[First Hit]

Datapages, Inc.Print this page

Fluid and Petrophysical Prediction in The Previous HitElasticNext Hit Domain Using Neural Network Method

Hermana, Maman; Najmi, Muhammad; Tuan Harith, Zuhar; Sum, Chow W.
Universiti Teknologi Petronas, Tronoh, Malaysia.

Interpretation in Previous HitelasticNext Hit Previous HitimpedanceNext Hit domain is a new method in geophysical prospect evaluation and development in Oil & Gas industry. Inspired by the success in lithology and fluid discrimination in Previous HitelasticNext Hit domain, we applied Neural Network technique into Previous HitelasticNext Hit volume to predict fluid and petrophysical properties in the reservoir. This study consist of three phases: 1) Correlation study between Previous HitElasticNext Hit Previous HitImpedanceNext Hit log and Petrophysical Log to determine chi angle optimum, 2) AVO response and EEI projection performed to construct seismic equivalent to petrophysical properties. To convert the reflectivity of EEI into Previous HitimpedanceNext Hit domain, the colored inversion is applied. 3) The relative Previous HitimpedanceNext Hit of petrophysical volume evaluated using supervised ANN method to determined fluid and petrophysical properties. The result shows there is a good correlation between petrophysical log and EEI log: maximum coefficient correlation between porosity, water saturation and resistivity occur at 23, 25 and 32 degrees. Relative Previous HitimpedanceNext Hit domain which is obtained from colored inversion has been checked with well logs, there is good matching between seismic Previous HitelasticNext Hit Previous HitimpedanceTop with logs. Finally, the absolute porosity, water saturation and resistivity estimated using supervised neural network. The results is consistent with petrophysical logs.


AAPG Search and Discovery Article #90155©2012 AAPG International Conference & Exhibition, Singapore, 16-19 September 2012