Log interpretation of carbonate rocks based on petrophysical facies constraints

The complex pore structure of carbonate reservoirs hinders the correlation between porosity and permeability.In view of the sedimentation,diagenesis,testing,and production characteristics of carbonate reservoirs in the study area,combined with the current trends and advances in well log interpretation techniques for carbonate reservoirs,a log interpretation technology route of“geological information constraint+deep learning”was developed.The principal component analysis(PCA)was employed to establish lithology identification criteria with an accuracy of 91%.The Bayesian stepwise discriminant method was used to construct a sedimentary microfacies identification method with an accuracy of 90.5%.Based on production data,the main lithologies and sedimentary microfacies of effective reservoirs were determined,and 10 petrophysical facies with effective reservoir characteristics were identified.Constrained by petrophysical facies,the mean interpretation error of porosity compared to core analysis results is 2.7%,and the ratio of interpreted permeability to core analysis is within one order of magnitude,averaging 3.6.The research results demonstrate that deep learning algorithms can uncover the correlation in carbonate reservoir well logging data.Integrating geological and production data and selecting appropriate machine learning algorithms can significantly improve the accuracy of well log interpretation for carbonate reservoirs.

Investigation of Electrical Parameters of Fresh Water and Produced Mixed Injection in High-Salinity Reservoirs

Assuming a reservoir with a typical salt-lake background in the Qaidam Basin as a testbed,in this study the var-iation law of the rock electrical parameters has been determined through water displacement experiments with different salinities.As made evident by the results,the saturation index increases with the degree of water injec-tion.When the salinity of the injected water is lower than 80000 ppm,the resistivity of the rock samplefirst decreases,then it remains almost constant in an intermediate stage,andfinally it grows,thereby giving rise to a‘U’profile behavior.As the salinity decreases,the water saturation corresponding to the inflection point of the resistivity becomes lower,thereby leading to a wider‘U’type range and a higher terminal resistivity.For dif-ferent samples,higher initial resistivity of the sample in the oil-bearing state,and higher resistivity after low-sali-nity water washing are obtained when a thicker lithology is considered.

Determination of Slaughter Performance in Transgenic Pigs Harboring Inducible IGF-I Gene

[ Objective] This study aimed to investigate the slaughter performance of transgenic pigs harboring IGF-I gene under tetracycline induction. [ Method ] Pigs were given diets with the addition of tetracycline. After 45 d of tetracycline induction, experimental pigs were weighed and slaughtered for parameter determina- tion. [ Result] The lean meat percentage of experimental pigs was improved by 8.92%, but various blood biochemical parameters and carcass components exhibited no significant changes. [ Conclusion ] Under tetracycline induction, transganic pigs harboring IGF-I gane demonstrated an increase in lean meat percentage without abnormal changes in other parameters.

Fukushima wastewater release:unanswered questions and global concerns

The decision by Japan to begin discharging the Fukushima wastewater into the ocean on August 24,2023 was followed by protests from several countries,including China,Russia,Korea,Vietnam,and deep concerns from the international community.This decision is related to the aftermath of the Fukushima Daiichi nuclear disaster that occurred in 2011,which destroyed the cooling system of the nuclear power plant and caused the reactor cores to overheat.Much water was used to cool down the reactors fuel rods;about 1.3 million cubic meters contaminated water with highly radioactive material was generated,which can fill more than 500 Olympic swimming pools[1].In order to reduce the levels of radioactivity,an Advanced Liquid Processing System(ALPS)was used to remove most radioactive contaminants from water.ALPS works by circulating water through a system of tanks and filters,which removes specific contaminants such as cesium and strontium,using a multi-step process that includes coagulation,flocculation,ion exchange,and absorption[1].Japan's government and some scientists have argued that the ALPS-treated water is safe for release into the ocean.According to their claims,the discharged water poses minimal risk to human health and the environment.However,concerns about the long-term effects of this discharge remain in scientists′minds.

Chatbots:a critical look into the future of the academia

Like every other societal domain,science faces yet another reckoning caused by a bot called ChatGPT(Chat Generative Pre-Trained Transformer).ChatGPT was introduced in November 2022 to produce messages that seem like they were written by humans and are conversational.With the release of the latest version of ChatGPT called GPT-4,and other similar models such as Google Bard,Chatsonic,Collosal Chat,these chatbots combine several(about 175 billion)neural networks pre-trained on large Language Models(LLMs),allowing them to respond to user promptings just like humans.GPT-4 for example can admit its mistakes and confront false assumptions thanks to the dialogue style,which also enables it to write essays and to keep track of the context of a discussion while it is happening.However,users may be deceived by the human-like text structure of the AI models to believe that it came from a human origin[1].These chatbot models could be better,even though they generate text with a high level of accuracy.Occasionally,they produce inappropriate or wrong responses,resulting in faulty inferences or ethical issues.This article will discuss some fundamental strengths and weaknesses of this Artificial intelligence(AI)system concerning scientific research.

