Session 16. Oral Presentation for: Reservoir simulation using multi-variate machine learning techniques

Presented on 20 May 2026: Session 16 Novel use of statistical and machine learning techniques in this study show that improved reservoir simulation results, history matched production and reserve estimates can be improved by integrating all available reservoir simulation, infill log and 4D seismic data. This can be set-up for real-time analysis without waiting for many iterations of the inputs (e.g. rigorous re-processing and inversion of the 4D seismic) with manual reservoir simulations. The key is these multi-variate techniques can integrate all data simultaneously in 3D to mimic the many steps of manual calibration. To access the Oral Presentation click ‘Supplementary data’ below. To read the full paper click here

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Publication Details

Journal
Australian Energy Producers journal.
Published
2026-06-18
DOI
https://doi.org/10.1071/ep26469
Primary Topic
Reservoir Engineering and Simulation Methods
Type
article
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Session 16. Oral Presentation for: Reservoir simulation using multi-variate machine learning techniques

Jones K. Ebinesan
Australian Energy Producers journal.
Reservoir Engineering and Simulation Methods
article

Session 16. Oral Presentation for: Reservoir simulation using multi-variate machine learning techniques

Jones K. Ebinesan
article en

Abstract

Presented on 20 May 2026: Session 16 Novel use of statistical and machine learning techniques in this study show that improved reservoir simulation results, history matched production and reserve estimates can be improved by integrating all available reservoir simulation, infill log and 4D seismic data. This can be set-up for real-time analysis without waiting for many iterations of the inputs (e.g. rigorous re-processing and inversion of the 4D seismic) with manual reservoir simulations. The key is these multi-variate techniques can integrate all data simultaneously in 3D to mimic the many steps of manual calibration. To access the Oral Presentation click ‘Supplementary data’ below. To read the full paper click here

Australian Energy Producers journal.Vol. 66(S2)
Curtin University (AU)
Openalex Percentile: Top 8%
Reservoir Engineering and Simulation Methods
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