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Various far-offset marine acquisition geometries have been widely deemed as promising for alleviating imaging difficulties in deepwater Gulf of Mexico (GOM). However, incorporating very far offsets into subsalt imaging remains challenging. In this case study in the GOM, we explore the benefits of far offsets using ocean bottom node (OBN) data with acquisition offsets up to 25 km and investigate the untapped potential of extremely far offsets of up to 50 km. Using far offsets above 12 km, and up to 25 km was not straightforward, but with some help, they significantly improved the subsalt images and were valuable for building the salt model in this study. Imaging benefits from extremely far offsets up to 50 km were also observed but usefulness for salt model building might be limited.

Variation of sound wave velocity in water (water velocity) and node positioning errors can cause strong 4D noise in ocean bottom node (OBN) time lapse processing if they are not addressed correctly. Here we proposed a method to jointly invert the water velocity and the node position from the recorded direct arrival time in the data. We then validated this method by synthetic and real OBN data examples from deep water Gulf of Mexico.

A workflow of azimuthal inversion is presented and successfully applied on a wide-azimuth seismic data. This workflow is based on a novel approach to quantitatively extract anisotropy information in a horizontal transverse isotropic (HTI-) medium. The method was first described by Mesdag (2016) and mimics anisotropic reflectivity behavior by isotropic forward modelling and anisotropy-transformed elastic properties. In this paper a concept of an Azimuthally varying Low Frequency Model (ALFM) is also introduced and demonstrated. The ALFM provides anisotropy information below seismic bandwidth, hereby reducing side-lobes of inverted magnitude of anisotropy, thus allowing for better anisotropy characterization.

Relatively large spectral differences exist between streamer and ocean bottom seismometer (OBS) data, mostly due to their different ghost effects – streamer data have both shot- and receiver-side ghost, while OBS data only have shot-side ghost. In a recent OBS-streamer 4D study in deepwater Gulf of Mexico, we investigated three schemes of spectral matching between OBS and streamer data: conventional 1D matching of streamer to OBS, receiver deghosting on streamer data only, and full deghosting on both surveys. We find that receiver deghosting on streamer data is better than 1D matching, providing a better match between the streamer and OBS data before migration and an increased 4D signal-to-noise ratio (S/N) after migration. However, we also found that source deghosting on both surveys does not improve 4D results; instead the spectra of streamer and OBS, especially at lower frequencies, are more different after source deghosting. Receiver deghosting alone on the streamer data gives the best 4D results among the three spectral matching schemes.

A method is described to allow quantitative usage of isotropic modeling and inversion in anisotropic media. Based on the Rüger reflectivity equations for HTI media transforms are designed for the elastic parameters used in pre-stack inversion. The transformed elastic parameters can be used in isotropic forward modeling and inversion to exactly mimic the anisotropic reflectivity behavior of the seismic data. The proposed method allows us to close the loop between well log data and seismic inversion results without having to revert to experimental anisotropic inversion algorithms. In this paper a synthetic feasibility study will be shown, indicating that we can exactly predict the outcome of a wide azimuth (WAZ) seismic inversion experiment based on isotropic elastic parameters and Thomsen’s anisotropy parameters.

A robust surface wave inversion has been developed to invert near surface S wave velocity for depth model building and shear statics correction. The algorithm utilizes mainly two most effective inversion engines: the non-linear least square Levenberg-Marquardt (LM) inversion and the differential evolution (DE) method. Both of them can minimize the dispersion curve distance for simpler cases, or directly solve the Eigen-determinant of the surface wave secular functions for more complex cases. The algorithm has been applied to an OBC 3D4C data from off shore Vietnam, where the near surface geology changes greatly from rapid depth varying reef structures to floodplain alluvial fans. The surface wave, it is the Scholte wave in this case, has demonstrates variety of dispersion patterns, which are used in the inversion and revealed the complex subsurface velocity model underneath the sea floor. The receiver side shear statics has been calculated based on the inverted Vs model and applied to the PS wave data, which not only saves man powers tremendously compared with the conventional shear statics method, but also provides a more accurate solution. The imaging results show much better event continuity and geologically interpretable horizons.

Most deblending approaches utilize coherency criteria in a certain domain to separate blended signals. Due to the presence of noise, such separation in the time domain can never be perfect. Conservative deblending is often performed in order to protect primary signals. As a consequence, residual source cross-talk noise can remain in the data after deblending, which could affect the subsequent pre-processing steps such as de-ghosting and de-multiple. Here, we present a wave equation-based demigration flow to help protect primary signals for deblending. It can be combined with existing deblending approaches to achieve clean deblended results with minimal primary damage. The workflow is tested on a numerically blended data set using acquired wide azimuth data. We also demonstrate its ability to overcome deblending challenges when the shots are coarsely sampled, and the dithering time is small.

OBN SRME that combines OBN and streamer data is known to be an effective way to predict surface-related multiples in OBN data. However, the available streamer data often have limited offset/azimuth coverage. Additionally, the double source wavelets due to the cross-convolution of OBN and streamer data limit the bandwidth (loss of low and high frequency) of the multiple prediction. OBN model-based water-layer demultiple (MWD) overcomes such limitations and is a good complement of OBN SRME; MWD replaces the streamer data with the water-bottom Green’s function that has no offset/azimuth limitation and keeps the full bandwidth of the input data. With Gulf of Mexico (GOM) OBN data over the Atlantis field, we illustrate the benefit of joint SRME and MWD over solely SRME with the improved attenuation of low-frequency multiples and deep peg-leg multiples.

Offshore development requires detailed understanding of subsurface reservoirs and proper well placement. Use of all available information in an integrated reservoir model leads to improved production rates and higher EUR. Conventional methods use well logs, geologic information, and structure from seismic interpretation in static reservoir models, which, in turn, predict future production and evaluate alternative management scenarios. However, these models, which use different data types in isolation, often fail replicate past production (history matching). An integrated seismic-to-simulation workflow is presented in this paper; dense 3D seismic data provide a great deal of lateral lithofacies and rock-property information that is essential to the static model.