Condition-based well-test scheduling

How we help our partners automate their well-test schedules with a data-driven approach

Value proposition

  • Allows the user more time to focus on decisions by automating the data gathering and analyses
  • Optimize the order of well tests with a balanced scheduling score, to better exploit test resources
  • Use scheduling scores as a preventive measure, by testing wells with high scores gain insight on issues like water coning


A central challenge when it comes to well-testing is figuring out which well to test next in order to optimally utilize the available test capacity. This is important as test capacity often is a constraining factor on many assets. This is true for both fields with test separators and fields that must do deduction testing.

It can be tedious to gather all the relevant information that needs to be evaluated to make a thorough assessment of which wells to test. Often the test schedule is a fixed rotation between wells and occasionally subjected to small changes that are based on gut feeling and subjective knowledge. Also, data-driven methods for detecting events like water coning demand accurate well rate data obtained from well-test. If all the relevant data was readily available in one place it could lead to better condition-based decisions about which well to test next.


Together with Lundin we launched a test scheduling campaign to see if we could take advantage of our software in the decision making process of which well to test next.

As the campaign went on our Well-test Scheduling application emerged.

With our Well-test Scheduling application engineers get live updates on data-driven recommendations for which wells to test. The recommendations are based on a weighted well-test score consisting of several indicator parameters for each well. The parameters and weights are configurable to match the needs of the field and even the well in question.

A list of the highest prioritized wells is available in a dashboard, with a breakdown of the well-test score for transparency and control. This way the engineers can easily check why a well gets prioritized by the algorithm, adding a new perspective to the decision process.


With our solution all the data relevant for assessing well-tests have been centralized in one place. This automates the tedious, and manual work of gathering data from different sources and gives the engineers more time and insight to actually evaluate the wells to be tested.

No wells are accidentally ignored as live data from each well is connected to the dashboard. During our initial two-week campaign with Lundin we already saw the potential benefits of the application. At one occasion a well was tested because the algorithm had picked up irregularities in one of its parameters. In fact, this well was not originally scheduled for testing, but Lundin sought to test it regardless.

Together with our other test optimization applications the Well-test Scheduling can be a powerful tool to become condition-based and make truly data-driven, unbiased decisions.