Reservoir Monitoring Data Driven Workflow Automation in Giant Onshore Oil Fields - An Integrated Approach for Resources Optimization and Improving Value of Information
Authors: Reddicharla Nagaraju , Rubio Erismar , Alshehhi Shamma Saeed , Naggar Hossam El Din Mohamed El , Selvamoorthy Geetha , Mathew Jim , Kumar Amit , Ali Mayada Sultan 
Published: October 2023

Abstract
The value of delivering and sustaining excellence in reservoir management is essential for enhanced recovery and meeting production objectives. To ensure sustainable reservoir management assets must continuously monitor, analyze and make decision to optimize key performance results and indicators. Aiming to improve efficiency and optimization in reservoir monitoring process, ADNOC Onshore established on of its kind digital data driven advanced automation system for addressing challenges such as collaboration, prioritization & optimization, resources unavailability, minimizing production deferment and improve activity execution performance. This paper presents a success story how ADNOC Onshore has digitally transformed reservoir monitoring process in Giant Onshore fields
This digital advanced automation is a unified solution for data gathering and data management, data driven analytics and collaborative business workflows. In this automation five critical workflows have been digitized, they include reservoir surveillance well candidate selection for data acquisition, rig-less resource planning & optimization, schedule optimization, monitoring data management and execution performance. All these components are governed by standard business processes among asset development and operations stakeholders. Automated Well candidate selection leverages data driven analytics by integrating well performance, historical data, integrity, accessibility, workovers, well events and offset wells based on reservoir management guidelines. As a next step activity prioritization is automated based on business impact and urgency before plan is sent for approval. The system estimates rig-less resources requirement and cost. The system allows to carry out rig-less planning and scheduling and shuffle activities based on resources availability. The scheduling module retrieves major shut down plans and minimizes production deferment. The System governs surveillance raw data, engineering analysis and interpretations as a single repository. Interactive dashboards are provided for monitoring activity execution performance as KPIs and follow-ups.
This implementation has enabled the asset teams to maximize the lifecycle value of hydrocarbon producing fields t that achieves the right balance between achieving production targets and information gathering. The automation system has been successfully implemented in four giant onshore producing fields by promoting collaboration with an integrated effort including Operations, Production engineering, Petroleum Engineering, reservoir engineering and well services. This implementation has improved the efficiency and reducing decision making process by 70%. Data management efforts have been reduced by 75% by integrating data generated at different business process steps with corporate data sources. 10% - 12% of total cost has been saved in reservoir surveillance activities through resources optimization and system has enabled to carry out surveillance activities on right well candidates through this efficient automated process.
Cost optimization takes central stage due to market dynamics in current conditions, this digital solution drives asset engineers to generate optimum plans with minimum efforts. The successful implementation case study presented herewith, demonstrates pragmatic approach followed in this data-driven automation and value generated utilizing this novel methodology.