This paper demonstrates how intelligent Field (I-Field) capabilities, including the Enterprise Monitoring System (EMS), are being used in real time to monitor the performance of 11 reservoirs across three Saudi Aramco carbonate Fields to meet the required crude blend, and to provide alerts to engineers when certain reservoir engineering requirements or strategies are violated. Using a real Field example, the paper discusses in detail an I-Field workflow used to monitor reservoir performance during a pre-injection period, starting from real time data gathering, validation and mapping, using Permanent Downhole Monitoring Systems (PDHMS) and integrated surface and subsurface modeling along with data mapping packages. Finally, the paper illustrates how integrated real time data and modeling results are used to optimize production and injection strategies for the three Fields for more efficient real time reservoir management.
During the planning phase for developing a new increment in Saudi Arabia (Figure 1), several challenges were identified suggesting the need for putting eight of the project's eleven reservoirs on power water injection to add reservoir energy prior to oil production start-up .
Tight flank permeability preventing enough aquifer support from reaching the crest area of the Field was identified to be a challenge for meeting production target of two of the eleven reservoirs. Long reach flank injectors with ± 2-km of reservoir exposure were recommended as the optimum solution to provide adequate injection rates to support producing area in two reservoirs .
Presence of a non-permeable tar mat across the flanks of the Field preventing aquifer support from reaching the producing area was identified to be a challenge for meeting production target of four of the eleven reservoirs. The need to drill or reactivate up-dip injectors placed ±30' above the tar-oil contact (TOC) was recommended as the optimum solution to provide adequate injection rates to support the producing area. Optimum well placement above tar was selected based on a massive data gathering project that was initiated to map the tar mat. Several studies were conducted to confirm minimum impact on ultimate recovery of wedge oil .