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AAPG Bulletin, Vol. 90 (2006), Program Abstracts (Digital)

7th Middle East Geosciences Conference and Exhibition
Manama, Bahrain
March 27-29, 2006

ABSTRACT: Multi-Attribute Previous HitSeismicNext Hit Volume Facies Classification for Predicting Fractures in Carbonate Reservoirs

Fernando A. Neves and Harold L. Triebwasser
Exploration Technical Services Department, Saudi Aramco, P.O. Box 6684, Dhahran, 31311, Saudi Arabia, phone: 96638736396, fax: 96638730475, [email protected]

Understanding the fault and fracture distribution and orientation prior to drilling and completion of production and injection wells is critical for optimal oil production and maximizing recovery. In recent years multi-volume Previous HitseismicNext Hit attributes have been used more efficiently to help map these localized faults or fractured zones within reservoirs. In this study, covering a portion (about 750 Km2) of the Ghawar field in Saudi Arabia, unsupervised Previous HitseismicNext Hit facies volume classification was applied to multiple Previous HitseismicNext Hit attribute cubes to predict fracture zones in the Arab-D carbonate reservoir.

The pre-stack time migrated 3D Previous HitseismicNext Hit dataset was processed to preserve relative amplitude information. Attribute analysis of the input Previous HitseismicNext Hit volume showed several areas containing East-West oriented lineaments. Many of these lineaments were not clearly observed either in time or horizon Previous HitseismicNext Hit amplitude slices. For lineament mapping, each lineament must be recognizable in more than one Previous HitseismicNext Hit attribute volume. The mapped Previous HitseismicNext Hit lineaments were interpreted to be small faults (or fractures) through which natural drainage may facilitate fluid migration through the reservoir. The long extent of these lineaments (several kilometers in length) suggests they are probably faults. A binary scheme (two Previous HitseismicNext Hit facies) of multi-volume Previous HitseismicNext Hit facies classification of fault-related Previous HitseismicNext Hit attributes was successful in clustering areas of the field where optimum oil flow rate wells have been observed. This analysis of post-stack Previous HitseismicTop attributes helped improve the understanding of observed well performance by mapping the distribution of fracture systems within the reservoir.


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