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Abstract
This paper assessed the impact of fluid invasion on well performance and productivity. OLGA simulation of fluid invasion into the well was done to generate data points for modelling the effect of fluid invasion on well performance and productivity. From the simulations, about 32 data points were generated which were exported to excel and was analyzed using data analysis toolpak. The outcome of the analysis generated a multi variate correlation which equated well performance in terms of volume flow rate to independent variables including the tubing total fluid content in the well. The trend volumetric plots from OLGA were used to indicate the onset of fluid invasion into the well and for this study, the critical volume flow prior to the onset of fluid invasion was 450,000 sm3/day and this occurred after about 38 hours of flow. The implication of this is that, below this rate, the well is underperforming due to fluid invasion and the continuous experience of fluid invasion will later cause a total formation damage, and when this occurs, the production is completely interrupted. The correlation revealed that the relationship between fluid content in the wellbore and the well productivity is inverse. That is, a decrease in fluid content in the wellbore results to an increase in the well productivity. With this correlation, at any point in time t, the well productivity can be predicted and from the value of the volume flow rate of the well, it can be confirmed if the wellbore is underperforming due to fluid invasion or not. The correlation was validated using statistical analysis by assessing the R square, P, Significance F values and the trend plots of the predicted volume flow rates and actual volume flow rates. These tests confirmed that the correlation is statistically significant.
Suggested Citation
Precious Chisom Jumbo-Egwurugwu & Franklin Okoro & Obo-Obaa Elera Njiran, 2022.
"Analysis of the impact of reservoir fluids invasion on well performance and productivity,"
International Journal of Research and Innovation in Applied Science, International Journal of Research and Innovation in Applied Science (IJRIAS), vol. 7(1), pages 103-111, January.
Handle:
RePEc:bjf:journl:v:7:y:2022:i:1:p:103-111
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