Peer-Reviewed Publications - 2022

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BEG Peer-reviewed Papers

Acevedo, J. P., Lemons, C. R., Young, M. H., McDaid, G., and Scanlon, B. R., 2022, Analysis of wastewater injection and prospect regions for induced seismicity in the Texas panhandle, United States: AAPG Bulletin, v. 106, no. 4, p. 679–699, http://doi.org/10.1306/EG.01072120005.

Ambrose, W. A., Hentz, T. F., and Smith, D. C., 2022, Facies variability and geologic controls on reservoir heterogeneity in deepwater slope reservoirs in the Pennsylvanian Cisco Group, Lake Trammel South field, Nolan County, Texas: Austin, Tex., The University of Texas at Austin, Bureau of Economic Geology, Report of Investigations, v. 288, 35 p., ISBN 978-1-970007-39-8, http://doi.org/10.23867/RI0288D.

Arciniega-Esparza, S., Hernández-Espriú, A., and Young, M. H., 2022, Implications of unconventional oil and gas development on groundwater resources: Current Opinion in Environmental Science and Health, v. 27, no. 100346, 9 p., http://doi.org/10.1016/j.coesh.2022.100346.

Bakhshian, S., Shariat, A., and Raza, A., 2022, Assessment of CO2 storage potential in reservoirs with residual gas using deep learning: Interpretation, v. 10, no. 3, p. SG11–SG20, http://doi.org/10.1190/INT-2021-0147.1.

Bhattacharya, S., 2022, Unsupervised time series clustering, class-based ensemble machine learning, and petrophysical modeling for predicting shear sonic wave slowness in heterogeneous rocks: Geophysics, v. 87, no. 5, p. D161–D174, http://doi.org/10.1190/geo2021-0478.1.

Bhattacharya, S., Ambrose, W., Ko, L. T., and Casey, B., 2022, Integrated detection and investigation of bad borehole section in the Wolfcamp Formation in the Midland Basin using machine learning, petrophysics, and core characterization: Interpretation, v. 10, no. 3, p. C19–C27, http://doi.org/10.1190/INT-2021-0165.1.

Bihani, A., Daigle, H., Santos, J. E., Landry, C., Prodanović, M., and Milliken, K., 2022, MudrockNet: semantic segmentation of mudrock SEM images through deep learning: Computers & Geosciences, v. 158, no. 104952, 10 p., http://doi.org/10.1016/j.cageo.2021.104952.

Bryndzia, L. T., Day-Stirrat, R. J., Hows, A. M., Nicot, J.-P., Nikitin, A., and Huvaz, O., 2022, A geochemical analysis of produced water(s) from the Wolfcamp formation in the Permian Delaware Basin, western Texas: AAPG Bulletin, v. 106, no. 6, p. 1265–1299, http://doi.org/10.1306/01282220180.

Bump, A., Bakhshian, S., Hovorka, S. D., and Rhodes, J., 2022, Criteria for depleted reservoirs to be developed for CO2 storage: Cheltenham, UK, IEA Environmental Projects Ltd., IEAGHG Technical Report, v. 2022-01, 114 p.

Buntin, R. C. C., Hasiotis, S. T., and Flaig, P. P., 2022, Evaluating the ichnofossil Teredolites as an indicator of salinity and paleoenvironment: Palaios, v. 37, no. 3, p. 53–72, http://doi.org/10.2110/palo.2020.074.

Burnham, B. S., Bond, C. E., Flaig, P. P., van der Kolk, D. A., and Hodgetts, D., 2022, Outcrop conservation: promoting accessibility, inclusivity, and reproducibility through digital preservation: The Sedimentary Record, v. 20, no. 1, p. 5–14, http://doi.org/10.2110/sedred.2022.1.2.

Burnham, B. S., Flaig, P. P., Brice, R. R., Spagnolo, M., and Young, M. H., 2022, Rapid sediment re-deposition may limit carbon release during catastrophic thermokarst lake drainage: GSA Today, v. 32, no. 5, p. 60–61, http://doi.org/10.1130/GSATG529GW.1.

Chen, W., Liu, X., Saad, O. M., Oboué, Y. A. S. I., Yang, L., Wang, H., and Chen, Y., 2022, 3-D seismic diffraction separation and imaging using the local rank-reduction method: IEEE Transactions on Geoscience and Remote Sensing, v. 60, no. 4507110, 10 p., http://doi.org/10.1109/TGRS.2021.3139314.

Chen, W., Saad, O. M., Oboué, Y. A. S. I., Yang, L., and Chen, Y., 2022, Retrieving the leaked signals from noise using a fast dictionary-learning method: Geophysics, v. 87, no. 1, p. V39–V49, http://doi.org/10.1190/GEO2021-0243.1.

Chen, W., Wang, H., Yang, L., Liu, X., and Chen, Y., 2022, Nonstationary local slope estimation via forward-backward space derivative calculation: Geophysics, v. 87, no. 1, p. N1–N11, http://doi.org/10.1190/GEO2021-0255.1.

Chen, Yangkang, Saad, O. M., Savvaidis, A., Chen, Yunfeng, and Fomel, S., 2022, 3D microseismic monitoring using machine learning: Journal of Geophysical Research: Solid Earth, v. 127, no. 3, article no. e2021JB023842, 27 p., http://doi.org/10.1029/2021JB023842.

Corrêa, R. S. M., Marrett, R., and Laubach, S. E., 2022, Analysis of spatial arrangement of fractures in two dimensions using point process statistics: Journal of Structural Geology, v. 163, no. 104726, 13 p., http://doi.org/10.1016/j.jsg.2022.104726.

Corrêa, R. S. M., Ukar, E., Laubach, S. E., Aubert, I., Lamarche, J., Wang, Q., Stockli, D. F., Stockli, L. D., and Larson, T. E., 2022, Episodic reactivation of carbonate fault zones with implications for permeability—an example from Provence, Southeast France: Marine and Petroleum Geology, v. 145, no. 105905, 21 p., http://doi.org/10.1016/j.marpetgeo.2022.105905.

