Studies of natural gas production prediction and risk assessment for tight gas in Sichuan Basin

Li, Haitao; Yu, Guoqing; Fang, Yizhu; Chen, Yu; Zhang, Dongming

doi:10.3389/feart.2022.1059832

Cited by 3 publications

(2 citation statements)

References 34 publications

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“…Niche model is a method to describe the ecological needs of species and analyze the suitability of species by using mathematical model and spatial projection through species distribution and environmental variables. It has been applied to the distribution of rare plants 10 , the alien species invasion 11 , wildlife protection 12 and other elds, which has achieved good results. Based on the known spatial distribution, MaxEnt (Maximum Entropy Model) model searches for key environmental factors, builds constraint sets, and simulates the relationship between spatial distribution and environmental factors.…”

Section: Introductionmentioning

confidence: 99%

Potential distribution prediction of Ceracris kiangsu Tsai in China

Fu,

Wen,

Shi

et al. 2024

Preprint

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In order to find out the potential suitable areas of Ceracris Kiangsu Tsai in China, and do a good job in early monitoring. Based on 314 species distribution points of C.kiangsu which were obtained from Chinese herbaria, literatures and investigation, and data of three future climate scenarios presented by CMIP6, two niche models (Garp, Maxent) were used to predict the suitable area of C.kiangsu in China. The result shows that the main environmental factors affecting the distribution of C.kiangsu are precipitation of driest month (bio14) and min temperature of coldest month (bio6). No matter now and future, the potential distribution areas of C. kiangsu in China are mainly in the south of Qinling-Huaihe River. The southern part of Hubei, the western part of Jiangxi and the eastern part of Hunan are highly-suitable areas for C. kiangsu under current scenario. As the climate warms in the future scenarios, the southern part of Yunnan, the southeast of Sichuan and the southwest of Chongqing will also become highly-suitable areas. It can be seen that the local vegetation and climate conditions of these areas mentioned above are more suitable for the survival of C. kiangsu. It is recommended that the local forestry authorities strengthen the monitoring of bamboo forests to prevent the damage caused by the introduction of C. kiangsu.

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Section: Introductionmentioning

confidence: 99%

Potential distribution prediction of Ceracris kiangsu Tsai in China

Fu,

Wen,

Shi

et al. 2024

Preprint

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“…Xia et al (2022) employed the MaxEnt model of climate and altitude as influential factors to evaluate and predict potential habitable regions for H. cunea in Henan Province. Li et al (2018), using the MaxEnt model and combining it with 105 known distribution points of H. cunea and nine environmental factors, predicted suitable areas the distribution range in Sichuan Province. Ji (2019) utilized the random forest model to forecast H. cunea presence in the North China Plain, showing that altitude, vegetation cover, and average temperatures during the wettest and warmest quarters as primary influencers of habitat suitability.…”

Section: Introductionmentioning

confidence: 99%

Analysis of the spatiotemporal trends and influencing factors of Hyphantria cunea in China

Zhou,

Gong,

et al. 2024

J. For. Res.

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In recent years, the situation of the Hyphantria cunea (Drury) (Lepidoptera: Erebidae), infestation in China has been serious and has a tendency to continue to spread. A comprehensive analysis was carried out to examine the spatial distribution trends and influencing factors of H. cunea. This analysis involved integrating administrative division and boundary data, distribution data of H. cunea, and environmental variables for 2021. GeoDetector and gravity analysis techniques were employed for data processing and interpretation. The results show that H. cunea exhibited high aggregation patterns in 2021 and 2022 concentrated mainly in eastern China. During these years, the focal point of the infestation was in Shandong Province with a spread towards the northeast. Conditions such as high vegetation density in eastern China provided favorable situations for growth and development of H. cunea. In China, the spatial distribution of the moth is primarily influenced by two critical factors: precipitation during the driest month and elevation. These play a pivotal role in determining the spread of the species. Based on these results, suggestions are provided for a multifaceted approach to prevention and control of H. cunea infestation.

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Uncertainty prediction of conventional gas production in Sichuan Basin under multi factor control

Li,

Yu,

Fang

et al. 2024

Front. Earth Sci.

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The establishment of a natural gas production model under multi factor control provides support for the formulation of planning schemes and exploration deployment decisions, and is of great significance for the rapid development of natural gas. Especially the growth rate and decline rate of production can be regulated in the planning process to increase natural gas production. The exploration and development of conventional gas in the Sichuan Basin has a long history. Firstly, based on the development of conventional gas production, the influencing factors of production are determined and a production model under multi factor control is established. Then, single factor analysis and sensitivity analysis are conducted, and multi factor analysis is conducted based on Bayesian networks. Finally, combining the multivariate Gaussian mixture model and production sensitivity analysis, a production planning model is established to predict production uncertainty under the influence of multiple factors. The results show that: 1) the production is positively correlated with the five influencing factors, and the degree of influence is in descending order: recovery rate, proven rate, growth rate, decline rate, and recovery degree. After being influenced by multiple factors, the fluctuation range of production increases and the probability of realization decreases. 2) The growth rate controls the amplitude of the growth stage, the exploration rate and recovery rate control the amplitude of the stable production stage, the recovery degree controls the amplitude of the transition from the stable production stage to the decreasing stage, and the decreasing rate controls the amplitude of the decreasing stage. 3)The article innovatively combines multiple research methods to further obtain the probability of achieving production under the influence of multiple factors, providing a reference for the formulation of production planning goals.

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Studies of natural gas production prediction and risk assessment for tight gas in Sichuan Basin

Cited by 3 publications

References 34 publications

Potential distribution prediction of Ceracris kiangsu Tsai in China

Potential distribution prediction of Ceracris kiangsu Tsai in China

Analysis of the spatiotemporal trends and influencing factors of Hyphantria cunea in China

Uncertainty prediction of conventional gas production in Sichuan Basin under multi factor control

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