Abstract
Every year, millions dollars of money have been spent to remove and inhibit scale deposition in upstream oil industry. Hence it is important to have reliable predictive software to gauge the risk of scaling tendency of a production facility. Several approaches are established to model the scaling tendency during oil recovery. The most conventional models consider the concepts of phenomenological and equilibrium thermodynamic. Both methods are static modeling of an aqueous solution that predicts the scaling tendency at given temperature and pressure. If the scaling assessment is to perform on a producing well where the water composition, three phase (gas-water-oil) distribution and physical conditions (temperature and pressure) are varied at different location, the evaluation process becomes very tedious and impractical.
Therefore, a dynamic scaling modeling instead of static modeling method is required. For the reasons that in addition to serve as a tool to alarm the risk of scale precipitation, it also indicates the amount of scale precipitated and the likelihood deposition location to enable employment of pro-active preventive treatment at early stage. A coupled thermodynamic-flow model simulator is proposed to accurately determine the scaling tendency, quantity and location of inorganic scale deposition in production tubing under flowing condition. This model will couple the effects of thermodynamic equilibrium and kinetic for flow in a producing tubing. This is a major advance on prior state-of-the-art static models that normally predict the scaling tendency for single temperature and pressure input.
A modeling framework is presented in this paper. The proposed scheme in developing the thermodynamic-flow model is described. A number of engineering conceptions were reviewed and all the elements that become the foundation of this thermodynamic-flow model were discussed.
The advantage of having this thermodynamic-flow model is a better flow assurance management, in which scale prevention and treatment design can be refined, leading to unnecessary production lost and reduce treatment cost.