Quantifying the partial penetration skin factor for evaluating the completion efficiency of vertical oil wells Academic Article uri icon

abstract

  • AbstractAn oil well's productivity is generally considered the standard measure of the well's performance. However, productivity depends on several factors, including fluid characteristics, formation damage, the reservoir's formation, and the kind of completion the well undergoes. How a partial completion can affect a well's performance will be investigated in detail in this study, as nearly every vertical well is only partially completed as a result of gas cap or water coning issues. Partially penetrated wells typically experience a larger pressure drop of fluid flow caused by restricted regions, thus increasing the skin factor. A major challenge for engineers when developing completion designs or optimizing skin factor variables is devising and testing suitable partial penetration skin and comparing completion options. Several researchers have studied and calculated a partial penetration skin factor, but some of their results tend to be inaccurate and cause excessive errors. The present work proposes experimental work and a numerical simulation model for accurate estimation of the pseudo-skin factor for partially penetrated wells. The work developed a simple correlation for predicting the partial penetration skin factor for perforated vertical wells. The work also compared the results from available models that are widely accepted by the industry as a basis for gauging the accuracy of the new correlation in estimating the skin factor. Compared to other approaches, the novel correlation performs well by providing estimates for the partial penetration skin factor that are relatively close to those obtained by the tested models. This work's main contribution is the presentation of a novel correlation that simplifies the estimation of the partial penetration skin factor in partially completed vertical wells.

author list (cited authors)

  • Abobaker, E., Elsanoose, A., Khan, F., Rahman, M. A., Aborig, A., & Noah, K.

publication date

  • January 1, 2021 11:11 AM