Application of fuzzy classifier fusion in determining productive zones in oil wells

Pedram Masoudi (1) , Behzad Tokhmechi (1) , Majid Ansari Jafari (1) , Behzad Moshiri (2)

1 School of Mining, Petroleum and Geophysics Engineering
2 School of Electrical an Computer Engineering

This study is an application of data fusion techniques, especially fuzzy theory, in determining oil producing zones through four nearby wells, located on an oil field in south west of Iran. Two fusing techniques, used here are based on Bayesian and fuzzy theories. At first, two Bayesian classifiers are being constructed by training in two different wells; then a fuzzy operator, called Sugeno discrete integral, is used to fuse outputs of two mentioned Bayesian classifiers. Finally, it is concluded that using fuzzy classifier fusion improves not only certainty and confidence of decision making, but also generalization ability of determining productive zones.

Keywords: pay zone; data fusion; fuzzy; Bayesian; Sugeno integral

Domains: Applied geology

Pedram Masoudi, Behzad Tokhmechi, Majid Ansari Jafari, Behzad Moshiri. Application of fuzzy classifier fusion in determining productive zones in oil wells. Energy Exploration and Exploitation, 2012, 30 (3), pp.403 - 416. ⟨10.1260/0144-5987.30.3.403⟩. ⟨insu-01382442⟩