Automated decision support expedites the identification and management of candidates for well intervention. Available on-premises, and in the cloud, these AI and workflow automation solutions deliver a breakthrough in proactivity by dramatically reducing the time and effort spent on well reviews with insights that enhance decision accuracy and quality.

Expedited screening, at scale

The traditional well review process is slow, manually intensive, and inefficient, resulting in a reduced impact to release production potential. A lack of standardization contributes to low confidence in decision making, with a high probability that information and models are not fully synchronized. Bespoke processes and engineering bias makes comparing opportunities difficult.

The approach to addressing these challenges begins by consolidating data across systems and sources—from reservoir properties to production data and well schematics. Automated decision support is provided through an integration of engineering best practices with advanced data science and use of historical data for the identification of workover, reactivation and behind casing opportunities.

Field-proven results include:

• Up to 90% in well review process time and cost savings.
• 100% production improvement in a mature field from associated intervention services.
• Results from automated decision support solutions can be made available for an integrated approach, served by a digitally enabled portfolio of comprehensive services that perform proactive interventions for wells in any condition, with reduced cost, risk, and environmental impact.

Continuously updated production enhancement opportunities

Machine learning is combined with advanced analytical models to generate insights and a continuously updated register of opportunities that can be ranked based on technical and economic criteria. Candidates can be tracked and expedited through the opportunity maturation stages, supported by an advisory solution that provides in depth technical evaluation and detailed work plans. Post-intervention key performance indicators can be captured for the continuous and automated improvement of the screening process.