OPTIMIZATION OF SEISMIC DATA RECONDITIONING TECHNIQUES TO IDENTIFY FACIES AND HYDROCARBON DISTRIBUTION USING ACOUSTIC IMPEDANCE INVERSION IN THE MINAHAKI FORMATION IN THE

Increasing the resolution of seismic data needs to be done to restore signals lost due to the attenuation process experienced by seismic waves due to absorption by the earth's layers. In this research, the Minahaki Formation as a carbonate reservoir generally has quite complex characteristic...

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Bibliographic Details
Main Author: Agatha Livyano, Fellicia
Format: Final Project
Language:Indonesia
Online Access:https://digilib.itb.ac.id/gdl/view/77896
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Institution: Institut Teknologi Bandung
Language: Indonesia
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Summary:Increasing the resolution of seismic data needs to be done to restore signals lost due to the attenuation process experienced by seismic waves due to absorption by the earth's layers. In this research, the Minahaki Formation as a carbonate reservoir generally has quite complex characteristics where the porosity and permeability have high heterogeneity due to depositional and diagenesis processes. This has an impact on increasing the complexity of interpretation. To address this problem, seismic data reconditioning was carried out to increase the resolution of the seismic data and Acoustic Impedance Inversion to interpret facies and map the distribution of hydrocarbons in the Minahaki Formation. The data used is 3D raw PSDM stack seismic, velocity data and well data. The main stages used in seismic data reconditioning are loop reconvolution, spectral balancing, and FXY-Deconvolution. The seismic data reconditioning process succeeded in increasing the signal at high frequencies, flattening the amplitude, increasing well seismic tie correlation¸ and clarifying the structure and continuity of the Minahaki Formation. Based on the results of the sensitivity analysis, AI was proven to be sensitive enough to separate hydrocarbons from wet carbonate with a cut-off of AI <8,900 m/s*g/cc. Model Based Inversion after reconditioning the seismic data was proven to have better correlation values than before, thereby increasing accuracy in identifying hydrocarbon facies and distribution. The pay reservoir area was identified as an area with AI <8,900 m/s*g/cc values located in the southeast of the study area. The facies of this area are identified as shelf margin and reworked deposits from the isolated carbonate platform of the Minahaki Formation. This shelf margin is in a windward area and is often exposed to wave currents, while the reworked deposit is deposit resulting from erosion from an isolated platform with a steep slope, so this area is expected to have good porosity.