Abu Dhabi Company for Onshore Oil Operations (ADCO) had a need for an exploration survey to delineate a low relief structure in onshore Abu Dhabi. The terrain is characterized by sand dunes of variable heights with some oilfield infrastructure, farms and conservation areas. ADCO tendered for a conventional survey but the successful bidder offered an economically attractive Single Sensor / Single Source (S4) option with the MD low frequency enhanced sweep. ADCO has tested some of the processing technology associated with S4 recording on vintage datasets and were keen to try them on a true S4 dataset.In particular it was very important that a good near surface model was obtained because of the low relief target. The use of the low frequency MD sweep, Shear Wave Inversion (SWI) and Simultaneous Joint Inversion (SJI) was an ideal approach to resolving the near surface model. There was an uphole program planned to calibrate the derived near surface model. The SWI volume was generated before the upholes were drilled so that any anomalies could be investigated.The crew with 50,000 channels mobilized and commenced operations on October 26th 2013 and completed the 604 Sq.km survey by December 25th. The survey consisted of 241,860 VP's and generated 3.5 billion traces. Despite this volume of data a field QC volume was generated on the crew utilizing a pre-defined velocity field developed in collaboration with ADCO and was delivered two days after the last shot. This volume was interpretable to guide the main processing team.Whilst the full processing and evaluation of the data is still ongoing, the early results have clearly shown that the S4 technique is ideally suited to acquisition in sand dune areas with infrastructure. This presentation outlines the details of this survey and the lessons learned.

Multiple attenuation was successfully performed on land seismic data in the difficult Abu Dhabi sand dune and sabkha environment. The keys to success were careful analysis plus selection and application of carefully designed data-adaptive multiple attenuation workflows. The demultiple success on the South East Abu Dhabi seismic data described in this paper was the result of a unique workflow developed specifically for this survey. Development of the workflow depended on rigorous analysis and consistent feedback from interpreters and geophysics specialists. Multiples with similar prestack moveout with offset to the primary events were successfully modeled and removed from seismic data to produce higher quality final seismic images. Onshore seismic data from the high sand dune South-Eastern Abu Dhabi area suffers from strong ambient noise and multiples that make exploration efforts difficult. Although a variety of techniques and algorithms exist for modeling and removing multiples from seismic data, there is no single method that is appropriate for all cases. Successful projects for the most difficult onshore multiple problems are often the result of careful analysis, selection and application of the right technology and the use of an appropriate data-adaptive workflow. The demultiple success on the South East Abu Dhabi seismic data demonstrates that with the proper tools and feedback it is possible to developed a workflow that can attenuate even the most difficult multiple noise. Introduction Onshore seismic data from the high sand dune South-Eastern Abu Dhabi area suffers from strong ambient noise and multiples that make exploration efforts difficult. Figure 1 is an elevation map of the study area with the large sand dunes shown in blue. The height of the dunes ranges from ~50–70m above MSL. During 2006 a multiple attenuation pilot was conducted over this approximately 300 sq km area. The objectives included multiple attenuation and improving the pre-stack and post-stack signal-to-noise ratio such that the data would be appropriate for AVO and reservoir characterization. The results from the multiple attenuation pilot demonstrated that both pre and poststack seismic data quality can be improved sufficiently to satisfying the pilot study objectives. The modern toolkit for multiple removal from pre-stack seismic data contains a variety of techniques designed to use various attributes of the multiples, such as their differential moveout, predictability, etc. Despite decades of research, no single algorithm or technique emerged to solve all of our multiple problems. Successful projects, especially for the most difficult multiple problems are the result of careful data analysis and the appropriate choice of algorithms by experienced geophysicists. Often the best results arise from a carefully designed workflow of data preconditioning and several multiple attenuation steps. Orthogonal geometry data sets, particularly those from high ambient noise environments, present one of the more difficult demultiple problems, at least for pre-stack data. Orthogonal geometries used for more economically feasible survey designs often provides poor or irregular sampling in one or more data domains.