Using of Machine Learning Algorithms for Development Analysis of a Brown oil Field Located in The Basement Rocks

M.V. Naugolnov; A.V. Antropov; J. Arsić

doi:10.3997/2214-4609.202156022

Using of Machine Learning Algorithms for Development Analysis of a Brown oil Field Located in The Basement Rocks
Authors M.V. Naugolnov¹, A.V. Antropov¹, J. Arsić¹
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Affiliations: ¹ NTC NIS-Naftagas
Publisher: European Association of Geoscientists & Engineers
Source: Conference Proceedings, Data Science in Oil and Gas 2021, Aug 2021, Volume 2021, p.1 - 5
DOI: https://doi.org/10.3997/2214-4609.202156022

Abstract

Summary

The purpose of the work is a new approach to the development analysis of brown oil field, that is located in basement rocks. Analysis is done for the tasks of the future implementation of the pressure maintenance system with the usage of advanced analytics tools and machine learning algorithms. The solution is based on the integration of well performance data and field studies, as well as on the study of the mutual influence of wells as a factor characterizing the fracture throughput, wells clasterisation and production forecast.

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2021-08-04

2024-04-20

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References

Belaidi, A., Bonter, D. A., Slightam, C., Trice, R. C.
1.Belaidi, A., Bonter, D. A., Slightam, C., Trice, R. C. (2016). The Lancaster Field: Progress in opening the UK’s fractured basement play.– Proceedings of the 8th Petroleum Geology Conference: Geological Society, London, Petroleum Geology Conference Series. Vol. 8; 385–398. http://doi.org/10.1144/PGC8.20
[Google Scholar]
ArtemPolivakho, MileDragosavac et al.
2.ArtemPolivakho, MileDragosavac et al. A Comprehensive Approach to Basement Fractured Reservoir Development in the Pannonian Basin: Case Study. SPE-187779-MS. https://doi.org/10.2118/187779-MS

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Using of Machine Learning Algorithms for Development Analysis of a Brown oil Field Located in The Basement Rocks

Conference Proceedings 2021, 1 (2021); https://doi.org/10.3997/2214-4609.202156022

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Using of Machine Learning Algorithms for Development Analysis of a Brown oil Field Located in The Basement Rocks

Abstract

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Most Cited This Month Most Cited RSS feed

The natural combination of full and image‐based waveform inversion

Poststack diffraction imaging using reverse‐time migration

Characterizing the effect of elastic interactions on the effective elastic properties of porous, cracked rocks

Fracture detection by Gaussian beam imaging of seismic data and image spectrum analysis

Laboratory measurements of guided‐wave propagation within a fluid‐saturated fracture