Predicting Heavy Oil Production by Hybrid Data-Driven Intelligent Models

Table 6

Production association rule results of CSS.

Influence factor	Association rule	Confidence
Steam injection volume	forzenset({“101”})-->forzenset({“1”})	0.728
Steam injection pressure	forzenset({“101”})-->forzenset({“5”})	0.512
Steam injection temperature	forzenset({“101”})-->forzenset({“10”})	0.382
Steam injection dryness	forzenset({“101”})-->forzenset({“13”})	0.583
Round of CSS	forzenset({“101”})-->forzenset({“20”})	0.628
Cycle of CSS	forzenset({“101”})-->forzenset({“22”})	0.457
Crude oil viscosity	forzenset({“101”})-->forzenset({“28”})	0.493
Soaking time	forzenset({“101”})-->forzenset({“29”})	0.378
Oil well opening times	forzenset({“101”})-->forzenset({“33”})	0.697
Oil saturation	forzenset({“101”})-->forzenset({“37”})	0.483
Permeability	forzenset({“101”})-->forzenset({“41”})	0.498
Porosity	forzenset({“101”})-->forzenset({“45”})	0.447
Reservoir temperature	forzenset({“101”})-->forzenset({“49”})	0.323
Reservoir pressure	forzenset({“101”})-->forzenset({“53”})	0.428
Reservoir thickness	forzenset({“101”})-->forzenset({“57”})	0.497