Application of the new multi-component suspension model for skin-factor evaluating on the wells equipped with gravel packs

UDK: 622.276.5.05
DOI: 10.24887/0028-2448-2018-12-63-67
Key words: filtration, deep bed filtration, gravel pack, sand production
Authors: M.M. Khasanov (Gazprom Neft PJSC, RF, Saint-Petersburg; Gazpromneft NTC LLC, RF, Saint-Petersburg), K.E. Lezhnev (Gazpromneft NTC LLC, RF, Saint-Petersburg; Peter the Great St. Petersburg Polytechnic University, RF, Saint-Petersburg), V.D. Pashkin (Saint-Petersburg State University, RF, Saint-Petersburg), A.P. Roshchektaev (Gazpromneft NTC LLC, RF, Saint-Petersburg)

and production can become a major problem during the development of weakly consolidated reservoirs. Sand control methods include various downhole filters such as slotted liners, wire wrapped screens, gravel packs, etc. However, only a few methods are capable to evaluate and predict the effectiveness of the sand control method depending on the geological and mechanical parameters of the reservoir.

The article presents a new model of multi component suspension that can be used to estimate the additional pressure drop due to the presence of gravel filter. The constructed model describes fluid flow with solid particles of different sizes in a porous medium. The model is based on the conservation of mass equations for individual phases in multiphase flow. The phases considered in the model include carrier fluid, mobile and trapped solid particles. Empirical relationships of suspension viscosity on the concentration of solid particles, the dependence for the particles trapping probability, and the formula connecting the permeability and the porosity of a gravel filter were used as constitutive relationships. In contrast to the previously presented models, in this article, particles of different sizes are considered as separate phases, so that particle size distribution is taken into account. Adaptation can be performed by comparing the model calculations with the results of numerical experiments based on the discrete element method or with field data. The model, set up by the first method, can be used to estimate the changes in the parameters of a gravel filter in time, based solely on the particle size distribution of the formation rock. The data obtained from the operation allows improving this evaluation.

In general, the presented model can be used to calculate the dynamic changes in the skin factor of a well equipped with a gravel filter, and also potentially to optimize the sizing criteria for gravel packs.


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