Decker, L., and Fomel, S., 2022, A variational approach for picking optimal surfaces from semblance-like panels: Geophysics, v. 87, no. 3, p. U93–U108, http://doi.org/10.1190/geo2021-0336.1.

Delshad, M., Umurzakov, Y., Sepehrnoori, K., Eichhubl, P., and Batista Fernandes, B. R., 2022, Hydrogen storage assessment in depleted oil reservoir and saline aquifer: Energies, v. 15, no. 8132, 24 p., http://doi.org/10.3390/en15218132.

Dommisse, R., 2022, Influence of stratigraphic modeling scales on shale oil resources assessment of the Midland Basin: GCAGS Journal, GCAGS Journal, v. 11, p. 104–114.

Eastwood, R. L., and Smye, K. M., 2022, Effects of overpressure on mechanical properties of unconventional shale reservoirs through novel use of a sonic overpressure indicator: Society of Petroleum Engineers Reservoir Evaluation & Engineering, v. 25, no. 1, paper no. SPE-208571-PA, p. 52–60, http://doi.org/10.2118/208571-PA.

Elsayed, H. S., Saad, O. M., Soliman, M. S., Chen, Y., and Youness, H. A., 2022, Attention-based fully convolutional DenseNet for earthquake detection: IEEE Transactions on Geoscience and Remote Sensing, v. 60, no. 5918610, 10 p., http://doi.org/10.1109/TGRS.2022.3194196.

Ershadnia, R., Wallace, C. D., Hajirezaie, S., Hosseini, S. A., Nguyen, T. N., Sturmer, D. M., Dai, Z., and Soltanian, M. R., 2022, Hydro-thermo-chemo-mechanical modeling of carbon dioxide injection in fluvial heterogeneous aquifers: Chemical Engineering Journal, v. 431, no. 133451, 23 p., http://doi.org/10.1016/j.cej.2021.133451.

Ershadnia, R., Wallace, C. D., Hajirezaie, S., Hosseini, S. A., Nguyen, T. N., Sturmer, D. M., Dai, Z., and Soltanian, M. R., 2022, Hydro-thermo-chemo-mechanical modeling of carbon dioxide injection in fluvial heterogeneous aquifers: Chemical Engineering Journal, v. 431, no. 4, article no. 133451, 23 p., http://doi.org/10.1016/j.cej.2021.133451.

Flaig, P. P., Denison, C. N., Ambrose, W. A., and Demchuk, T. D., 2022, Outcrop evidence for variations in channel-floodplain facies and stratal architectures across the Simsboro to Calvert Bluff transition, Wilcox Group, Butler, Texas: GCAGS Journal, v. 11, p. 83–103.

Flinch, J. F., and Soto, J. I., 2022, Structure and Alpine tectonic evolution of a salt canopy in the western Betic Cordillera (Spain): Marine and Petroleum Geology, v. 143, no. 105782, 30 p., http://doi.org/10.1016/j.marpetgeo.2022.105782.

Forstner, S. R., and Laubach, S. E., 2022, Scale-dependent fracture networks: Journal of Structural Geology, v. 165, no. 104748, 21 p., http://doi.org/10.1016/j.jsg.2022.104748.

Fu, C., Gong, Z., Chen, L., Yang, S., Zhang, L., and Chen, Y., 2022, 3-D structural complexity-guided predictive filtering: a comparison between different non-stationary strategies: IEEE Transactions on Geoscience and Remote Sensing, v. 60, no. 5915415, 15 p., http://doi.org/10.1109/TGRS.2022.3172940.

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.

Gale, J. F. W., Fall, A., Yurchenko, I. A., Ali, W. A., Laubach, S. E., Eichhubl, P., and Bodnar, R. J., 2022, Opening-mode fracturing and cementation during hydrocarbon generation in shale: an example from the Barnett Shale, Delaware Basin, West Texas: AAPG Bulletin, v. 106, no. 10, p. 2103–2141, http://doi.org/10.1306/01062219274.

Ge, J., Nicot, J.-P., Hennings, P. H., Smye, K. M., Hosseini, S. A., Gao, R. S., and Breton, C. L., 2022, Recent water disposal and pore pressure evolution in the Delaware Mountain Group, Delaware Basin, Southeast New Mexico and West Texas, USA: Journal of Hydrology: Regional Studies, v. 40, no. 101041, 17 p., http://doi.org/10.1016/j.ejrh.2022.101041.

Geng, Z., Chen, Y., Fomel, S., and Liang, L., 2022, LOUD: local orthogonalization-constrained unsupervised deep-learning denoiser: IEEE Transactions on Geoscience and Remote Sensing, v. 60, no. 5924912, 12 p., http://doi.org/10.1109/TGRS.2022.3226404.

Geng, Z., Hu, Z., Wu, X., Liang, L., and Fomel, S., 2022, Semisupervised salt segmentation using mean teacher: Interpretation, v. 10, no. 3, p. SE21–SE29, http://doi.org/10.1190/INT-2021-0191.1.

Geng, Z., Zhao, Z., Shi, Y., Wu, X., Fomel, S., and Sen, M., 2022, Deep learning for velocity model building with common-image gather volumes: Geophysical Journal International, v. 228, no. 2, p. 1054–1070, http://doi.org/10.1093/gji/ggab385.

Han, S., Lӧhr, S. C., Abbott, A. N., Baldermann, A., Farkaš, J., McMahon, W., Milliken, K. L., Rafiei, M., Wheeler, C., and Owen, M., 2022, Earth system science applications of next-generation SEM-EDS automated mineral mapping: Frontiers in Earth Science, v. 10, no. 956912, 22 p., http://doi.org/10.3389/feart.2022.956912.

