Abstract
The asset Oso-Yuralpa has 7 fields and 323 completions, located in the Blocks 7 & 21 of Ecuador. The oil cumulative production reaches 168.5 MMSTB. The active wells produce using electric submergible pump, hydraulic jet pumps and natural flow, mainly from 3 production zones. In surface, the production is processed in two flow stations, with high capacity processing.
This project was focused on Oso Field, located in the asset north area. Due the aggressive drilling campaign and the consequent increase in the daily production activities, has created the need to evaluate the impact on the surface facilities.
The scope of this study is evaluating different field development plans, integrating reservoir to surface facilities, that includes reservoir description, well models configuration, fluids gathering network, process facilities and economic indicators, with the objective of visualize and optimize field production, better decision making and operational planning considering long term life cycle.
Working in four scenarios was evaluated, as follow:
Base Case: Operations at current situation.
Drilling New Wells: Execution of drilling campaign to create 35 new wells using four rigs.
Drilling Campaign with Delays: Considering delays in drilling schedule.
Drilling Campaign with one rig less: This scenario considers one rig less.
The results in terms of cumulative production and recovery factor, estimates a maximum recovery factor of 4.2%, with and an additional cumulative production of 87.52 MMSTB with an increase of 1023 MMUSD in the Net Present Value (NPV). The Operating costs increase in 30% due investments in drilling campaign and fluid processing in surface.
As conclusion, the fourth scenario (Drilling Campaign with one rig less) gives the highest profitability index with the lower operational costs, which represent the recommended development plan.
The implementation of and integrated asset study, permit evaluate the project profitability in different scenarios, identify bottlenecks in surface network and measure the investment and costs uncertainty.
The present study allows the knowledge sharing between disciplines, making possible evaluate and visualize the asset development with sustainable technical and financial indicators.
The continuous evaluation of integrated models, serve as base for further production optimization and risk analysis studies, and could be applied in other assets.
