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NMR applications

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Nuclear magnetic resonance (NMR) log data can be analyzed independently or in combination with conventional-log and core data. As an independent logging service, NMR can provide porosity, permeability index, and complete information on fluid type and saturation of the flushed zone. Some data-interpretation methods operate in the echo-decay time domain, while others operate in the T2-relaxation domain.

Applications

The three key applications of NMR logging include:

Porosity determination

Permeability estimation

Hydrocarbon fluid typing

Other applications

Residual oil (Sxo) calculation

Estimation of residual-oil saturation is one of the oldest applications of NMR logging. Unlike resistivity-log analysis, NMR analysis does not rely on formation-water salinity to obtain water saturation. This feature provides NMR logging with a distinct advantage over conventional resistivity analysis in mixed or unknown salinity conditions—an advantage that can be extremely useful in waterflood or steamflood projects for evaluating residual-oil saturation after the flood or to look for bypassed oil. Initially, NMR evaluation of residual-oil saturation required use of a dopant (e.g., Mn-EDTA and MnCl2) to flush the invaded zone with paramagnetic ions to shorten the bulk relaxation time of the brine. This process enabled separation of the oil and water signals, leading to direct measurement of Sxo. With the combination of modern multifrequency NMR tools and new methods of analysis, such as Enhanced Diffusion Method (EDM) and time-domain analysis (TDA), the use of borehole dopant is no longer necessary.[1][2] Standalone NMR interpretation is possible in oil-based mud (OBM), but in water-base-mud (WBM), it is possible only when Swirr is known.

Viscosity evaluation

In water-wet rocks, the NMR-relaxation spectrum is controlled by viscosity[3][4]; relaxation is directly related to viscosity, η, by Eq.1:

RTENOTITLE....................(1)

For oil and water, the diffusion constant, D0, can be approximated by Eq.2:

RTENOTITLE....................(2)

where A = 2.5 for water, A = 1.3 for oil, and TK is temperature in K.

NMR properties of gas can be obtained from published charts that relate viscosity to (1) the center of the relaxation curve, (2) to an American Petroleum Inst. (API) standard value,[5] or (3) from published formulas.[6] These published sources assume that methane is the dominant component of the gas. In the absence of laboratory data at in-situ conditions, reservoir NMR properties can be estimated by use of Eq.1. One note of caution:Eqs.1' and 2 are based on "dead oil" measurements. As discussed in NMR petrophysics, the relaxation-time dependence on viscosity/temperature of live crude oil may differ significantly from correlations based on hydrocarbon liquids at ambient conditions.[7][8][9]

Anisotropy and geomechanics

NMR T1 and T2 relaxometry and derived permeability can be used to determine the Biot elastic constant, which is used for estimating pressures that are critical to [10][11] :

  • Sand control
  • Hydraulic fracturing
  • Wellbore stability
  • Determination of formation stress

Low-permeability (tight) sandstones

Field experience indicates that invasion or imbibition in tight sands is very shallow. Depending on borehole size, the diameter of invasion, and fluid properties, a mandrel tool may have sufficient DOI to measure beyond the flushed zone. A combined interpretation using both T1 and T2 can provide positive identification of fluids in these reservoirs.[12] In addition, in these tight formations, in which formation testers typically may not obtain a fluid sample within a reasonable time period, NMR fluid characterization can separate hydrocarbon from oil filtrate and other pore fluids.[13]

Heavy oil, tar sands, and tar mats

The early acquisition of reliable viscosity information is essential to efficient development of heavy-oil reservoirs. NMR logs offer a viable alternative to downhole fluid sampling for determining viscosity information in heavy-oil reservoirs.[14][15][16] The presence of tar mats in a reservoir, commonly near the bottom of the oil column, may form vertical permeability barriers and, thereby, isolate the oil leg from the water-drive aquifer. NMR logs, in conjunction with conventional logs, can provide accurate identification of tar-mat levels and viscosity estimation, from empirical relationships.[17]

