Porosity Prediction of a Carbonate Reservoir in KF Prospect, North East Java Basin Based on The Integration of Seismic Attribute and Acoustic Impedance Inversion

Abstrak

Porosity prediction is still an obstacle and a challenge for geologists and geophysics in the carbonate reservoir of KF prospect, although the surrounding field has high hydrocarbon production. Well data, seismic data, there are still not many that can be used as a reference for reservoir characterization due to the lack of exploration wells around the RF prospect. As a consequence, the prediction of porosity is difficult to map, and this results makes it difficult to interpret hydrocarbon traps and determine prospects for new wells.

In order to have a better porosity prediction, data integration of geological data, well log data, the latest seismic data, seismic attribute extraction and utilization of acoustic impedance inversion are used to optimize the geological interpretation. Regional geology data provide the understanding that the structural trap is coming from E-W direction. The structures that develop in the East Java Basin are mostly in the form of anticlines and faults and stratigraphy are found when carbonate unit onlap and cover high sections of bedrock. In addition, the well log data shows the determination of the formation boundary location in the prospect and greatly contributes as an input to the acoustic impedance inversion process. Besides that, extraction of seismic attribute, in this case, it uses the instantaneous phase attribute which shows the continuity of the seismic layer laterally and the continuity of the seismic trace which contributes to the clearer carbonate build-up on the seismic reflector which is then reinforced by regional stratigraphy which shows that there is a carbonate build-up in high areas.

By doing the well seismic tie, it is obtained seismic data at true depth and the role of the instantaneous phase attribute is also very useful in the picking process, because the discontinuity of the seismic traces is seen more clearly so it makes the picking process easier. And to predict porosity, an inversion model is built to produce a map of the distribution of the porous zone in the target area from the interpolated well logs and target horizon.

Based on this analysis, the distribution of high porosity or porous zones is found in the northern and southern areas of the fault. The construction of acoustic impedance inversion models and structural map are interpreted as important factors in determining porous zones and can be interpreted using integrated geological and geophysical data.