Simultaneous assimilation of production and seismic data: application to the Norne field
Automatic history matching using production and seismic data is still challenging due to the size of seismic datasets. The most severe problem, when applying ensemble-based methods for assimilating large datasets, is that the uncertainty is usually underestimated due to the limited number of models in the ensemble compared with the dimension of the data, which inevitably leads to an ensemble collapse. Localization and data reduction methods are promising approaches mitigating this problem. In this paper, we present a new robust and flexible workflow for assimilating seismic attributes and production data. The methodology is based on sparse representation of the seismic data, using methods developed for image denoising. We propose to assimilate production and seismic data simultaneously, and to ensure equal weight on these data types, we apply scaling based on the initial data match. Further, a newly developed flexible correlation-based localization technique is used for both data types. The workflow is successfully implemented for the released Norne benchmark dataset, and an iterative ensemble smoother is used for the simultaneous assimilation of production and seismic data. We show that the methodology is robust and ensemble collapse is avoided. Furthermore, the proposed workflow is flexible, as it can be applied to seismic data or inverted seismic properties, and the methodology requires only moderate computer memory. The results show that through this method, we can successfully reduce the data mismatch for both production data and seismic data.
KeywordsHistory matching Norne field Seismic inversion Petro-elastic models Fluid flow Ensemble smoother Sparse representation
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The authors thank Equinor (operator of Norne field) and its license partners ENI and Petoro for the release of the Norne data. Further, the authors acknowledge the IOR Center for Integrated Operations at NTNU for cooperation and coordination of the Norne Cases. We also thank Schlumberger for providing academic software licenses to ECLIPSE and Petrel and CGG for providing an academic software license for HampsonRussell.
Finally, the authors acknowledge Ivar Sandø for very useful geophysical discussions.
The authors acknowledge financial support from the CIPR/ NORCE cooperative research project “4D Seismic History Matching” which is funded by industry partners Eni, Petrobras, and Total E&P NORGE, as well as the Research Council of Norway (PETROMAKS2). We also acknowledge the Research Council of Norway and the industry partners, ConocoPhillips Skandinavia AS, Aker BP ASA, Eni Norge AS, Total E&P Norge AS, Equinor ASA, Neptune Energy Norge AS, Lundin Norway AS, Halliburton AS, Schlumberger Norge AS, and Wintershall DEA, of The National IOR Centre of Norway for support.
The views expressed in this paper are the views of the authors and do not necessarily reflect the views of Equinor and the Norne license partners.
- 1.Abadpour, A., Bergey, P., Piasecki, R.: 4D seismic history matching with ensemble Kalman filter-assimilation on Hausdorff distance to saturation front. In: SPE Reservoir Simulation Symposium. Society of Petroleum Engineers. SPE-163635-MS (2013)Google Scholar
- 2.Aki, K., Richards, P.: Quantitative Seismology. Geology Seismology. University Science Books. https://books.google.no/books?id=pWhEPgAACAAJ (2002)
- 3.Alfonzo, M., Oliver, D., MacBeth, C.: Analysis and calibration of 4D seismic data prior to 4D seismic inversion and history matching-Norne field case. In: 79Th EAGE Conference and Exhibition 2017-Workshops (2017)Google Scholar
- 4.Bhakta, T.: Better Estimation of pressure-saturation changes from time-lapse PP-AVO data by using non-linear optimization method. In: SEG Technical Program Expanded Abstracts 2015, pp. 5456–5460. Society of Exploration Geophysicists (2015)Google Scholar
