Improving Accuracy Of Fluid Contact Determination Through The Use Of An Auxiliary Transform Method
Abstract
Fluid contact(s) in reservoir sets the lower limit above which an accumulation of hydrocarbon (i.e. oil or gas) has the maximum level of mobility under a specific circumstance. This mobile hydrocarbon determines the reservoir’s production feasibility. In this light, an accurate knowledge over position of fluid contact contributes to accuracy in the estimation of initial hydrocarbon in place and its corresponding reserves. Determination of fluid contact in reservoir may utilize any available sources of information but well pressure survey data is usually regarded as the primary source of information. Despite the importance, the data is sometimes not in ideal condition usually marked by absence in clear change of pressure gradient and/or data scatter for various reasons. The use of Hough transform – as introduced by Kang and Xue (2009) – for supporting fluid contact detection can solve the problem. In this study, the method that is usually used for, among others, recognizing regular shapes in images has been successfully applied for fluid contact detection. The study uses three sets of data with different level of difficulty, and the technique proves to work well for the all cases. The study also shows that the Hough transform can be used reliably in a simple way without employing the full weight of it.
Keywords
Full Text:
PDFReferences
Hough, P.V.C. (1962). A method and means
for recognizing complex patterns: US Patent
,069,654.
Kang, X.Q. and Xue, Y.J. (2009). An improved
plot for wireline pressure data gradient interpretation.
Petrophysics, vol. 50, No. 3, June, pp. 226
– 236.
Casasent, D. and Krishnapuram, R. (1987).
Curved object location by Hough transformations
and inversions. Pattern Recognition, vol 20 no. 2,
p.181 – 188.
Xu, L., Oja, E., and Kultanen, P. (1990). A
new curve detection method: randomized Hough
transform (rht). Pattern Recognition Letters, vol.
, no.5, p. 331 – 338.
DOI: https://doi.org/10.29017/SCOG.34.3.802
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.