PEMANFAATAN METODA INVERSI DAN PROBABILISTIC NEURAL NETWORK PADA DATA SEISMIK DALAM PENENTUAN ZONA RESERVOAR BATUGAMPING (CARBONATE BUILDUP) DI LAPANGAN SUKO, CEKUNGAN JAWA TIMUR UTARA

Abstract

Limestone particularly Carbonate Buildup is one type of reservoir potential as a hydrocarbon accumulation. Problems often encountered in the analysis are the type of reservoir porosity deployment complexity that is very different from other rocks. The understanding of porous area as a zone of a reservoir in the body Carbonate buildup will provide an overview in the development and determination of drilling new wells. Identification of potential zones in carbonate buildup can be done with the approach of the seismic data inversion process and multi-attribute with neural network method. Seismic inversion process is the reverse of the forward modeling process which will produce Acoustic impedance value that describes not only the boundary between the layers but also a layer of rock itself (Layer Properties). Validation of the results of the inversion process is done by creating a density map using multi-attribute process with probabilistic neural network method. The results of the inversion and multi-attribute process is expected to provide an overview of the deployment area having a large porosity which can serve as a reservoir zone. The results from the combination of the two methods showed that the reservoir zone is in the central part of carbonate buildup that field through the development of new drilling process can be directed at the zone.

Keywords: AI inversion, Multi-attribute PNN, Carbonate Buildup