My Publications

To deliver, disseminate, and share a diversified, valued, and experienced knowledge to the local and global scientific and professional communities.

Books

    • Al-Fattah, S.M., Barghouty, M.F., Dabbousi, B.O., et al. (2011). Carbon capture and storage: Technologies, policies, economics, and implementation strategies. Leiden, Netherlands: CRC Press. Download
    • Mohaghegh, S.D., Al-Fattah, S.M., and Popa, A.S. (2011). Artificial intelligence and data mining applications in the E&P industry. Richardson, TX, USA: Society of Petroleum Engineers.Download
    • Al-Fattah, S.M. (2011). Innovative methods for analyzing and forecasting world gas supply.Germany: Lambert Academic Publishing. Download

Reviewed Books with Testimonial

  • Pettit, Justin. (2017). The Final Frontier: E&P’s Low-Cost Operating Model. Hoboken, New Jersey: Wiley. Download

Journal Articles

  • Al-Fattah, S.M. (2019). Artificial intelligence approach for modeling and forecasting oil-price volatility, SPE Reservoir Evaluation & Engineering 22(3), 817-826. https://doi.org/10.2118/195584-PA. Download
  • Huntington, H., Al-Fattah, S.M., Huang, Z., Gucwa, M., and Nouri, A. (2014). Oil price drivers and movements: The challenge for future research. Alternative Investment Analyst Review Journal, 2(4), 11-28. Download
  • Al-Fattah, S.M. (2013). National oil companies: Business models, challenges, and emerging trends. Corporate Ownership and Control Journal11(1), 727-735.Download
  • Matar, W., Al-Fattah, S.M., Atallah, T., and Pierru, A. (2013). An introduction to oil market volatility analysis. OPEC Energy Review, 37(3), 247-269.
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  • Al-Fattah, S.M., Dallag, M.M., and Smith, C. (2010). Intelligent surveillance tools improve field management efficiency. Oil Review Middle East, 13(4) 74-76.
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  • Al-Fattah, S.M., and Al-Nuaim, H.A. (2009). Artificial-intelligence technology predicts relative permeability of giant carbonate reservoirs. SPE Reservoir Evaluation & Engineering, 12(1), 96-108. DOI:10.2118/109018-PA. Download
  • Al-Fattah, S.M., Dallag, M., Abdulmohsin, R.A., Al-Harbi, W.A., and Issaka, M.B. (2008). Intelligent integrated dynamic surveillance tool improves field management practices. Saudi Aramco Journal of Technology, (Summer issue), 12-21. Download
  • Al-Fattah, S.M. (2006). Time series modeling for U.S. natural gas forecasting. e-Journal of Petroleum Management and Economics, Petroleum Journals Online,(Apr. 28)17 pages. ISSN: 1718-7559. Download
  • Al-Fattah, S.M. (2004). Equations for water/oil relative permeability in Saudi Arabian sandstone reservoirs. Saudi Aramco Journal of Technology, (Summer issue), 48-58.Download
  • Al-Fattah, S.M. and Startzman, R.A. (2003). Neural network approach predicts U.S. natural gas production, SPE Production & Facilities Journal, 18(2), 84-91. DOI:10.2118/82411-PA. Download
  • *Al-Fattah, S.M. and Startzman, R.A. (2000). Forecasting world natural gas supply. J Pet Technol52(5), 62-72. DOI: 10.2118/62580-PA. [Featured management paper]Download
  • Al-Fattah, S.M. and Al-Marhoun, M.A. (1995). Evaluation of empirical correlations for bubblepoint oil formation volume factor. Saudi Aramco Journal of Technology, (Winterissue).Download
  • Al-Fattah, S.M. and Al-Marhoun, M.A. (1994). Evaluation of empirical correlations for bubblepoint oil formation volume factor. J. Petroleum Science and Engineering 11(4), 341-350. Download

