Formation fluid characterization using flowline viscosity and density data an oil-based mud environment

• US 7,134,500 B2
• Filed: 12/19/2003
• Issued: 11/14/2006
• Est. Priority Date: 12/19/2003
• Status: Active Grant

• Current Assignee: Schlumberger Technology Corporation (Schlumberger NV)
• Original Assignee: Schlumberger Technology Corporation (Schlumberger NV)
• Inventors: Betancourt, Soraya Sofia, Ramakrishnan, Terizhandur S.
• Primary Examiner(s): Tsay, Frank
• Application Number:
  US10/741,078
• Publication Number:
  US 20050133261A1
• Time in Patent Office: 1,061 Days
• Field of Search: None
• US Class Current: 166/369
• CPC Class Codes: E21B 49/0875 determining specific fluid parameters
• CPC Class Codes: G01N 11/00 Investigating flow properties of materials, e.g. viscosity, plasticity; Analysing materials by determining flow properties
• CPC Class Codes: G01N 33/2823 raw oil, drilling fluid or polyphasic mixtures hydrocarbon content of earth materials G01N33/241; prospecting G01V; drilling per se E21B
• CPC Class Codes: G01N 9/36 Analysing materials by measuring the density or specific gravity, e.g. determining quantity of moisture methods of measurement in general G01N9/02 - G01N9/32

Abstract

A method for characterizing formation fluid using flowline viscosity and density data in an oil-based mud environment includes: making an initial estimate of the density and viscosity of the individual components of the sampled fluid; measuring the volume fractions, density, and viscosity of the total mixture of formation fluid; computing the density and viscosity of the total mixture using the estimate and the measured volume fractions; comparing the computed values with the measured values; and updating the estimate based on the comparison until convergence. The process is repeated as additional data are acquired until the converged computed values differ only by an acceptable amount.

Claims

1. A method for characterizing formation fluid using flowline viscosity and density data in an oil-based mud (OBM) environment, said method comprising:

a) providing an initial estimate of at least one of the density and viscosity of the crude oil and oil filtrate components of the mixture of formation fluid and OBM;

b) measuring the volume fractions, and at least one of the density and viscosity of the total mixture of formation fluid and OBM;

c) computing at least one of the density and viscosity of the total mixture using the estimate of at least one of the density and viscosity and the measured volume fractions;

d) comparing the at least one of the computed density and viscosity of the total mixture with the at least one of the measured density and viscosity of the total mixture; and

e) charactexizing the formation fluid by updating the estimate of the at least one of the density and viscosity of the individual components of the formation fluid based on the comparison of the computed density and viscosity of the total mixture with the measured density and viscosity of the total mixture.

2. The method according to claim 1, wherein:

said step of measuring is performed with an optical fluid analyzer.

3. The method according to claim 1, further comprising:

f) normalizing the volume fraction of crude oil and oil filtrate prior to computing density, wherein

said step of computing density is performed according to

ρ

_t=ρ

_co{circumflex over (z)}_co(1−

z_w)+ρ

_of{circumflex over (z)}_of(1−

z_w)+ρ

_wz_w

where ρ

_t is density of the total mixture, ρ

_co is the density of crude oil, {circumflex over (z)}_co is the normalized volume fraction of crude oil, z_co is the volume fraction of water, ρ

_of is the density of oil filtrate, {circumflex over (z)}z_of is the normalized volume fraction of oil filtrate, and ρ

_w is the density of water.

4. The method according to claim 3, wherein:

the normalized volume fraction of crude oil {circumflex over (z)}_co is computed according to

${\hat{z}}_{\mathrm{co}}=\frac{z_{\mathrm{co}}}{z_{\mathrm{co}}+z_{\mathrm{of}}}$

where z_co is the volume fraction of crude oil, and z_of is the volume fraction of oil filtrate.

5. The method according to claim 4, wherein:

the normalized volume fraction of oil filtrate {circumflex over (z)}_of is computed according to.

${\hat{z}}_{\mathrm{of}}=\frac{z_{\mathrm{of}}}{z_{\mathrm{co}}+z_{\mathrm{of}}}.$

6. The method according to claim 1, wherein:

said step of computing viscosity is performed according to

$\frac{{\mathrm{\mu <br><br>}}_t}{{\mathrm{\mu <br><br>}}_o}=1+z_w\left(\frac{{\mathrm{\mu <br><br>}}_o+\frac{5}{2}<br><br>{\mathrm{\mu <br><br>}}_w}{{\mathrm{\mu <br><br>}}_o+{\mathrm{\mu <br><br>}}_w}\right)$

where μ

_t is the viscosity of the total mixture, μ

_o is the viscosity of the crude oil and oil filtrate mixture, z_w is the volume fraction of water, and μ

_w is the viscosity of water.

7. The method according to claim 5, wherein:

the volume fraction of water is not measured but is computed according to

$z_w=\frac{z_w^0<br><br>{\hat{z}}_{\mathrm{of}}}{1+z_w^0<br><br>{\hat{z}}_{\mathrm{of}}-z_w^0}$

where z_w⁰ is the volume fraction of the water in the OBM as originally constituted and {circumflex over (z)}_of is the normalized volume fraction of oil filtrate.

8. The method according to claim 1, wherein:

the volume fraction of water is taken to be zero regardless of what is measured and z_co+z_of=1 where z_co is the volume fraction of crude oil and z_of is the volume fraction of oil filtrate.

9. The method according to claim 1, further comprising:

iteratively repeating steps (b) through (e), wherein said estimate of said computing step is an updated estimated provided by said updating step.

10. The method according to claim 9, wherein:

said step of updating is performed with a least squares algorithm.