Carbonates and complex lithologies

NMR-log evaluation is relatively routine in what might be termed "conventional reservoirs," namely those of homogenous lithology and uniform pore sizes, typically sandstone and chalk reservoirs.[18][19] In contrast, log evaluation of complex and heterogeneous reservoirs, with complex pore geometries, is not straightforward. These reservoirs include, in particular, the highly important Middle East carbonates, as well as other reservoirs comprised of mixed lithologies and mineralogies, or both, in which wettability may also vary. In these reservoirs, there is likely no simple relationship between petrophysical properties and porosity. Instead of a dependence on the volume of pore space, they are dependent on:

  • Typically heterogeneous pore distribution
  • Pore types
  • Pore connectivity
  • Grain sizes

This fundamental difference between siliciclastic and carbonate rocks (primarily the result of diagenetic processes) limits the applicability of routine NMR methods, especially permeability evaluation.[20] Improving NMR evaluation of carbonates has proved challenging and is the subject of a number of recent studies and proposed techniques.[21][20][22][23][24]

Pseudocapillary-pressure curves

As discussed in NMR petrophysics, establishing a correlation between NMR T2 distribution and mercury-injection capillary pressure (MICP) is fundamental to NMR interpretation and the computation of Sw. Once such correlations are established for a particular reservoir or field, pseudocapillary-pressure curves can be generated directly from the NMR-log relaxation-time distributions.[25][26][27][28]

Producibility

Accurate determination of bulk-volume-irreducible (BVI) water enables evaluation of reservoir-fluid (e.g., gas, oil, and water) contacts, production characteristics (producibilty), and the determination of net and recoverable reserves.[29][30] Furthermore, NMR-derived permeability can be used to generate idealized flow profiles across a completion interval. These profiles provide a diagnostic tool for identifying nonflowing portions of the zone and the need for remedial work.[31][32]

Combined NMR applications

NMR tools have shallow depths of investigation and provide results only for the invaded zone. NMR-log data can be integrated with core data and conventional log data (i.e., neutron, density, acoustic, and resistivity) in post-acquisition processing to provide improved determinations of reservoir rock properties, hydrocarbon storage capacity, and reservoir productivity in a variety of environments including gas-bearing and low-resistivity reservoirs. Interpretation models that include NMR data can provide more reliable results than those using only conventional logs.

The combination of NMR and deep-resistivity data provides a complete analysis of the fluids in the uninvaded zone. Resistivity measurements alone cannot distinguish between capillary-bound and movable water, but they do represent deep investigations of fluid saturation. Furthermore, resistivity-based methods are often inadequate or unreliable in reservoirs in which salinity and lithology vary. The addition of NMR-derived BVI and clay-bound-water (CBW) from the flushed or invaded zone can significantly enhance the estimation of resistivity-based fluid saturation, both in clastics and carbonates. The addition of NMR data allows the identification and evaluation of water-free production in low-resistivity formations (Fig.1).[33][34][35]

  • Fig.1 – Integrated-NMR-resistivity shaly sand analysis. Whereas resistivity logs (Track 2) read very low values and indicate that the zone below XX200 is water wet, NMR measurements show that BVI (Track 4, gray) increases with depth. However, T2 measurements (Tracks 3 and 4) suggested the presence of hydrocarbon, which testing confirmed in what turned out to be a water-free zone.

    Fig.1 – Integrated-NMR-resistivity shaly sand analysis. Whereas resistivity logs (Track 2) read very low values and indicate that the zone below XX200 is water wet, NMR measurements show that BVI (Track 4, gray) increases with depth. However, T2 measurements (Tracks 3 and 4) suggested the presence of hydrocarbon, which testing confirmed in what turned out to be a water-free zone.

