A, B, C, D, E, and F = minerals
and fluid Volumes to be evaluated1,2,3,4,5,6, and 7 = tool responses α _{i,j }= response parameters
2: M = Mdw + Kdw * (0.258 * Y + 0.2 * (1 - e^(-16. 4 * Y))) Then solve for SWt from: 3: COND = (1 / A) * PHIt^M * SWt^N * (((SWt – SWb) / (SWt)) * CONDw + (CONDbw * SWb / SWt))
CECclay = clay cation exchange capacity (meq/cm3)
DENSclay = clay density (g/cc) Vcbw = clay bound water volume
1.
Cluster 2.
Assign lithologies to each cluster 3.
Model to obtain (main goals): a.
Porosity b.
Sw c.
Perm d.
Net Pay 4.
Assign mineralogy to each mode
(= cluster = rock type) 5.
Compute matrix density and matrix response for NPHI,
PEF, GR, DT; Compute
matrix CEC and So 6.
Determine porosity
(TPOR, VIRR, VWB) & Sw 7.
Compute porosity response for NPHI, PEF, DT
8.
Compute bulk rock RHOB, NPHI, PEF, DT, GR
for each mode.
Use clustering probability assignmentsalong with mean values of RHOB, NPHI compute RHOB, NPHI profiles, core sample RHOB = Sum (Pi * mean RHOBi) 9.
Check “balances” (objective functions)
a. Sw <=1.0
b. In “tight” rocks TPOR ~ (VIRR + VWB) and Ro ~ Rt c.
M_GD ~ G_GDd. M_RHOB ~ G_RHOB e. M_NPHI ~ G_NPHI Add (if whole core data is
available): f.
Modeled core por, perm, grain density, surface area =
Core values Also, add (if logs are
available):
g.
M_PEF ~ G_PEF,
and M_DT ~ G_DT 10.
Adjust mineralogy as needed to obtain balances 11.
Iterate on porosity, permeability, Sw, net pay ….
12.
Calibrate against core data
(Por, Perm, GD)
(i.e., adjust inputs as needed to “match”) 13.
Iterate on porosity, permeability, Sw, net pay ….
14.
Compute complete profiles for RHOB, NPHI ...Model RHOB = (matrix density)(1-TPOR) + (TPOR)(Sw)(RHOwater)(1-Xmf) + (TPOR)(1-Sw)(GOR) (RHOgas)(1-Xmf) + (TPOR)(1-Sw)(1-GOR)(RHOoil)(1-Xmf) + (TPOR)(RHOfiltrate)(Xmf)
where Xmf = fractional mud filtrate
invasion 15.
Rw can vary with rock type 16.
Adjust “invasion factor”
(for NPHI balance) 17.
Set probability “target”
(eliminates “fuzzy” data points) |
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