History matching by jointly perturbing local facies proportions and their spatial distribution: Application to a North Sea reservoir

Reservoir modeling and flow simulation are used to improve the understanding of complex flow behaviors in a reservoir and to predict future reservoir performance. History matching is an integral part of any reservoir modeling study when the reservoir has produced for some time. History matching is the process where properties in the reservoir model are changed until the production data from the model matches the field data. lti-parameter probability perturbation method is a robust history matching technique that was developed to allow large-scales properties to be efficiently perturbed. Perturbing probabilities rather than actual petrophysical properties guarantee that the conceptual geologic model is maintained and that any history matching related artifacts are avoided. Creating reservoir models that match all types of data are likely to have more prediction power than methods where some data are not honored. Previous work with the probability perturbation method however, has been limited to only the location of geologic bodies. The current work describes a new technique that also accounts for the proportion of bodies. The proportion of geologic bodies often varies significantly throughout the reservoir, and it is a parameter that is rarely known with any certainty. The current method couples the perturbation of the location and proportion of bodies so as to improve the efficiency of the method while continuing to honor the geologic information known about the reservoir. thod is first demonstrated on a synthetic example where facies locations and proportions are simultaneously perturbed. Perturbing both of these properties results in significantly faster history matched models than perturbing facies alone. This technique is further demonstrated on a North Sea hydrocarbon reservoir. In the reservoir, a number of lenticular calcite bodies with very low permeability significantly affect fluid flow; however, the location and proportion of the bodies are generally unknown. The local proportions and positions are stochastically modeled and perturbed to match 5 1/2 yr of historical flow rate data and RFT pressure data. The history matched reservoir models more accurately reproduce the field production data, and the reservoir description of the simulation model is more realistic.