Multiple Linear Regression Theory Based Performance Optimization of Bakken And Eagle Ford Shale oil Reservoirs
Journal Title: International Journal of engineering Research and Applications - Year 2018, Vol 8, Issue 1
Abstract
This paper presents the application of multiple linear regression modelling (MLR) to evaluate the performance of the Bakken shale oil and Eagle Ford gas condensate reservoirs in the United States.A critical review and analysis were made on the unconventional reservoirs and also on using CO2 huff-n-puff, and flooding processes for enhanced oil recovery (EOR).A total of four models was taken for the analysis, such as the Bakken and Eagle Ford reservoirs with CO2 huff-n-puff process and another two models with CO2 Flooding. Injection pressure, injection rate, injection time, number of cycle, carbon dioxide soaking time, fracture halflength, fracture conductivity, fracture spacing, porosity, permeability, and initial reservoir pressure as taken as inputs and cumulative oil production, and oil recovery factor was taken as outputs. The reservoirs was designed for 30 years of oil production and this is considered as DMU and the Chi-Square test was used to validate the model for the goodness of fit. From the statistical results, it was investigated that the performance of the Eagle Ford reservoir in both scenarios of huff-n-puff and flooding were better than the Bakken reservoir model, even the χ2 test has validated the Eagle Ford gas condensate reservoir model as good.
Authors and Affiliations
Venkat Pranesh, Vivek Thamizhmani, S. Ravi kumar, Sujeeth Padakandla
Keywords
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- EP ID EP393376
- DOI 10.9790/9622-0801026688.
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