ENHANCED OIL RECOVERY

Extracting oil from tight reservoir formations is notoriously difficult. These rocks have tiny, poorly connected pores and properties that vary wildly across the formation—all of which make conventional waterflooding ineffective. Water channels through easier paths, leaving most of the oil trapped. Smart Water Injection offers a different approach by adjusting the chemistry of injected water—tweaking salt content and ionic composition—to change how oil and rock interact at the molecular level. This wettability shift helps release trapped oil. I used CMG software to simulate Smart Water performance in two low-permeability reservoirs: one moderately heterogeneous (0.45 mD) and one ultra-tight and highly variable (0.28 mD). I adjusted relative permeability curves and capillary pressure functions to represent the wettability changes Smart Water causes. The results were striking. Smart Water boosted recovery by 37% in the moderate-heterogeneity case and 66% in the ultra-tight reservoir compared to conventional waterflooding. These numbers prove Smart Water can unlock significant oil volumes even in reservoirs considered extremely challenging. This study shows Smart Water is both technically sound and economically viable for tight formations. The simulation workflow developed here provides a practical screening tool for identifying good candidates without expensive upfront lab work

The effectiveness and efficiency of “enhanced oil recovery EOR process” carried out “is” directly related “to the” increment of the reservoir inflow well performance. This Thesis adapted the Simpson rule, trapezoidal rule and equation of trendline in predicting the incremental oil from successful enhanced oil recovery processes. “Incremental oil values of Enhanced Oil Recovery projects have been obtained in the past using the” Trapezoidal rule, Simpsons rule, and equation of trendline using Microsoft excel package with both former posing “approximates the area under a curve with a straight line segment” while the later posing anti derivative of the trendline equation as an approximate value for the incremental oil. Undermining “the accuracy and significance of the incremental oil values obtained by these methods. In this work”, Simpson Rule and Trapezoidal Rule were “applied to the respective rate-time data and the concept of finite difference was introduced to account for the error term”. Experimental data was used for the analysis (Olaoye, Taiwo, & olafuyi, 2022). “Result showed more accurate predictions of Incremental oil by the” methods used in this thesis as compared to Cubic spline and Decline curve. Since, incremental oil values rightly measures the success of any EOR project by estimating accurate volumes of oil produced via such displacement mechanism, it imply that adopting the trapezoidal and Simpson Rule will aid better estimations of the economic values of projects and effective management decision making (Olaoye, Taiwo, & olafuyi, 2022). Reducing the step size(s) of the rate time curve showed more accurate results of incremental oil which is consequential in Trapezoidal rule and Simpson rule than equation of trendline, third methodology used in this thesis to fix conclusively the amount of incremental oil.