11. The method according to claim 10, wherein:

said step of comparing is performed according to

$E=\underset{i=1}{\overset{N}{\sum <br><br>}}<br><br>\frac{1}{{\mathrm{\sigma <br><br>}}_{\mathrm{\rho <br><br>}}^{{\left(i\right)}^2}}<br><br>{\left({\mathrm{\rho <br><br>}}_t^{\left(i\right)}-{\mathrm{\rho <br><br>}}_{\mathrm{tm}}^{\left(i\right)}\right)}^2+\frac{1}{{\mathrm{\sigma <br><br>}}_{\mathrm{\mu <br><br>}}^{{\left(i\right)}^2}}<br><br>{\left({\mathrm{\mu <br><br>}}_t^{\left(i\right)}-{\mathrm{\mu <br><br>}}_{\mathrm{tm}}^{\left(i\right)}\right)}^2$

where ρ

_t⁽ⁱ⁾ is the calculated density of the total mixture at iteration (i), ρ

_tm⁽ⁱ⁾ is the measured density of the total mixture at iteration (i), μ

_t⁽ⁱ⁾ is the calculated viscosity of the total mixture at iteration (i), μ

_tm⁽ⁱ⁾ is the measured viscosity of the total mixture at iteration (i), σ

_ρ

⁽ⁱ⁾² is the variance in ρ

_tm(i), σ

_μ

⁽ⁱ⁾² is the variance in μ

_tm(i), E is an error, and N is the total number of time points considered.

12. The method according to claim 11, wherein:

said least squares algorithm is an error minimization algorithm which is performed with (N) number of measured and calculated densities and viscosities of crude oil and oil filtrate in order to provide a calculation of at least one of said crude oil density and said crude oil viscosity.

13. The method according to claim 12, further comprising:

comparing determinations of said at least one of the density and viscosity of the total mixture made at different sampling times to make a final estimate of the component properties.

14. The method according to claim 13, wherein:

said comparing determinations comprises comparing determinations of both said density and viscosity to determine whether said comparisons are within a desired tolerance.

15. A method for characterizing hydrocarbon fluid in a reservoir, comprising:

a) estimating the expected viscosity and density of the components of the hydrocarbon fluid;

b) calculating the density and viscosity of the hydrocarbon fluid based on the estimates of the viscosity and density of the components;

c) measuring the viscosity and density of the hydrocarbon fluid;

d) comparing the calculated density and viscosity of the hydrocarbon fluid with the measured density and viscosity; and

e) characterizing the hydrocarbon fluid in the reservoir by updating the estimates of the viscosity and density of the components based on the comparison.

16. The method according to claim 15, further comprising:

f) drilling a wellbore into the reservoir formation prior to said step of measuring, wherein

said step of estimating is performed with knowledge about the reservoir and the mud used during drilling.

17. The method according to claim 15, further comprising:

f) determining the volume fractions of the hydrocarbon fluid by measurement prior to said step of calculating.

18. The method according to claim 17, wherein:

said step of calculating the density and viscosity of the hydrocarbon fluid is based on the determination of volume fractions as well as on the estimates of the viscosity and density of the components.

19. The method according to claim 15, wherein:

said step of measuring includes sampling fluid with a flow-line device.

20. The method according to claim 15, wherein:

said step of comparing includes application of a least squares algorithm.

21. The method according to claim 15, wherein:

said step of computing density includes computing a normalized volume fraction of crude oil and a normalized volume fraction of oil filtrate.

22. The method according to claim 15, further comprising:

iteratively repeating steps (b) through (e), wherein said estimate of said calculating step is an updated estimated provided by said updating step.

23. The method according to claim 22, wherein:

said step of updating is performed with a least squares algorithm.

24. The method according to claim 23, wherein:

said step of comparing is performed according to

$E=\underset{i=1}{\overset{N}{\sum <br><br>}}<br><br>\frac{1}{{\mathrm{\sigma <br><br>}}_{\mathrm{\rho <br><br>}}^{{\left(i\right)}^2}}<br><br>{\left({\mathrm{\rho <br><br>}}_t^{\left(i\right)}-{\mathrm{\rho <br><br>}}_{\mathrm{tm}}^{\left(i\right)}\right)}^2+\frac{1}{{\mathrm{\sigma <br><br>}}_{\mathrm{\mu <br><br>}}^{{\left(i\right)}^2}}<br><br>{\left({\mathrm{\mu <br><br>}}_t^{\left(i\right)}-{\mathrm{\mu <br><br>}}_{\mathrm{tm}}^{\left(i\right)}\right)}^2$

where ρ

_t⁽ⁱ⁾ is the calculated density of the total mixture at iteration (i), ρ

_tm⁽ⁱ⁾ is the measured density of the total mixture at iteration (i), μ

_t⁽ⁱ⁾ is the calculated viscosity of the total mixture at iteration (i), μ

_tm⁽ⁱ⁾ the measured viscosity of the total mixture at iteration (i), σ

_ρ

⁽ⁱ⁾² is the variance in ρ

_tm(i), σ

_μ

⁽ⁱ⁾² is the variance in μ

_tm(i), E is an error, and N is the total number of time points considered.

25. The method according to claim 24, wherein:

said least squares algorithm is an error minimization algorithm which is performed with (N) number of measured and calculated densities and viscosities of crude oil and oil filtrate in order to provide a calculation of at least one of said crude oil density and said crude oil viscosity.

26. The method according to claim 25, further comprising:

comparing determinations of said density and viscosity of the total mixture made at different sampling times to make a final estimate of the component properties.

27. The method according to claim 26, wherein:

said comparing determinations comprises comparing determinations of said density and viscosity to determine whether said comparisons are within a desired tolerance.