Sweep Management with floodOPT

In mature conventional floods, significant optimization can be achieved by adjusting well rates to realign patterns, enhancing sweep efficiency, and reducing fluid cycling. Streamlines facilitate this process by identifying injector-producer pairs and quantifying their connections over time. Using this information, floodOPT generates well rate targets for both injectors and producers over a desired forecast period to improve oil recovery and minimizing recycling of injected volumes.

floodOPT Workflow

1

Simulation/Surveillance Model Through End of History

The starting point for optimizing an existing flood begins with a 3DSL simulation or surveillance model extending through the end of historical data.

  1. For a simulation model, an acceptable well-level history match is important, as the efficiency of each well pair is determined by the ratio of simulated produced oil to simulated injected water (or CO2) associated with the pair.
  2. For a surveillance model, historical production and injection data are matched by design. However, remaining fluid-in-place maps are generated using a material balance calculation applied at the well-pair level.
2

Select Wells (Patterns) and Set Constraints

FloodOPT is based on the principle of adjusting well rates to optimize sweep patterns. It allows users to select specific patterns (injectors linked to associated producers), define the aggressiveness of rate adjustments (strategies), set minimum and maximum well voidage limits (well constraints), and ensure compliance with broader field constraints (reservoir constraints).

3

Generate Target Rates

Run FloodOPT to generate target rates that enhance sweep efficiency and minimize cycling while adhering to the selections and constraints defined in step 2.

4

Forecast

Both simulation and surveillance models can be used to predict the response to the new target rates generated by FloodOPT in step 3. 
The forecast duration is user-defined. FloodOPT can also be run at a preset frequency (e.g., every n months) to track how rate targets evolve in response to changes in flood efficiency over time.

Features

 
floodOPT is based on either a surveillance or simulation model and allows to: