Characterization and Evaluation Method of Streamline Field in High Water Cut Reservoir

doi:10.11885/j.issn.1674-5086.2020.10.22.02

Abstract

Abstract: By extracting the spatial coordinates and attribute data of particles in streamline field obtained through numerical simulation, we established a characterization method of streamline field with streamline cluster flow rate, streamline cluster potential and streamline cluster oil content. The streamline field is classified and evaluated by density peak algorithm, and the clustering effect of streamline classification is verified by S_Dbw coefficient. Finally the method of quantitative characterization and evaluation of streamline field in high water cut reservoir is formed. The results show that the three parameters can better reflect the distribution relationship and size of flow rate and potential between injection and production wells than conventional methods. Streamline strength grades in different regions can be quantitatively determined by clustering and grading of characterization parameters. The method is applied to an actual block in an eastern oilfield. The whole streamline field is divided into 14 types. The displacement intensity of each region is quite different. Through streamline field reconstruction, the streamline field grade are adjusted from 14 types to 7 types, the flow heterogeneity is weakened, and the reservoir productivity is improved obviously.

Key words: density peak algorithm, machine learning, streamline field, equilibrium displacement, streamline cluster

CLC Number:

TE345

LIU Chaoyang, GUO Qi, LI Gang, HUANG Bo, WANG Zhenyu. Characterization and Evaluation Method of Streamline Field in High Water Cut Reservoir[J]. Journal of Southwest Petroleum University(Science & Technology Edition), 2023, 45(1): 89-96.

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URL: http://journal15.magtechjournal.com/Jwk_xnzk/EN/10.11885/j.issn.1674-5086.2020.10.22.02

http://journal15.magtechjournal.com/Jwk_xnzk/EN/Y2023/V45/I1/89

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