Effect of high temperature short time infrared roasting of peanuts

Roasting is the most common processing method that enhances color,and texture.In this study,infrared roasting of peanuts was done using an infrared rotary dryer.Roasting was operated at 90%infrared power(630 W)with different rotating speed(1 and 2 r/min).The effect of roasting was studied at different moisture levels(7.66%,11.49%,and 13.72%db).From the study,the color parameter,L*value,was found to be significantly different(P<0.05),and it decreased with the decrease in rotating speed,and the∆E value varies from 2.32 to 10.56.Results also showed that the antioxidant activity decreased with the reduction in rotating speed as lesser revolutions took longer roasting time,and the values decreased from 84.34%to 71.74%.Minimal changes in total phenolic content were found and varied from 3.62 to 2.10 mg/g GAE,an appropriate limit for good-quality roasted peanuts.The hardness of roasted peanuts ranged from 12.25 to 39.43 N.Moisture content 13.72%,and 1 r/min is the best possible treatment for infrared peanut roasting,significantly enhancing the quality of peanuts.This study concluded that high-power short-time infrared roasting could give good-quality roasted peanuts with optimum bioactive compounds.

Peanut drying:Effects of various drying methods on drying kinetic models,physicochemical properties,germination characteristics,and microstructure

The current work aims to explore the suitable drying technique for peanut pods which can be used for seeds or edible peanuts.Four drying methods,namely naturally-open sun drying as the control check(CK),hot air drying(HAD),pulsed vacuum drying(PVD),and radio frequency combined hot air drying(RF-HAD),were employed to dry peanut pods,and their effects on the nutritional quality attributes in terms of protein,fat,fatty acid contents,etc.,germination characteristics,microstructure,color,texture,acid value and peroxide value of peanuts were explored.Mathematical models of peanuts drying with four drying methods were also established.According to the statistical parameters including the determination coefficient(R^(2))、root mean square error(RMSE)and chi-square value(v^(2)),theWeibull model was best for predicting the moisture ratio change kinetics of peanuts during its four drying processes.There were significant differences in physicochemical indexes of peanut by different drying methods(p<0.05).Fat and oleic acid contents under RF-HAD were significantly higher than those by the other three drying methods.Compared with the naturally-open sun drying,RF-HAD reduced drying time by 76.70%and the microstructure of RF-HAD peanuts produced larger and more cavities.The RF-HAD kept better comprehensive nutritional quality,but the germination rate was reduced by 27.80%.PVD could maintain good nutritional quality and germination rate among these mechanical drying technologies.However,PVD had a longer drying time of 9.5 h than RF-HAD and HAD,and the microstructure of pulsed vacuum dried peanuts showed dense structure and less cavity.Hot air-dried peanut kernel held the highest protein(28.75%),fatty acids contents(26.11%)and germination rate(88.00%).However,peanut kernel dried by HAD showed poor qualities,such as high acid value,peroxide value and large color changes.These findings indicated RF-HAD was a promising drying technique for edible peanuts regarding the higher drying rate and better-quality preservation,while HAD was suitable for peanut seeds drying as it could well protect the germination rate.

Experimental and numerical study on the shrinkage-deformation of carrot slices during hot air drying

In order to further understand the mechanism of material volume change in the drying process,numerical simulations(considering or neglecting shrinkage)of heat and mass transfer during convective drying of carrot slices under constant and controlled temperature and relative humidity were carried out.Simulated results were validated with experimental data.The results of the simulation show that the Quadratic model fitted well to the moisture ratio and the material temperature data trend with average relative errors of 5.9%and 8.1%,respectively.Additionally,the results of the simulation considering shrinkage show that the moisture and temperature distributions during drying are closer to the experimental data than the results of the simulation disregarding shrinkage.The material moisture content was significantly related to the shrinkage of dried tissue.Temperature and relative humidity significantly affected the volume shrinkage of carrot slices.The volume shrinkage increased with the rising of the constant temperature and the decline of relative humidity.This model can be used to provide more information on the dynamics of heat and mass transfer during drying and can also be adapted to other products and dryers devices.

