--> Characterisation of a Tight Gas Reservoir using Seismic Attributes

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Characterisation of a Tight Gas Reservoir using Seismic Attributes, Ohanet Field, Algeria

By

 Michael Jamieson1, Joe Boztas1, Hocine Khemissa2, Spencer Quam1

(1) BHP Billiton Petroleum, London, United Kingdom (2) SONATRACH, London, United Kingdom

 The Ohanet Field is situated in the Illizi Basin 400 km. southwest of Hassi Messaoud, Algeria. The field is a NW - SE trending, fault-bounded anticline 35 km. long by 5 km. wide, and has 2 productive horizons: Silurian fluvio-deltaic sands and Ordovician glacio-marine sands. In July 2000 a Risk Service Contract was executed between SONATRACH and a joint venture led by BHP Billiton Petroleum with Japan Ohanet Operating Company, Petrofac Ohanet, and Woodside as partners to commercialize the gas reserves in the 2 reservoir intervals, together with reserves in 2 other reservoirs. Included in the work commitment was the recording of ~1000 sq. km. of 3D seismic.

The primary Ordovician reservoir consists of tight (0.5-40 md. permeability) turbiditic sands consisting largely of 2 facies: stacked channels, and thick lobes displaying mega-ripple marks. The sand is 30-50 m. thick, which is just above seismic tuning thickness, and is acoustically hard compared to the encasing shales. Petrophysical modeling predicts that the presence of porosity reduces the positive impedance contrast between the overlying shale and reservoir sand, such that the reflection strength weakens. A crossplot of well average porosity vs amplitude provides confidence that seismic attributes can predict areas of better quality reservoir.

Seismic attributes were extracted from the 3D seismic data, and were used to statistically guide population of reservoir properties in a geocellular model. The attribute work revealed geological features that tied with facies determined from core in old wells, and that were substantiated in newly drilled wells. The resulting model is being used to guide the continuing development of the reservoir, and to predict ultimate recovery.