In the early days of 3D seismic, there was a common tendency to classify the objectives of any survey as being either "structural" or "stratigraphic". The parameters selected for the survey design and data acquisition, and those selected for the subsequent data processing, would often change depending upon the classification. If we look at the interpretation of most 3D surveys we can see that this simple classification is not justified. More and more information is extracted from every data set, and then used to improve our understanding of the reservoir. Most 3D surveys collected today are, to a greater or lesser extent, being used as important components in reservoir characterization studies. The objectives of such studies being the integrated understanding of the reservoir's structure, the lithology, and the pore fluids.

Although significant time and effort is usually spent trying to achieve the optimum technical design for these 3D surveys, there are always compromises because of cost, time and other influences such as environmental impact. The technology available for recording and processing seismic data in a cost effective and timely manner often results in limitations in the results which are provided to the interpreter. It is important for the interpreter to understand the nature and relative importance of these limitations. In recent years, an increasing number of time lapse (4D) seismic surveys have been acquired. In these cases the seismic data is the subject of additional objectives i.e., the monitoring of fluid movements through the reservoir and the subsequent use of this information to update the reservoir simulation model. These reservoir monitoring studies present some additional requirements on both acquisition and data processing systems, if the studies are to be successful.

This paper discusses some of the data acquisition and data processing issues which must be considered when acquiring seismic surveys for reservoir characterization and monitoring.


In reservoir characterization an initial model of the reservoir is built using all of the available well information, geological and petrophysical data, together with a structural interpretation from the seismic data. The model can then be refined using as much additional information as can be extracted from the seismic data by inversion methods1–2. The quality of the updated model will be directly related to the resolution of the seismic data. In order to optimize the seismic resolution at the level of the reservoir, data acquisition and processing methods should be designed to achieve a good signal-to-noise ratio over as broad a signal bandwidth as possible. Since high resolution also implies the ability to position reflection energy accurately in both space and depth, near surface (static) and velocity models used in the imaging processes are very important. Knowledge of the phase of the recorded data and the ability to achieve a good tie of the seismic data to the wells is also necessary.

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