The combination of conventional deep-resistivity data with NMR-derived CBW, BVI, FFI, and MPHI can greatly enhance petrophysical estimations of effective pore volume, water cut, and permeability. It is the preferred technique for identifying low-resistivity pay zones. Fig.1 presents the results of Halliburton’s MRI analysis (MRIAN) service in a turbidite sequence. The sand below XX200 depth has an average resistivity of approximately 0.5 ohm-m (Track 2) and average neutron-density porosity of approximately 38% (Track 4). A quick look, or preliminary analysis, using only the conventional data presented in Tracks 1, 2, and 4, would label this a wet zone. MRIL-NMR data are also presented in Track 1 (T2-distribution bin data), Track 2 [NMR-derived permeability (Coates)], and Track 3 (VDL presentation of T2 distribution). The MRIAN results, BVI, and FFI are presented in Track 4. BVI gradually increases with depth, suggesting that the sand is fining downward (i.e., as sand grains become finer, the volume of capillary-bound water that they hold increases). Comparison of the BVI with the resistivity profile (Track 2) shows that the resistivity decreases where the bound water increases. The MRIAN analysis clearly shows that the zone does not contain any movable water and will produce only oil. The interval below XX200 was tested and produced oil with no water.[36]

The combination of NMR fluid identification with resistivity-derived saturation provides a better understanding of hydrocarbon movement in gas monitoring, as seen in the following field example (Fig.2).

  • Fig.2– Integrated-NMR and resistivity analysis.

    Fig.2– Integrated-NMR and resistivity analysis.

NMR and logging while drilling (LWD) logs were run in a deviated Middle East light-oil carbonate reservoir to monitor gas injection. NMR logs were well suited for gas monitoring by use of the TDA technique and were not affected by formation-water salinity.[37] NMR gas-corrected porosity was in close agreement with core porosity; conventional log-porosity was low because of salinity effects. Combined interpretation of water-saturation analyses from tools with different depths of investigation identified the movable fluid present in the reservoir as WBM filtrate. Track 1 contains T2 bin data and conventional SP and gamma ray curves; Track 2 shows NMR-permeability derived from the standard Coates model and LWD resistivity; Track 3 contains a T2 distribution in a variable-density format; Track 4 contains T2 distributions of data acquired with long TW and short TW; Track 5 is the differential spectrum; Track 6 contains TDA results; and Track 7 contains MRIAN results.

NMR acoustic/density combination

Because NMR tools are affected by the lower HI in gas-bearing reservoirs, a moving tool may not fully polarize the gas, which has a long T1. Conventional acoustic and density logs are not influenced by these factors and, when used jointly with NMR logs, they can provide robust porosity evaluation.[38][39] The basic assumptions of these techniques are that the reference porosity is measured correctly (e.g., appropriate matrix density is used) and that the NMR TW is long enough to recover the water but not all of the gas. If the TW is too short, a false gas signal may be seen. One way to check whether the TW is appropriate is to log with a longer wait time (e.g., TW = 2 seconds rather than 1 second) and look for a significant difference in porosity (i.e., the porosity may be slightly higher because of increased polarization of the gas).

Nomenclature

A = pore-fluid-specific value used to approximate the diffusion constant
D0 = molecular diffusion coefficient, gauss/cm
Sw = water saturation, %
Swirr = irreducible water saturation, %
Sxo = flushed-zone saturation, %
T1 = longitudinal relaxation time, seconds
T2 = transverse relaxation time, seconds
TK = absolute temperature, K
TW = polarization (wait) time, seconds
η = fluid viscosity, cp

