A Survey of Combining Association Rules for Pre-warning of Oil Production Problems
Periods of sub-optimal production rates, or complete shut-downs, add negative numbers to the revenue
graph for oil companies. Oil and gas are produced from several reservoirs and through many wells with
varying gas/oil proportion, making it a complex process that is difficult to control. As a part of a threestep
process for utilizing data in the oil production domain, this thesis derive methods for combining
event patterns, called restricted association rules, in time series in order to warn about future anomalies in
oil production processes. Two problems have been considered: Network learning and network reasoning.
The suggested solution consists of building an Association Rules Network (ARN) from the rule set given
as input. After transforming the hypergraph-based ARN to a directed acyclic graph, correlations between
nodes are found by applying the shortest-path principle. Motivated by the shortcomings of this simple
solution, it is shown how a method for learning Bayesian networks with support for representation of
temporal dependencies can be derived from the initial ARN. The concept, named Temporal Bayesian
Network of Events (TBNE), is a powerful, but yet complex solution that enjoys the properties of Bayesian
network reasoning while at the same time representing temporal information. This thesis has shown that
it is theoretically feasible to combine restricted association rules in order to create a network structure
for reasoning. It is concluded that the final choice of solution must be based on a carefully consideration
of the trade-off between complexity and expressiveness, and that a natural continuation is testing the
suggested concepts with real data.
Place, publisher, year, edition, pages
Institutt for datateknikk og informasjonsvitenskap , 2007. , 65 p.
ntnudaim:3490, MTDT datateknikk, Intelligente systemer
IdentifiersURN: urn:nbn:no:ntnu:diva-16746Local ID: ntnudaim:3490OAI: oai:DiVA.org:ntnu-16746DiVA: diva2:536424
Mollestad, Torulf, Førsteamanuensis II