Bureau of Economic Geology

Peer-Reviewed Publications - 2023

Other Years: 2023 2022 2021 2020 2019 2018 2017 2016 2015 2014 2013 2012 2011 2010 2009 2008 2007 2006 2005 2004 2003 2002 2001 2000

BEG Peer-reviewed Papers In Press

Avigyan Chatterjee, Igonin, N., and Trugman D., 2022, A real-time and data-driven ground motion prediction framework for earthquake early warning: Bulletin of the Seismological Society of America, http://doi.org/10.1785/0120220180.

Bhattacharya, S., Wisian, K., Savvaidis, A., and Eros, M., 2022, Integrated subsurface characterization of a low-temperature geothermal test site, Gulf Coast, Texas: Second International Meeting for Applied Geoscience & Energy© 2022 Society of Exploration Geophysicists and the American Association of Petroleum Geologists, 28 August - 2 September, 2022, Houston, TX, p. 2007–2011, http://doi.org/10.1190/image2022-3745410.1.

Bump, A., Bakhshian, S., Hovorka, S. D., and Joshua Rhodes, 2022, Criteria for Depleted Reservoirs to be Developed for CO2 Storage: IEAGHG.

Fu, Q., Peng, J., and Janson, X., 2022, Reply to comment on ‘‘Dynamic climatic changes during the late Pennsylvanian icehouse: new insight from high-resolution geochemical records in the Cline Shale, North America” by Peng, Fu and Janson: Gondwana Research, v. 109, p. 166–167, http://doi.org/10.1016/j.gr.2022.04.022.

Hopmans, J.W., Green, T.R., and Young, M. H., 2022, Western USA multistate research project on “water movement in soils” – a retrospective: Vadose zone journal, 7 p., http://doi.org/10.1002/vzj2.20245.

Hosseini, S. A., Hovorka, S. D., Savvaidis, A., Kavoura, F., and Nicot, J.-P., 2022, Current State of Knowledge Regarding the Risk of Induced Seismicity at CO2 Storage Projects: IEA GREENHOUSE GAS R&D PROGRAMME, no. 2022-02.

Jin, L., Curry, W., Zoback, M., Hussenoeder, S., Savvaidis, A., Nicot, J.-P., Hennings, P., and Bhargava, P., 2022, Rapid geomechanical analysis of injection-related earthquakes: Second International Meeting for Applied Geoscience & Energy © 2022 Society of Exploration Geophysicists and the American Association of Petroleum Geologists, 28 August - 2 September, 2022, Houston, TX, p. 1531–1535, http://doi.org/10.1190/image2022-3740083.1.

Jonathon Knapp, Larson, T., and Sivil, J. E., 2022, Subsurface Characterization for Energy Applications, in B Lee Drake, Brandi L MacDonald, Advances in Portable X-ray Fluorescence Spectrometry: Instrumentation, Application and Interpretation: Royal Society of Chemistry, p. 251 - 297, http://doi.org/10.1039/9781839162695.

Kyle, J. R., Stockli, D. F., McBride, E. F., and Elliott, B. A., 2022, Covering the Great Unconformity in southern Laurentia: detrital zircon studies of provenance evolution during Cambrian marine transgression (Llano Uplift, Texas): Geological Society of America Bulletin, 15 p., http://doi.org/10.1130/B36389.1, online publication info -- to be revised.

Larson, T., Loucks, R. G., Sivil, J. E., Hattori, K., and Zahm, C., 2022, Machine learning classification of Austin Chalk chemofacies from high-resolution X-ray fluorescence core characterization: AAPG Bulletin, http://doi.org/10.1306/09232220095.

Liu, L., Xu, J., Stockli, D.F., Lawton, T., and Blakey, R.C., 2022, Decoding post-orogenic sediment recycling and dispersal using detrital zircon core and rim ages: Basin Research, 21 p., http://doi.org/10.1111/bre.12719.

Peng, S., LaManna, J., Periwal, P., and Shevchenko, P., 2022, Water imbibition and oil recovery in shale: dynamics and mechanisms using integrated centimeter-to-nanometer-scale imaging: SPE Reservoir Evaluation & Engineering, no. SPE-210567-PA, http://doi.org/10.2118/210567-PA.

Peng, S., Shevchenko, P., and Ko, L. T., 2022, Shale wettability: untangling the elusive property with an integrated imbibition and imaging technique and a new hypothetical theory: SPE Reservoir Evaluation & Engineering, no. SPE-212276-PA, http://doi.org/10.2118/212276-PA.

Wisian, K., 2022, Geothermal Energy on Solar System Bodies: Journal of the British Interplanetary Society, v. 75, no. 9, p. 315–320.

BEG Peer-reviewed Papers

Chen, W., Oboué, Y. A. S. I., and Chen, Y., 2023, Retrieving useful signals from highly corrupted erratic noise using robust residual dictionary learning: Geophysics, v. 88, no. 1, p. WA55–WA64, http://doi.org/10.1190/geo2022-0168.1.

Chen, Y., Fomel, S., and Abma, R., 2023, Joint deblending and source time inversion: Geophysics, v. 88, no. 1, p. WA27–WA35, http://doi.org/10.1190/geo2022-0149.1.

Gale, J. F. W., Elliott, S.J., Rysak, B. G., and Laubach, S. E., 2023, The critical role of core in understanding hydraulic fracturing, in Neal, A., Ashton, M., Williams, L. S., Dee, S. J., Dodd, T. J. H. and Marshall, J. D., eds., Core values: the role of core in twenty-first century reservoir characterization: Geological Society of London, Special Publication, v. 527, no. 1, 16 p., http://doi.org/10.1144/SP527-2021-198.

Hosseini, S., Larson, R., Shokouhi, P., Kumar, V., Prathipati, S., Kifer, D., Garcez, J., Ayala, L., Reidl, M., Hill, B., and and three others, 2023, Reservoir modeling using fast predictive machine learning algorithms for geological carbon storage, in Mishra, S., ed., Machine learning applications in subsurface energy resource management: Boca Raton, Fla., CRC Press, p. 233-250, http://doi.org/10.1201/9781003207009-17.

Lee, J., and Lumley, D. E., 2023, Predicting shale mineralogical brittleness index from seismic and elastic property logs using interpretable deep learning: Journal of Petroleum Science and Engineering, v. 220, part A, no. 111231, 14 p., http://doi.org/10.1016/j.petrol.2022.111231.

Saad, O. M., Fomel, S., Abma, R., and Chen, Y., 2023, Unsupervised deep learning for 3D interpolation of highly incomplete data: Geophysics, v. 88, no. 1, p. WA189–WA200, http://doi.org/10.1190/GEO2022-0232.1.

Yang, L., Fomel, S., Wang, S., Chen, X., Chen, W., Saad, O., and Chen, Y., 2023, Denoising of distributed acoustic sensing data using supervised deep learning: Geophysics, v. 88, no. 1, p. WA91–WA104, http://doi.org/10.1190/geo2022-0138.1.

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