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In 4D seismic, the velocity model used for imaging and reservoir characterization can change over calendar time as the reservoir is produced. This is particularly true for heavy-oil reservoir produced by steam simulation (EOR). We propose an automatic 4D update of the 3D velocity model using an efficient technique based on 4D pre-stack time migration (4D-PSTM) that describes the pre-stack differential kinematic effects by matching the 4D dataset. On real continuous 4D seismic data, the 4D-PSTM allows us to quantify interval velocity variations that can be used to map temperature changes in the reservoir in agreement with petro-elastic model expectations.

A flexible Radon modelling algorithm using time-frequency sparseness weights is introduced. The method may be used for a number of applications and combines the dealiasing and time resolution benefits of existing methods. Compared with a frequency domain sparseness approach, the proposed method results in improved attenuation of low moveout multiples and better primary preservation. Demultiple results using a North Sea dataset are shown.

The paper gives an overview of a full 4C deblending process and its results up to migration in the case of a real 2D 4C dataset acquired offshore Malaysia. Special emphasis is put on the deblending QCs and the specificities of the deblending flow for the PP and PS datasets.

Analysis of time-lapse data is performed on migrated seismic images, which represent the spatial and time-lapse variability of the medium’s reflectivity. The process of migration effectively rotates the wavelet so that it is normal to the imaged reflectors. Processes used in 4D reservoir analysis such as deconvolution, inversion and warping need to follow the structure of the data. The traditional 1D convolutional approach does not honour this directivity. For this reason, we introduce a wave equation based approach which provides an effective platform for structurally consistent reservoir analysis. This includes applications such as wavelet extraction, warping and 4D time-strain inversion.

A new methodology is presented for building near-surface static corrections models consisting on multi-physics measurements integration. The methodology was applied in two geological contexts: presence of a complex, multi-layered sandy overburden on Kahlouche area, and important weathered zone fluctuations due to shallow complex geology on Reggane. Electric and electromagnetic methods were chosen to characterize near-surface geology and improve the existing up-holes velocity models. Seismic/resistivity cross-correlations provide detailed transit time maps fully integrable in the seismic static corrections processing workflow.

We discuss the problem of creating low frequency models for inversion and suggest a simple facies trend-based method which reduces reliance on prior laterally-varying assumptions about the heterogeneity of native reservoir properties. In our example, we were able to identify key hydrocarbon-bearing facies from inversions and tie them accurately to the corresponding petrophysical facies derived from logs

The oil-bearing fractured granite basement rocks are a very important and complicated hydrocarbon reservoir in offshore Vietnam. In this paper, we present a case study of improving the fracture imaging in the Cuu Long Basin offshore Vietnam through Broadband technology, which not only provide great uplift in the low frequency penetration but also make it possible to incorporate TTI/HTI anisotropy inside granite basement. We will review the issues with conventional data and present the new approach, the result and its importance as to the interpretation for drilling.

Model-based water-layer demultiple (MWD) is an effective method for attenuating water-layer-related multiples (WLRMs), especially in shallow water environments. Regular 3D MWD use regularized common-offset cubes for both shot- and receiver-side multiples. We propose a selective-input adaptation of the regular 3D MWD workflow that uses both regularized shot gathers and regularized cubes as input and prioritizing the data selected for model prediction; data is first selected from regularized shot gathers and then regularized cubes. We demonstrate with field data that this selective-input MWD works better than regular MWD, especially for high-order multiple reverberations.

Blended acquisition of ocean bottom node (OBN) surveys may provide important time savings when the survey duration is tightly constrained. We present a method that focuses on the deblending of OBN data recording two simultaneous sources in the Gulf of Mexico. By knowing the respective shot time interval and shot location of two or more sources in the continuous recording data, we can extract the common receiver gathers of each source and deblend them using an iterative coherency-enhancement and subtraction method. In this method, the initial energy model is estimated in the Tau-P domain, and the noise model is estimated adaptively in the curvelet domain. Results show little signal leakage after three iterations of separation.