- •The geometrical parametrs ot the 3d surveys
- •Contents
- •Introduction
- •1. 3D seismic surveys
- •Figure 1.1 – The scheme of process of transformation of a sound signal
- •Figure 1.2 – The example of different angles (azimuth) and distances (offset)
- •2. The factors influence on design of 3d seismic surveys
- •Figure 2.1 – The example of a model built for a complex sub-surface area
- •3. 3D data geometries
- •3.1 Data coordinates
- •3.2 Marine-data geometries
- •3.3 Land-data geometries
- •3.3.1 Wide-azimuth geometries
- •Conclusion
- •Glossary
- •Literature
- •Аннотация
1. 3D seismic surveys
Seismic reflection imaging is based on the principle that acoustic energy (sound waves) will bounce, or «reflect» off the interfaces between layers within the earth’s subsurface. During a seismic reflection survey acoustic energy is imparted into the earth with a seismic source. These sources are impacted upon an aluminum strike plate ground surface to create high frequency seismic energy. After impact of the source the sound waves propagate and spread out along spherical wavefronts in all directions. The usable sound energy travels into the earth (signal), while some energy is lost into the air or along the ground surface (noise) [1].
The earth is characterized by many layers, each with different physical properties. When sound waves traveling through the earth encounter a change in the physical properties of the material in which they are traveling, they will either reflect back to the surface or penetrate deeper into the earth (where they may again be reflected at another interface). At a geologic interface some seismic energy is always transmitted while some is reflected. The acoustic impedance is a measure of how seismic energy will react when it encounters a subsurface layer. This physical property is closely associated with the density of a layer. Contrasts in acoustic impedance create seismic reflection interfaces. Subsurface reflections of seismic energy, therefore, most often occur at the interfaces between lithologic changes (a transition from sediment to rock, for example). As a result, seismic reflections make it possible to map the stratigraphy below a site.
Areas of structural deformation, such as fractures, can also be observed using seismic reflection. A fractured rock surface produces different reflections than a continuous rock surface. Acoustic energy is diffracted by fractured rock surfaces in much the same way that a visual image is distorted in a shattered mirror. Identifying diffracted energy patterns is one way in which geologic structures such as faults and fractures can be mapped using seismic reflection surveys [2].
During a seismic reflection survey high-speed digital data recording systems (seismographs) and acoustic sensors (geophones) are used to measure reflected sound waves. Compressional waves (p-waves) are a type of seismic waves. Compressional waves are so named because the wave fronts propagate through the earth mechanically; when one particle moves and compresses the next particle. The figure 1.1 (A) shows the wavefront of sound waves impinging on a geophone. The particle motion in the earth moves the geophone body, which houses a magnet within a suspended coil inside the geophone. This action produces an analog voltage signal that is proportional to the ground motion (figure 1.1(B)). The seismograph then digitizes the analog signal by breaking the signal into discrete time samples, and creates a digital level (a numeric value) for the amplitude of the signal during that time sample (figure 1.1 (C)). The data in surveys are digitized to 21-bit resolution, which means the analog geophone signal is broken into 221 or 2,097,152 levels. The analysis of the final processed wavelet (figure 1.1 (D)), which is the result of the post-survey data reduction process, and is a high resolution, distortion free representation of the subsurface [3].
Since 2D data collection occurs along a line of receivers, the resultant image represents only a section below the line. Unfortunately this method does not always produce a clear image of the geology. 2D data can often be distorted with diffractions and events produced from offline geologic structures, making accurate interpretations difficult.
