Shale gas production evaluation framework based on data-driven models

Increasing the production and utilization of shale gas is of great significance for building a clean and low-carbon energy system.Sharp decline of gas production has been widely observed in shale gas reservoirs.How to forecast shale gas production is still challenging due to complex fracture networks,dynamic fracture properties,frac hits,complicated multiphase flow,and multi-scale flow as well as data quality and uncertainty.This work develops an integrated framework for evaluating shale gas well production based on data-driven models.Firstly,a comprehensive dominated-factor system has been established,including geological,drilling,fracturing,and production factors.Data processing and visualization are required to ensure data quality and determine final data set.A shale gas production evaluation model is developed to evaluate shale gas production levels.Finally,the random forest algorithm is used to forecast shale gas production.The prediction accuracy of shale gas production level is higher than 95%based on the shale gas reservoirs in China.Forty-one wells are randomly selected to predict cumulative gas production using the optimal regression model.The proposed shale gas production evaluation frame-work overcomes too many assumptions of analytical or semi-analytical models and avoids huge computation cost and poor generalization for numerical modelling.

Review of Carbon Emissions Trading Production Model and Research on Its Applications in China

With the Kyoto Protocol entering into effect in many countries one after another,carbon trading has come into being and developed quickly.China is the main supplier of carbon emissions rights in the world,but such transactions are still in the stage of Clean Development Mechanism (CDM) projects without its own trading system,which is not conducive for China to win the rights of carbon pricing in the international market.Low-carbon and emissions reduction is the international trend nowadays,and therefore,it is particularly necessary and urgent to investigate the issue of carbon trading in China.In this paper,the authors have reviewed Putty-Clay Vintage,which is a model of production function for carbon trading,revealing the main points,contributions and shortcomings of the model.Combined with China's national conditions,the authors have investigated the application of this model in China's carbon trading from four different angles,including enterprise production optimization,financial market development,national macro-economy,and the allocation of emission quota.This study aims to provide China's enterprises with an analytical framework when participating in carbon trading in the future and it is beneficial for them to make optimal production planning when considering the cost of carbon emissions reduction.

Thermodynamic Research on Precipitates in Low Carbon Nb-Microalloyed Steels Produced by Compact Strip Production

Microalloying element Nb in low carbon steels produced by compact strip production （CSP） process plays an important role in inhibiting recrystallization, decreasing the transformation temperature and grain refinement.With decreasing the rolling temperature, dislocations can be pinned by carbonitrides and the strength is increased. Based on the two sublattice model, with metal atom sublattice and interstitial atom sublattice,a thermodynamic model for carbonitride was established to calculate the equilibrium between matrix and carbonitride. In the steel produced by CSP, the calculation results showed that the starting temperature of precipitation of Ti and Nb are 1340℃ and 1040℃, respectively. In the range of 890-950℃, Nb rapidly precipitated. And the maximum of the atomic fraction of Nb in carbonitride was about 0.68. The morphologies and energy spectrum of the precipitates showed that （NbTi） （CN） precipitated near the dislocations. The experiment results show that Nb rapidly precipitated when the temperature was lower than 970℃, and the atomic fraction of Nb in carbonitride was about 60%-80%. The calculation results are in agreement with the experiment data. Therefore the thermodynamic model can be a useful assistant tool in the research on the precipitates in the low carbon steels produced by CSP.

Multiproduct and multistage integrated production planning model and algorithm based on an available production capacity network

This research attempts to devise a multistage and multiproduct short-term integrative production plan that can dynamically change based on the order priority and virtual occupancy for application in steel plants. Considering factors such as the delivery time, varietal compatibility between different products, production capacity of variety per hour, minimum or maximum batch size, and transfer time, we propose an available production capacity network with varietal compatibility and virtual occupancy for enhancing production plan implementation and quick adjustment in the case of dynamic production changes. Here available means the remaining production capacity after virtual occupancy.To quickly build an available production capacity network and increase the speed of algorithm solving, constraint selection and cutting methods with order priority were used for model solving. Finally, the genetic algorithm improved with local search was used to optimize the proposed production plan and significantly reduce the order delay rate. The validity of the proposed model and algorithm was numerically verified by simulating actual production practices. The simulation results demonstrate that the model and improved algorithm result in an effective production plan.

