An Accurate Simulation Model in a New Virgin Production Layer in Sungai Gelam-C Field: Challenges, Data Analogue, and Further Improvement

Abstract

Defining forecast oil production of new layer N1 sand is challenging. In initial stage of field development, data availability in static to dynamic is limited, especially Special Core Analysis (SCAL). Production test data used to validate model was inadequate in history matching phase. Therefore, new method is needed and conducted to deliver accurate model in proposing new drilling wells.

Regional geological concept and lithology log data indicating that existing N sand and new N1 sand was deposited in same environment so they could be analogized alike. Correlation between static pressure, flowing pressure, and production rate of existing N sand used as an approach to construct the relative permeability curve of new N1 sand. Production rate is predicated on the amount of saturation within the reservoir rock. Increasing water saturation causes in decrease of effective permeability. J-function reconstruction and contact determination are conducted from water saturation versus depth in existing wells’ log analysis.

In 2020, two wells were drilled based on latest simulation model, located in outer existing wells with radius around 400-500 meters. In updated static model, there is no major difference to the previous one. The last two wells drilled encountered similar sand facies of marine deposit with thickness of 11.5 meters (15% thicker than estimated), and porosity near 22% (8% bigger than estimated). Like static model, the dynamic model is also had a good accuracy. Static formation pressure, dynamic formation pressure, and multi rate test were being used to validate reservoir simulation by comparing to actual data in the last one year (December 2019-December 2020) which resulting a good relation to the actual production data (oil production cumulative 230.2 MSTB forecast vs 220.7 MSTB actual).

By applying this validation method of data limited-reservoir model will help us to minimize subsurface risk and deliver accurate deliverability of model and production’s well performance. This method could be implemented and as a standard of new sand reservoir development.