Abstract

This paper discusses a production efficiency improvement (PEI) case study using an Integrated Asset Model (IAM) in a super-giant brown field consisting of more than a thousand well strings producing from multi-layered reservoir with different properties. This paper discusses various scenarios that were considered to carry out production efficiency improvement and system bottleneck identification using IAM model integrated within digital framework consisting of automated workflows and advanced data integration.

IAM solution was implemented in a super-giant brown field to help users to carry out complete system-analysis to assist in delivering production-mandates, identifying sustainability and removing potential bottlenecks for improvements.

This solution incorporates integration of validated well and network models within a digital-layer, in which various analytical-processes and workflows are automated and integrated with multiple corporate-data-sources. This centralized production-optimization based collaborative-platform enables user to carry out various scenarios while taking into account different operating constraints. Validated and calibrated well and network models were integrated within these workflows, updating them on daily basis, thereby providing representative well and network performance parameters.

This paper discusses several case studies that were carried out utilizing an integrated asset model, thereby achieving fundamental business objective of production efficiency improvement. For this purpose, full field network models consisting of more than a thousand calibrated well strings were analyzed within a digital IAM framework.

Various what-if scenarios were adapted to conceptualize an engineering approach in which various reservoir, well and facility level guidelines were incorporated for identifying true potentials of the system. This holistic approach provided users the capability to carry out a detailed analysis to achieve various key production objectives such as reducing production deferrals, compensating production shortfalls, identifying total system capacity and thereby enhancing production efficiency.

Key challenges and recommendations for improving production efficiency and establishing standardized well potential determination methodology were also highlighted from the case study. Lastly, identification of the true production limits of the reservoir, wells, and the surface network were made possible which is fundamental to the delivery of the long term field development plan.

Identifying true capacity at the well and field level is a challenging task in a field with more than ten development area with completely different fluid properties and production capacities. A standardized IAM solution approach made this estimation possible. This approach also helped in minimizing potential production deferment thereby leading to cost optimization of total system.

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