Forecasting Incremental Oil Production of a Polymer Pilot Extension in the Matzen Field Including Quantitative Uncertainty Assessment
- Maria-Magdalena Chiotoroiu (OMV) | Joerg Peisker (OMV) | Torsten Clemens (OMV) | Marco R. Thiele (Streamsim Technologies/Stanford University)
- Document ID
- Society of Petroleum Engineers
- SPE Improved Oil Recovery Conference, 11-13 April, Tulsa, Oklahoma, USA
- Publication Date
- Document Type
- Conference Paper
- 2016. Society of Petroleum Engineers
- 5.6 Formation Evaluation & Management, 5.1.5 Geologic Modeling, 2.1 Completion Operations, 5.4 Enhanced Recovery, 5 Reservoir Desciption & Dynamics, 3 Production and Well Operations, 2.1.3 Sand/Solids Control, 2 Well completion, 1.6.10 Coring, Fishing, 5.6.5 Tracers, 1.6 Drilling Operations, 5.3.6 Chemical Flooding Methods (e.g., Polymer, Solvent, Nitrogen, Immiscible CO2, Surfactant, Vapex)
- pilot test, extension planing, forecasting, polymer flooding, uncertainty assessment
- 3 in the last 30 days
- 235 since 2007
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The polymer pilot project performed in the 8 TH reservoir of the Matzen field showed encouraging incremental oil production. To further improve the understanding of recovery effects resulting from polymer injection, an extension of the pilot is planned by adding a second polymer injector.
Forecasting of the incremental oil production needs to take the uncertainty of the geological models and dynamic parameters into account. We propose a workflow which comprises a geological sensitivity and clustering step followed by a dynamic calibration step for decreasing the objective function to improve the reliability of a probabilistic forecast of the incremental oil recovery.
For the geological sensitivity, hundreds of geological realizations were generated taking the uncertainty in the correlation of the sand and shale layers, logs, cores and geological facies into account. The simulated tracer response was used as dissimilarity distance to classify the geological realizations. Clustering was then applied to select 70 representative realizations (centroids) from a total of 800 to use in the full-physics dynamic simulation.
In the dynamic simulation, an objective function comprising liquid rate and tracer concentration of the back-produced fluids was introduced.
To further improve the calibration, the P50 value of incremental oil production as derived from simulation was compared with the incremental oil production determined from Decline Curve Analysis from the wells surrounding the polymer injection well. The mismatch between the P50 and the Decline Curve Analysis was improved by adjusting polymer viscosity.
The calibrated models were then used to for a probabilistic forecast of incremental oil due to an additional polymer injector and to estimate the expected polymer concentration at the producing wells.
|File Size||3 MB||Number of Pages||16|
Bianco, A.; Cominelli, A.; Dovera, L.; Naevdal. G. and Valles, B. 2007. History Matching and Production Forecast Uncertainty by Means of Ensemble Kalman Filter: A Real Field Application. Paper SPE 107161 presented at the SPE Europec/EAGE Annual Conference and Exhibition. London. United Kingdom. 11–14 June 2007.
Laoroongroj, A.; Gumpenberger, T. and Clemens, T. 2014. Polymer Flood Incremental Oil Recovery and Efficiency in Layered Reservoirs Including Non-Newtonian and Viscoelastic Effects. Paper SPE 170657 presented at the SPE Annual Technical Conference and Exhibition. Amsterdam. Netherlands. 27–29 October 2014.