Authors : John Adler, Selvia Lorena Br Ginting, Bagus Endar B. Nurhandoko and Pongga Dikdya Wardaya
Abstract: Seismic wave parameter plays very important role to characterize reservoir properties whereas pore parameter is one of the most important parameter of reservoir. Therefore, wave propagation phenomena in pore media is important to be studied. By referring this study, in-direct pore measurement method based on seismic wave propagation can be developed. Porosity play important role in reservoir, because the porosity can be as compartment of fluid. Many type of porosity like primary as well as secondary porosity. Carbonate rock consist many type of porosity, i.e., inter granular porosity, moldic porosity and also fracture porosity. The complexity of pore type in carbonate rocks make the wave propagation in these rocks is more complex than sand reservoir. We have studied numerically wave propagation in carbonate rock by finite difference modeling in time-space domain. The medium of wave propagation was modeled by base on the result of pattern recognition using artificial neural network. The image of thin slice of carbonate rock is then translated into the velocity matrix. Each mineral contents including pore of thin slice image are translated to velocity since mineral has unique velocity. After matrix velocity model has been developed, the seismic wave is propagated numerically in this model. The phenomena diffraction is clearly shown while wave propagates in this complex carbonate medium. The seismic wave is modeled in various frequencies. The result shows dispersive phenomena where high frequency wave tends to propagate in matrix instead pores. In the other hand, the low frequency waves tend to propagate through pore space even though the velocity of pore is very low. Therefore, this dispersive phenomena of seismic wave propagation can be the future indirect measurement technology for predicting the existence or intensity of pore space in reservoir rock. It will be very useful for the future reservoir characterization.
John Adler, Selvia Lorena Br Ginting, Bagus Endar B. Nurhandoko and Pongga Dikdya Wardaya, 2017. Application Artificial Neural Network-Image Processing to Seismic Wave Propagation of Carbonate Rock. Journal of Engineering and Applied Sciences, 12: 199-203.