Horne, E. A., Hennings, P. H., Smye, K. M., Staniewicz, S., Chen, J., and Savvaidis, A., 2022, Structural characteristics of shallow faults in the Delaware Basin: Interpretation, v. 10, no. 4, p. T807–T835, http://doi.org/10.1190/INT-2022-0005.1.

Horne, E. A., Smye, K. M., and Hennings, P. H., 2022, Structure and characteristics of the basement in the Fort Worth Basin, in Callahan, O. A., and Eichhubl, P., eds., The geologic basement of Texas: a volume in honor of Peter T. Flawn: The University of Texas at Austin, Bureau of Economic Geology, Report of Investigations, v. 286, 30 p., http://doi.org/10.23867/RI0286C7.

Hosseini, S. A., Alfi, M., Nicot, J.-P., and Nuñez-López, V., 2022, Demonstration of de-facto CO2 storage at a CO2-EOR site, Cranfield, MS, in Gerdes, K. F., ed., Carbon dioxide capture for storage in deep geologic formations—results from the CO2 Capture Project: UK, Short Run Press Limited, v. 5, p. 473-526.

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: Cheltenham, UK, IEA Environmental Projects Ltd., IEAGHG Technical Report, v. 2022-02, 63 p.

Hovorka, S. D., 2022, Testing geophysical methods for assessing CO2 migration at the SECARB Early Test, Cranfield, Mississippi, USA, in Huang, L., ed., Geophysical monitoring for geologic carbon storage: American Geophysical Union and John Wiley & Sons [copublication], Geophysical Monograph, v. 272, p. 361-382, http://doi.org/10.1002/9781119156871.ch21.

Huang, D., Horne, E., Kavoura, F., and Savvaidis, A., 2022, Characteristics of seismogenic structures and 3D stress state of the Delaware Basin of West Texas as constrained by earthquake source mechanisms: Seismological Research Letters, v. 93, no. 6, p. 3363–3372, http://doi.org/10.1785/0220220054.

Huang, G., Chen, X., Saad, O. M., Chen, Yunfeng, Savvaidis, A., Fomel, S., and Chen, Yangkang, 2022, High-resolution and robust microseismic grouped imaging and grouping strategy analysis: Geophysical Prospecting, v. 70, no. 6, p. 980–1002, http://doi.org/10.1111/1365-2478.13216.

Hudec, M. R., and Jackson, M. P. A., 2022, Salt tectonics in deepwater settings, in Rotzien, J., Yeilding, C., Sears, R., Hernández-Molina, F. J., and Catuneanu, O., eds., Deepwater sedimentary systems—science, discovery, and applications: Amsterdam, Elsevier, p. 149-177.

Jin, L., Wojtanowicz, A. K., and Ge, J., 2022, Prediction of pressure increase during waste water injection to prevent seismic events: Energies, v. 15, no. 6, article no. 2101, 22 p., http://doi.org/10.3390/en15062101.

Juárez-Arriaga, E., Lawton, T. F., Solari, L. A., and Stockli, D. F., 2022, Stratigraphy and origin of Upper Cretaceous wedge-top and proximal foredeep deposits in the Mexican foreland basin, east-central Mexico: Journal of South American Earth Sciences, v. 114, no. https://doi.org/10.1016/j.jsames.2021.103681, 18 p., http://doi.org/10.1016/j.jsames.2021.103681.

Kaur, H., Zhong, Z., Sun, A., and Fomel, S., 2022, Time-lapse seismic data inversion for estimating reservoir parameters using deep learning: Interpretation, v. 10, no. 1, p. T167–T179, http://doi.org/10.1190/INT-2020-0205.1.

Knapp, J., Larson, T. E., and Sivil, J. E., 2022, Subsurface characterization for energy applications, in Drake, B. L., and MacDonald, B. L., eds., Advances in portable X-ray fluorescence spectrometry—instrumentation, application and interpretation: Croydon, UK, Royal Society of Chemistry, p. 251-297, http://doi.org/10.1039/9781839162695.

Lahiri, S., Milliken, K., Vrolijk, P., Desbois, G., and Urai, J. L., 2022, Mechanical compaction mechanisms in the input sediments of the Sumatra subduction complex – insights from microstructural analysis of cores from IODP Expedition 362: Solid Earth, v. 13, p. 1513–1539, http://doi.org/10.5194/se-13-1513-2022.

Lai, J., Wang, G., Fan, Q., Pang, X., Li, H., Zhao, F., Li, Y., Zhao, X., Zhao, Y., Huang, Y., Bao, M., Qin, Z., and Wang, Q., 2022, Geophysical well-log evaluation in the era of unconventional hydrocarbon resources: a review on current status and prospects: Surveys in Geophysics, v. 43, p. 913–957, http://doi.org/10.1007/s10712-022-09705-4.

Lancia, M., Yao, Y., Andrews, C. B., Wang, X., Kuang, X., Ni, J., Gorelick, S. M., Scanlon, B. R., Wang, Y., and Zheng, C., 2022, The China groundwater crisis: a mechanistic analysis with implications for global sustainability: Sustainable Horizons, v. 4, no. 100042, 10 p., http://doi.org/10.1016/j.horiz.2022.100042.

Lee, J., Lumley, D. E., and Lim, U. Y., 2022, Improving total organic carbon estimation for unconventional shale reservoirs using Shapley value regression and deep machine learning methods: AAPG Bulletin, v. 106, no. 11, p. 2297–2314, http://doi.org/10.1306/02072221021.

Li, H., Greenhalgh, S., Liu, B., Liu, X., Hao, Q., and Chen, Y., 2022, A generalized seismic attenuation compensation operator optimized by 2-D mathematical morphology filtering: IEEE Transactions on Geoscience and Remote Sensing, v. 60, no. 4510515, 15 p., http://doi.org/10.1109/TGRS.2022.3186595.

Li, H., Liu, X., Liu, B., Greenhalgh, S., AI-Shuhail, A. A., and Chen, Y., 2022, Bandwidth-insensitive extended centroid frequency-shift method for near-surface Q estimation: Geophysics, v. 87, no. 2, p. V75–V86, http://doi.org/10.1190/geo2021-0110.1.

