RESERVOIR ESTIMATION USING GEOSTATISTICAL PREDICTION AND MODELLING IN “DAVOR” FIELD, NIGER DELTA.

Abstract

This research work was aimed at analysing, modeling and predicting reservoir petrophysical properties of ‘DAVOR’ Field, and estimating its hydrocarbon reserves using geostatistical approach. The analysed data consist of 3D seismic data and suite of logs from five (5) wells comprising gamma ray (GR), resistivity (ILLD), neutron porosity (NPHI) and bulk density (RHOB). From the well log analysis, the determined petrophysical parameters were porosity (Ø), volume of shale (SH), water saturation (Sw) and permeability (K). Synthetic seismogram created was used to tie the wells to seismic sections. Three horizons namely A, B, and C were identified and twenty four (24) fault lines were mapped and interpreted on the seismic sections. The result of these on time and depth structural maps revealed the anticlinal structures and fault assisted closure as the trapping system for hydrocarbon accumulation in the study area. The result from the analysed petrophysical data for reservoir C which has the highest net thickness with an average values of porosity (24%), permeability (7843mD) and water saturation (0.56) were geostatistically distributed across the wells and further subjected to stochastic modelling after being upscale. The deterministic estimation value of STOIIP was 34.13MMSTB while the probability values of the Monte Carlos simulation of P10, P50 and P90 are 25.48, 35.25 and 41.55MMSTB respectively. This study has revealed that geostatistical method for prediction and modelling reservoir petrophysical properties adopted is a better hydrocarbon exploration tool than the conventional deterministic approach.