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Assisted History Matching and Uncertainty Analysis Workflow for a Large Oilfield in Middle East

Authors
Ahmed Ismail (ADNOC ONSHORE) | Yasser Hazem (ADNOC ONSHORE) | Mazna Naji Al Obaidi (ADNOC ONSHORE) | Kirill Bogachev (Rock Flow Dynamics) | Evgenii Gusarov (Rock Flow Dynamics) | Konstantin Shelepov (Rock Flow Dynamics) | Maksim Kuzevanov (Rock Flow Dynamics)
DOI
https://doi.org/10.2118/196729-MS
Document ID
SPE-196729-MS
Publisher
Society of Petroleum Engineers
Source
SPE Reservoir Characterisation and Simulation Conference and Exhibition, 17-19 September, Abu Dhabi, UAE
Publication Date
2019
Document Type
Conference Paper
Language
English
ISBN
978-1-61399-669-0
Copyright
2019. Society of Petroleum Engineers
Keywords
Middle East, Assisted History Matching, Carbonate Reservoir, Large, Uncertainty Analysis
Downloads
14 in the last 30 days
100 since 2007
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Abstract

This paper proposes an assisted history matching (AHM) and uncertainty analysis workflow that was applied to facilitate the history matching of a giant carbonate reservoir in Middle East. The objective was to identify and quantify reservoir uncertainties and assess their impact on the field performance. In addition, to create a sufficient number of realizations to allow combinations of all uncertainties to capture a combined effect.

A real field case is represented by a consistent workflow that iteratively updates the ranges and number of reservoir uncertainties constrained by the actual measurements. The process has the following steps: definition of global uncertainty, sensitivity analysis, exclusion of less influential parameters, experimental design, revision of uncertainty matrix, and run optimization algorithms. The approach was firstly implemented at a global level and then continued to a regional level. The primary objective function is consisted of oil and water production mismatches, and the plan is to upgrade the objective function to include more parameters for further model HM enhancements.

Initially, the workflow was based on five uncertainty parameters. Ten sensitivity analysis cases were performed and tornado chart analysis suggested excluding some parameters that have less impact on the match quality, hence the objective function. Next, experimental design using Latin Hypercube was performed which allows seeing a combined effect of uncertainty parameters. During several experimental design iterations, the uncertainty parameter matrix was revised and a total number of uncertainty parameters was increased from 5 to 17. Finally, a total number of 260 experimental cases were completed, however, no good history match case was obtained. Therefore, a transition from the global level to a regional level was performed. The most sensitive identified uncertainties at global level were absolute permeability, vertical permeability anisotropy, pore volume and fault transmissibility. At the regional level, additional permeability multipliers for well regions were added to the uncertainty matrix. After that, a good quality matched cases were obtained.

Field scale and complexity were the main drive to implement AHM workflow. In a giant carbonate reservoir with long history and complex geology, a classical history matching method with unique solution cannot assure an accurate model predictability. The key advantages of this approach were the facilitating of the HM process and reducing of the total calculation time.

File Size  1 MBNumber of Pages   11

Jorn Van Doren, SPE, Gijs van Essen, SPE, Shell Global Solutions International B.V., Ove Wilson, Ellen Zijlstra, Petroleum Development Oman. A Comprehensive Workflow for Assisted History Matching Applied to a Complex Mature Reservoir.

Miroslav Budilin, Aliia Nurullina, Andrey Koryuzlov, Repsol; Anton Muryzhnikov, llya Smrnov, Dmitry Eydinov, Rock Flow Dynamics. Integrated Uncertainty Quantification for Development Planning of a Large Field.

Boxiao, Chevron Energy Technology; Eric W. Bhark, Chevron Asia Pacific E&P; Stephen J. Gross(ret.), Travis C. Billiter, and Kaveh Dehghani, Chevron Energy Technology. Best Practices of Assisted History Matching Using Design of Experiments.

A. M. Al-Samhan, Kuwait Oil Compnay; O. M. Gurpinar, M. Ansairzadeh, J. T. Wang, J. O. Moreno, Schluberger, M. R. Banagale, Kuait Oil Company. Challenges and Solutions of history Matching a Giant Reservoir Model: An Example from the Greater Burgan Field, Kuwait.

Van Doren J., Van Essen G., Wilson O.B. 2012. A Comprehensive Workflow for Assisted History Matching Applied to a Complex Mature Reservoir, SPE-154383-MS

Budilin M., Nurullina A., Koryuzlov A., Aldana W., Bernuzzi N., Arnez R., Muryzhnikov A., Smirnov I., Eydinov D. 2016. Integrated Uncertainty Quantification for Development Planning of a Large Field, SPE-182008-MS

Shelepov K., Struchkov I., Poltoranin V., Trusova A., Chashchin M., Kuzevanov M., Buchinskiy S., SPE-191572-18RPTC-MS. Reservoir Development Aspects and Surface Facilities Design of Gas Condensate Fields with Oil Rims.

Kathrada M. 2009. Uncertainty Evaluation of Reservoir Simulation Models Using Particle Swarms and Hierarchical Clustering, doctoral dissertation, Heriot-Watt University

Mohamed L., Christie M.A., Demyanov V. 2010. Reservoir Model History Matching with Particle Swarms: Variants Study, SPE-129152-MS.

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