Consistent Integration of Drill-Stem Test Data into Reservoir Models on a Giant Field Offshore Norway
- Jon Sætrom (Resoptima AS) | Harald Selseng (Lundin Norway AS) | Alister MacDonald (Lundin Norway AS) | Tore Kjølseth (Lundin Norway AS) | Odd Kolbjørnsen (Lundin Norway AS)
- Document ID
- Society of Petroleum Engineers
- SPE Annual Technical Conference and Exhibition, 26-28 September, Dubai, UAE
- Publication Date
- Document Type
- Conference Paper
- 2016. Society of Petroleum Engineers
- 5.6 Formation Evaluation & Management, 1.10 Drilling Equipment, 1.10 Drilling Equipment, 5.6.3 Pressure Transient Testing, 5 Reservoir Desciption & Dynamics
- Ensemble based methods, Uncertainty Quantification, Drill-stem test, Reservoir modelling, History matching
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When considering the task of creating reservoir models for fields under development, dynamic data measurements often have limited impact compared with static (geophysical and geological) data. This is not necessarily true for the Johan Sverdrup field offshore Norway, where exceptional reservoir properties make the data from eight drill-stem tests (DSTs) particularly interesting. For this reason, it is important to utilize the information found in the collected static and dynamic data in a consistent manner, to improve the understanding of the reservoir. This is especially true for the Avaldsnes High area, located in the southeastern part of the Johan Sverdrup field, where the observed thickness is below the seismic resolution, and the DST data from four wells indicate permeabilities in the range of 20 to 80 Darcy, with an overlapping radius of investigation.
In this paper, we apply an ensemble-based approach to generate a large set of reservoir models for the Avaldsnes High area of the Johan Sverdrup field, all of which are plausible given the current observed static and dynamic data. We consider multiple modelling scenarios, introducing uncertainty in the sand thickness, facies (rock type) description and the permeability modelling. Unlike conventional pressure transient analysis (PTA), where we analyze the DSTs separately, and the non-uniqueness in the data interpretation is hard to address and quantify, this is not the case with the ensemble-based approach. Since we conduct the static and dynamic data conditioning simultaneously, we can consistently address possible ambiguities in interpreted permeabilities, thicknesses and flow barriers seen in the conventional PTA analysis. The study reveals that by conditioning the generated models to dynamic data we introduce clear spatial trends in both the sand thickness and permeability. In particular, we greatly reduce the potential downside with respect to the sand thickness in the Avaldsnes High area.
|File Size||32 MB||Number of Pages||18|
Houzé, O., Viturat, D., & Fjære, O. S. (2015). Dynamic Data Analysis. http://www.kappaeng.com/documents/flip/dda/index.html#84.