First Application of Wave Equation Based-AVO Inversion on a Carbonate Reservoir in UAE

Abstract

Abstract Carbonate reservoirs, by definition, present additional challenges compared to clastic sections in seismic reservoir characterization. The lower porosities often hinder the robust detection of fluids using traditional inversion methods, and the whole rock less sensitive to AVO (Amplitude Versus Offset). Additionally, many carbonate reservoirs exhibit property contrasts that greatly surpass the 0.1 reflection coefficient, where linear convolutional models best approximate the seismic signal effectively. The WEB-AVO Reservoir Characterization technology addresses key uncertainties in onshore carbonate reservoirs arising from inherent heterogeneities and lateral porosity variations, first because of the nature of the derived properties, which are the inverses of the Bulk Modulus (Compressibility), inverse of the Shear Modulus (Shear Compliance) and the Bulk Density. These properties serve as direct parameters for reservoir properties of interest. Notably, Compressibility being approximately three times more sensitive to fluids than Acoustic Impedance (Gisolf, 2016). enabling fluid detection in lower porosity ranges when compared to Acoustic Impedance. In addition, the nature of WEB-AVO, being based on the full wave equation and not the linearization of Zoeppritz equations, allows it to inherently handle the scattering seismic often present in carbonate sections. This includes interbed multiples and mode conversions, which can be a major challenge, especially with the land data. The technology also accounts for transmission effects. This minimizes the need for significant preconditioning for the inversion, as the scheme has the full physics required for acquired seismic data, as opposed to having to modify the acquired seismic data to fit the linear inversion models. WEB-AVO was tested on onshore seismic data from the R Field, Abu Dhabi. WEB-IMI analysis was conducted to understand the scattering patterns in the subsurface and optimize the inversion window. The study aims at generating well-validated elastic properties that are directly related to reservoir properties spatially, using data that has not undergone gather preconditioning. These properties were later validated using the blind well test and its lateral predictability to capture the heterogeneity of the reservoir away from the wells. This technique removes the small-reflectivity and primaries-only limitations of linear and reflectivity-based inversion schemes. Additionally, it enables the determination of elastic parameters that are more directly connected to rock properties of interest, such as porosity. In this geological setting, the ability to work on gathers in the presence of multiples has a significant positive impact on both cost and turn-around time.