Li, X., and Horita, J., 2022, Kinetic and equilibrium reactions on natural and laboratory generation of thermogenic gases from Type II marine shale: Geochimica et Cosmochimica Acta, v. 333, p. 263–283, http://doi.org/10.1016/j.gca.2022.07.020.

Li, X., Birdwell, J. E., and Horita, J., 2022, Bulk and intramolecular carbon isotopic compositions of propane from laboratory pyrolysis of oil shale of the Green River: implications for isotope structures of kerogens: International Journal of Coal Geology, v. 264, no. 104141, 14 p., http://doi.org/10.1016/j.coal.2022.104141.

Li, X., Mastalerz, M., and Horita, J., 2022, Gas generation and intramolecular isotope study in laboratory pyrolysis of the Springfield coal from the Illinois Basin: Organic Geochemistry, v. 171, no. 104466, 11 p., http://doi.org/10.1016/j.orggeochem.2022.104466.

Li, Xueying, Long, D., Scanlon, B. R., Mann, M. E., Li, Xingdong, Tian, F., Sun, Z., and Wang, G., 2022, Climate change threatens terrestrial water storage over the Tibetan Plateau: Nature Climate Change, v. 12, p. 801–807, http://doi.org/10.1038/s41558-022-01443-0.

Li, Z., Zhang, Z., Scanlon, B. R., Sun, A. Y., Pan, Y., Qiao, S., Wang, H., and Jia, Q., 2022, Combining GRACE and satellite altimetry data to detect change in sediment load to the Bohai Sea: Science of The Total Environment, v. 818, no. 151677, 10 p., http://doi.org/10.1016/j.scitotenv.2021.151677.

Lin, L., Zhong, Z., Cai, Z., Sun, A. Y., and Li, C., 2022, Automatic geologic fault identification from seismic data using 2.5D channel attention U-net: Geophysics, v. 87, no. 4, p. IM111–IM124, http://doi.org/10.1190/geo2021-0805.1.

Liu, L., Stockli, D. F., Lawton, T. F., Xu, J., Stockli, L. D., Fan, M., and Nadon, G. C., 2022, Reconstructing source-to-sink systems from detrital zircon core and rim ages: Geology, v. 50, no. 6, p. 691–696, http://doi.org/10.1130/G49904.1.

Liu, X., Shao, G., Yuan, C., Chen, X., Li, J., and Chen, Y., 2022, Mixture of relevance vector regression experts for reservoir properties prediction: Journal of Petroleum Science and Engineering, v. 214, no. 110498, p. 12, http://doi.org/10.1016/j.petrol.2022.110498.

Liu, Xingye, Shao, G., Liu, Y., Liu, Xiwu, Li, J., Chen, X., and Chen, Y., 2022, Deep classified autoencoder for lithofacies identification: IEEE Transactions on Geoscience and Remote Sensing, v. 60, no. 5909914, 14 p., http://doi.org/10.1109/TGRS.2021.3139931.

Loucks, R. G., and Reed, R. M., 2022, Implications for carbonate mass-wasting complexes induced by volcanism from Upper Cretaceous Austin Chalk strata in the Maverick Basin and San Marcos Arch areas of south-central Texas, USA: Sedimentary Geology, v. 432, no. 106120, 18 p., http://doi.org/10.1016/j.sedgeo.2022.106120.

Loucks, R. G., Peng, S., Hattori, K. E., Periwal, P., Lambert, J. R., Zahm, C. K., and Ko, L. T., 2022, Depositional systems, lithofacies, and reservoir characterization of the Upper Cretaceous Austin Chalk, Brookeland and Burr Ferry fields in East Texas and western Louisiana: GCAGS Journal, v. 11, p. 37–57.

Ludvigson, G. A., Diefendorf, A. F., Suarez, M. B., González, L. A., Corcoran, M. C., Schlanser, K, Flaig, P. P., McCarthy, P. J., van der Kolk, D., Houseknecht, D., and Sanders, M., 2022, Stable isotope tracers of cretaceous arctic paleoprecipitation: Geosciences, v. 12, no. 143, 17 p., http://doi.org/10.3390/geosciences12040143.

Luo, H., Zhang, T., Yan, J., and Gong, J., 2022, Rare earth elements and yttrium (REY) distribution pattern of lower Cambrian organic-rich shale in Yichang area, Western Hubei Province, South China, and source of carbonate minerals: Applied Geochemistry, v. 136, no. 105173, 21 p., http://doi.org/10.1016/j.apgeochem.2021.105173.

Male, F., and Jensen, J. L., 2022, Three common statistical missteps we make in reservoir characterization: AAPG Bulletin, v. 106, no. 11, p. 2149–2161, http://doi.org/10.1306/07202120076.

Menzel, M. D., Urai, J. L., Ukar, E., Decrausaz, T., and Godard, M., 2022, Progressive veining during peridotite carbonation: insights from listvenites in Hole BT1B, Samail ophiolite (Oman): Solid Earth, v. 13, no. 8, p. 1191–1218, http://doi.org/10.5194/se-13-1191-2022.

Menzel, M. D., Urai, J. L., Ukar, E., Hirth, G., Schwedt, A., Kovács, A., Kibkalo, L., and Kelemen, P. B., 2022, Ductile deformation during carbonation of serpentinized peridotite: Nature Communications, v. 13, no. 3478, 13 p., http://doi.org/10.1038/s41467-022-31049-1.

Morris, P. D., Sylvester, Z., Covault, J. A., and Mohrig, D., 2022, Channel trajectories control deep-water stratigraphic architecture: The Depositional Record, v. 8, no. 2, p. 880–894, http://doi.org/10.1002/dep2.189.

Nicot, J.-P., Smyth, R. C., Darvari, R., and McKinney, S. T., 2022, New hydrogeochemical insights on a West Texas desert spring cluster: Trans-Pecos Balmorhea-Area Springs: Applied Geochemistry, v. 142, no. 105331, 14 p., http://doi.org/10.1016/j.apgeochem.2022.105331.

