Parameter sensitivity analysis and parameter identifiability analysis of electrochemical model under wide discharge rate

Wang, Wenwen; Zhou, Xingzhen; Zhang, Weige; Sun, Bingxiang; Shi, Jinkai; Huang, Qinhe

doi:10.1016/j.est.2023.107788

Cited by 10 publications

(1 citation statement)

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“…Artificial intelligence is a convolutional recursive hybrid deep learning proxy model suitable for automatic reservoir history fitting and uncertainty quantification. 27 This study is based on an image to sequence proxy modeling framework, integrating residual convolutional networks and multilayer recurrent neural networks to construct a high-precision proxy model for reservoir numerical simulation, effectively enhancing the accuracy and efficiency of modeling. By applying a multimodal distributed estimation solving algorithm to automatic history fitting, the problem of multiple solutions faced by automatic history fitting is effectively solved.…”

Section: Research Progress In Artificial Intelligence Technologymentioning

confidence: 99%

Current Status and Prospects of Artificial Intelligence Technology Application in Oil and Gas Field Development

Wang,

Wei,

Xiong

et al. 2024

ACS Omega

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Artificial intelligence technology will be increasingly applied in the oil and gas industry. The rapid development of artificial intelligence technology can solve problems such as high environmental sensitivity and complex production processes in the oil and gas industry. In recent years, emerging technologies represented by artificial intelligence have developed rapidly, assisting petroleum enterprises in digital transformation and intelligent upgrading. This article elaborates on the development trend of artificial intelligence technology. Based on the business scenarios and characteristics of the oil and gas industry, the application status of artificial intelligence technology in domestic and foreign petroleum technology service enterprises was summarized and analyzed. The application scenarios of artificial intelligence technology in the fields of dynamic analysis of oil and gas reservoirs, intelligent historical fitting, numerical simulation proxy models, and production plan optimization were analyzed with emphasis. Based on the problems and challenges faced in the development process of oil and gas reservoirs, it is proposed that petroleum enterprises should attach importance to the "three modernizations" innovation of data standardization, oil and gas field intelligence, and platform collaboration, in order to achieve more refined intelligent analysis and management of oil and gas reservoirs and quickly develop more targeted oil and gas reservoir development plans to assist in the intelligent transformation of oil and gas reservoir development. On this basis, prospects for future artificial intelligence technology are proposed, pointing out that the development of artificial intelligence technology will be faster and faster, and there will be higher demand for artificial intelligence technology in the construction of digital oil and gas fields in China in the future. The research results have important reference value for the development of the oil and gas industry.

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Section: Research Progress In Artificial Intelligence Technologymentioning

confidence: 99%