I2AM: a Semi-Automatic System for Data Interpretation in Petroleum Geology

AI*IA Workshop and Prize for Celebrating 100th Anniversary of Alan Turing's Birth

Denis Ferraretti ; Giacomo Gamberoni ; Evelina Lamma

Others  :  http://ceur-ws.org/Vol-860/paper5.pdf
PID  :  45897

来源: CEUR

【 摘 要 】

The natural complexities of petroleum reservoir systems continue to provide a challenge to geoscientists. In petroleum geology, exploration and production wells are often analysed using image logs and the use of all the available borehole data to completely characterize the reservoir potentials and performance is an important task. The development of reliable interpretation methods is of prime importance regarding the reservoir understanding and data integration is a crucial step in order to create useful description models and to reduce the amount of time necessary for each study. Artificial intelligence, data mining techniquesand statistical methods are widely used in reservoir modelling, for instance in prediction of sedimentary facies3.[First Paragraph]