Progress of Gas Injection EOR Surveillance in the Bakken Unconventional Play—Technical Review and Machine Learning Study

Jin Zhao, Lu Jin (), Xue Yu, Nicholas A. Azzolina, Xincheng Wan, Steven A. Smith, Nicholas W. Bosshart, James A. Sorensen and Kegang Ling
Additional contact information
Jin Zhao: Energy & Environmental Research Center, University of North Dakota, Grand Forks, ND 58202, USA
Lu Jin: Energy & Environmental Research Center, University of North Dakota, Grand Forks, ND 58202, USA
Xue Yu: Energy & Environmental Research Center, University of North Dakota, Grand Forks, ND 58202, USA
Nicholas A. Azzolina: Energy & Environmental Research Center, University of North Dakota, Grand Forks, ND 58202, USA
Xincheng Wan: Energy & Environmental Research Center, University of North Dakota, Grand Forks, ND 58202, USA
Steven A. Smith: Energy & Environmental Research Center, University of North Dakota, Grand Forks, ND 58202, USA
Nicholas W. Bosshart: Energy & Environmental Research Center, University of North Dakota, Grand Forks, ND 58202, USA
James A. Sorensen: Energy & Environmental Research Center, University of North Dakota, Grand Forks, ND 58202, USA
Kegang Ling: Department of Energy and Petroleum Engineering, University of North Dakota, Grand Forks, ND 58202, USA

Energies, 2024, vol. 17, issue 17, 1-32

Abstract: Although considerable laboratory and modeling activities were performed to investigate the enhanced oil recovery (EOR) mechanisms and potential in unconventional reservoirs, only limited research has been reported to investigate actual EOR implementations and their surveillance in fields. Eleven EOR pilot tests that used CO 2 , rich gas, surfactant, water, etc., have been conducted in the Bakken unconventional play since 2008. Gas injection was involved in eight of these pilots with huff ‘n’ puff, flooding, and injectivity operations. Surveillance data, including daily production/injection rates, bottomhole injection pressure, gas composition, well logs, and tracer testing, were collected from these tests to generate time-series plots or analytics that can inform operators of downhole conditions. A technical review showed that pressure buildup, conformance issues, and timely gas breakthrough detection were some of the main challenges because of the interconnected fractures between injection and offset wells. The latest operation of co-injecting gas, water, and surfactant through the same injection well showed that these challenges could be mitigated by careful EOR design and continuous reservoir monitoring. Reservoir simulation and machine learning were then conducted for operators to rapidly predict EOR performance and take control actions to improve EOR outcomes in unconventional reservoirs.

Keywords: unconventional reservoirs; Bakken; enhanced oil recovery; EOR surveillance; gas injection; technical review; pilot tests; machine learning (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: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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