Research on application of deep learning network in unconventional oil and gas development
Artificial intelligence represented by deep learning has been recognized as the core technology for the transformation and upgrading of oil exploration and development technology.Well test interpretation is rapidly evolving towards automatic model recognition and artificial interpretation with the powerful learning ability of deep learning.Early production prediction was mainly based on known features,and the research on automatically extracting features from measured data was attracted attention.In addition,positive progress has been made in production prediction based solely on wellhead pressures.Generative adversarial networks are replacing the digital core reconstruction method based on the multi-point geological statistic,but how to meet the constraints such as fractures,porosity,and permeability remains challenging.Partial differential equation solving is undergoing subversive changes.Traditional solving methods based on nonlinear equations are ushering in an era of intelligent solving.Based on the physical nature,the single neural network structure evolves into a complex network structure.Large-scale models will be the future trend with the development of artificial intelligence technology.Therefore,the relevant research goes hand in hand,and strengthening data collection and building large-scale models will be one of the important tasks for future oilfield development in China.
deep learningoil and gas developmentwell test interpretationproduction predictionartificial intelligence
万方数据
维普
