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Data Connections by Datagration
PetroVisor™ Workover Candidate Advisory | From Sporadic Manual Opportunity Selection to an Automated Advisory for Middle East NOC

A NOC’s upstream oil and gas business focuses on exploring, developing, and producing crude oil and natural gas in a key Middle East oil-producing region. Leveraging advanced technologies and strategic partnerships, the NOC aims to optimize production, enhance recovery rates, and maintain a competitive edge in the industry.


The client faced challenges related to limited availability of fast, quick, and flexible solutions for rig and rig-less intervention opportunities. The manual quarterly update of their workover opportunity register took one week per well, and the absence of a standardized systematic screening workflow further complicated the selection process.


The primary objective was to enhance well intervention success rates through the combination of technical, risk, and financial evaluations. Specific goals included optimizing CAPEX efficiency by selecting top rig-less intervention and workover candidates, detecting underperforming and unhealthy wells, and introducing automation for unified data models and daily/monthly advisory.


The PetroVisor advisory system transformed the manual opportunity selection process into a dynamic, automated advisory for the client. Key components of the solution included a unified data model incorporating relational databases, well models, logs, and spreadsheets. Technical and financial dashboards in Spotfire provided comprehensive visualization, complemented by inactive string prioritization for both rig and rig-less interventions, detection of underperforming and unhealthy wells, well conversion to gas-lift, and identification of water shut off candidates.

Core Functionalities Utilized from PetroVisor

  • Unified data model with data integrations from over 30 sources.
  • Technical and financial dashboards in Spotfire:
    • Inactive string prioritization for rig and rig-less interventions.
    • Detection of underperforming and unhealthy wells.
    • Well conversion to gas-lift.
    • Identification of water shut off candidates.
  • Best practices captured in P# script developed with the involvement of the client’s asset team.
  • Machine learning algorithms and multi-criteria decision analysis for workover candidate selection.

The implementation of PetroVisor's workover candidate advisory solution resulted in significant benefits for the client:

  • Enhanced focus on value-adding actions, leading to time savings.
  • Increased well intervention success rate by selecting the most suitable candidates.
  • Reduced downtime and deferred wells.
  • Improved ROI from workover expenses and streamlined rig-less and workover scheduling.
  • Achieved materially increased efficiency of rig-less interventions - validated through field trials.
  • Maximized sustainable incremental oil generated from workover expenses.

The success of PetroVisor and the client’s commitment to innovation in data analytics have been acknowledged with this work nominated as an ADIPEC 2021 finalist in "Digital Transformation of the Year Project."


To explore in-depth details about PetroVisor's Workover Candidate Advisory and its transformative impact on the client’s operations, please refer to the following references:

  1. SPE-207274-MS: “Automated Well Portfolio Optimization for a Mature Hydrocarbon Field in the Middle East”​
  2. SPE-203022: “Artificial Intelligence Assisted Well Portfolio Optimization - An Automated Reservoir Management Advisory System To Maximize The Asset Value”
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