Green AMDM: A Sustainable Asset Master Data Framework for Minimizing Redundant Data in a Carbon-Conscious Oil and Gas Industry

Enterprise Resource Planning (ERP) systems are essential in the oil and gas sector when managing complex and asset-heavy operations. Yet, inefficient Asset Master Data Management (AMDM), characterized by duplicated, inconsistent, and outdated records, limits business efficiency and undermines ESG reporting and carbon accountability. This article addresses these issues by proposing a Green AMDM model that integrates governance systems, sustainable practices, and fuzzy logic–based duplication identification and ESG score valuation. The mixed-method evaluation, using semi-structured interviews, structured complementary surveys, and an in-depth case study of PetroChina Southwest Oil and Gas Field (Block A), demonstrated the efficacy of the framework. The study shows that the proposed framework improves governance quality, removes duplicated asset data, improves the reliability of ESG reporting, and supports more precise CO2 tracking. The study integrates research and practical contributions by proposing a sustainable and AMDM model that is state-driven, scalable and adaptable across industries with significant assets.

Authors

Publication Details

Journal
International Journal For Multidisciplinary Research
Published
2025-09-16
DOI
https://doi.org/10.36948/ijfmr.2025.v07i05.55903
Primary Topic
Reservoir Engineering and Simulation Methods
Type
article
Field-Weighted Citation Impact
0.00
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article

Green AMDM: A Sustainable Asset Master Data Framework for Minimizing Redundant Data in a Carbon-Conscious Oil and Gas Industry

S. Rajendran
International Journal For Multidisciplinary Research
Reservoir Engineering and Simulation Methods
article

Green AMDM: A Sustainable Asset Master Data Framework for Minimizing Redundant Data in a Carbon-Conscious Oil and Gas Industry

S. Rajendran
article en

Abstract

Enterprise Resource Planning (ERP) systems are essential in the oil and gas sector when managing complex and asset-heavy operations. Yet, inefficient Asset Master Data Management (AMDM), characterized by duplicated, inconsistent, and outdated records, limits business efficiency and undermines ESG reporting and carbon accountability. This article addresses these issues by proposing a Green AMDM model that integrates governance systems, sustainable practices, and fuzzy logic–based duplication identification and ESG score valuation. The mixed-method evaluation, using semi-structured interviews, structured complementary surveys, and an in-depth case study of PetroChina Southwest Oil and Gas Field (Block A), demonstrated the efficacy of the framework. The study shows that the proposed framework improves governance quality, removes duplicated asset data, improves the reliability of ESG reporting, and supports more precise CO2 tracking. The study integrates research and practical contributions by proposing a sustainable and AMDM model that is state-driven, scalable and adaptable across industries with significant assets.

International Journal For Multidisciplinary ResearchVol. 7(5)
Openalex Percentile: Top 68%
Reservoir Engineering and Simulation Methods
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