References

  1. ↑ Flaum, C., Bedford, J., and Kleinberg, R.L. 1998. Bound Water Volume, Permeability and Residual Oil Saturation From Incomplete Magnetic Resonance Logging Data. Presented at the SPWLA 39th Annual Logging Symposium, Keystone, Colorado, USA, 26–29 May. SPWLA-1998-UU.
  2. ↑ Akkurt, R., Marschall, D., Eyvazzadeh, R.Y. et al. 1999. Determination of Residual Oil Saturation by Use of Enhanced Diffusion. SPE Res Eval & Eng 2 (3): 303-309. SPE-56990-PA. http://dx.doi.org/10.2118/56990-PA
  3. ↑ Freedman, R., Heaton, N., Flaum, M. et al. 2002. Wettability, Saturation, and Viscosity Using the Magnetic Resonance Fluid Characterization Method and New Diffusion-Editing Pulse Sequences. Presented at the SPE Annual Technical Conference and Exhibition, San Antonio, Texas, USA, 29 September-2 October. SPE-77397-MS. http://dx.doi.org/10.2118/77397-MS
  4. ↑ Cory, D.G., Sen, P.N., Guzmn-Garcia, A.G. et al. 2002. Nmr Identification Of Fluids And Wettability In Situ In Preserved Cores. Petrophysics 43 (1): 13. SPWLA-2002-v43n1a1.
  5. ↑ Akkurt, R., Tutunjian, P.N., Guillory, A.J. et al. 1996. NMR Logging of Natural Gas Reservoirs. The Log Analyst 37 (6): 33. SPWLA-1996-v37n6a1.
  6. ↑ Prammer, M.G., Mardon, D., Coates, G.R. et al. 1995. Lithology-Independent Gas Detection by Gradient-NMR Logging. Presented at the SPE Annual Technical Conference and Exhibition, Dallas, 22-25 October. SPE-30562-MS. http://dx.doi.org/10.2118/30562-MS
  7. ↑ Winkler, M., Freeman, J., and Appel, M. 2004. The Limits Of Fluid Property Correlations Used in NMR Well Logging; an Experimental Study of Reservoir Fluids at Reservoir Conditions. Presented at the SPWLA 45th Annual Logging Symposium, Noordwijk, The Netherlands, 6–9 June. SPWLA-2004-DD.
  8. ↑ Hirasaki, G.J., Lo, S.-W., and Zhang, Y. 2003. NMR properties of petroleum reservoir fluids. Magn. Reson. Imaging 21 (3–4): 269-277. http://dx.doi.org/10.1016/S0730-725X(03)00135-8
  9. ↑ Chen, S., Zhang, G., Kwak, H. et al. 2004. Laboratory Investigation of NMR Crude Oils and Mud Filtrates Properties in Ambient and Reservoir Conditions. Presented at the SPE Annual Technical Conference and Exhibition, Houston, 26-29 September. SPE-90553-MS. http://dx.doi.org/10.2118/90553-MS
  10. ↑ Klimentos, T. 2003. NMR Applications in Petroleum Related Rock-Mechanics: Sand Control, Hydraulic Fracturing, Wellbore Stability. Presented at the SPWLA 44th Annual Logging Symposium, Galveston, Texas, USA, 22–25 June. SPWLA-2003-HHH.
  11. ↑ van der Zwaag, C.H., Veliyulin, E., Skjetne, T. et al. 2003. Deformation and Failure of Rock Samples Probed by T1 and T2 Relaxation. Magn. Reson. Imaging 21 (3–4): 405-407. http://dx.doi.org/10.1016/S0730-725X(03)00151-6
  12. ↑ Mullen, M. et al. : Mullen, M., Bray, J., and Bonnie, R. 2005. Fluid Typing With T1 NMR: Incorporating T1 and T2 Measurements for Improved Interpretation in Tight Gas Sands and Unconventional Reservoirs. Presented at the SPWLA Annual Logging Symposium, New Orleans, 26–29 June. SPWLA-2005-III.
  13. ↑ Longis, C., Vignau, S., and White, J.H. 2005. NMR and Capture Spectroscopy Help Resolve Producibility and Fluid Distribution in the North Alwyn Triassic. Presented at the SPE Annual Technical Conference and Exhibition, Dallas, 9-12 October. SPE-96609-MS. http://dx.doi.org/10.2118/96609-MS