Production forecasting methods for different types of gas reservoirs

Hydrocarbon production in oil and gas fields generally progresses through stages of production ramp-up,plateau(peak),and decline during field development,with the whole process primarily modeled and forecasted using lifecycle models.SINOPEC's conventional gas reservoirs are dominated by carbonates,low-permeability tight sandstone,condensate,volcanic rocks,and medium-to-high-permeability sandstone.This study identifies the optimal production forecasting models by comparing the fitting coefficients of different models and calculating the relative errors in technically recoverable reserves.To improve forecast precision,it suggests substituting exponential smoothing method-derived predictions for anomalous data caused by subjective influences like market dynamics and maintenance activities.The preferred models for carbonate gas reservoir production forecasts are the generalized Weng's,Beta,Class-I generalized mathematical,and Hu-Chen models.The Vapor pressure and Beta models are optimal for forecasting the annual productivity of wells(APW)from gas-bearing low-permeability tight sandstone reservoirs.The Wang-Li,Beta,and Yu QT tb models are apt for moderate-to-small-reserves,single low-permeability tight sandstone gas reservoirs.The Rayleigh,Hu-Chen,and generalized Weng's models are suitable for condensate gas reservoirs.For medium-to-high-permeability sandstone gas reservoirs,the lognormal,generalized gamma,and Beta models are recommended.

Production prediction for fracture-vug carbonate reservoirs using electric imaging logging data

Considering the fluid flow non-darcy characteristics in fracture-vug carbonate reservoirs, a new multi-scale conduit flow model production prediction method for fracture-vug carbonate reservoirs was presented using image segmentation technique of electric imaging logging data. Firstly, based on Hagen-Poiseuille's law of incompressible fluid flow and the different cross-sectional areas in single fractures and vugs in carbonate reservoirs, a multi-scale conduit flow model for fracture-vug carbonate reservoir was established, and a multi-scale conduit radial fluid flow equation was deduced. Then, conduit flow production index was introduced. The conduit flow production index was calculated using fracture-vug area extracted from the result of electrical image segmentation. Finally, production prediction of fracture-vug carbonate reservoir was realized by using electric imaging logging data. The method has been applied to Ordovician fracture-vug carbonate reservoirs in the Tabei area, and the predicted results are in good agreement with the oil testing data.

The carbon fluxes in different successional stages:modelling the dynamics of tropical montane forests in South Ecuador

Background： Tropical forests play an important role in the global carbon（C） cycle.However, tropical montane forests have been studied less than tropical lowland forests, and their role in carbon storage is not well understood.Montane forests are highly endangered due to logging, land-use and climate change.Our objective was to analyse how the carbon balance changes during forest succession.Methods： In this study, we used a method to estimate local carbon balances that combined forest inventory data with process-based forest models.We utilised such a forest model to study the carbon balance of a tropical montane forest in South Ecuador, comparing two topographical slope positions（ravines and lower slopes vs upper slopes and ridges）.Results： The simulation results showed that the forest acts as a carbon sink with a maximum net ecosystem exchange（NEE） of 9.3 Mg C？（ha？yr）-1during its early successional stage（0–100 years）.In the late successional stage, the simulated NEE fluctuated around zero and had a variation of 0.77 Mg C？（ha？yr）–1.The simulated variability of the NEE was within the range of the field data.We discovered several forest attributes（e.g., basal area or the relative amount of pioneer trees） that can serve as predictors for NEE for young forest stands（0–100 years） but not for those in the late successional stage（500–1,000 years）.In case of young forest stands these correlations are high, especially between stand basal area and NEE.Conclusion： In this study, we used an Ecuadorian study site as an example of how to successfully link a forest model with forest inventory data, for estimating stem-diameter distributions, biomass and aboveground net primary productivity.To conclude, this study shows that process-based forest models can be used to investigate the carbon balance of tropical montane forests.With this model it is possible to find hidden relationships between forest attributes and forest carbon fluxes.These relationships promote a better understanding of the role of tropical montane forests in the context of global carbon cycle, which in future will become more relevant to a society under global change.

Estimation of the embodied carbon in China's wood products trade using input–output methodology

This study calculates the embodied carbon in imports,exports,net exports,and the processing trade of China's wood product sector between 2001 and 2016 using a non-competitive input-output(I-O)model.The results demonstrate that embodied carbon showed a decreasing trend between 2001 and 2016.Embodied carbon was lowest in wood furniture imports and highest in paper and paperboard imports.The embodied carbon in sawnwood and veneer sheet exports was the lowest and paper and paperboard exports was the highest.The embodied carbon in the processing trade of paper and paperboard was the highest.To reduce the embodied carbon in China's wood products,the government should promote technological transformation and upgrading and encourage the implementation of green technology innovation.

