Joint History Matching of Multiple Types of Field Data in a 3D Field-Scale Case Study

William Chalub Cruz (), Xiaodong Luo and Kurt Rachares Petvipusit
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William Chalub Cruz: University of Stavanger, 4021 Stavanger, Norway
Xiaodong Luo: Norwegian Research Centre (NORCE), 5008 Bergen, Norway
Kurt Rachares Petvipusit: Equinor, 5254 Bergen, Norway

Energies, 2022, vol. 15, issue 17, 1-22

Abstract: This work presents an ensemble-based workflow to simultaneously assimilate multiple types of field data in a proper and consistent manner. The aim of using multiple field datasets is to improve the reliability of estimated reservoir models and avoid the underestimation of uncertainties. The proposed framework is based on an integrated history matching workflow, in which reservoir models are conditioned simultaneously on production, tracer and 4D seismic data with the help of three advanced techniques: adaptive localization (for better uncertainty quantification), weight adjustment (for balancing the influence of different types of field data), and sparse data representation (for handling big datasets). The integrated workflow is successfully implemented and tested in a 3D benchmark case with a set of comparison studies (with and without tracer data). The findings of this study indicate that joint history matching using production, tracer and 4D seismic data results in better estimated reservoir models and improved forecast performance. Moreover, the integrated workflow is flexible, and can be extended to incorporate more types of field data for further performance improvement. As such, the findings of this study can help to achieve a better understanding of the impacts of multiple datasets on history matching performance, and the proposed integrated workflow could serve as a useful tool for real field case studies in general.

Keywords: joint history matching; iterative ensemble smoother; production, tracer and 4D seismic data (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
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