Digital Solution for Well Surveillance in Stacked Reservoirs with Near-Critical Fluid Systems

Abstract

Fully compositional integrated asset models (FC-IAM) are being deployed for an increasing number of fields in the company's portfolio. Field A described in this work comprises four stacked reservoirs, each containing a near-critical fluid system with significant compositional depth gradient. Augmenting the FC-IAM with high-frequency sensor data as well as proprietary tools to actively monitor well performance helps identify and pursue opportunities to maximize the oil production rate from the field, subject to several system constraints. Fluid properties were modelled with a cubic equation of state tuned to laboratory data to address some key challenges: Near-critical fluid systems giving rise to compositional variation versus depth.Injection of produced gas that develops multi-contact miscibility with the original reservoir fluids.Blending of fluids at surface from four stacked reservoirs.Operational requirement to maintain the bottom-hole pressure above saturation pressure.Validation of raw well test data before shrinkage correction (line conditions). Compositional surface network models are run automatically on hourly basis and compared against real-time data. A surveillance algorithm identifies opportunities and assigns them to well owners. Activities are managed through a high-level tracking and value-capture system. The asset team is consistently maintaining the well and surface network models assisted by the digital solution. The surveillance automation engine creates a feedback loop with the engineers which ensures that the models are of sufficient quality for production optimization. Models reproduce the actual oil and gas produced rates within the accepted accuracy range and are used routinely in optimization scenarios. The surface network model is also run in transient mode to study and optimize flow in two large subsea multiphase pipelines. Total value generation from implementation of the complete framework therefore exceeds expectation based on the steady-state production gain. The intangible value associated to reducing engineers’ workload, better data accessibility, HS&E and efficiency of operations has set a strong foundation for the strategy of the company to grow its enterprise value through increased volume and cost reduction. Implementation of a compositional model framework is still uncommon as most integrated asset models rely on a black-oil formulation for the fluid property description. Near-critical fluid systems undergoing miscible gas injection add an additional layer of complexity in terms of modeling and surveillance efforts. Real-time data have proven indispensable for keeping the IAM up to date and for identifying opportunities for optimizing the production.