Distributed Database for Scaling Up Real-time EDR Data Processing

Abstract This paper presents a novel distributed database architecture that supports a large-scale rig digital twin solution by processing over 1-Billion real-time Electronic Drilling Recorder (EDR) data points and 50-Million database queries per day. This novel architecture significantly improves scalability, performance and fault tolerance while reducing compute cost when compared to conventional monolithic database architecture for real-time, high data volume applications.

Authors

R.McL. Whitney
Alice Wang (ORCID: https://orcid.org/0000-0001-8827-3780)
P. Acosta

Publication Details

Published: 2025-04-14
DOI: https://doi.org/10.2118/224359-ms
Citations: 2
Primary Topic: Structural Health Monitoring Techniques
Type: article
Field-Weighted Citation Impact: 1.91

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article

Distributed Database for Scaling Up Real-time EDR Data Processing

R.McL. Whitney, Alice Wang, P. Acosta

Apr 14, 2025

2 citations

Structural Health Monitoring Techniques

1.91

article

Distributed Database for Scaling Up Real-time EDR Data Processing

R.McL. Whitney, Alice Wang, P. Acosta

April 14, 2025article en

2 citations

Abstract

Openalex Percentile: Top 16%

Structural Health Monitoring Techniques

1.91

DOI Source OpenAlex

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Distributed Database for Scaling Up Real-time EDR Data Processing — R.McL. Whitney, Alice Wang, et al. · (2025) | TGRS Research Map | TGRS