Seismic Data Processing (May 16)

Fourier transform is from time domain to frequency domain. All the process and analysis were conducted in frequency domain.

In marine data acquisition, the boat is moving continuously, towing the air gun and streamers at the same time.

The properties that determine how long it takes a seismic wave to travel through a material are density and seismic velocity. Density refers to the mass per unit volume of the material, while seismic velocity is the speed at which the wave travels through the material. These two properties are directly related to each other, as materials with higher density tend to have higher seismic velocities. Therefore, the correct answer is density and seismic velocity.

Refracted and direct wave can be remove by FK Filtering process.

The Fourier Transform is a mathematical tool that allows us to analyze a waveform by decomposing it into its individual sinusoidal components. It is used to convert time domain data, such as a waveform in the time domain, into the frequency domain, where we can see the different frequencies present in the signal. This transformation is achieved through an algorithm, making the statement "An algorithm used to convert time domain data to Fourier domain" the best description of the Fourier Transform among the given options.

Attributes analysis will be conducted in post-stack processing.

Trace editing is the correct processing step for the purpose of removing a single noisy trace or dead trace. This step involves manually reviewing and modifying the seismic data to eliminate any unwanted or irrelevant traces that may interfere with the interpretation or analysis of the data. By removing the noisy or dead trace, the overall quality and accuracy of the data can be enhanced, allowing for better analysis and interpretation of the seismic information.

Cross correlation operations involve shifting and multiplication, which are also part of convolution. However, folding is not a part of cross correlation. Folding refers to flipping the signal horizontally, which is not done in cross correlation. Instead, cross correlation calculates the similarity between two signals by sliding one signal over the other and calculating the sum of the element-wise products. Therefore, folding is the operation that cross correlation does not take part in convolution.

Harmonic signal can be identify using Fourier series.

Other answer options also correct, but not best represent the seismic data processing.

Gain and trace balancing is the correct answer because it refers to the processes that involve restoring the amplitude energy. Gain balancing refers to adjusting the gain or amplification of a signal to ensure that it is at the desired level. Trace balancing, on the other hand, involves adjusting the amplitude of individual traces within a signal to achieve a balanced overall waveform. Both of these processes are essential in restoring the amplitude energy of a signal.

Spiking Deconvolution is the correct processing step for the data enhancement purpose described. This technique is used to convert a broad wavelet into a spike, which helps to improve resolution. Deconvolution is a mathematical operation that removes the effects of convolution from a signal, and in this case, it is used to enhance the data by sharpening the wavelet and increasing the resolution. Spiking Deconvolution specifically focuses on transforming a broad wavelet into a spike, which can be beneficial in various applications such as seismic data processing.

The standard tape format during the acquisition is SEGD and SEG2. These formats are commonly used in the field of geophysical exploration for storing and transmitting seismic data. SEGD is an acronym for Society of Exploration Geophysicists Data Exchange Format, which is a standard format for storing seismic data on magnetic tapes. SEG2, on the other hand, refers to the SEG-Y Revision 2 format, which is a widely used industry standard for storing seismic data in digital form. Both formats are essential for efficient data exchange and analysis in the field of geophysics.

Automatic gain control is the correct processing step for enhancing data by temporarily increasing the amplitude during a display session. This technique automatically adjusts the gain of a signal to maintain a consistent output level, regardless of variations in input signal strength. By increasing the amplitude, the data can be displayed more prominently and effectively, allowing for better visualization and analysis.

Predictive deconvolution is the correct processing step for removing water bottom multiples without velocity analysis. Predictive deconvolution is a technique used in seismic data processing to suppress or remove multiples, which are unwanted reflections that occur due to the presence of multiple layers of rock or fluid in the subsurface. This technique uses a predictive filter to estimate and subtract the multiples from the seismic data, thus enhancing the primary reflections of interest. In this case, predictive deconvolution is specifically used to remove water bottom multiples without the need for velocity analysis.

To prevent artifacts from appearing on the data after the FK filtering process, an anti-alias filter is used. This filter helps to remove or reduce high-frequency components in the data that can cause aliasing, which is the distortion or artifacts that occur when the sampling rate is too low to accurately capture the original signal. By applying an anti-alias filter before the FK filtering process, these artifacts can be minimized or eliminated, resulting in enhanced data quality.

The correct processing step for the data enhancement purpose of removing refraction signal and differentiating it from reflections is Mute, FK Filter. Muting involves suppressing or zeroing out specific time intervals in the seismic data where the refraction signal is expected to occur. This helps in isolating the reflections and enhancing their clarity. FK (Frequency-Wavenumber) filtering is then applied to further separate the desired reflections from the remaining noise and unwanted signals.

Spherical divergence correction is the correct processing step for enhancing data by increasing the amplitude due to wave propagation effects. This technique is used to compensate for the decrease in amplitude that occurs as waves propagate through space. By applying spherical divergence correction, the amplitude of the waves can be increased, resulting in enhanced data quality.

The correct processing step for the data enhancement purpose of placing shot/receiver separations in trace headers is geometry calculation. This step involves calculating the distances between the shot and receiver locations and storing this information in the trace headers. This helps in accurately positioning the seismic data and enables further analysis and interpretation of the data.

The correct processing step for data enhancement in this case is the amplitude spectrum. The amplitude spectrum helps to identify the strongest frequencies in the data, allowing for the separation of signal and noise. By analyzing the amplitude spectrum, one can determine which frequencies contribute the most to the overall signal and distinguish them from the unwanted noise.