A Reservoir Management System for the World’s First Thermal Gas Oil Gravity Drainage Project

Author:

Rawnsley Keith1,Ikwumonu Augustine1,Bettembourg Solenn1,Putra Pristwanto1,Al-Ismaili Ibrahim1

Affiliation:

1. Petroleum Development

Abstract

Abstract Thermally Assisted Gas Oil Gravity Drainage of a fractured carbonate heavy oil field in Oman is starting the full field phase. Unlike a normal steam flood, steam is used as a heating agent to enhance the existing gravity drainage mechanisms. The project has been piloted successfully. The project start-up sequence consists of increasing off take from deviated producers followed by steam injection and aquifer pump-off. Steam will progressively fill the fractures whilst heated oil drains down in the matrix blocks and accumulates in an oil rim below the steam in the fractures. The fracture oil rim will be lowered by approximately 100m. Horizontal producers will be completed in the final fracture oil rim position. As no analogues exist a large degree of flexibility has been incorporated in the field development plan to cover uncertainties including caprock integrity, erratic oil rim movement and heterogeneous steam distribution. To facilitate decision making an enhanced reservoir surveillance, modelling and management system has been built. Reservoir pressures, oil rim positions, temperatures and rock strain data are obtained from a range of observation wells. Further data are obtained from surface uplift, microseismic monitoring and fluid sampling. Static, fracture, dynamic and geomechanical reservoir models have guided the design of the reservoir surveillance program and underlie the operating guidelines for the reservoir. These provide operator reactions for a wide range of "what-if" events. A corporate real time data portal has been optimised for the unique requirements of this project allowing for analysis of all data streams. A system allows 3D display, through time, of reservoir data and model forecasts to ensure optimum performance analysis. Initial application has resulted in identification of optimised well configurations and start-up sequence giving higher oil forecasts. The learning is being applied further in Oman and has wider application.

Publisher

SPE

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