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The AAPG/Datapages Combined Publications Database
AAPG Bulletin
Abstract
AAPG Bulletin, V.
Fault
Zones for Reservoir Modeling: An Example from the Gullfaks Field, Northern
North Sea
1Manuscript received July 24, 1997;
revised manuscript received November 4, 1998; final acceptance December
4, 1998.
2Badley Earth Sciences Ltd, North
Beck Lane, Hundleby, Spilsby, Lincs PE23 5NB, United Kingdom; e-mail: [email protected]
3Norwegian Petroleum Directorate,
Prof. Olav Hanssensvei 10, N-4001 Stavanger, Norway.
4Norwegian Petroleum Directorate,
Prof. Olav Hanssensvei 10, N-4001 Stavanger, Norway. Present address: Statoil,
4035 Stavanger, Norway.
ABSTRACT
Pressure data from exploration and production
wells have been projected onto the modeled The calculated
A fault
-seal study was performed for part of
the Gullfaks field (North Sea) as an aid to improve reservoir management
of this complexly faulted structure. The operator's (Statoil) map data
were used to build a three-dimensional model of the
fault
network. Together
with petrophysical logs, this model was used to compute the variation of
fault
-seal potential (shale gouge ratio or
fault
-zone percent shale) on
each
fault
surface.
fault
surfaces. The preproduction
pressure differences at sealing faults (separating different hydrocarbon
columns) provide information about the capillary seal at the faults. Across-
fault
pressure drops at particular times during production also have been displayed.
These dynamic pressure drops provide a guide to the permeability of the
fault
zones after flow has started.
fault
parameters (displacement
and shale gouge ratio) can be converted to
fault
-zone thickness and permeability
and can be used to derive
fault
transmissibility modifiers for reservoir
simulations. Maps have been produced showing reservoir juxtaposition areas
and calculated
fault
permeabilities along faults throughout the study area.
These parameters are compatible with the recorded pressure history and
tracer movement between wells, and will enable key reservoir management
decisions to be tested and optimized.
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