Reservoir Characterization Using Neural and Fractal Analysis: Lithofacies Classification Using Artificial Neural Networks Combined with Fractal Analysis. Applications - Softcover

Aliouane, Leila; Ouadfeul, Sid-Ali; Boudella, Amar

 
9786209873997: Reservoir Characterization Using Neural and Fractal Analysis: Lithofacies Classification Using Artificial Neural Networks Combined with Fractal Analysis. Applications

Inhaltsangabe

Most of the world's oil reserves come from improved exploitation of already known fields using increasingly sophisticated methods. Recoverable reserves are therefore estimated based on the various methods of field exploitation. Given this trend, every oil company must have a detailed understanding of the internal architecture of its underground reservoirs. To this end, identifying a reservoir's lithofacies allows us to drill in porous areas with lower clay content. Identifying the lithofacies is the first step in reservoir characterization. The lithofacies consists of a description of the various geological formations comprising a well. To solve our most complex problems, we need to go beyond standard mathematical techniques. As an alternative, we need to supplement conventional analysis methods with several emerging methodologies, such as artificial intelligence. This book reports on and contributes to investigating the potential of new connectionist techniques in reservoir characterization.

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Über die Autorin bzw. den Autor

Leila ALIOUANE is a lecturer and researcher at the University of Boumerdès (UMBB). She holds a habilitation in geophysics. As a member of the Labophyt research laboratory, she is the author of several publications. Her research focuses on the characterization of conventional and unconventional reservoirs.

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