Carbon productivity convergence club and its initial conditions: China's construction industry

A three-stage method is proposed to study the convergence clubs for the dynamic total factor carbon productivity (DCP) and the initial conditions. The first stage is to measure the DCP that reflects the initial difference. The second stage is to identify the convergence club of DCP. The last stage is to examine the initial factors that may affect the formation of the convergence club. Construction industry data from 30 provinces in China's Mainland from 2005 to 2016 were adopted to conduct an empirical study. The empirical results showed that (1) the arithmetic mean value of China’s provincial DCP showed an upward trend and the standard deviation showed an expanding trend.(2) There are five convergence clubs, but 13 provinces failed to converge to any club.(3) The higher the degree of construction industry marketization in 2005, the greater the probability that the provinces belong to a club with higher DCP. To improve the DCP, the effective diffusion of low-carbon construction technologies and the market-oriented reform of state-owned construction companies should be promoted. The three-stage method can also be applied to study different industries in different countries or regions.

Mathematical Model to Estimate Carbon Footprint for EEG Incubation

This work presents a performance comparison between several incubators models including CO2 and NH4 emission.A mathematical model for incubators carbon foot print was developed to estimate CO2 and NH4 emission.The program written by C++language including convert line.The modular structure of program consists of a main programme and series of independent subroutine:each one deals with a specific parameter of the required data.The computer programme has a wide range of applicability several values of size of the machine(NO.egg),Fertility(F),Heat production embryo(HPe),maximum CO2 level(CO2)m,CO2 level incoming air(CO2)I,RQ value(RQ)to estimate Heat production(HP),CO2 production,Ventilation(V),Ventilation of egg(Vegg)Input data:Enter size of the machine,Fertility(F),Heat production embryo(HPe),maximum CO2 level(CO2)m,CO2 level incoming air(CO2)I,RQ value(RQ)the results As the growth period passed from the first day of the twenty-first day,the amount of heat produced increased from 0.0001 to 0.35 w/egg,and ventilation from 0 to 352 m^3/hr as well as the amount of carbon dioxide produced from 0.0000158 to 0.04318 lit/hr/Mach.As the number of eggs increased from 5,000 to 30,000 eggs,each of the heat produced increased from 923.4 to 5540.4 kg/hr,the resulting carbon dioxide from 32 to 190 lit/hr/Mach,and ventilation from 9 to 54 m^3/hr.

Ecosystem service multifunctionality of mixed conifer-broad-leaved forests under climate change and forest management based on matrix growth modelling

Climate change and forest management are recognized as pivotal factors influencing forest ecosystem services and thus multifunctionality.However,the magnitude and the relative importance of climate change and forest management effects on the multifunctionality remain unclear,especially for natural mixed forests.In this study,our objective is to address this gap by utilizing simulations of climate-sensitive transition matrix growth models based on national forest inventory plot data.We evaluated the effects of seven management scenarios(combinations of various cutting methods and intensities)on the future provision of ecosystem services and multifunctionality in mixed conifer-broad-leaved forests in northeastern China,under four climate scenarios(SSP1-2.6,SSP2-4.5,SSP5-8.5,and constant climate).Provisioning,regulating,cultural,and supporting services were described by timber production,carbon storage,carbon sequestration,tree species diversity,deadwood volume,and the number of large living trees.Our findings indicated that timber production was significantly influenced by management scenarios,while tree species diversity,deadwood volume,and large living trees were impacted by both climate and management separately.Carbon storage and sequestration were notably influenced by both management and the interaction of climate and management.These findings emphasized the profound impact of forest management on ecosystem services,outweighing that of climate scenarios alone.We found no single management scenario maximized all six ecosystem service indicators.The upper story thinning by 5%intensity with 5-year interval(UST5)management strategy emerged with the highest multifunctionality,surpassing the lowest values by more than 20%across all climate scenarios.In conclusion,our results underlined the potential of climate-sensitive transition matrix growth models as a decision support tool and provided recommendations for long-term strategies for multifunctional forest management under future climate change context.Ecosystem services and multifunctionality of forests could be enhanced by implementing appropriate management measures amidst a changing climate.

CGE Model Measures Carbon Duty's Impact on China's Exports

Carbon-motivated border tax adjustment is a unilateral international trade policy aimed at compensating for the loss ofcompetitiveness of carbon-intensive products due to carbon dioxide abatement actions.It violates fundamental principlesof the UNFCCC and potentially conflicts with the core WTO principle of non-discrimination as reflected in the GATTArticle Ⅰ and Article Ⅲ.Based on an analysis of carbon emissions embodied in China’s industrial exports,this paperevaluates with a recursive dynamic CGE model the potential impacts of the carbon duty on China’s industrial production,exports and employment.The results of a simulation show that with a tariff rate of US＄30 or US＄60 per ton of carbon,theoutput of China’s industrial sectors would decline by 0.62-1.22 percent,exports by 3.53-6.95 percent,and employment by1.22-2.39 percent.The authors suggest several measures of alleviating the impacts of carbon duty and put forward a carbonduty policy based on carbon consumption per capita as a countermeasure.

