Marchenko imaging assisted by vertical seismic profiling data for land seismic data in the Middle East

Abstract

Attenuating interference from internal multiples has challenged seismic data imaging in the Middle East basins. The challenge results from the strong short-period internal multiples that exhibit nearly indistinguishable characteristics from the primaries reflected from the underlying reservoirs due to predominantly horizontal strata and occasional low-relief structures, as indicated in the Jurassic formations in Kuwait. To address the internal-multiple issues, multiple prediction followed by adaptive subtraction is the most common approach in the industry. However, due to the similarities between primaries and multiples, applying adaptive subtraction poses a high risk of primary-amplitude damage, preventing quantitative seismic data interpretation. Therefore, we examine the Marchenko method that retrieves Green’s functions from surface seismic data for target-oriented imaging without applying adaptive subtraction. Marchenko imaging has produced promising results on several offshore seismic data sets, but an onshore application is still needed. To better understand the effects of internal multiples and implement Marchenko imaging, we perform integrated analysis through well-log, vertical seismic profiling (VSP), and seismic data from a hydrocarbon field in Kuwait. In addition, we use VSP data to cross-check the retrieved Green’s functions and estimate the scaling factor of the Marchenko method. The results indicate that (1) the poor imaging at the center of the field is due to the destructive interference of internal multiples, (2) the reverberation of internal multiples between the evaporite formations of the overburden is the most likely candidate that affects the seismic images of the Jurassic reservoirs, (3) the retrieved Green’s functions conform to the recorded Green’s functions from VSP data, and (4) Marchenko imaging provides a means to improve the seismic images of the Jurassic formations in Kuwait.