Business driver: A gas producer switches from a pressure based control to a flow based control method. Operations will subsequently heavily depend on future capacity planning. Because the dependency on capacity information has increased, the importance of data integrity has also risen. Due to this data-quality and –integrity have become important issues: operators rely on the data to advise gas traders on the capacity for the upcoming one to four hours.
The mu-Engine can test the data quality per production-unit and whether a dataset’s quality is good, bad or unsure. When a dataset is marked as bad, a detailed report can also be requested. The detection algorithm which facilitates dataset evaluation uses a “state based rule set”. This means that the rule set is dependent on the state of the production-unit in question. The state can be transitioning, shutdown or stable.
The mu-Engine can test the data quality per production-unit and whether a dataset’s quality is good, bad or unsure. When a dataset is marked as bad, a detailed report can also be requested. The detection algorithm which facilitates dataset evaluation uses a “state based rule set”. This means that the rule set is dependent on the state of the production-unit in question. The state can be transitioning, shutdown or stable.
Figure 1: automatic detection and tagging of data quality per unit.