Emissions tracking in well construction using distributed ledger technology and numerical models

Well construction in the oil and gas industry generates substantial emissions, necessitating precise tracking to meet environmental regulations and sustainability targets. This paper explores an innovative approach combining numerical modeling with distributed ledger technology (DLT) to monitor and manage emissions throughout the well construction process. Unlike traditional methods, which often rely on retrospective data collection, this method leverages real-time simulations and a decentralized data framework to provide actionable insights. By focusing on predictive modeling and data integration, we propose a system that enhances emissions accountability and supports operational efficiency. Case studies demonstrate its practical application, while the discussion addresses implementation challenges and future potential.

Authors

Publication Details

Journal
International Journal of Science and Research Archive
Published
2025-06-27
DOI
https://doi.org/10.30574/ijsra.2025.15.3.1074
Primary Topic
Reservoir Engineering and Simulation Methods
Type
article
Field-Weighted Citation Impact
0.00
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article

Emissions tracking in well construction using distributed ledger technology and numerical models

Muhammad Ahsan
International Journal of Science and Research Archive
Reservoir Engineering and Simulation Methods
article

Emissions tracking in well construction using distributed ledger technology and numerical models

Muhammad Ahsan
article en

Abstract

Well construction in the oil and gas industry generates substantial emissions, necessitating precise tracking to meet environmental regulations and sustainability targets. This paper explores an innovative approach combining numerical modeling with distributed ledger technology (DLT) to monitor and manage emissions throughout the well construction process. Unlike traditional methods, which often rely on retrospective data collection, this method leverages real-time simulations and a decentralized data framework to provide actionable insights. By focusing on predictive modeling and data integration, we propose a system that enhances emissions accountability and supports operational efficiency. Case studies demonstrate its practical application, while the discussion addresses implementation challenges and future potential.

International Journal of Science and Research ArchiveVol. 15(3)
Openalex Percentile: Top 82%
Reservoir Engineering and Simulation Methods
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