Nikolinakou, M. A., Whittle, A. J., Germaine, J. T., and Zhang, G., 2022, Consolidation properties and structural alteration of Old Alluvium: Acta Geotechnica, v. 17, no. 5, p. 1569–1584, http://doi.org/10.1007/s11440-021-01330-6.

Ning, C., Sun, L., Zeng, H., Hu, S., Li, Y., Pan, W., Yao, Z., Yuan, W., and Sun, C., 2022, Characteristics of collapsed subsurface paleokarst systems and controlling factors of subsurface paleokarst development in the Lianglitage Formation, Halahatang oilfield, Tarim Basin, NW China: Marine and Petroleum Geology, v. 137, no. 105488, 18 p., http://doi.org/10.1016/j.marpetgeo.2021.105488.

Oboué, Y. A. S. I., Chen, Yunfeng, Bai, M., Chen, W., and Chen, Yangkang, 2022, Erratic and random noise attenuation using adaptive local orthogonalization: Geophysics, v. 87, no. 4, p. V381–V396, http://doi.org/10.1190/geo2021-0785.1.

Ogiesoba, O. C., and Zeng, H., 2022, Identification of sandstone-rich zones in upper bathyal, deep water environment on south Texas Gulf Coast: Interpretation, v. 10, no. 2, p. T265–T278, http://doi.org/10.1190/INT-2021-0139.1.

Peng, J., and Larson, T. E., 2022, A novel integrated approach for chemofacies characterization of organic-rich mudrocks: AAPG Bulletin, v. 106, no. 2, p. 437–460, http://doi.org/10.1306/05112120210.

Peng, J., Fu, Q., and Janson, X., 2022, Dynamic climatic changes during the Late Pennsylvanian icehouse: new insight from high-resolution geochemical records in the Cline Shale, North America: Gondwana Research, v. 106, p. 247–258, http://doi.org/10.1016/j.gr.2022.01.012.

Rateb, A., Scanlon, B. R., and Fakhreddine, S., 2022, How severe is water stress in the MENA region? insights from GRACE and GRACE-FO satellites and global hydrological modeling, in Al Saud, M. M., ed., Applications of space techniques on the natural hazards in the MENA region (ch. 4): Cham, Switzerland, Springer Nature Switzerland, p. 51–65, http://doi.org/10.1007/978-3-030-88874-9_4.

Rateb, A., Sun, A., Scanlon, B. R., Save, H., and Hasan, E., 2022, Reconstruction of GRACE mass change time series using a Bayesian framework: Earth and Space Science, v. 9, no. e2021EA002162, 13 p., http://doi.org/10.1029/2021EA002162.

Reed, R. M., and Loucks, R. G., 2022, Textures, mineralogy, and reservoir properties of an altered mafic tuff core from the Upper Cretaceous (Lower Campanian) of Central Texas: GCAGS Journal, v. 11, 15 p.

Ren, B., Jensen, J. L., Lake, L. W., Duncan, I. J., and Male, F., 2022, Analysis of vertical permeability and its influence on CO2 enhanced oil recovery and storage in a carbonate reservoir: Society of Petroleum Engineers Reservoir Evaluation & Engineering, v. 25, no. 3, p. 414–432, http://doi.org/10.2118/205995-PA.

Roberts, A. K., Ambrose, W. A., Flaig, P. P., Steel, R. J., and Olariu, C., 2022, Controls on facies variability and distribution during the Pennsylvanian glacial period from the lower Strawn Group, Fort Worth basin, Texas: AAPG Bulletin, v. 106, no. 8, p. 1679–1702, http://doi.org/10.1306/02072221057.

Romanak, K. D., and Dixon, T., 2022, CO2 storage guidelines and the science of monitoring: achieving project success under the California Low Carbon Fuel Standard CCS Protocol and other global regulations: International Journal of Greenhouse Gas Control, v. 113, no. 103523, 10 p., http://doi.org/10.1016/j.ijggc.2021.103523.

Rueda, V., Young, M. H., Faust, K., Rateb, A., and Leibowicz, B. D., 2022, System dynamics modeling in local water management: assessing strategies for the city of Boerne, Texas: Water, v. 14, no. 3682, 19 p., http://doi.org/10.3390/w14223682.

Ruiz Maraggi, L. M., Lake, L. W., and Walsh, M. P., 2022, A Bayesian framework for addressing the uncertainty in production forecasts of tight-oil reservoirs using a physics-based two-phase flow model: SPE Reservoir Evaluation & Engineering, v. 25, no. 03, p. 486–508, http://doi.org/10.2118/209203-PA.

Ruiz Maraggi, L. M., Lake, L. W., and Walsh, M. P., 2022, A two-phase flow model for reserves estimation in tight-oil and gas-condensate reservoirs using scaling principles: SPE Reservoir Evaluation & Engineering, v. 25, no. 01, p. 81–98, http://doi.org/10.2118/199032-PA.

Ruiz Maraggi, L. M., Lake, L. W., and Walsh, M. P., 2022, Rate-pseudopressure deconvolution enhances rate-time models production history-matches and forecasts of shale gas wells: SPE Reservoir Evaluation & Engineering, v. 25, no. 04, p. 684–703, http://doi.org/10.2118/208967-PA.

Ruiz Maraggi, L. M., Lake, L. W., and Walsh, M. P., 2022, Using Bayesian leave-one-out and leave-future-out cross-validation to evaluate the performance of rate-time models to forecast production of tight-oil wells: SPE Reservoir Evaluation & Engineering, v. 25, no. 04, p. 730–750, http://doi.org/10.2118/209234-PA.

Rysak, B., Gale, J. F. W., Laubach, S. E., Ferrill, D. A., and Olson, J. E., 2022, Mechanisms for the generation of complex fracture networks: observations from slant core, analog models, and outcrop: Frontiers in Earth Science, v. 10, no. 848012, 18 p., http://doi.org/10.3389/feart.2022.848012.

