing to ultrahigh porosity,exceptional thermal stability,and wide structural diversity.However,when it comes to ultra-low concentration gas detection,technical bottlenecks of MOFs appear due to the poor adsorption capacity at ppm-/ppblevel concentration and the limited sensitivity for signal transduction.Here,we present hybrid MOF-polymer physi-chemisorption mechanisms integrated with infrared(IR)nanoantennas for highly selective and ultrasensitive CO_(2) detection.To improve the adsorption capacity for trace amounts of gas molecules,MOFs are decorated with amino groups to introduce the chemisorption while maintaining the structural integrity for physisorption.Additionally,leveraging all major optimization methods,a multi-hotspot strategy is proposed to improve the sensitivity of nanoantennas by enhancing the near field and engineering the radiative and absorptive loss.As a benefit,we demonstrate the competitive advantages of our strategy against the state-of-the-art miniaturized IR CO_(2) sensors,including low detection limit,high sensitivity(0.18%/ppm),excellent reversibility(variation within 2%),and high selectivity(against C_(2)H_(5)OH,CH_(3)OH,N_(2)).This work provides valuable insights into the integration of advanced porous materials and nanophotonic devices,which can be further adopted in ultra-low concentration gas monitoring in industry and environmental applications.

SELECTIVE SULFUR DIOXIDE DETERMINATION BY GAS DIFFUSION FLOW INJECTION ANALYSIS WITH CHEMILUMINESCENT DETECTION

Sulfur dioxide has been found to decrease the chemiluminescence of luminol-iodine system.A new determination method for sulfur dioxide in atmosphere is developed by applying this reaction to a flow injection gas diffusion separation system.This permits the determination of sulfur dioxide selectively and rapidly.

Detection and analysis of gas tightness of continuous annealing furnaces

When a cold rolled strip is being treated in a continuous annealing furnace which is full of protective gas, the gas tightness of the furnace body, the connected facilities and the gas channels become an important indicator that directly affects the product＇s surface quality and shows the technical level of the design, the manufacture and the installation. By considering the problems of the gas tightness of a vertical annealing furnace in the installation and maintenance, this thesis evaluates the gas tightness indicator and gas tightness related level of the furnace body and the circulation duct, while studying and analyzing the technologies of negative-pressure leak detection and sealing.

A gas kick early detection method outside riser based on Doppler ultrasonic wave during deepwater drilling

The feasibility of gas kick early detection outside the riser was analyzed based on gas-liquid multiphase flow theory.Then an experimental platform for gas kick early detection based on Doppler ultrasonic wave was established and the propagation experiments in two-phase flow of gas-water(sucrose solutions)were conducted.The time and frequency domains of the Doppler ultrasonic wave signals during the experiments were analyzed.The results show that:(1)No matter the pump was on or off,the detected average Doppler ultrasonic signal voltage increased first and then decreased with the increase of the gas void fraction,and had a quadratic function relation with gas void fraction,so the average voltage change of the monitored signals can be used to deduce the approximate gas void fraction.The Doppler ultrasonic wave signal voltage was significantly reduced in magnitude and variation in the solution with higher viscosity,and the viscosity has stronger impact on the magnitude of signal than density.(2)When the pump was stopped,the Doppler shift increased with the increase of gas void fraction,and the two showed a nearly linear relation,so the detected amount of Doppler shift can reflect the variation of gas void fraction quantitatively.When the pump was on,the sound energy produced by frequency converter had a more significant impact on amplitude spectrum than gas void fraction,so it is impossible to determine whether gas kick occurs by frequency domain signal analysis.(3)This method is a non-contact measurement,with no contact with the drilling fluid and no disruption to the drilling operation.It can quantitatively characterize the gas void fraction according to the change of Doppler ultrasonic signal,enabling earlier detection of gas kick.

Intra-Cavity Absorption Sensors for Gas Detection Using Wavelength Sweep Technique

Wavelength sweep technique （WST） is introduced into intra-cavity fiber laser （ICFL） for low concentration gas detection. The limitation induced by noise can be eliminated using this method, and the performance of the system is improved. The sensitivity of the system is reduced to less than 300 ppm. With WST, sweeping characteristic of the ICFL can be described according to known gas absorption spectra.

