History Matching of Object-Based Stochastic Reservoir Models
- Lin Y. Hu (Institut Francais du Petrole IFP) | Sandra Jenni (Institut Francais du Petrole IFP)
- Document ID
- Society of Petroleum Engineers
- SPE Journal
- Publication Date
- September 2005
- Document Type
- Journal Paper
- 312 - 323
- 2005. Society of Petroleum Engineers
- 5.1.2 Faults and Fracture Characterisation, 3.3.6 Integrated Modeling, 4.1.5 Processing Equipment, 5.1.1 Exploration, Development, Structural Geology, 5.1 Reservoir Characterisation, 5.6.4 Drillstem/Well Testing, 4.3.4 Scale, 5.5.8 History Matching, 5.1.5 Geologic Modeling, 5.8.6 Naturally Fractured Reservoir, 4.1.2 Separation and Treating
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This paper first reviews the basic concepts of the widely used object-basedBoolean model for modeling heterogeneous reservoirs. Then, we present amethodology for calibrating Boolean simulations to dynamic production data.This methodology is based on a generalization of the gradual deformation methodthat was initially developed for calibrating pixel-based Gaussian-relatedreservoir models to dynamic data. Finally, two examples are presented and theresults show the validity of the previously mentioned methodology. Inparticular, this methodology is potentially applicable to history matching offaulted and fractured reservoir models.
In the last 2 decades, different stochastic models have been developed fordescribing reservoir heterogeneities of different depositional environments andat different scales. These models can be classified in three types: pixel-basedmodels (e.g., Gaussian-related stochastic models), object-based models (e.g.,Boolean models), and process-based models. Pixel-based models are relativelyeasy to be constrained by quantitative data, but they are often unable todescribe complex geological features, particularly at the field-appraisal stagewith few well data. On the contrary, process-based models can reproduce complexgeological features, but they are highly difficult to constrain by quantitativedata. In the case in which geological objects can be clearly identified(fractures, faults, channels, and vacuoles), object-based models can be a goodcompromise between pixel-based and process-based models. There are manyexamples of geological modeling of fluvial-deltaic reservoirs using theobject-based approach.1-6 This approach is also used for representing fault andfracture networks.7,8 Fig. 1 shows an object-based model of fracture swarms andsubseismic faults in a reservoir field.
Constraining object-based reservoir models to dynamic production data is ofgreat importance for their application in reservoir engineering. During thelast decade, the research on this problem has been oriented to parameterizingindividually each object and then calibrating these parameters (together withall the other parameters) to production data.9-11 This approach cannot beeasily extended to field-scale models with multiple geological objects becauseof the large number of parameters and the difficulty for preserving the modelconsistency when changing these parameters.
|File Size||1 MB||Number of Pages||12|
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