Solving the Challenges of a Complex Integrated Production System in Camisea Field Using Novel Modeling Techniques

Camisea asset is possibly the most important mega gas asset in South America, and constitutes for more than 90% of Peru’s gas production. The asset consists of several fields with varying degrees of subsurface complexities, multiple fluid types ranging from very lean to very rich gas condensate. The combined production is routed to gas processing plant via a network of pipelines. The entire development is in an environmentally sensitive area and adds to the complexity of the surface network design process. For these reasons, performing integrated production systems simulations is essential for designing the surface network with appropriate fidelities for each component of the IPSM..

In current work, a complex integrated production system was developed for Block A of the asset. It is a 2-field system with complex fluid behavior. The various fluids blend in the well tubings, as well in the combined surface network. The produced gas is treated in the plant for liquid extraction, and dry gas is routed for sales and re-injection. For all this work, a new multi-fidelity IPSM tool was used in both implicit as well as explicit coupling mode.

This was achieved by doing both implicit as well as explicit coupling of the reservoir simulation models with well models and surface network model. As a result of this work, a reliable long-term production forecast of the field could be performed. Additionally, the pipe design and network constraints could be evaluated and compression needs variation with time could be assessed. Lastly, with the use of a fit-for-purpose fidelity level for any IPSM component, more efficient and reliable forecasts could be readily generated.

A comparison between implicit and explicit coupling of IPSM components is generally missing from the available literature. This study fills in this gap by providing the option to do the two couplings using a single simulation tool, thus providing a consistent comparison. In addition to the various long-term production forecasts, the benefits and drawbacks of the two coupling approaches has been presented in this paper.