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In this study, a linear programming (l1-norm) sparse spike inversion (LPSSI) technique is used to estimate acoustic impedance distribution in the subsurface of the Blackfoot Field, Alberta, Canada. The aim of study is to determine high-resolution subsurface rock properties from the low-resolution seismic data and characterise the clastic Glauconitic channel. There are many traditional post-stack seismic inversion techniques available to estimate rock properties from seismic data, but LPSSI is a relatively simple and quick to compute subsurface model that can be used for qualitative as well as quantitative interpretation. The technique is applied in two steps; first, composite traces near to well locations are extracted and inverted for acoustic impedance, and comparison with well log impedance is used to optimise the LPSSI parameters. Analysis of the composite traces indicates that the algorithm has good performance with high correlation (0.97). In the second step, LPSSI is applied to the Blackfoot seismic data to estimate the distribution of acoustic impedance in the subsurface. Analysis of inverted acoustic impedance shows a low impedance anomaly ranging from 6500 to 8500 m/s*g/cc at the 1060–1075 ms time interval, which is characterised as a clastic Glauconitic sand channel. Thereafter, to confirm the sand channel, another important rock property, porosity, is estimated in the inter-well region using multi-attribute analysis. Analysis of the porosity shows the presence of a high porosity (15–22%) zone in the 1060–1075 ms time interval which coincides with the low impedance zone and confirms the presence of the sand channel. [ABSTRACT FROM AUTHOR]

The prime objective of this study is to find the suitable petrophysical parameters which depict the maximum change in seismic amplitude due to fluid substitution. Therefore, in the present study the petrophysical parameters are analysed to detect the most sensitive parameters due to fluid substitution. The analysis is performed in three steps: In the first step, the Gassmann fluid substitution is performed and a considerable change in velocity, density, impedance, lambda–mu–rho parameters and Shuey's parameters is examined. The study shows that the most sensitive parameters are A (intercept), which shows the maximum drop of 22% with respect to CO2 injection, and B (gradient), which shows the maximum increase of 10% with CO2 injection in the formation. Thereafter, in the second step, the seismic forward modelling is performed to examine the changes in seismic amplitude by the fluid substitution in the formation. The analysis depicts that the seismic amplitude increases steadily with increasing CO2 saturation. The amplitude increases by 4% at 20% CO2 injection, by 8% at 50% CO2 injection and the seismic amplitude increases by 12% at 100% CO2 injection in the target zone. Finally, in the third step, the numerical modelling is performed to assess the ability of seismic methods to detect the CO2 plume accurately by injecting CO2 plume of cylindrical shape. The analysis shows that the CO2 plume can be detected more prominently by analysing the impedance volume rather than the seismic amplitude section. This study is helpful in deciding which parameters should be monitored carefully in fluid replacement modelling projects. [ABSTRACT FROM AUTHOR]

In the present paper, a seismic inversion based on genetic algorithm (GA) is performed to characterise the reservoir using seismic data only from the Blackfoot field, Alberta, Canada. The algorithm is first tested on synthetically generated data to optimise the GA parameters. The error analysis between the inverted and the expected results suggested that the performance of algorithm is exceptionally satisfactory. Thereafter, the inversion is performed for real seismic data from the Blackfoot field. The seismic data is first inverted for acoustic impedance section and then it is transformed into the velocity and density sections using the relation derived from the well-log data. The interpretation of the inverted/derived results depicts a low-amplitude anomaly zone between 1055 and 1065 ms time interval, which is characterised as a reservoir. The results demonstrate the efficacy and applicability of the GA in reservoir characterisation from the seismic data alone. This study is very helpful for the offshore projects where the information about well logs are missing. [ABSTRACT FROM AUTHOR]