Abstract

The CRS method assumes subsurface reflector elements with dip and curvature. The corresponding CRS stacking operator is not limited to a single CMP gather, but collects the reflection energy of a subsurface element from all contributing traces, including neighbour CMPs of the imaging location. CRS imaging of the sparse 3D data provided a strong increase in subsurface resolution, and signal-to-noise ratio. It also resolve the faulting which was largely buried in noise in conventional images. The combination of sparse 3D aquisition with CRS processing prove to be a suitable strategy for achieving good subsurface resolution at limited costs.

Introduction

Seismic acquisition in frontier areas faces a high risk when dealing with remote areas with difficult access, limited operation times due to seasonal influences and governmental restrictions, and a large uncertainty in the design of optimum acquisition parameters. Under such circumstances, high-fold 3D seismic surveying is not feasable, but 2D surveying may also not be appropriate to describe the areal extent of potential targets.

Sparse 3D surveys are frequently used as a compromise. A land data example from North Africa is presented here where large bin sizes (50x50m), and low data fold kept the acquisition turnaround in an acceptable time range. Seismic investigations focussed on flat target horizons, and low-throw faulting in the target regions. As expected, the results of standard time processing could not compete with results from nearby high-fold surveys. A much lower signal-to-noise ratio provided a very restricted resolution of the subsurface.

In an attempt to increase resolution, a CRS time processing was applied to these data. The CRS, or Common Reflection Surface method, is well suited to tackle noise problems in low-fold data, since it uses a much higher stacking fold than conventional time domain imaging. CRS obtains this high fold by assuming subsurface reflector elements with dip and curvature. In addition to the desired increase of signal-to-noise ratio and reflector continuity, the CRS processing aimed at resolving the faulting which was almost completely buried in noise in conventional images.

CRS Method

In time domain seismic imaging, the NMO/DMO stacking technique has been dominant for many decades. However, the simple subsurface model of the NMO stack, the loss in resolution by the DMO process, and the dependence on a user-derived velocity model has motivated the search for alternative time domain imaging methods.

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