Shale gas well productivity potential evaluation based on data-driven methods: case study in the WY block

Evaluating the productivity potential of shale gas well before fracturing reformation is imperative due to the complex fracturing mechanism and high operation investment. However, conventional single-factor analysis method has been unable to meet the demand of productivity potential evaluation due to the numerous and intricate influencing factors. In this paper, a data-driven-based approach is proposed based on the data of 282 shale gas wells in WY block. LightGBM is used to conduct feature ranking, K-means is utilized to classify wells and evaluate gas productivity according to geological features and fracturing operating parameters, and production optimization is realized through random forest. The experimental results show that shale gas productivity potential is basically determined by geological condition for the total influence weights of geologic properties take the proportion of 0.64 and that of engineering attributes is 0.36. The difference between each category of well is more obvious when the cluster number of well is four. Meanwhile, those low production wells with good geological conditions but unreasonable fracturing schemes have the greatest optimization space. The model constructed in this paper can classify shale gas wells according to their productivity differences, help providing suggestions for engineers on productivity evaluation and the design of fracturing operating parameters of shale gas well.

Production Scheduling of Personalized Fashion Goods in a Mass Customization Environment

The COVID-19 pandemic has put fashion manufacturers’ needs for optimization in the spotlight. This study argues that mass customization is becoming increasingly instrumental for offering consumers individualized solutions and that suppliers of fashion have to look for more sophisticated solutions in order to face the increasing demand for more sustainable products. With the deduction of a mathematical model derived from production sequencing it became evident that sustainability can be associated with a level production schedule and that cost-based production optimization is useful in achieving holistic sustainability in the fashion industry. The flexibility in the conceived mathematical model specifications allows for a generalizable approach, not limited to a single branch of the fashion industry. This paper additionally delivers a cost-based optimization approach which fashion companies, operating in a mass customization production layout, can easily implement without extensive know-how. The proposed two-stage algorithm is based on the concept of level scheduling. In a first stage, the algorithm determines a feasible production sequence in a time-efficient way while, in the second stage, it further advances the efficiency of the solution. Thus, it offers a framework to optimize a production in a mass customization environment and can contribute to a company taking major steps towards a holistic sustainable orientation as available resources are used more (cost) efficiently.

Production, Optimization, Characterization and Drought Stress Resistance by β-Glucan-Rich Heteropolysaccharide From an Endophytic Fungi Colletotrichum alatae LCS1 Isolated From Clubmoss (Lycopodium clavatum)

Endophytic entities are ubiquitous in nature with all-square bioactivity ranging from therapeutic effects toward animals to growth promoting attributes and stress tolerance activities in case of green plants. In the present study, the club moss Lycopodium clavatum for the first time has been subjected for the isolation of endophytic fungi. An exopolysaccharide (EPS) extracted from Colletotrichum alatae LCS1, an endophytic fungi isolated from L. clavatum Linn., was characterized as a β-glucan heteropolymer (composed of mannose, rhamnose, arabinose, glucose, galactose, and fucose) which plays a pivotal role in obliterating the drought stress in rice seedlings (Oryza sativa) when applied at an amount of 20, 50, and 100 ppm. The fresh weight contents of rice tissue (39%), total chlorophyll (33%), proline (41%), soluble sugar content (26%) along with antioxidant enzymes such as catalase, peroxidase, and super-oxide dismutase increased (in comparison to control of non-EPS treated seedlings) while malondialdehyde content had reduced markedly after 30 days of regular treatment. The drought resistance of rice seedling was observed at peak when applied at 50 ppm dosage. Vital parameters for EPS production like fermentation duration (5 days), medium pH (6), nutrient (carbon (glucose-7 g%/l), nitrogen (yeast extract-0.4 g%/l), and mineral (NaCl-0.10 g%/l) sources, oxygen requirements (O2 vector or liquid alkane-n-hexane, n-heptane, n-hexadecane), and headspace volume (250 ml Erlenmeyer flask- 50 ml medium, 200 ml-headspace volume) were optimized to obtain an enhanced EPS yield of 17.38 g/L−59% higher than the preoptimized one. The present study, for the first time, reported the β-glucan rich heteropolysaccharide from Colletotrichum origin which is unique in structure and potent in its function of drought stress tolerance and could enhance the sustainable yield of rice cultivation in areas facing severe drought stress.