Value Optimization of Nigerian Gas Fields with Various Maturity Levels, Through Integrated Asset Modelling

Several infill wells and a new undeveloped field are planned to be integrated into the production of four legacy gas fields, each at different maturity levels, sharing complex surface network facilities. This study demonstrates how a fit for purpose coupled Integrated Asset Model (IAM) enhances production by: prioritizing the drilling sequence, scheduling workovers, optimizing the compression strategy. The coupled model of this asset was built in the integration platform. It combines five 3-dimensional gridded reservoir models, managed by a commercial reservoir simulator, some tens of tank material balance reservoir models and a complex production surface network. The gas surface network model considers: i) about forty gas wells, with several levels of completion, that can be routed to either one of four gathering networks with different pressure levels; ii) three compressors; iii) associated gas and gas lift from nearby oil wells; iv) routing changes with time. The integration platform manages the coupling, facilitating all data exchanges between the network simulator and the reservoir models. The integrated model contains two main workflows: Well management and Field production optimization. These workflows aim to replicate field operations logic (e.g., closing wells at liquid loading risk, prioritizing wells with lower WGR, adapting wells routing) and suggest actions to (re)activate wells, prioritizing gas or condensate production. The constructed integrated model identified the most impactful surface network constraints and proposed timely actions to enable production maximization, such as: upgrading medium pressure compressor capacity; selecting the optimal internal diameter for a new flowline; revising the drilling sequence; optimizing the well completion strategy. The integrated asset model was validated against historical measurements, with 2023 gas production predictions aligning with measured production. Pressure loss estimates for main pipes in the surface network model matched measured losses between different manifolds. The model confirmed the technical feasibility of producing incremental stakes from both infill wells in legacy fields and a new undeveloped field, considering shared surface facility constraints. Several optimization and debottlenecking options were proposed to unlock the asset’s potential, including delaying the switch from high pressure to medium pressure manifold for some new wells; upgrading medium pressure compression capacity; revising the re-completion sequence. Thanks to the high scalability of the reservoir simulator, and to the massive computation resources of our HPC cluster, simulating the 25-year forecast in the coupled integrated model takes 12 hours, allowing the model to be used for regular optimization.