Name
Title | ||
|---|---|---|
Lithology Recognition During Oil Well Drilling Based on Fuzzy-adaptive Hamming Network |
Abstract | ||
|---|---|---|
In order to satisfy the urgent demand for real-time lithology recognition of bit position during oil well drilling, a method of lithology feature extraction had been presented using the relation between curve variation trend of the real-time estimated drillable value and material of core lithology. Based on this method and fuzzy-adaptive Hamming network, a novel method had been proposed to realize real-time lithology recognition. This method avoids the shortages existing in ordinary method based on logging curve and human estimation, such as inaccuracy of lithology, bad real-time ability, etc. The results from simulation experiment of testing samples show that the classifying speed is fast and the classifying is steady and effective. The proposed network is fit to fuzzy quantity and analog quantity with proper quantity of samples and classes. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1109/ISDA.2006.186 | ISDA (1) |
Keywords | Field | DocType |
feature extraction,real time,object recognition,satisfiability,fuzzy set theory,simulation experiment | Hamming code,Pattern recognition,Computer science,Fuzzy logic,Fuzzy set,Feature extraction,Artificial intelligence,Oil well,Drilling,Lithology,Cognitive neuroscience of visual object recognition | Conference |
Volume | Issue | ISBN |
1 | null | 0-7695-2528-8 |
Citations | PageRank | References |
1 | 0.41 | 1 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tiehong Gao | 1 | 2 | 1.46 |
| Junyi Cao | 2 | 29 | 4.44 |
| Minglu Zhang | 3 | 27 | 15.35 |
| Jiangbo Qi | 4 | 1 | 0.41 |