02154nmc a2200241 4500 20260520010449.0 260224s xxu 068.82 553.28 C62 15730 Simposio Campos Maduros COMBINANDO MACHINE LEARNING Y FÍSICA DE RESERVORIOS PARA LA OPTIMIZACIÓN DE YACIMIENTOS MADUROS EN LA CUENCA DEL GOLFO SAN JORGE, ARGENTINA 12/10/2023 ; 12/10/2023 16 p. ; 23-38 The Zorro project is located inside the Cerro Dragon field which is subdivided in nine blocks due to main faults delimitating the structure and the reservoir rock distribution. The majority part of the oil production of the project is associated to secondary recovery. This work presents the results of the application of a waterflood optimization workflow powered by data physics modeling using data from the Golfo San Jorge basin. The proposed workflow combines traditional reservoir engineering equations with machine learning, data assimilation techniques and advanced optimization algorithms. The models incorporate real data, which can be updated continuously, allowing the engineers to evaluate different scenarios and identify the optimum injection plans for the asset. As the models honors physical principles, this methodology provides long-term predictions and ensure physical feasible results. The result is a sample of the application of a dynamic workflow and how the digital transformation process is providing value to the oil and gas industry. The obtained production increase shows how multidisciplinary teams are enhanced by the inclusion of technology, managing to optimize processes and production. CONGTP Galliano, Federico 767 Medda, Fernando 59482 Gutiérrez, Fernando 59512 Plotno, Sebastián 61478 Congreso de Exploración y Desarrollo de Hidrocarburos (11er : 2022 nov. 8 - 11 : Mendoza) 61064 196175 196175 https://biblioteca.iapg.org.ar/ArchivosAdjuntos/Conexplor2022/Simp.CamposMaduros/campos-maduros02.pdf 0 0 0 0 263894 BVIAPG BVIAPG 068.82 553.28 C62 15730 2026-03-06 200068593 0 068.82 553.28 C62 15730 200068593 2026-03-06 00:41:35 2026-03-06 ARCHIVO