Output details
15 - General Engineering
Robert Gordon University
Article title
UCS Neural Network Model for Real Time Sand Prediction
Type
D - Journal article
Title of journal
International Journal of Engineering Research in Africa
Article number
-
Volume number
2
Issue number
-
First page of article
1
ISSN of journal
1663-4144
Year of publication
2010
URL
-
Number of additional authors
2
Additional information
This work explored the power and intelligence of Neutral artificial technique to predict the Unconfined Compressive Strength (UCS) of clastic rocks. UCS is a very important parameter for evaluating risks of sand failure and production from clastic reservoirs. The work is pioneering in the use of NN technique to predict the geomechanical, geological and geophysical properties of clastic reservoir rocks in REAL TIME. It has inspired lots of other related works and generated some interests in research collaboration with the WERG (Professor of Health Informatics, South Bank University)
Interdisciplinary
-
Cross-referral requested
-
Research group
None
Proposed double-weighted
No
Double-weighted statement
-
Reserve for a double-weighted output
No
Non-English
No
English abstract
-
