calculation procedure for exponent of capillary pressure curve from laboratory data

[hojbarnaz]

[QUOTE=itag;126509]Folks
I have an interest in cap pressure data - and had a quick look at the data.
Firstly some of the data is just plain "bad" - particularly the last 2 ( high perm) sets as Sw is lowered. Now the "why"

Centrifuge cap pressure require a model-based interpretation in the lab. The original 'Hasler Bruner' theory used in the early 90's by one well known lab produces quite different results to that based on 'Forbes' particularly when the Pc data doesn't asymptote. (check what method was used for your data). Secondly - if you spin a sample too fast - ie at very high rpm , you exceed recommended Bond # parameters - and literally desaturate the core beyond what is reasonable for the reservoir. In that regard saturation of 1% are entirely possible in the lab ... they area just meaningless for your intended application. My immediate thought would be that this is likley what happened - but without knowing the centrifuge dimensions/conditions this is guesswork. Either way these samples are not meaninful at lower Sw's

Looking at the rest of your data - sample 183281 plots "out of perm order". There may be reasons for this - eg different facies. There is also another reason that I have seen reported in the literature and that is incomplete sample cleaning /preparation prior to testing that has left many small pores non-water wet. See SCA2006-16 for a very convincing discussion of this effect ( and how simple hg cap-pressure measurement can help identify this effect ). SCA are papers presented by the Society of Core Analysts and are freely available on the web.

If we discard this out-of-order sample, this leaves you with 3 possible candidates.

The next analysis needs to define a normalised saturation S*. Your formulaes above need to be adjusted for drainage conditions that start from Sw=1. use S*=(Sw-Swir)/(1-Swir). You may need to iterate a bit on Swir for each data set - but you can use the lowest Sw in most cases. For sample 2 I used 0.28

No simply plots pc vs S* on a log-log plot seeking straight line trends ( for the exponents). We note some curvature at very high Sw - which again we tend to discount if "spin-up" a time offset effects impact experiment. Whats left is surprisingly OK. I get a slope of about -0.8 which implies a Lambda of 1.25 ( which is also reasonable)

I ended up fitting J*ScosT= 9.3*(S*)^-1/1.25 to the valid data. 2 out of 3 match quite well and the third is acceptable.
Sample 183291 plots up OK using Swir of 0.08.

The 3 remaining data sets make reasonable sense ... they have the right ordering of entry pressure effects
dear
itag
if you could provide your analysis file , will be helpful to understand and realize on about the procedure you speak, as i am layman in this subject and learning from experts like you little bit

[elvirus]

Can any body help me solve for Corey's exponents?
Keo=0.204;
Kew=0.128;
Sw=[14.3 63.3 66.0 68.1 68.7 69.1 72.9 74.8 76.4 76.9 77.8 79.4]';
Kro=[1.0 0.12 0.0513 0.0161 0.0113 0.0094 0.0025 0.0011 0.0004 0.0002 0.0000 0.0000]';
Krw=[0.000 0.342 0.376 0.398 0.400 0.402 0.436 0.464 0.503 0.530 0.529 0.627]';