Saad, O. M., and Chen, Y., 2022, CapsPhase: capsule neural network for seismic phase classification and picking: IEEE Transactions on Geoscience and Remote Sensing, v. 60, no. 5904311, 11 p., http://doi.org/10.1109/TGRS.2021.3089929.

Saad, O. M., Chen, Yunfeng, Savvaidis, A., Chen, W., Zhang, F., and Chen, Yangkang, 2022, Unsupervised deep learning for single-channel earthquake data denoising and its applications in event detection and fully automatic location: IEEE Transactions on Geoscience and Remote Sensing, v. 60, no. 5921310, 10 p., http://doi.org/10.1109/TGRS.2022.3209932.

Saad, O. M., Chen, Yunfeng, Savvaidis, A., Fomel, S., and Chen, Yangkang, 2022, Real-time earthquake detection and magnitude estimation using vision transformer: Journal of Geophysical Research: Solid Earth, v. 127, no. e2021JB023657, 19 p., http://doi.org/10.1029/2021JB023657.

Saad, O. M., Chen, Yunfeng, Trugman, D., Soliman, M. S., Sami, L., Savvaidis, A., Khamis, M. A., Hafez, A. G., Fomel, S., and Chen, Yangkang, 2022, Machine learning for fast and reliable source-location estimation in earthquake early warning: IEEE Geoscience and Remote Sensing Letters, v. 19, no. 8025705, 5 p., http://doi.org/10.1109/LGRS.2022.3142714.

Saad, O. M., Oboué, Y. A. S. I., Bai, M., Samy, L., Yang, L., and Chen, Y., 2022, Self-attention deep image prior network for unsupervised 3-D seismic data enhancement: IEEE Transactions on Geoscience and Remote Sensing, v. 60, no. 5907014, 14 p., http://doi.org/10.1109/TGRS.2021.3108515.

Saad, O. M., Soliman, M. S., Chen, Y., Amin, A. A., and Abdelhafiez, H. E., 2022, Discriminating earthquakes from quarry blasts using capsule neural network: IEEE Geoscience and Remote Sensing Letters, v. 19, no. 8029605, 5 p., http://doi.org/10.1109/LGRS.2022.3207238.

Scanlon, B. R., Fakhreddine, S., Reedy, R. C., Yang, Q., and Malito, J. G., 2022, Drivers of spatiotemporal variability in drinking water quality in the United States: Environmental Science & Technology, v. 56, no. 18, p. 12965–12974, http://doi.org/10.1021/acs.est.1c08697.

Scanlon, B. R., Rateb, A., Anyamba, A., Kebede, S., MacDonald, A. M., Shamsudduha, M., Small, J., Sun, A., Taylor, R. G., and Xie, H., 2022, Linkages between GRACE water storage, hydrologic extremes, and climate teleconnections in major African aquifers: Environmental Research Letters, v. 17, no. 1, article no. 014046, 15 p., http://doi.org/10.1088/1748-9326/ac3bfc.

Scanlon, B. R., Reedy, R. C., and Wolaver, B. D., 2022, Assessing cumulative water impacts from shale oil and gas production: Permian Basin case study: Science of The Total Environment, v. 811, no. 152306, 11 p., http://doi.org/10.1016/j.scitotenv.2021.152306.

Schemper, P., Loucks, R. G., and Fu, Q., 2022, Depositional systems, lithofacies, and lithofacies stacking patterns of the Jurassic Smackover Formation (Oxfordian) and Buckner Anhydrite (Kimmeridgian) in Van Zandt County, Texas: a type-cored section from northeast Texas: GCAGS journal, v. 11, p. 16–36.

Shakiba, M, Lake, L. W., Gale, J. F. W., and Pyrcz, M. J., 2022, Multiscale spatial analysis of fracture arrangement and pattern reconstruction using Ripley's K-function: Journal of Structural Geology, v. 155, no. 104531, 14 p., http://doi.org/10.1016/j.jsg.2022.104531.

Shao, D., Zhang, T., Li, Y., Milliken, K. L., Zhang, Y., and Song, H., 2022, Effects of confining pressure and microscale heterogeneity on hydrocarbon retention and pore evolution from artificial maturation of Eagle Ford Shale: International Journal of Coal Geology, v. 260, no. 104057, 18 p., http://doi.org/10.1016/j.coal.2022.104057.

Shao, D., Zhang, T., Zhang, L., Li, Y., and Meng, K., 2022, Effects of pressure on gas generation and pore evolution in thermally matured calcareous mudrock—insights from gold-tube pyrolysis of the Eagle Ford Shale using miniature core plugs: International Journal of Coal Geology, v. 252, no. 103936, 15 p., http://doi.org/10.1016/j.coal.2022.103936.

Sharman, G. R., Stockli, D. F., Flaig, P., Raynolds, R. G., Dechesne, M., and Covault, J. A., 2022, Tectonic influence on axial-transverse sediment routing in the Denver Basin, in Craddock, J. P., Malone, D. H., Foreman, B. Z., and Konstantinou, A., eds., Tectonic evolution of the Sevier-Laramide hinterland, thrust belt, and foreland, and postorogenic slab rollback (180–20 Ma): Boulder, Colo., Geological Society of America, Special Paper, v. 555, p. 293-311, http://doi.org/10.1130/2021.2555(11).

Soto, J. I., Déverchère, J., Hudec, M. R., Medaouri, M., Badji, R., Gaullier, V., and Leffondré, P., 2022, Crustal structures and salt tectonics on the margins of the western Algerian Basin (Mediterranean Region): Marine and Petroleum Geology, v. 144, no. 105820, 30 p., http://doi.org/10.1016/j.marpetgeo.2022.105820.

