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The increasing demand for petroleum products has posed a challenge to the search for oil and gas. This search for hydrocarbon has developed due to advances in computational techniques to evaluate the probability of hydrocarbon proneness of a basin, thereby limiting the risk factor associated with hydrocarbon. This study was therefore designed to assess the hydrocarbon potential and generate a static reservoir model of UDI Field, Onshore Niger Delta.
Well, the correlation was carried out to establish stratigraphic continuity of the reservoir sand bodies. The identified potential reservoir intervals were tied to the seismic data using available check shot survey data. With a good match achieved, seismic events were interpreted through paying attention to reflection continuity, amplitude and frequency. Interpreted horizons were converted to surfaces using a convergent interpolation algorithm. Faults within the Field showed a dominant East-West trend with two (2) major faults and five (5) minor ones. A Pixel-based facies model was built based on the normal distribution of the upscaled lithofacies log using the Sequential Indicator Simulation algorithm. Petrophysical models were built by constraining the petrophysical logs to the facies models using Sequential Gaussian simulation algorithm.
Four potential reservoir intervals, A100, A125, A150 and A200 were delineated. Average petrophysical parameters were computed for all the four intervals and the results revealed the reservoir intervals to be of good quality. Sand A100 has the highest average porosity value of 29.4%, while Sand A200 has the lowest value of 25.3%. Net-to-gross ratio also follows the pattern of decreasing value with depth. Sand A150 has the highest average gross thickness value, 170.4 m, while Sand A200 has the least thickness of 80.5 m. The net-to-gross ratio preserved the pattern of gross thickness and this resulted in Sand A150 still having the highest Net thickness and Sand A200 having the least Net sand thickness. The relatively large net sand thicknesses, high net-to-gross ratio values and the high porosity values all support the reservoir intervals within UDI Field to be of good quality.
Extrapolations of reservoir properties away from good control honored the geological interpretation of reservoir Sand A125 thereby reducing the subsurface reservoir uncertainties.
The availability of pressure data of the reservoir will help in establishing whether the reservoir is compartmentalized and hence the model can be updated to accommodate the effect of compartmentalization.
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