Phisand 0
Phisand NMR 0.5
GR 700 OBMI Sand Shale 1
Neutron Density 0.4 0.2 0
Rv , Rh 0
Anisotropy 10 100 0 510 15 0
T2 Distribution
10 100 1,000 Cutoff
0
Fsand
Fsand NMR 0.5
1
Rt Scanner Rsand NMR Rsand
0 10 100 0
NMR Fluids 0.2 0.4 Oil Porosity
OBM Water Total
HC Volume 0 0.2 0.4
Rt Scanner Data
AIT Data NMR Data
103 Fshale
102 Rsand 101 800 100
Rshale-v = 3.4 Rshale-h = 0.58
Shale
10–1 10–1 900 100 101 Rh, ohm.m 102 103
1,000
> Integration of data in an anisotropic reservoir. A laminated reservoir is inferred from the OBMI image data (between Tracks 1 and 2). Processing began by calculating sand volumes (Track 1) from density-neutron and NMR data. Horizontal, Rh, and vertical, Rv, resistivities (Track 3), derived from the Rt Scanner tool, were used to compute the electrical anisotropy (Track 4, green). The shales and the laminated sand-shale intervals exhibit anisotropy. The T2 distributions from the NMR data (Track 5) indicate bimodal fluid distributions in the intervals where sand is present, but not in the shales. Free fluid is to the right of the T2 cutoff, and clay-bound fluid associated with the shale is to the left. Sand fractions were computed with inputs from both the NMR and the Rt Scanner data (Track 6). Sand resistivity (Track 7) was calculated from Rt Scanner data using intervals
program of the field, and use of three-shell data has been adopted as a best practice. However, one limitation of the MR Scanner
tool’s ability to identify fluid type came to light during the analysis of the data from this field. NMR fluid properties, acquired from just a few inches into the formation, can be of little help in identifying fluid contacts when invasion exceeds the 4.0-in. DOI of Shell No. 8. In these cases, MDT modular formation dynamics tester fluid gradients and DSTs are required to provide the needed information.
Resolution Solution
The trend in log interpretation and tool design has been toward resolving and measuring increasingly thinner beds. This is critical in the interpretation
19. Cao Minh C and Sundararaman P: “NMR Petrophysics in Thin Sand/Shale Laminations,” paper SPE 102435, presented at the SPE Annual Technical Conference and Exhibition, San Antonio, Texas, September 24–27, 2006.
Cao Minh C, Joao I, Clavaud J-B and Sundararaman P: “Formation Evaluation in Thin Sand/Shale Laminations,” paper SPE 109848, presented at the SPE Annual Technical Conference and Exhibition, Anaheim, California, USA, November 11–14, 2007.
with free fluid as defined by the MR Scanner tool. The NMR fluid saturations indicate oil, water and OBM filtrate (Track 8). Hydrocarbon (HC) volumes are displayed for comparison (Track 9). They are computed from NMR data (green), the Rt Scanner data (red) and Archie’s water saturation equation using traditional AIT array induction imager tool outputs derived from the Rt Scanner data (black). Traditional Archie saturation underestimated the HC volume throughout the interval, significantly reducing the calculated net pay and hydrocarbon in place. Finally, the petrophysicist identified the laminated pay intervals using a modified Klein plot (inset) that incorporates Rt Scanner data, NMR data and high-resolution porosity measurements. Productive zones are highlighted on the log (Track 3, magenta).
of anisotropic, laminated sand-shale sequences. However, it is not possible to resolve extremely thin laminations with NMR tools because of the general requirement to stack successive measure ments to achieve an adequate signal-to-noise ratio. With a CMR tool, the smallest aperture window is a 6-in. [15.2-cm] station measurement. The MR Scanner tool’s main-antenna measure ment window is 18 in. Recent developments demonstrate that even at this lower resolution, NMR data are still useful in analyzing and interpreting laminated sequences. NMR data provide complementary petrophysical measure ments of the reservoir fluid properties that resistivity and porosity measurements cannot.19
There are three general methods used to analyze thin-bed reservoirs using well logs.20
20. Claverie M, Azam H, Leech R and Van Dort G: “A Comparison of Laminated Sand Analysis Methods— Resistivity Anisotropy and Enhanced Log Resolution from Borehole Image,” presented at the Petroleum Geology Conference and Exhibition (PGCE), Kuala Lumpur, November 27–28, 2006.
21. Anderson B, Barber T, Leveridge R, Bastia R, Saxena KR, Tyagi AK, Clavaud J-B, Coffin B, Das M, Hayden R, Klimentos T, Cao Minh C and Williams S: “Triaxial Induction—A New Angle for an Old Measurement,” Oilfield Review20, no. 2 (Summer 2008): 64–84.
Traditionally, imaging logs are used to characterize the laminations, separating sand from shale. Other, lower-resolution data are then deconvolved using the higher-resolution image data. These outputs are used in Archie’s equation to compute water saturation. One drawback to this method is that imaging tools make very shallow readings and thus rely on good borehole conditions to acquire quality data. Furthermore, full quantitative analysis, using deconvolution techniques, is often inconclusive, and fluid properties and type are rarely quantifiable.
In a second method, NMR data quantify the type and volume of fluids in a reservoir section. But since it is not possible to resolve thin beds with NMR tools, this method lumps the fluids together and differentiates bound fluid from free fluid.
22. For more on the use of modified Klein plots: Cao Minh C, Clavaud J-B, Sundararaman P, Froment S, Caroli E, Billon O, Davis G and Fairbairn R: “Graphical Analysis of Laminated Sand-Shale Formations in the Presence of Anisotropic Shales,” Petrophysics49, no. 5 (October 2008): 395–405.
23. Hürlimann MD, Freed DE, Zielinski LJ, Song YQ, Leu G, Straley C, Cao Minh C and Boyd A: “Hydrocarbon Composition from NMR Diffusion and Relaxation Data,” Transactions of the SPWLA 49th Annual Logging Symposium, Edinburgh, Scotland, May 25–28, 2008, paper U.
22 Oilfield Review
Depth, m
20 ft
Pay Zones
Rv, ohm.m
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