Abstract
In seismic exploration, there is continuous drive towards more dense data sampling to better image complex geological structures. Recent advances in acquisition such as Wide-Azimuth, Multi-Azimuth or Rich-Azimuth acquisition can deliver a more diverse range of source, azimuth and offset sampling. To collect such data, multiple source and receiver vessels are deployed, thereby increasing the costs of the survey significantly. In conventional acquisition, there is zero time overlap between shot records, and data are recorded discontinuously. The source domain is often poorly sampled, leading to aliasing. In simultaneous acquisition, data can be recorded continuously, and temporal overlap between shots is allowed. Consequently, more sources are fired during the same period of acquisition, which greatly enhances the flexibility in survey geometries. As a result, a more densely sampled data set in terms of source spacing, but also azimuth and offset distributions can be obtained. In terms of efficiency, simultaneous acquisition can contribute by reducing survey times, which is of particular value in critical situations where small acquisition timewindows dominate due to severe safety, environmental or economic restrictions. As such, from an acquisition point of view, simultaneous acquisition holds the promise of both efficiency and quality improvements. However, unless source separation can be achieved to a sufficiently high degree, the enormous potential benefits of simultaneous sources remain unrealized. Two approaches are currently utilized by the industry to achieve source separation: methods based on random noise attenuation and inversion-based methods. By regarding the energy from secondary sources as incoherent noise, after sorting the acquired data into an appropriate domain, the interference noise appears as random spikes which could be attenuated using well-known random noise removal procedures. Alternatively, inversion-driven methods aim to construct the separated sources through the minimization of a cost function that describes the “data misfit”. In such methods, incoherent energy is no longer regarded as noise that is to be removed. Instead, this energy is recognized as a representation of coherent events belonging to (one of) the interfering shots. An inversion approach aims to distribute all energy in the blended shot records by reconstructing the individual unblended shot records at their respective locations. In this abstract, an inversion-driven method is utilized that uses coherency measures to reconstruct the individual shot gathers from the blended data. The method is demonstrated to be capable of separating sources, even in the presence of strong diffraction energy. The method can be used in conjunction with other methods, resulting in so-called hybrid solutions. A simultaneous source wide-azimuth 3D data set from the Gulf of Mexico is presented.
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