Rock physics modeling of heterogeneous carbonatereservoirs： porosity estimation and hydrocarbon detection

In heterogeneous natural gas reservoirs, gas is generally present as small patchlike pockets embedded in the water-saturated host matrix. This type of heterogeneity, also called "patchy saturation", causes significant seismic velocity dispersion and attenuation. To establish the relation between seismic response and type of fluids, we designed a rock physics model for carbonates. First, we performed CT scanning and analysis of the fluid distribution in the partially saturated rocks. Then, we predicted the quantitative relation between the wave response at different frequency ranges and the basic lithological properties and pore fluids. A rock physics template was constructed based on thin section analysis of pore structures and seismic inversion. This approach was applied to the limestone gas reservoirs of the right bank block of the Amu Darya River. Based on poststack wave impedance and prestack elastic parameter inversions, the seismic data were used to estimate rock porosity and gas saturation. The model results were in good agreement with the production regime of the wells.

A visible-light-assisted Pd/TiO_(2)gas sensor with carbon nanotubes electrodes for trace formaldehyde detection

Owing to the ppb-level detection standard toward the toxic and harmful gas,the detection of trace gases has become an important subject in the field of indoor environment management.However,the traditional resistive gas sensors hardly meet the requirement due to the weak signal generated by trace gas molecules that are difficult to capture.Herein,a visible-light-assisted Pd/TiO_(2)gas sensor is proposed to endow the effective detection of trace formaldehyde(HCHO)gas without heating temperature.Benefiting from the enhanced photocatalytic properties of TiO_(2)by Pd decoration,the visible-light-assisted Pd/TiO_(2)gas sensor can detect the HCHO gas as low as80×10^(–9)at room temperature.The successful preparation of nanoscale TiO_(2)sensing layer is facilitated by the ultrathin carbon nanotube interdigital electrode in the gas sensor,which avoids the discontinuity of the sensing layer caused by the excessive thickness of the traditional metal electrode.In addition,the whole preparation process of the Pd/TiO_(2)gas sensor with carbon nanotube electrodes is compatible with mainstream CMOS fabrication technology,which is expected to realize the batch fabrication and micro-integrated application of gas sensors.It is expected that our work can provide a new strategy for the batch preparation of high-performance trace HCHO gas sensors and their future applications in portable electronic devices such as smartphones.

Raman signal enhancement for gas detection using a dual near-concentric cavities group

Effective methods are urgently required to optimize Raman spectroscopy technology to ameliorate its low detection sensitivity.Here,we superposed two near-concentric cavities to develop a dual near-concentric cavities group(DNCCG)to assess its effect on gas Raman signal intensity,signal-to-noise ratio(SNR),and limit of detection(LOD).The results showed that DNCCG generally had higher CO_(2) Raman signal intensity than the sum of two near-concentric cavities.Meanwhile,the noise intensity of DNCCG was not enhanced by the superposition of near-concentric cavities.Accordingly,DNCCG increased the SNR.The LOD for CO_(2) was 24.6 parts per million.DNCCG could be an effective method to improve the detection capability of trace gases and broaden the dynamic detection range,which might aid the future development of innovative technology for multicomponent gas detection.

Gas sensor array based on carbon-based thin-film transistor for selective detection of indoor harmful gases

The identification of indoor harmful gases is imperative due to their significant threats to human health and safety.To achieve accurate identification,an effective strategy of constructing a sensor array combined with the pattern recognition algorithm is employed.Carbon-based thin-film transistors are selected as the sensor array unit,with semiconductor carbon nanotubes(CNTs)within the TFT channels modified with different metals(Au,Cu and Ti)for selective responses to NH_(3),H_(2)S and HCHO,respectively.For accurate gas species identification,an identification mode that combines linear discriminant analysis algorithms and logistic regression classifier is developed.The test results demonstrate that by preprocessing the sensor array’s sensing data with the LDA algorithm and subsequently employing the LR classifier for identification,a 100%recognition rate can be achieved for three target gases(NH3,H2S and HCHO).This work provides significant guidance for future applications of chip-level gas sensors in the realms of the Internet of Things and Artificial Intelligence.

Combining TDLAS and multi-fusion algorithms for methane gas concentration detection

High-precision methane gas detection is of great importance in industrial safety, energy production and environmental protection, etc. However, in the existing measurement techniques, the methane gas concentration information is susceptible to noise, which leads to its useful signal being drowned by noise. A fusion algorithm of variational modal decomposition(VMD) and improved wavelet threshold filtering is proposed, which is used in combination with tunable diode laser absorption spectroscopy(TDLAS) to implement a non-contact, high-resolution methane gas concentration detection. The fusion algorithm can perform noise reduction and further segmentation of the methane gas detection signal. And the simulation and experiment verify the effectiveness of the fusion algorithm, and the experimental results show that for the detection of air containing 10 ppm, 30 ppm, 60 ppm, 80 ppm, and 99 ppm methane, the errors are 12.75%, 8.18%, 3.37%, 2.46%, and 1.78%, respectively.