生产性服务业集聚对碳生产率的空间溢出效应

为探究生产性服务业集聚能否成为解决“稳增长、促减排”两难困境的良方,论文基于2009—2020年中国30个省份的面板数据,构建中介与空间效应模型,探讨生产性服务业集聚与碳生产率的影响机制和时空特征并进行空间溢出效应分析。结果表明:生产性服务业集聚显著提高碳生产率并存在异质性特征,其促进作用自东部到西部逐渐显著,高端生产性服务业集聚更能推动碳生产率发展;科技创新在生产性服务业集聚影响碳生产率过程中发挥中介作用;本地生产性服务业集聚通过辐射效应对邻近地区碳生产率水平产生正向空间溢出效应,有助于形成地区间绿色协调发展的空间格局。

数字经济赋能黄河流域新质生产力及低碳转型的路径研究

为了探究数字经济赋能黄河流域新质生产力培育及城市低碳转型的现实路径、给黄河流域生态保护和高质量发展相关研究提供参考,在对数字经济、新质生产力与低碳转型互促机制理论分析基础上,基于“宽带中国”试点城市这一准自然实验,以低碳转型程度为被解释变量,以数字经济的代理变量“宽带中国”试点政策为核心解释变量,把能源效率、产业结构、消费低碳转型水平作为表征新质生产力的中介变量,利用2011—2022年黄河流域76个城市的面板数据,运用多期双重差分模型进行了实证分析。结果表明:1)数字经济发展能够显著推进黄河流域城市低碳转型;2)数字经济的低碳转型效应在黄河流域具有城市等级与城市规模异质性,在中心城市其效应更显著,在小城市、中等城市、大城市的效应依次递增;3)新质生产力对数字经济低碳转型效应具有重要的中介作用,供给侧能源效率的提升、产业结构优化升级是其显著助力黄河流域城市低碳转型的两条具体路径。提出了全面推动黄河流域数字经济发展、加快形成新质生产力培育的重要着力点、多措并举持续推进黄河流域低碳转型等建议。

数字乡村赋能农业碳生产率的门槛效应分析

数字乡村发展是建设数字中国和推动乡村振兴的重要组成部分,对中国式现代化目标的实现发挥着重要作用。文章基于2011—2021年我国30个省份的面板数据,系统构建数字乡村评价指标体系,并利用非线性动态门槛回归模型,从环境规制视角深入探讨数字乡村对农业碳生产率的影响效应。研究发现,样本期内我国数字乡村发展水平呈现较为稳定的上升趋势,但地区间发展不平衡,区域差异较大。数字乡村对农业碳生产率的影响存在显著的环境规制异质性门槛效应:在较低的环境规制水平下,数字乡村发展不利于农业碳生产率提升;而随着环境规制水平不断提升并超过临界值时,在一定程度上会激发数字乡村对农业碳生产率的赋能效应,进而促进农业碳生产率的提高,即数字乡村与农业碳生产率之间呈现“U”型关系。

粮食主产区种植业低碳发展效率测算与差异化补偿研究

【目的】测算粮食主产区种植业低碳发展效率和碳补偿额度,为健全粮食主产区利益补偿机制提供参考。【方法】利用三阶段超效率SBM-DEA模型测算粮食主产区种植业低碳发展效率,并依据地区碳收支核算、碳交易价格和碳补偿系数确定各主产区碳补偿额度。【结果】1)2010—2020年黑龙江、吉林、内蒙古、江西、四川5个省、自治区碳汇水平最高,湖北、河北碳汇水平最低;2)根据三阶段SBM-DEA模型测算,各主产区低碳发展效率分布较为稳定,其中湖北、河南为低碳发展高效率地区,四川、河北为低碳发展低效率地区。【结论】根据低碳发展效率测算各主产区碳补偿额度,河南、山东和江苏的利益补偿额度最高,辽宁、江西和河北利益补偿额度最低。针对低碳发展效率进行差异化碳补偿,有利于提高粮食主产区发展低碳粮食生产的积极性。

