Brownfield-Surface Network Debottlenecking and Mitigation Analysis: A Case Study

摘要

When liquid production has levelled out despite continuing drilling and adding new wells into a production network, a surface network bottleneck issue may be suspected. The initial stage and cost- effective option in determining whether surface production was being restricted by excessive backpressure on the wellhead, or a certain part of the facility, can be done using surface network modeling. The result of surface network modelling itself is very often challenging due to minimal data availability and data uncertainties, or unclear characterization between a surface bottleneck issue and other problems such as artificial lifting and poor well performance. These challenges may be related to each other and often impede conclusions in determining any source of bottlenecks. We discuss a case study and elaborate a detailed workflow to utilize a fully benchmarked surface network model with individual well models for bottleneck identification. Using the proposed workflow, production data analysis is performed prior to building the surface network model itself and eliminates confusion between production optimization related issues and any surface bottleneck. Benchmarking of the model and selection of appropriate flow correlations are used to provide a robust surface network model. Some pipelines or connections with potential bottleneck problems are successfully identified from the modelling that are later compared with field inspection to seek any potential bottlenecking evidence or indication. Based on high-level diagnosis, amongst many other possibilities, an emulsion-management challenge was suspected in the root-cause analysis, especially for gas-lifted wells. The study was completed with sensitivity analyses of different debottlenecking scenarios to further evaluate potential mitigation plan to maximize the brownfield’s life and achieve the field’s economics objective.