Conference Papers

  • Al-Fattah, S.M. (2019). Artificial intelligence transformative technology of global energy and economics. Invited speech presented at the 2nd Artificial Intelligence Week Middle East, Dubai, UAE.
  • Al-Fattah, S.M. (2018a). Intelligent gasoline demand analytics: A case study of Saudi Arabia. Proceeding paper accepted at the 36th USAEE/IAEE North American Conference, Washington, D.C., USA.
  • Al-Fattah, S.M. (2018b). Intelligent oil demand outlook analytics. Proceeding paper acceptedat the IAEE Asian Conference, Wuhan, China.
  • Le Thiez, P., Al-Fattah, S.M., Barghouty, M.F., Le Gallo, Y., Rambourg, D, Brugeron, A., and Quinquis, H. (2011). A new carbon capture and storage initiative in Saudi Arabia: Development of an innovative GIS-based system for managing source-sink matching scenarios. Paper presented at the 10th Annual Conference on Carbon Capture and Sequestration, Pittsburgh, PA, USA.
  • Al-Bishara, M., Al-Fattah, S.M., Nashawi, I.S., and Malallah, A.H. (2009). Forecasting OPEC crude oil supply. Paper SPE-120350 presented at the SPE Middle East Oil and Gas Show and Conference, Manama, Bahrain. Download
  • Al-Fattah, S.M. (2007a). Artificial intelligence technology predicts relative permeability of giant carbonate reservoirs. Paper SPE-109018 presented at the 2007 SPE Offshore Europe, Aberdeen, United Kingdom. Download
  • Al-Fattah, S.M. (2007b). Artificial neural networks determine relative permeability of carbonate reservoirs. Paper presented at the 2007 SPE Middle East Oil Show and Conference, Manama, Bahrain.
  • Al-Fattah, S.M., Dallag, M.M., Al-Abdalmohsen, R.A., Al-Harbi, W.A., and Issaka, M.B. (2006a). Intelligent integrated dynamic surveillance tool improves field management practices. Paper SPE-99555 presented at the SPE Intelligent Energy Conference, Amsterdam, Netherlands. DOI:10.2118/99555-MS.
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  • Al-Fattah, S.M., Dallag, M.M., Al-Abdalmohsen, R.A., Al-Harbi, W.A., and Issaka, M.B. (2006b). Intelligent integrated dynamic surveillance tool improves field-management practices. Paper presented at the SPE Annual Saudi Arabia Technical Symposium, Dhahran, Saudi Arabia.
  • Al-Fattah, S.M. (2005a). Artificial neural network models predict two-phase relative permeability of carbonate reservoirs. Paper presented at the SPE/EAGE Reservoir Characterization and Simulation Symposium, Dubai, United Arab Emirates.
  • Al-Fattah, S.M. (2005b). Time series modeling for U.S. natural gas forecasting. Paper IPTC-10592 presented at the SPE International Petroleum Technology Conference, Doha, Qatar. DOI: 10.2523/IPTC-10592-MS. Download
  • Al-Fattah, S.M. (2003). Empirical equations for water/oil relative permeability in Saudi sandstone reservoirs. Paper SPE-85652 presented at the SPE Annual International Conference and Exhibition, Abuja, Nigeria. DOI: 10.2118/85652-MS. Download
  • Al-Fattah, S.M. and Startzman, R.A. (2001a). Neural network approach predicts U.S. natural gas production. Paper SPE-67260 presented at the SPE Production and Operations Symposium, Oklahoma, OK, USA. DOI:10.2523/67260-MS. Download
  • Al-Fattah, S.M. and Startzman, R.A. (2001b). Predicting natural gas production using artificial neural network. Paper SPE-68593 presented at the SPE Hydrocarbon Economics and Evaluation Symposium, Dallas, TX, USA. DOI:10.2118/68593-MS. Download
  • Al-Fattah, S.M. and Startzman, R.A. (2000). Forecasting world natural gas supply. Paper SPE-59798 presented at the 2000 SPE/CERI Gas Technology Symposium, Calgary, Canada. DOI: 10.2118/59798-MS. Download
  • Al-Fattah, S.M. and Startzman, R.A. (1999). Analysis of worldwide natural gas production. Paper SPE-57463 presented at the 1999 SPE Eastern Regional Meeting, Charleston, WV, USA. DOI: 10.2118/57463-MS. Download

Working Papers

  • Al-Fattah, Saud M. (2019). Non-OPEC conventional oil: Production decline, supply outlook and key implications, (USAEE Working Paper No. 19-405). Ohio, USA: United States Association for Energy Economics. DOI: http://dx.doi.org/10.2139/ssrn.3388784. Download
  • Al-Fattah, Saud M. (2018a).Reasonable predictions of oil prices: Why is it so difficult?Available at SSRN Electronic Journal: DOI: dx.doi.org/10.2139/ssrn.3378015.Download
  • Al-Fattah, Saud M. (2018b).A Hybrid artificial-intelligence predictive model for crude oil demand: A Case study for a high producer and a high consumer. SSRN Electronic Journal. DOI: dx.doi.org/10.2139/ssrn.3378041. Download
  • Al-Fattah, S.M. (2013). Artificial neural network models for forecasting global oil market volatility, (USAEE Working Paper No. 13-112). Ohio, USA: United States Association for Energy Economics. DOI: Download
  • Al-Fattah, S.M. (2013). National oil companies: Business models, challenges, and emerging trends,(USAEE Working No. 13-138). Ohio, USA: United States Association for Energy Economics.DOI: http://dx.doi.org/10.2139/ssrn.2299879. Download
  • Huntington, H, Al-Fattah, S.M., Huang, Z., Gucwa, M., and Nouri, A. (2013). Oil markets and price movements: A survey of models,(USAEE Working Paper No. 13-129).Ohio, USA: United States Association for Energy Economics. DOI: http://dx.doi.org/10.2139/ssrn.2264034. Download
  • Al-Fattah, S.M. (2012). The role of national and international oil companies in the petroleum industry,(USAEE Working Paper No. 13-137). Ohio, USA: United States Association for Energy Economics. DOI: http://dx.doi.org/10.2139/ssrn.2299878.Download
  • Matar, W., Al-Fattah, S.M., Atallah, T.N., and Pierru, A. (2012). An introduction to oil market volatility analysis, (USAEE Working Paper No. 12-152).Ohio, USA: United States Association for Energy Economics. DOI: http://dx.doi.org/10.2139/ssrn.2194214.Download

Online References