- 5.Bhakta, T., Avseth, P., Landrø, M.: Sensitivity analysis of effective fluid and rock bulk modulus due to changes in pore pressure, temperature and saturation. J. Appl. Geophys. 135, 77–89 (2016). https://doi.org/10.1016/j.jappgeo.2016.09.012. http://www.sciencedirect.com/science/article/pii/S092698511630266X. New trends in Induced PolarizationCrossRefGoogle Scholar
- 7.Bhakta, T., Luo, X., Nævdal, G.: Ensemble based 4D seismic history matching using a sparse representation of AVA data. In: SEG Technical Program Expanded Abstracts 2016, pp. 2961–2966. Society of Exploration Geophysicists (2016)Google Scholar
- 14.Emerick, A.A., Reynolds, A.C.: History-matching production and seismic data in a real field case using the ensemble smoother with multiple data assimilation. In: SPE Reservoir Simulation Symposium. Society of Petroleum Engineers. SPE-163675-MS (2013)Google Scholar
- 16.Fahimuddin, A., Aanonsen, S., Skjervheim, J.A.: Ensemble based 4D seismic history matching–integration of different levels and types of seismic data. In: 72Nd EAGE Conference & Exhibition (2010)Google Scholar
- 20.Gassmann, F.: ÜBer die Elastizität poröser Medien. Vierteljahresschrift Nat. Gesellschaft 96, 1–23 (1951)Google Scholar
- 21.Grana, D.: Bayesian inversion methods for seismic reservoir characterization and time-lapse studies. Ph.D. thesis, Stanford University (2013)Google Scholar
- 24.Huang, X., Meister, L., Workman, R., et al.: Reservoir characterization by integration of time-lapse seismic and production data. In: SPE Annual Technical Conference and Exhibition. Society of Petroleum Engineers (1997)Google Scholar
- 25.Huang, Y., Alsos, T., Sørensen, H.M., Tian, S.: Proving the value of 4D, seismic data in the late-life field–Case study of the Norne main field. First Break 31(9), 57–67 (2013)Google Scholar
- 26.IO Center/NTNU: Norne benchmark case. http://www.ipt.ntnu.no/∼norne/wiki/ (2019)
- 31.Lorentzen, R., Bhakta, T., Grana, D., Luo, X., Valestrand, R., Nævdal, G.: History matching of real production and seismic data in the Norne field. In: ECMOR XVI - 16th European Conference on the Mathematics of Oil Recovery. Barcelona, Spain. https://doi.org/10.3997/2214-4609.201802231 (2018)
- 32.Lorentzen, R.J.: Norne initial ensemble. https://github.com/rolfjl/Norne-Initial-Ensemble (2017)
- 37.Luo, X., Bhakta, T., Nævdal, G.: Correlation-based adaptive localization with applications to ensemble-based 4D seismic history matching. SPE J. 23(02). SPE-185936-PA (2018)
- 40.Mavko, G., Mukerji, T., Dvorkin, J.: The rock physics handbook: tools for seismic analysis of porous media. Cambridge University Press (2009)Google Scholar
- 42.Petrel seismic sampling. https://www.software.slb.com/products/petrel/petrel-geophysics/seismic-sampling (2019)
- 44.Russell, B.H.: Introduction to seismic inversion methods, vol. 2. Society of Exploration Geophysicists Tulsa (1988)Google Scholar
- 46.Sheriff, R., Geldart, L.: Exploration seismology. Cambridge University Press. https://books.google.no/books?id=k5-EQgAACAAJ (1995)
- 48.Stephen, K.D., Kazemi, A.: Improved normalization of time-lapse seismic data using normalized root mean square repeatability data to improve automatic production and seismic history matching in the Nelson field. Geophys. Prospect. 62(5), 1009–1027 (2014). https://doi.org/10.1111/1365-2478.12109 CrossRefGoogle Scholar
- 49.Stephen, K.D., Kazemi, A., Sedighi, F.: Assisted seismic history matching of the Nelson field: managing large numbers of unknowns by divide and conquer. In: EAGE Annual Conference & Exhibition incorporating SPE Europec. Copenhagen, Denmark. Paper SPE154892 (2012)Google Scholar
- 50.Tarantola, A.: Inverse problem theory and methods for model parameter estimation. SIAM (2005)Google Scholar
- 52.Zhang, Q., Chassagne, R., MacBeth, C.: 4D seismic and production history matching, a combined formulation using Hausdorff and FréChet metric. In: SPE Europec featured at 81st EAGE Conference and Exhibition. London, England. Paper SPE195542 (2019)Google Scholar