The untapped potential of zeolites in techno-augmentation of the biomaterials and food industrial processing operations:a review

Zeolites are aluminosilicate compounds with excellent selective,precise adsorption capabilities that find their potential applications in various sectors of the biomaterials and food industry.The zeolites from ages have been utilized in biomedicine,catalysis,detergent and air purification industries but their commercial applications in the biomaterials and food industry are not studied enough.Zeolites are known to reduce mycotoxins,toxic compounds,heavy metals,and microbes.The present review tries to summarize different arenas of zeolite applications in the biomaterials and food industry.The article also includes a discussion of individual applications of zeolitic properties like antimicrobial effect,food nanoreactors and intelligent food contact behaviour in brief.Moreover,sound coverage is given over zeolite classification,their synthesis and the modelling of their adsorption behaviour.The outcomes of the review emphasize the commercial viability of zeolites and their potential to serve as a possible alternative to many processing steps which ultimately will economise the production process in the food industry.This review also emphasizes extensive research that needs to be carried out to further improvise the capabilities of zeolites to overcome the challenges lying around them.

Sustainable flood management strategies for resilient cities

The world is suffering more and more serious climate change events this summer[1]:temperature records broken constantly,ocean waters as warm as hot tubs,floods are raging around the world.It has been confirmed that the July 2023 was the hottest month in recorded history and the average global temperature was 1.54ºC above the preindustrial average for July[2].The world seems to be entering the tipping points of climate change beyond which climate change will occur more dramatic and quickly,become self-perpetuating and difficult or impossible to undo[3].

Generative AI in education: To embrace it or not ?

Generative Artificial Intelligence(AI)has gained immense popularity,but it has also brought forth new challenges and concerns in academia.One major worry is AI-assisted cheating,where students use Generative AI to complete assignments and exams,leading to some U.S.schools banning its usage on campus[1].However,the developers of ChatGPT,OpenAI,assured the public that they never intended ChatGPT to be used deceitfully in schools or elsewhere.They are already working on mitigations to make it easier for anyone to recognize text produced by that system[2].Open AI went ahead to state that they were looking forward to working with educators on practical solutions,and other ways to help teachers and students benefit from AI.

Driving factors of carbon dioxide emissions in China： an empirical study using 2006-2010 provincial data

The rapid urbanization of China has increased pressure on its environmental and ecological well being. In this study, the temporal and spatial profiles of China＇s carbon dioxide emissions are analyzed by taking heterogeneities into account based on an integration of the extended stochastic impacts using a geographically and temporally weighted regression model on population, affluence, and technology. Population size, urbanization rate, GDP per capita, energy intensity, industrial structure, energy consumption pattern, energy prices, and economy openness are identified as the key driving factors of regional carbon dioxide emissions and examined through the empirical data for 30 provinces during 2006-2010. The results show the driving factors and their spillover effects have distinct spatial and temporal heterogeneities. Most of the estimated time and space coefficients are consistent with expectation. According to the results of this study, the heterogeneous spatial and temporal effects should be taken into account when designing policies to achieve the goals of carbon dioxide emissions reduction in different regions.

Real-time monitoring system for quality monitoring of jujube slice during drying process

The real-time monitoring and prediction system for quality attributes of jujube slices during the drying process was designed to solve the problem of destructive and inconvenient of the traditional quality detection method and realize quality online monitoring.Firstly,machine vision and automatic weighing were employed to monitor the color and moisture content changes of jujube slices in real-time.Secondly,correlation models between color parameter(a^(*)value)and nutritional quality attributes(vitamin C,reducing sugar)were established to predict vitamin C and reducing sugar content of jujube slices during the drying process.Finally,the upper computer monitoring software was integrated and designed based on LABVIEW virtual instrument,and the real-time monitoring system was tested and validated.Results showed that:the changing trends of color(L^(*),a^(*),and b^(*)values)monitored by the system were basically the same as the results detected by color difference meter,and the average errors of L^(*),a^(*),and b^(*)values were 0.93,0.52,and 0.73,respectively.The average relative error of moisture content between the system monitoring and manual static detection was 0.18%.The average error of vitamin C and reducing sugar content between the system prediction and manual detection were 50 mg/100 g in dry basis and 0.71g/100 g in dry basis,respectively.The current work can provide a useful reference for real-time monitoring of quality attributes of fruits and vegetables during the drying process.