The PEXEL algorithm application for automated history matching reservoir simulation mode

UDK: 622.276.7
DOI: 10.24887/0028-2448-2022-9-49-52
Key words: reservoir simulation model, history matching, automated history matching, digital field, digital twin, permeability
Authors: A.N. Ivanov (Vietsovpetro JV, the Socialist Republic Vietnam, Vung Tau), F.S. Khismatullina (Gubkin University, RF, Moscow), A.R. Aubakirov (Vietsovpetro JV, the Socialist Republic Vietnam, Vung Tau), I.V. Kurguzkina (Vietsovpetro JV, the Socialist Republic Vietnam, Vung Tau)

History matching requires a significant portion of simulation model creation time, so updating the "digital twin" on a daily basis has to be associated with minimizing manual labor. In this regard, the transition to automated history matching software becomes imperative. Some of the currently available software for the history matching has proven to be a good solution and allows controlling many parameters. However, because of multifactorial solving the task and the associated complexity in analyzing the results these tools are not widely used. An alternative is the history matching parameters by separate modules (permeability matching, aquifer matching, SCAL matching, etc.) with a preliminary analysis of the reasons of the difference between the actual and calculated values.

This paper presents a relatively simple and effective history matching algorithm that allows well operation parameters to be adjusted to actual data by making modifications to the permeability array. Iteratively, for each well, a cross sectional production analysis is performed and multipliers are calculated for each perforated cell. After that, an interpolation/extrapolation procedure is performed to obtain multipliers for permeability array. This algorithm is formalized, developed as software and tested on sectoral and full-size simulation models. The methodology for testing the history matching algorithm is described and the results of its application are presented. The analysis of calculations results shows that the application of automated history matching of the permeability array, using the described algorithm, allows to replace manual editing with high accuracy and efficiency, while doing it methodologically well. At the moment, the full cycle of history matching has not been implemented. Currently, a program is being developed to aquifer matching, SCAL matching. The SCAL matching algorithm is implemented using machine learning. The purpose of this article is to demonstrate the practical application of the developed automated history matching algorithm on synthetic and full-size simulation models.



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