BH field is one of the Globigerina limestone gas reservoir that exhibits strong seismic direct hydrocarbon indicator (DHI). This field is a 4-way dip faulted closure with Globigerina limestone as the main reservoir objective. The field was discovered back in 2011 by BH-1 exploration well and successfully penetrated about 350ft gross gas pay. BH-1 well was plugged and abandoned as Pliocene Globigerina limestone Mundu-Selorejo sequence gas discoveries. The laboratory analysis of sampled gas consists of 97.8% of CH4 and indicating a biogenic type of gas. This is the only exploration well drilled in this field and located on the crest of the structure. Seismic analysis both qualitative and quantitative, are common tools in delineating and characterizing reservoir. These methods usually make use of seismic data and well log collaboratively in the quest to reveal reservoir features internally. The lack of appraisal well in the area of study made the reservoir characterization process must be carried out thoroughly, incorporating several seismic datasets, both PSTM and PSDM, seismic gathers and stacks. Bounded by appraisal well limitation, this research looks into Gassmann's fluid substitution modeling, seismic forward modeling to confirm the DHI flat spot presence in the seismic, as well as seismic AVO analysis. Meanwhile, for quantitative analysis, model-based seismic post-stack inversion and simultaneous seismic pre-stack inversion were conducted in order to delineate the distribution of Globigerina limestone gas reservoir in BH Field. Through comprehensive analyses of qualitative and quantitative methods, this research may answer the challenge on how to intensively utilize seismic data to compensate the lack of appraisal well data in order to keep delivering a proper subsurface reservoir delineation.
Ensemble model of non-linear feature selection-based Extreme Learning Machine for improved natural gas reservoir characterization
