Page 212 - Machine Learning for Subsurface Characterization

Dimensionality reduction and clustering techniques Chapter 6 181

[24] Teklu TW, Alharthy N, Kazemi H, Yin X, Graves RM. Hydrocarbon and non-hydrocarbon
gas miscibility with light oil in shale reservoirs. In: SPE improved oil recovery symposium;
12–16 April; Tulsa, Oklahoma, USA. SPE: Society of Petroleum Engineers; 2014. p.
SPE-169123-MS.
[25] Reeder SL, Craddock PR, Rylander E, Pirie I, Lewis RE, Kausik R, et al. The reservoir
producibility index: a metric to assess reservoir quality in tight-oil plays from logs.
Petrophysics 2016;57(02):83–95.
[26] Rampersad PR, Ogbe DO, Kamath VA, Islam R. Impact of trapping of residual oil by mobile
water on recovery performance in miscible enhanced oil recovery processes. In: Low
permeability reservoirs symposium; 19–22 march; Denver, Colorado. SPE: Society of
Petroleum Engineers; 1995 [p. SPE-29563-MS].
[27] Kurtoglu B, Sorensen JA, Braunberger J, Smith S, Kazemi H. Geologic characterization of a
Bakken reservoir for potential CO 2 EOR. In: Unconventional resources technology
conference; 12–14 August; Denver, Colorado, USA. SPE: Society of Petroleum Engineers;
2013. p. 12–4 August.
[28] Sehbi BS, Frailey SM, Lawal AS. Analysis of factors affecting microscopic displacement
efficiency in CO 2 floods. In: SPE Permian Basin oil and gas recovery conference; 15–17
May; Midland, Texas. SPE: Society of Petroleum Engineers; 2001 [p. SPE-70022-MS].
[29] Teklu TW, Alharthy N, Kazemi H, Yin X, Graves RM, AlSumaiti AM. Phase behavior
and minimum miscibility pressure in nanopores. SPE Reserv Eval Eng 2014;17(03):396–403.
[30] Kulkarni MM. Multiphase mechanisms and fluid dynamics in gas injection enhanced
oil recovery processes. [Ph.D. General Exam Report] Baton Rouge, LA: The Craft and
Hawkins Department of Petroleum Engineering, Louisiana State University and A&M
College; 2004 (Jul).
[31] Zhao B, Shaw JM. Composition and size distribution of coherent nanostructures in Athabasca
bitumen and Maya crude oil. Energy Fuel 2007;21(5):2795–804.
[32] Jain V, Minh CC, Heaton N, Ferraris P, Ortenzi L, Ribeiro MT. Characterization of underlying
pore and fluid structure using factor analysis on NMR data. In: SPWLA 54th annual logging
symposium; 22–26 June; New Orleans, Louisiana. SPWLA: Society of Petrophysicists and
Well-Log Analysts; 2013 [p. SPWLA-2013-TT].
[33] Jiang T, Jain V, Belotserkovskaya A, Nwosu NK, Ahmad S. Evaluating producible
hydrocarbons and reservoir quality in organic shale reservoirs using nuclear magnetic
resonance (NMR) factor analysis. 2015/10/20/, SPE: Society of Petroleum Engineers; 2015.
[34] Jiang T, Rylander E, Singer PM, Lewis RE, Sinclair SM, editors. Integrated petrophysical
interpretation of Eagle Ford Shale with 1-D and 2-D nuclear magnetic resonance (NMR).
SPWLA 54th annual logging symposium; 2013 22–26 June; New Orleans, Louisiana.
Society of Petrophysicists and Well-Log Analysts; 2013.
[35] Sun B, Yang E, Wang H, Seltzer SJ, Montoya V, Crowe J, et al. Using NMR to characterize
fluids in tight rock unconventional and shale formations. In: SPWLA 57th annual logging
symposium; 25–29 June; Reykjavik, Iceland. SPWLA: Society of Petrophysicists and Well-
Log Analysts; 2016 [p. SPWLA-2016-PP].
[36] Ramakrishna S, Balliet R, Miller D, Sarvotham S, Merkel D. Formation evaluation In the
Bakken complex using laboratory core data and advanced logging technologies.
In: SPWLA 51st annual logging symposium; 19–23 June; Perth, Australia. SPWLA:
Society of Petrophysicists and Well-Log Analysts; 2010. p. SPWLA-2010–74900.
[37] Saidian M, Prasad M. Effect of mineralogy on nuclear magnetic resonance surface relaxivity: a
case study of middle Bakken and three forks formations. Fuel 2015;161:197–206.
[38] Nojabaei B, Johns RT, Chu L. Effect of capillary pressure on phase behavior in tight rocks and
shales. SPE Reserv Eval Eng 2013;16(3):281–9.