Sun, A. Y., Jiang, P., Yang, Z.-L., Xie, Y., and Chen, X., 2022, A graph neural network (GNN) approach to basin-scale river network learning: the role of physics-based connectivity and data fusion: Hydrology and Earth System Sciences, v. 26, no. 19, p. 5163–5184, http://doi.org/10.5194/hess-26-5163-2022.

Sun, A. Y., Yoon, H., Shih, C.-Y., and Zhong, Z., 2022, Applications of physics-informed scientific machine learning in subsurface science: a survey, in Karpatne, A., Kannan, R., and Kumar, V., eds., Knowledge-guided machine learning—accelerating discovery using scientific knowledge and data: Boca Raton, Fla., CRC Press, p. 111-132, http://doi.org/10.1201/9781003143376-5.

Sun, X., Zhang, T., and Walters, C. C., 2022, Geochemistry of oils and condensates from the lower Eagle Ford Formation, south Texas. Part 2: Molecular characterization: Marine and Petroleum Geology, v. 141, no. 105710, 23 p., http://doi.org/10.1016/j.marpetgeo.2022.105710.

Suriamin, F., and Ko, L. T., 2022, Geological characterization of unconventional shale-gas reservoirs, in Moghanloo, R. G., Unconventional shale gas development—lessons learned (ch. 2): Cambridge, MA, Gulf Professional Publishing, Elsevier, p. 33-70, http://doi.org/10.1016/B978-0-323-90185-7.00006-6.

Torres, M. E., Milliken, K. L., Hüpers, A., Kim, J.-H., and Lee, S.-G., 2022, Authigenic clays versus carbonate formation as products of marine silicate weathering in the input sequence to the Sumatra subduction zone: Geochemistry, Geophysics, Geosystems, v. 23, no. 4, article no. e2022GC010338, 17 p., http://doi.org/10.1029/2022GC010338.

Ulfah, M., Hosseini, S., Hovorka, S., Bump, A., Bakhshian, S., and Dunlap, D., 2022, Assessing impacts on pressure stabilization and leasing acreage for CO2 storage utilizing oil migration concepts: International Journal of Greenhouse Gas Control, v. 115, no. 103612, 13 p., http://doi.org/10.1016/j.ijggc.2022.103612.

Vereecken, H., Amelung, W., Bauke, S. L., Bogena, H., Brüggemann, N., Montzka, C., Vanderborght, J., Bechtold, M., Blöschl, G., Carminati, A., Javaux, M., Konings, A. G., Kusche, J., Neuweiler, I., Or, D., Steele-Dunne, S., Verhoef, A., Young, M., and Zhang, Y., 2022, Soil hydrology in the Earth system: Nature Reviews Earth and Environment, v. 3, p. 573–587, http://doi.org/10.1038/s43017-022-00324-6.

Verma, S., Bhattacharya, S., Fett, T., Avseth, P., and Lehocki, I., 2022, Imaging and interpretation: seismic, rock physics and image log analysis workflows for deepwater systems, in Rotzien, J., Yeilding, C., Sears, R., Hernández-Molina, F. J., Catuneanu, O., eds., Deepwater sedimentary systems: science, discovery and applications: Cambridge, Mass., Elsevier, p. 555-591, http://doi.org/10.1016/B978-0-323-91918-0.00015-3.

Wang, H., and Chen, Y., 2022, Iterative Gaussian mixture model and multi-channel attributes for arrival picking in extremely noisy environments: Geophysical Prospecting, v. 70, no. 2, p. 343–361, http://doi.org/10.1111/1365-2478.13164.

Wang, H., Chen, Yunfeng, Min, R., and Chen, Yangkang, 2022, Urban DAS data processing and its preliminary application to city traffic monitoring: Sensors, v. 22, no. 9976, 20 p., http://doi.org/10.3390/s22249976.

Wang, H., Chen, Yunfeng, Oboué, Y. A. S. I., Abma, R., Geng, Z., Fomel, S., and Chen, Yangkang, 2022, Simultaneous reconstruction and denoising of extremely sparse 5-D seismic data by a simple and effective method: IEEE Transactions on Geoscience and Remote Sensing, v. 60, no. 5909212, 12 p., http://doi.org/10.1109/TGRS.2021.3132257.

Wang, H., Chen, Yunfeng, Saad, O. M., Chen, W., Oboué, Y. A. S. I., Yang, L., Fomel, S., and Chen, Yangkang, 2022, A MATLAB code package for 2D/3D local slope estimation and structural filtering: Geophysics, v. 87, no. 3, p. F1–F14, http://doi.org/10.1190/geo2021-0266.1.

Wang, Y., Bai, M., Yang, L., Zhao, X., Saad, O. M., and Chen, Y., 2022, An unsplit CFS-PML scheme for the second-order wave equation with its application in fractional viscoacoustic simulation: IEEE Transactions on Geoscience and Remote Sensing, v. 60, no. 5905211, 11 p., http://doi.org/10.1109/TGRS.2021.3092714.

Wang, Y., Harris, J. M., Bai, M., Saad, O. M., Yang, L., and Chen, Y., 2022, An explicit stabilization scheme for Q-compensated reverse time migration: Geophysics, v. 87, no. 3, p. F25–F40, http://doi.org/10.1190/geo2021-0134.1.

Williams, T. S., Bhattacharya, S., Song, L., Agrawal., V., and Sharma, S., 2022, Petrophysical analysis and mudstone lithofacies classification of the HRZ shale, North Slope, Alaska: Journal of Petroleum Science and Engineering, v. 208, no. 109454, 11 p., http://doi.org/10.1016/j.petrol.2021.109454.

Wisian, K., 2022, Geothermal energy on solar system bodies: Journal of the British Interplanetary Society, v. 75, no. 9, p. 315–320.

Wisian, K., 2022, Geothermal energy on solar system bodies: Journal of the British Interplanetary Society, v. 75, no. 9, p. 315–320.

