The inflow performance prediction of a completion is one of the most important tasks in forecasting production performance of a well. When selecting an optimum completion design it is essential to compare different options and perform parametric studies, one of the key completion decisions being the selection of a cased and perforated or barefoot well. In cased and perforated wells, key inflow performance parameters include gun type, perforation penetration depth, shot density, shot phasing, depth of mud invasion and dependence of their effects on reservoir properties. The open literature hosts a plethora of inflow equations for some classic completion practices; however, complex options are not adequately addressed. More importantly, when one compares inflow performance of various completion options or conducts a parametric study of certain parameters, the relative calculation results do not always make sense.
In this paper, we describe an operator’s (Shell International Exploration and Production) in-house study to develop a consistent set of inflow performance equations that not only make sense in their own right, but also make good relative sense when comparing different completion options, particularly with regard to cased and perforated wells. Most of the significant open literature has been reviewed and a set of consistent inflow models have been compiled and developed. Many equations have been improved—e.g., perforation skin calculations, mechanical and total skin calculations, rate dependant skin for horizontal completions—and new equations have been derived for options not previously modelled in the literature (e.g., barefoot and perforated completions, double perforated completions, re-perforated completions and complex horizontal completions). All equations have been coded into the Shell Perforation Optimisation Tool (SPOTTM) software package, enabling engineers to easily and accurately predict and compare complex completion options for design decisions. Inflow performance calculation results of various completion scenarios and parametric studies are also presented.
Efficient and accurate selection of optimal collective communication algorithms using analytical performance modelling