基于绿色索洛模型的韶关市农业碳全要素生产率框架构建及减排潜力估计

在理论上构建了包含农业碳排放和碳吸收的正负环境要素在内的“绿色索洛模型”,考察能源资源投入和碳排污染对农业经济增长的影响与约束,以消除农业经济增长中的环境代价。2011—2021年韶关市面板数据进行实证检验,运用非期望产出的超效率SBM模型测度韶关市的农业碳全要素生产率,利用碳减排潜力模型测度韶关市农业碳减排潜力和潜力规模。结果表明:韶关市农业碳全要素生产效率均值为1.024,农业碳排放总量过剩,规模效率是制约农业碳全要素生产率提升的关键;韶关市农业碳减排潜力在波动中整体呈现上升趋势,农业碳减排潜力年均规模为7.254万t,农业碳减排仍有较大改进空间。据此提出补齐规模效率不佳短板、制定切实可行的碳减排措施的提升韶关市农业碳全要素生产率和持续推进农业碳减排的政策建议。

Three Stage Equilibrium Model for Coal Gasification in Entrained Flow Gasifiers Based on Aspen Plus

A three stage equilibrium model is developed for coal gasification in the Texaco type coal gasifiersbased on Aspen Plus to calculate the composition of product gas, carbon conversion, and gasification teml^erature. The model is divided into three stages including pyrolysis and combustion stage, char gas reaction stage, and gas p.hase reaction stage. Part of the water produced in thepyrolysis and combust!on stag.e is assumed to be involved inthe second stage to react with the unburned carbon. Carbon conversion is then estimated in the second stage by steam participation ratio expressed as a function of temperature. And the gas product compositions are calculated from gas phase reactions in the third stage. The simulation results are consistent with published experimental data.

Carbon forestry is surprising

Background： Forestry offers possibilities to sequestrate carbon in living biomass, deadwood and forest soil, as we as in products prepared of wood. In addition, the use of wood may reduce carbon emissions from fossil fuels. However, harvesting decreases the carbon stocks of forests and increases emissions from decomposing harvest residues. Methods： This study used simulation and optimization to maximize carbon sequestration in a boreal forest estate consisting of nearly 600 stands. A reference management plan maximized net present value and the other plans maximized the total carbon balance of a 100-, 200- or 300-year planning horizon, taking into account the carbon balances of living forest biomass, dead organic matter, and wood-based products Results： Maximizing carbon balance led to low cutting level with all three planning horizons. Depending on the time span, the carbon balance of these schedules was 2 to 3.5 times higher than in the plan that maximized net present value. It was not optimal to commence cuttings when the carbon pool of living biomass and dead organic matter stopped increasing after 150-200 years. Conclusions： Letting many mature trees to die was a better strategy than harvesting them when the aim was to maximize the long-term carbon balance of boreal Fennoscandian forest. The reason for this conclusion was that large dead trees are better carbon stores than harvested trees. To alter this outcome, a higher proportion of harvested trees should be used for products in which carbon is stored for long time.

Long-term organic and inorganic fertilizations enhanced basic soil productivity in a fluvo-aquic soil

The improvement of soil productivity depends on a rational input of water and nutrients, optimal field management, and the increase of basic soil productivity（BSP）. In this study, BSP is defined as the productive capacity of a farmland soil with its own physical and chemical properties for a specific crop season under local field management. Based on 19-yr data of the long-term agronomic experiments（1989–2008） on a fluvo-aquic soil in Zhengzhou, Henan Province, China, the decision support system for agrotechnology transfer（DSSAT ver. 4.0） crop growth model was used to simulate yields by BSP of winter wheat（Triticum aestivium L.） and summer maize（Zea mays L.） to examine the relationship between BSP and soil organic carbon（SOC） under long-term fertilization. Five treatments were included：（1） no fertilization（control）,（2） nitrogen, phosphorus and potassium fertilizers（NPK）,（3） NPK plus manure（NPKM）,（4） 1.5 times of NPKM（1.5NPKM）, and（5） NPK plus straw（NPKS）. After 19 yr of treatments, the SOC stock increased 16.7, 44.2, 69.9, and 25.2% under the NPK, NPKM, 1.5NPKM, and NPKS, respectively, compared to the initial value. Among various nutrient factors affecting contribution percentage of BSP to winter wheat and summer maize, SOC was a major affecting factor for BSP in the fluvo-aquic soil. There were significant positive correlations between SOC stock and yields by BSP of winter wheat and summer maize（P〈0.01）, and yields by BSP of winter wheat and summer maize increased 154 and 132 kg ha^（–1） when SOC stock increased 1 t C ha^（–1）. Thus, increased SOC accumulation is a crucial way for increasing BSP in fluvo-aquic soil. The manure or straw combined application with chemical fertilizers significantly enhanced BSP compared to the application of chemical fertilizers alone.