Amplitude Variation With Offset (Avo) Attribute Analysis for Seismic Reservoir Characterization and Seismofacies Study of Kuyolo Field, Niger Delta Basin

Abstract

Amplitude variation with offset (AVO) attributes analysis, based on integration of geophysical and petrophysical data has become an important and innovative tool for the detection of hydrocarbons in many exploration provinces of the world, including the Niger Delta Basin. The method has been demonstrated to be effective when seismic data processing is carefully done with detailed petrophysical modeling from complete well log suites. However, routine application of the method has from time to time yielded disappointing results largely due to poor or non-availability of shear wave data. Considering the need for reduced risk and enhanced productivity in today’s petroleum industry, a new and more efficient technique that ameliorates the problem of poor or non-availability of shear wave data is required. AVO Seismofacies methodology is one of such techniques and this approach was adopted for this study. It accounts for expected Amplitude Variation with Angle (AVA) effects, uses information from angle substacks, and effectively takes care of problems arising from the absence of data on shear waves, missing well log sections, and difficult well-to-seismic ties. The objectives of the study were to: (i) delineate (ii) map and (iii) characterize reservoirs in the Kuyolo field using the AVO Seismofacies approach. This approach involves quality control analysis of data, seismic data interpretation, shear wave data generation, reservoir fluid substitution via Gassmann technique, crossplots of elastic parameters and finally AVO Seismofacies analysis. The result of the quality control (QC) analysis shows that it was sufficient for the analysis of the Kuyolo field AVO anomalies. The result of the seismic data interpretation showed excellent tie of the well and seismic data with the R11 reservoir clearly delineated and mapped with high confidence. The result of the comparison of the actual well log measurements with the modelled well logs showed that the logs were relatively similar over all wells, with the trends and variations of density and velocities correctly modelled, especially in clean reservoirs. The analysis of the crossplots of modelled density (ρ) versus P-wave velocity (Vp) and Poisson’s Ratio (PR) versus acoustic impedance (IP) generated after water substitution over all the wells, showed overall good separation of water saturated sands and shales giving confidence that AVO Seismofacies methodology could be used to characterize the reservoirs. Cross-correlation analysis showed that substack pairs of Near – Mid and Mid – Far offsets were suitable for AVO analysis. The study revealed that cross-correlation between Near and Far offset substack were too low to allow an AVO analysis using this pairing of substacks. Substack pairs of Mid – Far were then selected to be used for this study. Average lambda and slope in degrees values of 0.24 and 37 degrees (370) extracted from the crossplots of filtered Mid and Far offset substacks at several locations and depths where there was no hydrocarbon were used to compute the AVO Seismofacies cube. All analyzed AVO anomalies gave fair responses fitting rather well on the AVO maps with the structural, sedimentary and stratigraphic interpretation, with anomaly shut-off at their base that could be interpreted as water/hydrocarbon contacts. Results of crossplot analysis of the amplitude values extracted at the top of R11 reservoir from filtered Near and Far substacks above the presumed Oil-Water-Contact (OWC) suggested Class II Reservoir sands. Thus the analysis carried out in the study area enhanced the identification and delineation of the hydrocarbon reservoir with high confidence. Additionally, the study has demonstrated that crossplot analysis such as those developed and analyzed in this work has helped to characterize the AVO Class of reservoir sands.