Open Access
| Issue |
E3S Web Conf.
Volume 520, 2024
4th International Conference on Environment Resources and Energy Engineering (ICEREE 2024)
|
|
|---|---|---|
| Article Number | 03019 | |
| Number of page(s) | 4 | |
| Section | New Progress in New Energy and Resource Utilization Technology | |
| DOI | https://doi.org/10.1051/e3sconf/202452003019 | |
| Published online | 03 May 2024 | |
- Passey, Q.R., Creaney, S., Kulla, J.B., et al. 1990. A ractical model for organic richness from porosity nd resistivity logs. AAPG Bulletin, 74(12): 1777–1794. [Google Scholar]
- Decker, A.D., Hill, D.G., Wicks, D.E.. 1993. Log-based as content and resource estimates for the Antrim hale, Michigan Basin. //Low Permeability eservoirs Symposium. Denver, Colorado: SPE [Google Scholar]
- Schmoker, J.W.. 1981. Determination of organicmatter ontent of Appalachian Devonian shales from amma-ray logs. AAPG Bulletin, 65(7): 1285–1298. [Google Scholar]
- Mahmoud, A.A.A., Elkatatny, S., Mahmoud, M., et al. 2017. Determination of the total organic carbon (TOC) ased on conventional well logs using artificial neural etwork. International Journal of Coal Geology, 179: 72–80. [CrossRef] [Google Scholar]
- Lee, J., Lim, U.Y., Lumley, D.. 2020. Improved TOC and ithology prediction for Wolfcamp shales using AVO ttribute analysis. //SEG Global Meeting Abstracts. EG, 3797–3806. [Google Scholar]
- Xu, J., He, Z.L., Dong, Y. et al. (2013). Total organic arbon content prediction of gas-bearing shale with eophysical methods. OGP, 48(S1):64–68. [Google Scholar]
- Wang, J., Shi, W.Z., Shu, Z.G. et al. (2016) TOC content uantitative prediction in organic rich shale. OGP, 51(3):596–604. [Google Scholar]
- Niu, C., Liu, Z.B., Wang, Y.C. et al. (2017). Quanititative valuation of Shahejie formation source rocks in iaohe sag with geophysical approaches. OGP, 52(1):131–137. [Google Scholar]
- Cai, D.M., Zhao, D.J., Peng, J.S. et al. (2018). Highquality ydrocarbon source rock identification and uantitative evaluation with multi-attribute inversion: case study of Liaodong south sub-sag, Bohai Bay asin. OGP, 53(02),330–338+222-223. [Google Scholar]
- Chen, Y.H., Yao, G.S., Liu, Z. et al. (2016). Total organic arbon quantitative prediction using seismic nformation. Journal of Central South University Science and Technology), 47(1):159–165. [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.