This document contains a comprehensive analysis of the results obtained for the expansion of enhanced oil recovery processes with chemicals improved with nanotechnology (NanoCEOR) based on experimental tests, effluent follow-up, and modeling through matching learning for four fields of interest (fields A, B, C, and D). Strategically, the nanofluids were designed at the laboratory level for each operating condition of interest to achieve profitability in implementing the pilots. The range of crude oil API varied between 19 and 30°, and synthetic brines were formulated with a representative variation of the ion content. Coreflooding tests were also conducted to evaluate the nanofluid performance under high-pressure and high-temperature conditions before injection into the reservoir. Representative fluids of the reservoirs of interest, core plugs with porosities between 12 and 26%, and representative reservoir conditions with temperatures between 52 and 65 °C were used. The nanofluid injection was carried out for six months in the field test for all cases. Currently, the NanoCEOR implementation allows cumulative oil increments close to 28,000, 80,000, 33,700, and 162,800 bbl for fields A, B, C, and D, respectively. It should be noted that an integrated analysis was carried out from the production and reservoir engineering areas to record the results of the NanoCEOR implementation. These results have been supported by monitoring the NanoCEOR process by evaluating the physical and chemical properties of the effluents. The results made it possible to determine the effect of nanofluids on oil incremental production. Finally, with this complete set of data, a machine learning model was used to reproduce the behavior in oil production with the application of nanofluids. In this way, it was possible to strongly integrate theory and practice to generate a system capable of accurately and timely predicting the response and needs of different wells during NanoCEOR implementation.