Print this pageAAPG GEO 2010 Middle East
Geoscience Conference & Exhibition
Innovative Geoscience Solutions – Meeting Hydrocarbon Demand in Changing Times
March 7-10, 2010 – Manama, Bahrain
Application of 3D Seismic Multi-Attribute and Neural Network Technique for 
Reservoir
Prediction: A Case Study for the Marrat Formation, Kuwait
(1) Exploration, Kuwait Oil Company, Ahmadi, Kuwait.
The use of 3D seismic attributes for predicting reservoir properties away from the well bore has been used routinely in the industry. Recently a study utilizing multi attribute analysis and neutral network technique applied to one of the Marrat reservoirs in west Kuwait has not only described the reservoir geometry but has also opened up new areas for exploration. Further, the seismic derived porosity volume has been also integrated with the geological model for future well placement.
The Middle Marrat limestone reservoir of Jurassic age in the Dharif field is one of the major oil producers in the area. This field discovered in 1988, is an elongated anticline trending NNE-SSW, with a major fault to the west. The reservoir thickness varies from 50-230ft and porosities ranging from 12 to 20%. Since a Pilot water injection program is being initiated, a good reservoir description would be essential for planning a successful injection program.
The seismic derived porosity volume derived from neural network analysis has been a key in identifying inter-well areas as well as regions away from the wells with good porosity which is consistent with the available geological information. Incorporating the porosity
volume as a “soft constraint” to the available geological model has further refined the model and is expected to assist in effective placement of future wells.