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Making inaccessible well and reservoir data available to engineers
Capturing and trending every Pressure Build-up Test to provide a more complete picture of the reservoir
Problem: Pressure build-up tests, performed after a well is shut-in can provide useful data about the reservoir’s permeability and pressure in drainage areas. From these insights and others, depletion plans can be updated more accurately.
Planned shut-in events happen every so often, limiting insight for reservoir engineers who may have to wait months to determine if the reservoir is performing in line with expectations.
However, unplanned shut-in events happen much more frequently, often unchecked and unobserved. Data from ad hoc pressure-build up are lost for such events, denying reservoir engineers the data to build richer analysis to support optimal depletion planning.
Solution: We worked with Harbour Energy to access data from their ESPs-fitted wells to automatically identify every shut-in event and capture the pressure build-up that follows.
Given ESPs frequently shutdown, Ingenuity is able to use the ESP Power tag to detect the event, pulling in related data from Harbour’s Asset Knowledge Graph (Well_Name, ESP_Inlet Pressure, ESP Power and the latest Oil and Water Rates) to visualise the pressure build-up as a trend.
Using a combination of Python scripts and Node_RED ®, we built an automated workflow which exposed an API and used Ingenuity’s Dynamic Dashboard widget to display tabulated results and trends related to pressure build-up, along with context about the well.
Moreover, the data is also stored in CSV files that the engineers can download with 1-click for further analysis.
Impact: Without pressure build-up data from these unplanned, frequent, well shut-in events, the reservoir engineering teams have been operating with limited data.
And yet, that data has always been available, just hidden and difficult to access until Ingenuity connected it up and presented it intuitively.
Often Ingenuity facilitates access to data, but in this case access to the data was the key challenge; almost impossible to overcome without the use of technology.
Once made available however, it now takes the engineer seconds to acquire it, giving them the headspace they need to do more valuable work.
Having the data with the associated trends and history, now improves engineers’ ability to properly characterise the reservoir and how it is changing as the field is produced.
With a richer set of data, the team is freed up to perform more robust depletion planning, as well as to test the effect of any interventions (pressure changes, stimulation, water injection, etc) more frequently.
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