(44f) Predicting the Potential of Asphaltene Deposition at Reservoir Condition in Lower Fars

Flow assurance plays a key role in effective production management. It is closely related to problems with solid deposits. Solids derived from fluid hydrocarbons such as waxes, asphaltenes, and hydrates. The occurrence of asphaltene deposition is one of the major problems that hinder hydrocarbon production. It can occur anywhere between the reservoir and the surface. Therefore, it is imperative that there be a procedure for minimizing the deposition of asphaltene in the production flow lines.

There are several screening criteria that can be considered to determine the asphaltene deposition. This research will conduct a study on different methodologies or categories to determine the stability of asphaltene: the first category is the stability criteria using indices such as: the colloidal instability index (CII), the colloidal stability index (CSI), the stability index (SI), and the asphaltene stability predicting model (ANJIS). These four methods are used to measure the stability of asphaltene using SARA analysis. The fifth one called modified CII which uses the compositions analysis of reservoir fluids, instead of SARA analysis, to determine the stability of asphaltene. The second category uses SARA Analysis to predict the stability via plots such as: Stankiewics plot (SP), De Boer plot, Sepulveda stability criterion (SCP). The third category is using compositional analysis of reservoir fluids and the equation of state model to predict the asphaltene onset pressure (AOP). In the last method a commercial software was used (PVTSIM) and Soave Redlich Kwong (SRK) equation of state model was used to predict asphaltene precipitations.

In this work, reservoir information, depth, compositional analysis, and SARA analysis from Lower Fars formation is provided by Kuwait Oil Company. These data are used to study the potential of asphaltene deposition at the reservoir level.

The stability criteria using indices and plots shows discrepancy in the results. The only two methods that shows all the datasets are stable are the modified CII and the EOS model.

As far as predicting asphaltene stability is concerned, the EOS method, based on compositional analysis and the thermodynamic model, appears to be the most reliable and trustworthy method. The other methods presented are observational rather than

thermodynamic. Using these criteria is intended as a quick and fast estimate of the stability potential of asphaltene, not for planning or management of asphaltene deposition issues.