There are thousands of mature oil and gas fields in the US with 100,000s of wells to monitor and optimize with an ever-shrinking skilled workforce. That means hundreds of wells for each production engineer to analyze daily. This routine work normally is not automated and leads to lengthy well-by-well reviews.
Missed Production Targets and Increased Costs
Regularly the best workover candidates with the highest potential production gain have been overlooked because they are not always obvious at first sight. Suboptimal workover investments lead to missed production targets and increased lifting costs.
The entire candidate screening model has been automated i.e. continuous automated screening for underperforming wells, including KPI calculations, data analytics, problem detection, cost and risk estimation, NPV calculation and ranking of workover opportunities. A knowledge base for improving decision making is built.
Added Value Gained
More Promising Workover Candidates and Standardized Work
Additional workover opportunities were identified that had gone unnoticed previously. As a result, the operator’s capital program started to deliver more production at a lower cost-per-barrel. Quickest return and lower workover costs per barrel. Technical and reservoir risk is lowered. Premature well abandonment is avoided (= extending well life and deferring well plugging costs). Engineering time is saved by highlighting the best opportunities, engineering time is spent on the most promising workover candidates, and work is standardized on best practices.
- Major European operator with more than 200 brownfields
- Major Middle East National Oil Company for one of the biggest offshore fields in the world