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Bulbul Ahmmed

Government of the United States of America - Los Alamos National Laboratory

Los Alamos, NM 87545

United States

  • Government of the United States of America - Los Alamos National Laboratory

SCHOLARLY PAPERS

5

DOWNLOADS

523

TOTAL CITATIONS

3

Scholarly Papers (5)

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1.

Risk Assessment for Accidental CO2 Pipeline Leakage in SimCCS

Published and presented at the 17th International Conference on Greenhouse Gas Control Technologies, GHGT-17, 20th -24th October 2024 Calgary, Canada , Proceedings of the 17th Greenhouse Gas Control Technologies Conference (GHGT-17) 20-24 October 2024
Number of pages: 12 Posted: 15 Nov 2024
Wenfeng Li, Bailian Chen, Zhiwei Ma, Bulbul Ahmmed, Mohamed Mehana and Rajesh Pawar
Government of the United States of America - Los Alamos National Laboratory, Government of the United States of America - Los Alamos National Laboratory, Government of the United States of America - Los Alamos National Laboratory, Government of the United States of America - Los Alamos National Laboratory, Government of the United States of America - Los Alamos National Laboratory and Los Alamos National Laboratory
Downloads 133 (565,439)
Citation 1

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CO2 pipeline transport, CO2 release, CO2 dispersion, Gaussian plume model, Estimated dispersion zone, SLAB model, SimCCS

2.

Feasibility of Offshore Geological CO2 Sequestration Projects: Evaluating the Impacts of Capture, Storage, and Transportation Costs

Proceedings of the 17th Greenhouse Gas Control Technologies Conference (GHGT-17) 20-24 October 2024
Number of pages: 7 Posted: 06 Jan 2025
Bulbul Ahmmed, Bailian Chen, Zhiwei Ma and Rajesh Pawar
Government of the United States of America - Los Alamos National Laboratory, Government of the United States of America - Los Alamos National Laboratory, Government of the United States of America - Los Alamos National Laboratory and Government of the United States of America - Los Alamos National Laboratory
Downloads 120 (613,149)

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CO2 sequestration, Offshore CO2 storage, pipeline transportation, CO2 infrastructure modeling

3.

Machine Learning and Shallow Groundwater Chemistry to Identify Geothermal Prospects in the Great Basin, USA

Number of pages: 26 Posted: 03 Apr 2022
Bulbul Ahmmed and Velimir V. Vesselinov
Government of the United States of America - Los Alamos National Laboratory and Carbon Solutions LLC
Downloads 118 (604,538)
Citation 1

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Geothermal, play fairway analysis, PFA, Great Basin, machine learning, NMFk

4.

Unified SimCCS Platform for Decision-Making in Carbon Capture, Transport, and Storage Infrastructure

Proceedings of the 17th Greenhouse Gas Control Technologies Conference (GHGT-17) 20-24 October 2024
Number of pages: 10 Posted: 25 Nov 2024
Bailian Chen, Zhiwei Ma, Bulbul Ahmmed, Quan Guo, Wenfeng Li, Mohamed Mehana, Meng Meng and Rajesh Pawar
Government of the United States of America - Los Alamos National Laboratory, Government of the United States of America - Los Alamos National Laboratory, Government of the United States of America - Los Alamos National Laboratory, Government of the United States of America - Los Alamos National Laboratory, Government of the United States of America - Los Alamos National Laboratory, Government of the United States of America - Los Alamos National Laboratory, Government of the United States of America - Los Alamos National Laboratory and Los Alamos National Laboratory
Downloads 89 (777,583)
Citation 1

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CO2 transport, SimCCS, optimization, decision support, global application

5.

Unsupervised Machine Learning and Magnetotellurics for Geothermal Play Development in the Tularosa Basin, New Mexico

Number of pages: 29 Posted: 25 May 2023
Elisabeth G. Rau, Bulbul Ahmmed, David Yeates, Stacy Atchley, Maruti Mudunuru and Luke Frash
affiliation not provided to SSRN, Government of the United States of America - Los Alamos National Laboratory, Baylor University, Baylor University, Government of the United States of America - Pacific Northwest National Laboratory and Government of the United States of America - Los Alamos National Laboratory
Downloads 63 (942,565)

Abstract:

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machine learning, geothermal resources, play development, magnetotellurics, MT