Method For Conditioning The Reservoir Model On 3D And 4D Elastic Inversion Data Applied To A Fluvial Reservoir In The North Sea
- Eli Zachariassen (Norsk Hydro) | Hilde Meisingset (Norsk Hydro) | Cecilie Otterlei (Norsk Hydro) | Trond Andersen (Norsk Hydro) | Kim Hatland (Hydro) | Trond Hoye (Hydro) | Gro Mangeroy (Hydro) | Frode Liestol (Hydro)
- Document ID
- Society of Petroleum Engineers
- SPE Europec/EAGE Annual Conference and Exhibition, 12-15 June, Vienna, Austria
- Publication Date
- Document Type
- Conference Paper
- 2006. Society of Petroleum Engineers
- 5.6.1 Open hole/cased hole log analysis, 1.6.9 Coring, Fishing, 5.5 Reservoir Simulation, 1.1 Well Planning, 2.2.2 Perforating, 2.4.3 Sand/Solids Control, 5.1.5 Geologic Modeling, 3.3.1 Production Logging, 5.1.9 Four-Dimensional and Four-Component Seismic, 5.1.8 Seismic Modelling, 5.4.2 Gas Injection Methods, 5.5.8 History Matching, 5.5.3 Scaling Methods, 1.2.3 Rock properties, 4.3.4 Scale, 5.1.7 Seismic Processing and Interpretation
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A work flow to improve the modeling of a fluvial reservoir is presented. Modeling of fluvial reservoirs can be very uncertain when only conditioned to well data. By utilising 3D and 4D seismic inversion data to condition the geological model, the uncertainty in the facies distribution is reduced. Cross plot of 3D elastic inversion data predicts facies better than acoustic impedance data or Vp/Vs data individually. By including 4D elastic inversion data, the correlation between the classified facies from seismic and the facies zonation in the wells, is further improved. A sand probability cube is computed from 3D and 4D elastic inversion data, and used to condition the geological model of the fluvial reservoir. Upscaling and flow simulation are carried out on a set of realisations. This results in a range of simulated production profiles. The dynamic information in the 4D seismic is then used to rank the realisations by comparing the real 4D data with forward modelled elastic parameters from the flow simulation model.
The described work flow is a new way of integrating different types of data in the modeling process in order to reduce uncertainties.The method is applied to the fluvial Ness reservoir in the Oseberg field in the North Sea.
Reservoir modeling and flow simulation contribute to reservoir management by predicting the reservoir response in term of production rates and total recovery. Stochastic models and simulations have been used to give a realistic image of the uncertainty in describing the hetereogeneities of the reservoir. A great challenge is to combine and utilize all available data: core and log data, outcrop studies, seismic data and production history, if available.
Traditional reservoir modelling utilizes well logs and, in some cases, 3D seismic data. More information can be extracted from the seismic by taking 4D data into account.
Cross plot of elastic parameters from a seismic inversion process can, in many cases, be used as input to lithology classification. Several publications have shown that it is possible to do litho-classification by cross plotting Acoustic impedance (AI) and the ratio between the compressional and the shear velocities (Vp/Vs) (Ødegaard and Avseth, 2004, Avseth et. al. 2005, Coléou et. al. 2005).
Cross plot of the changes in elastic parameters from 4D seismic can be used to classify 4D effects into saturation related or pressure related changes.
The proposed workflow is combining both 3D and 4D elastic inversion data to classify lithology. In the case of the 4D seismic, it is assumed that some of the observed production effects mainly can be related to sand facies only. By utilising this, it is possible to achieve a sand probability cube that has highest probabilities when both 3D and 4D seismic are utilised.
The workflow has been developed and tested for the fluvial Upper Ness reservoir unit in the Alfa Nord structure in the Oseberg Field. The Oseberg Field is located on a tilted fault block in the Horda Platform area, in the Norwegian North Sea sector, see Figure 1.
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