SIMPLIFIED COMPUTATIONAL TOOL FOR PREDICTING FORMATION DAMAGE IN OIL WELLS

Abstract

The present study underscores the significance of regular well test analysis to ensure the accuracy and consistency of data pertaining to the permeability and skin of exploratory wells. This study advances the development of a novel computer model, ASPIRE, which predicts formation damage in oil wells by analysing well-test data. In this context, identifying blocked pore throats in the formation close to the wellbore by paraffinic deposits (scales) and its influence on permeability necessitates routine well-test analysis. The software employs a modified linear regression model developed in this study to perfectly fit the well-test data's infinitely acting linear flow (IARF) region to a straight line. The cases "CASE 1" and "CASE 2" were considered for constant rate transient drawdown well test analyses. The findings indicate that Case 1, with a high skin factor, requires remedial action, such as stimulation, to increase the formation's permeability close to the wellbore for enhanced productivity. In contrast, Case 2 has higher permeability and lower skin factor than Case 1, so stimulation is not required. In addition, R-squared analyses were conducted to validate the results obtained from the developed tool. The analyses reveal an R-square value of 1 for all cases, indicating a 100% accuracy. Therefore, the study concludes that the developed tool is instrumental in accurately predicting formation damage in oil wells.

Keywords

• well
• test
• aspire
• production
• optimization
• model