Practical Application of Adaptive Least-Squares RTM to Advance Field Development and Uncover New Reserves in the Sub Salt Provinces

Abstract

Abstract

Seismic imaging algorithms are continuously evolving and the corresponding research is moving toward inversion-based methods such as least-squares migration (LSM, [Schuster, 1993, Nemeth et al., 1999, Duquet et al., 2000, and Tang, 2009]). Least-squares reverse time migration (LSRTM) has gained particular interest in recent years (e.g., Wong et al., 2011, Dong et al., 2012, Dai et al., 2013, Zhang et al., 2013, and Zhan et al., 2014) by virtue of its improved amplitude response, higher spatial resolution, reduced migration artifacts, and enhancement of complex structures (Zeng et al., 2014a) compared to conventional depth migration algorithms.

In general, LSRTM iteratively updates the seismic image with a similar workflow to what is used in full waveform inversion (FWI). One of the major differences between these two methods with respect to implementation is that LSRTM searches for a solution based on seismic reflectivity (geology) rather than seismic velocity.

In this presentation we extend the concept of adaptive imaging by altering migration parameters (such as aperture) during LSRTM iterations to speed up the convergence of the inversion focusing on the geology of the sediments related to potential reservoirs. We name this an “image adaptive” strategy because it is equivalent to applying natural weights to sediment images which are gently dipping in subsalt areas. We demonstrate the effectiveness of the proposed adaptive strategies via a 3D synthetic model derived from the true geology of the Gulf of Mexico (GoM). Lastly, we examine the results of the adaptive LSRTM approach on our multi-client wide-azimuth data acquired in the Freedom area of the GoM. Both the synthetic and real data examples based on the GoM data show significant improvements for images near the steeply dipped salt flanks and those below the base of salt within just a few LSRTM iterations. The images of shadow zone and subsalt area are significantly improved after a few iterations regardless of the practical limitations such as velocity error and weak illumination near and below the salt body. The success of the subsalt image improvements confirms the effectiveness of the adaptive LSRTM strategies and will assist exploration companies in developing subsalt fields and exploration targets.

AAPG Datapages/Search and Discovery Article #90260 © 2016 AAPG/SEG International Conference & Exhibition, Cancun, Mexico, September 6-9, 2016