Abstract:
The hydrocarbon in-place and reserves are of utmost importance to any investors planning to invest in the well development plan of any field. This research focuses on the application of geostatistics for constructing a geological model and the use of Monte Carlo Simulation for uncertainty analysis. The non-availability of datasets during field appraisal or interpretation has resulted in most cases, making logical assumptions based on the geology of an area and theory. The environment of deposition of the reservoir within the study field was determined using the motifs of the well log data. The well log data were also used for detailed petrophysical analysis of the delineated reservoirs within the field. Geologic structures such as faults were mapped across the 3-D seismic data. A synthetic seismogram was generated by convolving the reflection coefficient, derived from the change in acoustic impedance of lithologies, with a ricker wavelet. This was used to perform a seismic-well tie operation. Structural time maps were generated from the mapped horizons and depth converted using a velocity model derived from a polynomial function. A geological model was constructed by applying geostatistical methods to populate data spatially within the reservoirs. Uncertainty analysis using the Monte Carlo approach was performed on the reserves estimated from the static model. The results gave a high level of confidence on the estimated reserves in terms of the proven (P10), probable (P50) and possible (P90) reserves within the reservoir. The reservoirs were deposited within the fluvial sand and tidal channel environment. This implies that the reservoir will have good pore spaces and the pores throats will be well connected. As affirmed from the petrophysical modelling. This proves the wells are quite porous and saturated with hydrocarbon.
