A Systematic Approach to Evaluate Asphaltene Precipitation during CO2 Injection

Author:

Adyani Wan Nurul1,Daud Wan Ata1,Darman Nasir1,Memon Afzal2,Khan Ifadat Ali2,Jamaluddin Abul2

Affiliation:

1. PETRONAS

2. Schlumberger

Abstract

Abstract With declining oil production, the E&P companies are in search of applying innovative methodologies to improve recovery factors from existing fields. Gas injection is one of the most commonly used enhanced-oil recovery techniques in the oil and gas industry. Here, gas such as carbon dioxide, natural gas, or nitrogen is injected into the reservoir. Gas injection relies on the phase behavior of gas and crude oil mixtures that are strongly dependent on reservoir temperature, pressure and crude oil composition. In addition, water is also injected in alternating manner to alter the wettability of the porous medium, and hence improving the sweep efficiency. Carbon dioxide in combination with alternating water is usually injected in light to medium oil reservoirs in order to increase the ultimate oil recovery. Available data on carbon dioxide injection indicates that an additional recovery of 7% to 15% can be achieved (put reference here). Also, it has been illustrated in the literature that carbon dioxide may cause asphaltenes to precipitate in contact with oil in the laboratory pressure-volume-temperature equipment or in the reservoirs. The asphaltene precipitation mechanism in the porous medium can have serious consequences of blocking pore throats depending on the size of the asphaltene aggregates, and hence, the permeability. This paper presents a systematic approach and a workflow process to evaluate carbon dioxide miscibility evaluation criteria along with the propensity of asphaltene precipitation in the reservoir for a field located in South China Sea. In this study, measurements were conducted to define the minimum miscibility pressure and also, asphaltene precipitation locus during carbon dioxide injection process. Consequently, these data were used to develop thermodynamic models.

Publisher

SPE

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