Abstract

Near-shore oil reservoirs have become significantly depleted, forcing oil companies to explore unconventional reservoirs with huge investments and latest technologies. Among them, naturally fractured reservoirs (NFR) are found throughout the world and contain significant amount of oil reserves. Because of the unique features of a NFR, there are lots of uncertainties in exploration and field development of these complex reservoirs.

White Tiger is the biggest fractured basement reservoir up to now on the continental shelf of Viet Nam and even in the world. This reservoir has a very complicated geological structure: high temperature (more than 2840F) and closure stress (more than 6,000 psi). The total OIIP of this field has reached nearly 4 billion barrels with 6,561 feet of the oil bearing thickness in granite basement and has been produced by more than 200 wells, with a production rate of 180,000bbls/d. Due to the challenges of geology, it is essential to have successful operations as well as to reduce uncertainties and improve the efficiency of oil field management. With a large database collected from initial production stages, we have developed an integrated static and dynamic workflow to forecast oil production under several production scenarios for this reservoir. A successful assisted automatic history matching approach was done which can effectively accelerate the convergence problem and minimize computation mass of an inverse problem to construct a reliable model for complex reservoirs. Then a series of reservoir models are performed and analyzed by using a CMGTM simulator in order to evaluate the possibility of polymer flooding in the fractured basement reservoir. The results show that polymer flooding becomes an excellent candidate for enhanced oil recovery. Additionally, the polymer retention phenomenon by adsorption on the rock surface and precipitation by high salinity are deeply investigated. An optimum range of important factors are determined to reduce the effect of chemical adsorption, minimize mass of chemical loss, and improve economic efficiency of a chemical flooding process.