  14. ↑ Latorraca, G.A., Carison, R.M., Stonard, S.W. et al. 1999. Heavy Oil Viscosity Determination Using NMR Logs. Presented at the SPWLA Annual Logging Symposium, Oslo, Norway, 30 May–3 June. SPWLA-1999-PPP.
  15. ↑ Galford, J.E. and Marschall, D.M. 2000. Combining NMR and Conventional Logs to Determine Fluid Volumes and Oil Viscosity in Heavy-Oil Reservoirs. Presented at the SPE Annual Technical Conference and Exhibition, Dallas, 1-4 October. SPE-63257-MS. http://dx.doi.org/10.2118/63257-MS
  16. ↑ Seccombe, J., Bonnie, R.J.M., Smith, M. et al. 2005. Ranking Oil Viscosity in Heavy-Oil Reservoirs. Presented at the SPE/PS-CIM/CHOA International Thermal Operations and Heavy Oil Symposium, Calgary, 1-3 November. SPE-97935-MS. http://dx.doi.org/10.2118/97935-MS
  17. ↑ Nascimento, J.d.D.S. and Gomes, R.M.R. 2004. Tar Mats Characterization from NMR and Conventional Logs, Case Studies in Deepwater Reservoirs, Offshore Brazil. Presented at the SPWLA 45th Annual Logging Symposium, Noordwijk, The Netherlands, 6–9 June. SPWLA-2004-FF.
  18. ↑ Prammer, M., Menger, S., Knizhnik, S. et al. 2003. Directional Resonance: New Applications for MRIL. Presented at the SPE Annual Technical Conference and Exhibition, Denver, 5-8 October. SPE-84479-MS. http://dx.doi.org/10.2118/84479-MS
  19. ↑ Bustos, U.D., Ortiz, A.C., Breda, E.W. et al. 2004. Detecting Restricted Diffusion Effect when Identifying Hydrocarbons with NMR Logs. Presented at the SPE Annual Technical Conference and Exhibition, Houston, 26-29 September. SPE-90089-MS. http://dx.doi.org/10.2118/90089-MS
  20. ↑ 20.0 20.1 Westphal, H., Surholt, I., Kiesl, C. et al. 2005. NMR Measurements in Carbonate Rocks: Problems and an Approach to a Solution. Pure Appl. Geophys. 162 (3): 549-570. http://dx.doi.org/10.1007/s00024-004-2621-3
  21. ↑ Sun, B. and Dunn, K.-J. 2005. A global inversion method for multi-dimensional NMR logging. J. Magn. Reson. 172 (1): 152-160. http://dx.doi.org/10.1016/j.jmr.2004.10.003
  22. ↑ Rose, D., Hansen, P.M., Damgaard, A.P. et al. 2003. A Novel Approach to Real Time Detection of Facies Changes in Horizontal Carbonate Wells Using LWD NMR. Presented at the SPWLA 44th Annual Logging Symposium, Galveston, Texas, USA, 22–25 June. SPWLA-2003-CCC.
  23. ↑ Chen, S., Mette, M., Hursan, G. et al. 2005. Simple, Robust NMR-Based Indicators for Detection of Hydrocarbon Gas or Oil, Borehole Contamination, and Vugs. Presented at the SPE Annual Technical Conference and Exhibition, Dallas, 9-12 October. SPE-96409-MS. http://dx.doi.org/10.2118/96409-MS
  24. ↑ Fleury, M., Al-Nayadi, K., and Boyd, D. 2005. Water Saturation from NMR, Resistivity and Oil Base Core in a Heterogeneous Middle East Carbonate Reservoir. Presented at the SPWLA 46th Annual Logging Symposium, New Orleans, 26–29 June. Paper JJJ.
  25. ↑ Volokitin, Y., Hofman, J., Slijkermail, W. et al. 2001. Constructing Capillary Pressure Curves from NMR Log Data in the Presence of Hydrocarbons. Petrophysics 42 (4): 334.
  26. ↑ Glorioso, J.C., Aguirre, O., Piotti, G. et al. 2003. Deriving Capillary Pressure and Water Saturation from NMR Transversal Relaxation Times. Presented at the SPE Latin American and Caribbean Petroleum Engineering Conference, Port-of-Spain, Trinidad and Tobago, 27-30 April. SPE-81057-MS. http://dx.doi.org/10.2118/81057-MS
