Integration of time-lapse seismic data using the onset time approach: The impact of seismic survey frequency Thesis uri icon

abstract

  • The seismic inversion method using the seismic onset times has shown great promise for integrating frequent seismic surveys for updating geologic models. However, due to the high cost of seismic surveys, frequent seismic surveys are not commonly available. In this study, we focus on analyzing the impact of seismic survey frequency on the onset time approach, aiming to extend the advantages of onset time approach when infrequent seismic surveys are available. To analyze the impact of seismic survey frequency on the onset time approach, first, we conduct a sensitivity analysis based on the frequent seismic survey data (over 175 surveys) of steam injection in a heavy oil reservoir (Peace River Unit) in Canada. The calculated onset time maps based on seismic survey data sampled at various intervals from the frequent data sets are compared to examine the need and effectiveness of interpolation between surveys. Additionally, we compared the onset time inversion with traditional seismic amplitude inversion and quantitatively investigate the nonlinearity and robustness for these two inversion methods. The sensitivity analysis shows that using interpolation between seismic surveys to calculate the onset time, an adequate onset time map can be extracted from the infrequent seismic surveys. This holds good as long as there are no changes in the underlying physical mechanisms during the interpolation period. It is concluded that the linear interpolation is more efficient and robust than the Lagrange interpolation. A 2D waterflooding case demonstrates the necessity of interpolation for resolving into the large time span between the seismic surveys and obtaining more accurate model update and more efficient misfit reduction. The Brugge benchmark case shows that the onset time inversion method obtains comparable permeability update as the traditional seismic amplitude inversion method while being much more efficient. This results from the significant data reduction achieved by integrating a single onset time map rather than multiple sets of amplitude maps. The onset time approach also achieves superior convergence performance, resulting from its quasi-linear properties. It is found that the nonlinearity of the onset time method is smaller than that of the amplitude inversion method by several orders of magnitude.

author list (cited authors)

  • Liu, T., Chen, H., Hetz, G., & Datta-Gupta, A.

complete list of authors

  • Liu, Tian||Chen, Hongquan||Hetz, Gill||Datta-Gupta, Akhil

publication date

  • June 2020