Drilling fluid contamination determination for downhole fluid sampling tool

1. A method for determining fluid contamination, comprising:

obtaining a fluid sample, wherein the fluid sample comprises a reservoir fluid contaminated with a well fluid;

using one or more optical sensors to obtain a measurement of the fluid sample, wherein the measurement comprises a petroleum compositional measurement, wherein the petroleum compositional measurement comprises one or more component mole fractions of the reservoir fluid, and wherein the petroleum compositional measurement comprises spectral data;

obtaining input parameters, wherein the input parameters comprise fluid properties obtained from the measurement of the fluid sample and mud filtrate composition;

representing a mud composition as a Gaussian distribution;

selecting a plurality of input data during a pumpout;

determining calculated fluid properties of the reservoir fluid based, at least in part, on the spectral data and an equation of state filtrate analysis;

comparing the calculated fluid properties to the input parameters to determine if a tolerance criterion is met, wherein the tolerance criterion is a tolerance error; and

generating an output if the tolerance criterion is met, wherein the output comprises the calculated fluid properties or an estimate of the fluid contamination.

2. The method of claim 1 , further comprising conditioning the equation of state filtrate analysis with a principal component analysis.

3. The method of claim 2 , wherein the principal component analysis comprises despiking an original dataset, performing a robust principal component analysis on the original dataset to obtain a principal component analysis score, applying a robustfit regression to the principal component analysis score to obtain a reconstructed dataset, and computing a fluid composition from the reconstructed dataset.

4. The method of claim 3 , wherein the despiking an original dataset is performed by a Hampel filter.

5. The method of claim 3 , wherein the computing a fluid composition is performed by a Neural Network.

6. The method of claim 3 , further comprising using the principal component analysis score to estimate a clean formation fluid composition.

7. The method of claim 3 , wherein the method further comprises: inverting the principal component analysis score to form an inverted asymptotic principal analysis score; and estimating one or more clean formation fluid compositions based, at least in part, on the inverted asymptotic principal analysis score.

8. The method of claim 1 , further comprising removing the reservoir fluid based at least in part on the calculated fluid properties.

9. The method of claim 1 , wherein obtaining the fluid sample comprises operating a downhole fluid sampling tool in a wellbore to obtain the fluid sample.

10. The method of claim 1 , wherein the well fluid comprises a drilling fluid.

11. The system of claim 1 , wherein the equation of state filtrate analysis further comprises a non-cubic equation of state.

12. A system for determining fluid contamination, comprising:

a downhole fluid sampling tool operable to obtain a fluid sample of a reservoir fluid contaminated with a well fluid while the downhole fluid sampling tool is disposed in a wellbore; and

a processing unit operable to (i) obtain a measurement of the fluid sample from one or more optical sensors, wherein the measurement is a petroleum compositional measurement, wherein the petroleum compositional measurement comprises one or more component mole fractions, and wherein the petroleum compositional measurement comprises spectral data (ii) obtain input parameters, wherein the input parameters comprise fluid properties obtained from the measurement of the fluid sample and mud filtrate composition; (iii) represent a mud composition as a Gaussian distribution; (iv) select a plurality of input data during a pumpout; and (v) determine calculated fluid properties of the reservoir fluid based, at least in part, the spectral data and an equation of state filtrate analysis.

13. The system of claim 12 , wherein the processing unit is further operable to condition the equation of state filtrate analysis with a principal component analysis.

14. The system of claim 13 , wherein the processing unit is further operable to despike an original dataset, perform a robust principal component analysis on the original dataset to obtain a principal component analysis score, apply a robustfit regression to the robust principal component analysis score to obtain a reconstructed dataset, and compute a fluid composition from the reconstructed dataset.

15. The system of claim 14 , wherein the processing unit is further operable to despike an original dataset and where despiking is performed by a Hampel filter.

16. The system of claim 14 , wherein computing the fluid composition is performed by a Neural Network.

17. The system of claim 14 , wherein the processing unit is further operable to use the principal component analysis score, and wherein the principal component analysis score is used to estimate a clean formation fluid composition.

18. The system of claim 12 , wherein the well fluid comprises a drilling fluid.

19. The system of claim 12 , wherein the processing unit is further operable to obtain the fluid sample comprising operating a downhole fluid sampling tool in a wellbore to obtain the fluid sample.

20. The system of claim 12 , wherein the processing unit is further operable to compare the calculated fluid properties to the input parameters to determine if a tolerance criterion is met, wherein the tolerance criterion is a tolerance error; and generate an output if the tolerance criterion is met, wherein the output comprises component mole fractions or the reservoir fluid or an estimate of the fluid contamination.