  27. ↑ Grattoni, C.A. et al. 2003. An Improved Technique for Deriving Drainage Capillary Pressure from NMR T2 Distributions. Presented at the International Symposium of the Society of Core Analysts, Pau, France, 21–24 September. SCA 2003-25.
  28. ↑ Dastidar, R., Rai, C., and Sondergeld, C. 2004. Integrating NMR With Other Petrophysical Information to Characterize a Turbidite Reservoir. Presented at the SPE Annual Technical Conference and Exhibition, Houston, 26-29 September. SPE-89948-MS. http://dx.doi.org/10.2118/89948-MS
  29. ↑ Corbelleri, A., Ortea, J., Lenge, D. et al. 1996. Application of the Magnetic Resonance Logging in San Jorge Basin (Argentina). Presented at the SPWLA Annual Logging Symposium, New Orleans, 16–19 June. SPWLA-1996-VV.
  30. ↑ Davis, B., McDonald, T., and Aly, M. 2002. Practical Applications of NMR Technology Enhance Formation Evaluation, Testing and Completion Decisions. Presented at the SPE Western Regional/AAPG Pacific Section Joint Meeting, Anchorage, Alaska, 20-22 May. SPE-76717-MS. http://dx.doi.org/10.2118/76717-MS
  31. ↑ Soliman, M.Y., Creel, P., Rester, S. et al. 2000. Technology Integration of Conformance and Magnetic Resonance Imaging Enhances Stimulation Treatment. Presented at the SPE Permian Basin Oil and Gas Recovery Conference, Midland, Texas, USA, 21-23 March. SPE-59530-MS. http://dx.doi.org/10.2118/59530-MS.
  32. ↑ Weiland, J., Teff, C., and Donovan, G. 2004. Integrating NMR, Rock Mechanics, and Production Evaluation to Optimize Hydrocarbon Production in Deepwater GOM. Presented at the SPWLA 45th Annual Logging Symposium, Noordwijk, The Netherlands, 6–9 June. SPWLA-2004-VVV.
  33. ↑ Chitale, D.V., Day, P.I., and Coates, G.R. 1999. Petrophysical Implications of Laboratory NMR and Petrographical Investigation on a Shaly Sand Core. Presented at the SPE Annual Technical Conference and Exhibition, Houston, 3-6 October. SPE-56765-MS. http://dx.doi.org/10.2118/56765-MS
  34. ↑ Hodgkins, M.A. and Howard, J.J. 1999. Application of NMR logging to reservoir characterization of low-resistivity sands in the Gulf of Mexico. AAPG Bull. 83 (1): 114-127.
  35. ↑ Ostroff, G.M. and Shorey, D.S. 1999. Integration of NMR and Conventional Log Data For Improved Petrophysical Evaluation of Shaly Sands. Presented at the SPWLA 40th Annual Logging Symposium, Oslo, Norway, 30 May-3 June. Paper OOO.
  36. ↑ Marschall, D., Gardner, J.S., Mardon, D. et al. 1995. Method for Correlating NMR Relaxometry and Mercury Injection Data. Presented at the Society of Core Analysts International Symposium, San Francisco, California, USA, 12–14 September. SCA-9511.
  37. ↑ Coates, G.R., Xiao, L.Z., and Prammer, M.G. 1999. NMR Logging: Principles and Applications, 234. Houston: Halliburton Energy Services.
  38. ↑ Freeman, J.J., Freedman, R., Cao Minh, C. et al. 1998. Combining NMR and Density Logs for Petrophysical Analysis in Gas-Bearing Formations. Presented at the SPWLA 39th Annual Logging Symposium, Denver, 26–29 May. Paper II.
  39. ↑ Minh, C.C., Gubelin, G., Ramamoorthy, R. et al. 1999. Sonic-Magnetic Resonance Method: A Sourceless Porosity Evaluation in Gas-Bearing Reservoirs. Presented at the SPE Annual Technical Conference and Exhibition, Houston, 3-6 October. SPE-56767-MS. http://dx.doi.org/10.2118/56767-MS

