With an ever-shrinking professional workforce, there are thousands of mature oil and gas fields in the United States with 100,000s of wells to monitor and optimize. That implies each production engineer must monitor and analyze tens or hundreds of wells on daily basis. This routine labor is rarely automated or standardized within all company assets which results in long well-by-well assessment, identifying the poor performing wells.
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. Moreover, different evaluation logic and output between different teams are usually observed due to the lack of standardizing company best practices.
With the Production Optimization App, 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 discovered that may have previously gone unreported. Moreover, a prioritized list of workover candidates promotes the lowest workover cost per barrel with the lowest technical risk, hence the quickest return. As a result, the operator's capital program began to deliver more production at a reduced cost per barrel. Premature well abandonment is prevented (well life is extended, and well plugging costs are deferred). By emphasizing the best opportunities, engineering time is saved and spent on the most promising workover candidates, and evaluation assessment work is standardized using company best practices.