Multi-attribute rotation scheme: A tool for reservoir properties prediction from seismic inversion attributes

Abstract

The multi-attribute rotation scheme (MARS) is a methodology that uses a numerical solution to estimate a transform to estimate petrophysical properties from elastic attributes. This is achieved by estimating a new attribute in the direction of maximum change of a target property in an n-dimensional Euclidian space formed by n attributes, and subsequent scaling of this attribute to the target unit properties. This approach is performed using well logderived elastic attributes and petrophysical properties, and posteriorly applied over seismically-derived elastic attributes. In this study MARS was applied to predict a transform to estimate water saturation and total porosity from elastic attributes, using a two-and three-dimensional approach, respectively. The final goal of this workflow is to apply these transforms over seismically-derived attributes to generate volumes of these properties, which can be used in exploration and production settings for reservoir characterization and delineation, as well as soft variables in geostatistical workflows for static model generation and reserve estimation.

Quantitative Seismic Interpretation of a Class-1 AVO Turbiditic System Located Offshore Cote d’Ivoire, West Africa

“…lithology and porosity, but they are relatively insensitive to the effects of fluid saturation, thereby reinforcing the need to use a probabilistic framework to assess fluid saturation prediction uncertainty as a more effective way to assess this problem. This paper presents an example of the aforementioned case, where an AVO Class-1 turbidite system was characterized in terms of porosity and lithology using the deterministic multi-attribute rotation scheme (MARS) (Alvarez et al, 2015), and the fluid saturation was evaluated using a statistical rock physics (SRP) method based on a probabilistic litho-fluid facies classification (Mukerji et al, 2001) with the goal of determining the most likely fluid scenario and, at the same time, quantifying the uncertainty in the prediction. The combination of rock physics analysis with these deterministic and probabilistic approaches offers a way to improve the understanding of geological features and contributes to the de-risking of potential hydrocarbon prospects in the area.…”