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Extreme Thin-Beds Formation Evaluation*

 

Chanh Cao Minh1 and Olivier Billon2

Search and Discovery Article #40403 (2009)

Posted April 6, 2009

 

*Adapted from oral presentation at AAPG International Conference and Exhibition, Cape Town, South Africa, October 26-29, 2008

 

1Schlumberger, Katy, Texas (mailto:[email protected] )

2Total, Luanda, Angola

 

Abstract

 

Extreme thin-beds are defined as shale volume fraction exceeding 90%. In these cases, effective porosity in the sand layers rarely exceeds 5 p.u. The combination of high shale content and low porosity pushes formation evaluation to its limits.  Not only are new technology tools needed, but a good interpretation procedure is important as small parameters changes can alter the petrophysical results dramatically. Finally, control of the petrophysical results is also critical as the thin-bedded zones are seldom tested due to their low storage volume and producibility.

 

We present a thin-bed case in West Africa where the shale volume fraction averages 94% and the sand effective porosity averages 2 p.u. Other complications include the presence of numerous tight cemented streaks and bad holes. We use a triaxial induction and NMR logs in the formation evaluation of extreme thin-beds. The workflow explains how to:

 

·   recognize the extreme thin beds from the above logs,

·   choose the shale point in a formation that averages 90% shale volume,

·   select the shale Previous HitanisotropyNext Hit parameters and the shale porosity,

·   discriminate tight streaks,

·   overcome bad holes,

·   estimate the fluid type and hydrocarbon content in the thin sands.

 

The primary goal is to establish the vertical continuity of the hydrocarbon column for the field, rather than the reserves in the thin beds.

 

 

uAbstract

uFigure Captions

uThin beds analysis

uExtreme thin beds

uConclusions

uReferences

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

uAbstract

uFigure Captions

uThin beds analysis

uExtreme thin beds

uConclusions

uReferences

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

uAbstract

uFigure Captions

uThin beds analysis

uExtreme thin beds

uConclusions

uReferences

 

 

 

 

 

 

Figure Captions

 

fig01

Figure 1. Laminated Sand/Shale shows the characteristics T2 bimodal distribution. The experiment shows how NMR can be used to estimate sand layers that are physically below the measurement aperture. Diffusion log shows oil in the thin beds.

fig02

Figure 2. Hydrocarbon-bearing sand laminations show large Previous HitanisotropyNext Hit about 6. Water-bearing sands have Previous HitanisotropyNext Hit about 1. Shales have Previous HitanisotropyNext Hit about 4. The crossplot on the right shows the laminated pay (magenta), water (cyan) and shale (green).

fig03

Figure 3. Combining NMR and Rv, Rh for quantitative thin beds analysis. The 4 critical sand porosity (Phisand), N/G (Fsand), resistivity (Rsand) and hydrocarbon content (HC vol) are cross-validated between NMR and Previous HitanisotropyNext Hit techniques. Verification with imaging log and core.

fig04

Figure 4. Schema of extreme thin beds definition (Fsh > 90% or Phi sand < 5 p.u.).

fig05

Figure 5. Example of extreme thin beds evaluation using OH logs, Rv/Rh, Hi-Res NMR, Fluid NMR and Resistivity imaging logs.

 Thin Beds Analysis

 

There are 3 methods of choice to analyze thin beds from well logs. The conventional method is to use imaging logs, look for fine layering, then deconvolve the low-resolution logs. Since imaging logs are shallow, they rely on good borehole conditions. Net-to-Gross can be obtained, but full quantitative analysis of porosity/saturation as well as fluid type/property remains difficult.

 

The second method is to use NMR logs. It has been shown that shale porosity averages into the ‘bound fluid’ region and sand porosity averages into the ‘free fluid’ region of the T2 spectrum. Therefore, laminated sand/shale shows the characteristic T2 bimodal distribution as seen in Figure 1 . NMR diffusion also identifies fluid type, property and volume in the thin beds.

 

The third method is to use ‘horizontal’ resistivity, Rh and ‘vertical’ resistivity, Rv. It has been shown that hydrocarbon-bearing thin sands show high Previous HitanisotropyTop (Rv/Rh) whereas water-bearing sands do not (Figure 2). Combining NMR and Rv/Rh allows the petrophysicist to control the 4 critical sand parameters: sand fraction (or Net-to-Gross), sand porosity, sand resistivity, and total hydrocarbon type and volume (Figure 3).

 

Extreme Thin Beds

 

Extreme thin beds are defined as having more than 90% shale fraction or less than 5 p.u. effective sand porosity. An example is shown in Figure 4. Consider a 1cm-thick 30 p.u. sand layer in a 6 in (15 cm) data sampling interval with zero effective shale porosity. The sand fraction is 1/15 = 6.6%. The shale fraction is 14/15 = 93.4%. The effective sand porosity is 30/15 = 2 p.u. Such a sand/shale lamination qualifies as extreme thin beds. They are commonly ignored in classical formation evaluation using conventional density, neutron, gamma-ray and resistivity logs.

 

In these situations, fluid type matters more than reserves in the thin beds, mainly to assess the vertical continuity of the hydrocarbon column between the adjacent thick sands. For example, one would like to know if there is a single contact or multiple contacts? Where does the fluids change occur? What does it change to? These answers can impact the reservoir model and hence, the field development plan.

 

Conclusions

 

The workflow in extreme thin beds is summarized below:

 

·Recognition: use Imaging, Rv/Rh, NMR relaxation logs.

·Fluid analysis: Rv/Rh , NMR relaxation-diffusion logs.

·Quantitative analysis: combination of Rv/Rh and NMR for consistent results. Bad holes are

overcome by using deep NMR reading. Tight streaks that have zero porosity are also

discriminated from porous sand layers using NMR.

 

The wish-list includes full cores, sampling with Wireline Formation Testers and production tests.

 

References

 

Cao-Minh, C., J.-B. Clavaud, P. Sundararaman, S. Froment, E. Caroli, O. Billon, G. Davis, and R. Fairbairn, 2007, Graphical analysis of laminated sand/shale formations in the presence of anisotropic shale, World Oil, v. 228/9, p. 37-44.

 

Cao-Minh, C., I. Joao, J.-B. Clavaud, and P. Sundararaman, 2007, Formation evaluation in thin sand/shale laminations, SPE 109848.

 

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