Noteworthy papers in OnePetro

Cao Minh, C., Crary, S. F., Zielinski, L., Liu, C., Jones, S., & Jacobsen, S. J. (2012, January 1). 2D-NMR Applications in Unconventional Reservoirs. Society of Petroleum Engineers. doi:10.2118/161578-MS

Altunbay, M., Ismail, S. B., aula, nurul, & Das, S. (2012, January 1). Translating Petrophysics to Engineering Economics. Society of Petroleum Engineers. doi:10.2118/159191-MS

Minh, C. C., Jaffuel, F., Poirier, Y., Haq, S. A., Baig, M. H., & Jacob, C. (2011, May 14). Quantitative Estimation Of Formation Damage From Multi-Depth Of Investigation Nmr Logs. Society of Petrophysicists and Well-Log Analysts.

Toumelin, E., Sun, B., Manzoor, A., Keele, D., Wasson, M., & Sagnak, A. (2011, May 14). Revisiting Log-Inject-Log Nmr For Remaining Oil Determination: A Field Application Of T2-D Nmr In The Permian Basin. Society of Petrophysicists and Well-Log Analysts.

Chen, S., Di Rosa, D. E., Gyllensten, A., Georgi, D., & Tauk, R. S. (2008, April 1). Use of the NMR Diffusivity Log To Identify and Quantify Oil and Water in Carbonate Formations. Society of Petroleum Engineers. doi:10.2118/101396-PA

Gladkikh, M., Chen, J., & Chen, S. (2008, January 1). Method Of Determining Formation Grain Size Distribution From Acoustic Velocities And Nmr Relaxation Time Spectrum. Society of Petrophysicists and Well-Log Analysts.

Nicot, B., Fleury, M., & Leblond, J. (2007, January 1). Improvement Of Viscosity Prediction Using Nmr Relaxation. Society of Petrophysicists and Well-Log Analysts.

Galarza, T., Giordano, S., Fontanarosa, M. B., Saubidet, M. E., Altunbay, M., Saavedra, B. E., & Romero, P. A. (2007, January 1). Pore-Scale Characterization and Productivity Analysis by Integration of NMR and Openhole Logs: A Verification Study. Society of Petroleum Engineers. doi:10.2118/108068-MS

Akkurt, R., Kersey, D. G., & Zainalabedin, K. A. (2006, January 1). Challenges for Everyday-NMR: An Operator's Perspective. Society of Petroleum Engineers. doi:10.2118/102247-MS

Looyestijn, W. J., & Hofman, J. (2005, January 1). Wettability Index Determination from NMR Logs. Society of Petroleum Engineers. doi:10.2118/93624-MS

Altunbay, M., Sy, R., & Martain, R. (2003, January 1). Formation Damage Assessment and Remedial Economics from Integration of NMR and Resistivity Log data. Society of Petroleum Engineers. doi:10.2118/84384-MS

Altunbay, M., Martain, R., & Robinson, M. (2001, January 1). Capillary Pressure Data From NMR Logs And Its Implications On Field Economics. Society of Petroleum Engineers. doi:10.2118/71703-MS

Romero, P., & Quintairos, M. (2001, January 1). New Applications of NMR in Understanding Heavy-Oil Behavior. Society of Petroleum Engineers. doi:10.2118/69696-MS

Crary, S., Pellegrin, F., & Simon, B. (1997, January 1). Nmr Applications In The Gulf Of Mexico. Society of Petrophysicists and Well-Log Analysts

Chang, D., Vinegar, H. J., Morriss, C., & Straley, C. (1994, January 1). Effective Porosity, Producible Fluid And Permeability In Carbonates From Nmr Logging. Society of Petrophysicists and Well-Log Analysts.


External links

Use this section to provide links to relevant material on websites other than PetroWiki and OnePetro

See also

Nuclear magnetic resonance (NMR) logging

NMR petrophysics

NMR logging tools

Porosity determination with NMR logging

Permeability estimation with NMR logging

Fluid typing with NMR logging

Planning for NMR log data collection

PEH:Nuclear_Magnetic_Resonance_Applications_in_Petrophysics_and_Formation_Evaluation

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