Reservoir Modeling from Lucapa Field, Angola: Advanced Methods for Complex Reservoir Model Grid Construction

Jay Byers¹, Francesca Fazzari², and Enrique Hung^1
1Southern Africa - New Field Development, Chevron International Exploration & Production Company, Houston, TX
²Exploration & Reservoir Characterization Services, Chevron Energy Technology Company, Houston, TX

Lucapa field is a large Miocene-age oil field located in Block 14, Angola. The field was discovered in 2006 with the Lucapa-1 exploration well. Water depths in the field area range from 3000’-6000’. The field is adjacent to the Congo River Canyon and is characterized as a deepwater mid-slope turbiditic channel deposit consisting of reservoirs throughout the Middle Miocene section. Depth to the primary reservoir is 7000’-8000’ (2000’-4000’ DBML).

Grid-based reservoir modeling at Lucapa field is challenging due to the following considerations: 1) complex channel and channel element configuration, 2) graben-style Y-faulting, 3) penetration of the grid by salt bodies, and 4) erosion of the grid by near-surface canyon-cutting processes associated with the Congo Canyon.

Channel element layering geometries were driven by detailed reservoir characterization methods. Structural modeling of graben-style Y-faulting was achieved through the use of the faulted S-Grid process. It is important that the region of the grid penetrated by the salt dome be identified and considered prior to model layer construction and property propagation. The Miocene reservoir section of the Lucapa field was eroded by the paleo-Congo River Canyon during Plio-Pleistocene time and had to be identified and removed from the grid prior to any variogram-based reservoir property distributions.

At the conclusion of the reservoir model grid construction, several lessons learned included:
1) Involve all potential modeling stakeholders from the beginning of the process to ensure all technical uncertainties and complexities are considered.
2) Ensure constant interaction between static and dynamic modeling personnel to insure that fluid flow simulation of static grid geometry complexities will be achievable.
3) Establish acceptable levels of balance between reservoir model realism and simplicity.

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