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Emission Reduction in Oil & Gas Subsurface Characterization Workflow with AI/ML Enabler

Thanh Thuy Nguyen Thi, Lee Samie, Nguyen The, Duyen Le Quang

Inżynieria Mineralna

2023

no. 2, vol. 1

289--294

According to (McKinsey & Company, 2020), drilling and extraction operations are responsible for 10% of approximately 4 billion tons of CO2 emitted yearly by Oil and Gas sector. To lower carbon emissions, companies used different strategies including electrifying equipment, changing power sources, rebalancing portfolios, and expanding carbon-capture-utilization-storage (CCUS). Technology evolution with digital transformation strategy is essential for reinventing and optimizing existing workflow, reducing lengthy processes and driving efficiency for sustainable operations. Details subsurface studies take up-to 6–12 months, including seismic & static analysis, reserve estimation and simulation to support drilling and extraction operations. Manual and repetitive processes, aging infrastructure with limited computing-engine are factors for long computation hours. To address subsurface complexity, hundred-thousand scenarios are simulated that lead to tremendous power consumption. Excluding additional simulation hours, each workstation uses 24k kWh/month for regular 40 hours/month and produces 6.1kg CO2. Machine Learning (ML) become crucial in digital transformation, not only saving time but supporting wiser decision-making. An 80%-time-reduction with ML Seismic and Static modeling deployed in a reservoir study. Significant time reduction from days-tohours-to-minutes with cloud-computing deployed to simulate hundreds-thousands of scenarios. These time savings help to reduce CO2-emissions resulting in a more sustainable subsurface workflow to support the 2050 goal.

Building a new “hospital governance” model based on the made in Vietnam lean management philosophy through the practice of the Covid-19 pandemic

Tien Thanh Nguyen, Dang Minh Nguyen, Thanh Thuy Nguyen Thi

Annals of Computer Science and Information Systems

2022

Vol. 34

221--226

Research and propose a new model of ``Hospital governance'' based on The Made in Vietnam lean management philosophy a model is written based on recent research on practical activities in Vietnamese hospitals. The studied model has been effectively applied in some hospitals in Vietnam and provides the application process and some conditions for successful implementation. The model can be extended to domestic and international hospitals, including developed and developing countries.