Evaluating the Development of a Multi Stacked Gas-Condensate Field to Supply LNG Using A Multi-Tiered Optimization Tool

Lemke, Alexander van Nauta (Shell Global Solutions Int. BV) | Bouts, Marcel (Shell Global Solutions Int. BV) | Drohm, Julius (Shell Global Solutions Int. BV)

OnePetro 

For the screening of a significant new LNG development a multi-tiered optimization tool was built with the following objectives:

To optimise the sequence of drilling and producing condensate and gas from a field consisting of multiple stacked reservoirs.

To understand that gas requirements could be fulfilled to supply gas to the multiple planned LNG trains

To evaluate if the tool delivered export results of various scenarios for economic screening and future auditing

 

An integrated model was built consisting of a Controlling Optimization Software (Resolve) to communicate and control the link between a Surface Network Development (GAP), the wells (Prosper), material balance model (MBAL) and a data export and plotting software (Excel). Visual workflow programming in Resolve allowed for simple adjustment of constraints and inputs through all the linked models which can optimise of multiple scenarios.

Parameters that were optimised included:

Sequence of reservoirs to produce

Well phasing over the different reservoirs showing varying condensate gas ratios

Well type, count and respective targeted reservoir

Surface infrastructure including pipelines

Compressor timing

 

The fully integrated model provided the required flexibility for evaluating various scenarios while delivering credible consistent results. Running quick scenarios can help to make decisions for the planning of the surface network and production thus helping to reduce CAPEX. Using central controlling software simplified varying both subsurface and surface constraints for the LNG development. This included seasonality influenced safety margins, the addition of compression as soon as the gas rate potential drops below critical levels and drilling new wells into the optimal reservoir when required to fill the LNG trains.