Wu, Y., Long, D., Lall, U., Scanlon, B. R., Fuqiang, T., Xudong, F., Zhao, J., Zhang, J., Wang, H., and Hu, C., 2022, Reconstructed eight-century streamflow in the Tibetan Plateau reveals contrasting regional variability and strong nonstationarity: Nature Communications, v. 13, no. 6416, p. 801–807, http://doi.org/10.1038/s41467-022-34221-9.

Yang, D., Xu, X., and Scanlon, B. R., 2022, Multisource remote sensing data facilitate ecohydrological simulations without runoff calibration: Hydrological Processes, v. 36, no. e14773, 13 p., http://doi.org/10.1002/hyp.14773.

Yang, L., Wang, S., Chen, X., Saad, O. M., Chen, W., Oboué, Y. A. S. I., and Chen, Y., 2022, Unsupervised 3-D random noise attenuation using deep skip autoencoder: IEEE Transactions on Geoscience and Remote Sensing, v. 60, no. 5905416, 16 p., http://doi.org/10.1109/TGRS.2021.3100455.

Yang, W., Long, D., Scanlon, B. R., Burek, P., Zhang, C., Han, Z., Butler, J. J., Jr., Pan, Y., Lei, X., and Wada, Y., 2022, Human intervention will stabilize groundwater storage across the North China Plain: Water Resources Research, v. 58, no. 2, article no. e2021WR030884, 21 p., http://doi.org/10.1029/2021WR030884.

Young, M. H., and Or, D., 2022, Global water cycle from a soil perspective, in Hallett, P., ed., Encyclopedia of soils in the environment (2d ed.): Elsevier, 8 p., http://doi.org/10.1016/B978-0-12-822974-3.00121-X.

Yu, J., Shi, K., Wang, Q., Liu, B., Han, J., Song, Y., Kong, Y., and Jiang, W., 2022, Structural diagenesis of deep carbonate rocks controlled by intra‐cratonic strike‐slip faulting: an example in the Shunbei area of the Tarim Basin, NW China: Basin Research, v. 34, no. 5, p. 1601–1631, http://doi.org/10.1111/bre.12672.

Zeng, H., Xu, Z., Liu, W., Janson, X., and Fu, Q., 2022, Seismic-informed carbonate shelf-to-basin transition in deeply buried Cambrian strata, Tarim Basin, China: Marine and Petroleum Geology, v. 136, no. 105448, 18 p., http://doi.org/10.1016/j.marpetgeo.2021.105448.

Zeng, L., Gong, L., Guan, C., Zhang, B., Wang, Q., Zeng, Q., and Lyu, W., 2022, Natural fractures and their contribution to tight gas conglomerate reservoirs: a case study in the northwestern Sichuan Basin, China: Journal of Petroleum Science and Engineering, v. 210, no. 110028, http://doi.org/10.1016/j.petrol.2021.110028.

Zeng, Z., Zhu, H., Zeng, H., Yang, X., and Xu, C., 2022, Seismic sedimentology analysis of fluvial-deltaic systems in a complex strike-slip fault zone, Bohai Bay Basin, China: implications for reservoir prediction: Journal of Petroleum Science and Engineering, v. 208, part E, no. 109290, 15 p., http://doi.org/10.1016/j.petrol.2021.109290.

Zhang, F., Wang, R., Chen, Yunfeng, and Chen, Yangkang, 2022, Spatiotemporal variations in earthquake triggering mechanisms during multistage hydraulic fracturing in western Canada: Journal of Geophysical Research: Solid Earth, v. 127, no. 8, 18 p., http://doi.org/10.1029/2022JB024744.

Zhang, J., Ukar, E., Qu, J., Zhang, B., Zhao, H., Zhang, Y., and Wang, Z., 2022, Periclinal fold systems in thick-bedded mudstones: a case study of the Early Cretaceous Hekou Group, Lanzhou Basin, NW China: Journal of Structural Geology, v. 161, no. 104678, 14 p., http://doi.org/10.1016/j.jsg.2022.104678.

Zhang, Q., Chen, Yunfeng, Zhang, F., and Chen, Yangkang, 2022, Improving receiver function imaging with high-resolution Radon transform: Geophysical Journal International, v. 230, no. 2, p. 1292–1304, http://doi.org/10.1093/gji/ggac116.

Zhang, R., Sun, Q., Cui, L., Jia, Y., Huang, W.-F., Ahmadian, M., and Liu, Q. H., 2022, Accelerating hydraulic fracture imaging by deep transfer learning: IEEE Transactions on Antennas and Propagation, v. 70, no. 7, p. 6117–6121, http://doi.org/10.1109/TAP.2022.3161325.

Zhang, T., Sun, X., Walters, C. C., Sundaram, A., and Calla, T. J., 2022, Geochemistry of oils and condensates from the lower Eagle Ford formation, south Texas. Part 1: Crude assay measurements and SimDist modeling: Marine and Petroleum Geology, v. 139, no. 105576, 16 p., http://doi.org/10.1016/j.marpetgeo.2022.105576.

Zhang, Y., Zhang, T., Huang, D., Shao, D., and Luo, H., 2022, Geochemical and paleontological evidence of early Cambrian dynamic ocean oxygenation and its implications for organic matter accumulation in mudrocks at the Three Gorges area, South China: Marine and Petroleum Geology, v. 146, no. 105958, 17 p., http://doi.org/10.1016/j.marpetgeo.2022.105958.

Zhang, Y., Zhang, T., Huang, D., Shao, D., and Luo, H., 2022, Geochemical and paleontological evidence of early Cambrian dynamic ocean oxygenation and its implications for organic matter accumulation in mudrocks at the Three Gorges area, South China: Marine and Petroleum Geology, v. 146, no. 105958, 17 p., http://doi.org/10.1016/j.marpetgeo.2022.105958.

Zu, S., Cao, J., Fomel, S., Yang, L., Saad, O. M., and Chen, Y., 2022, Robust local slope estimation by deep learning: Geophysical Prospecting, v. 70, no. 5, p. 847–864, http://doi.org/10.1111/1365-2478.13208.


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