Tengfei Lin

Semisupervised multiattribute seismic facies analysis

AbstractOne of the key components of traditional seismic interpretation is to associate or “label” a specific seismic amplitude package of reflectors with an appropriate seismic or geologic facies. The object of seismic clustering algorithms is to use a computer to accelerate this process, allowing one to generate interpreted facies for large 3D volumes. Determining which attributes best quantify a specific amplitude or morphology component seen by the human interpreter is critical to successful clustering. Unfortunately, many patterns, such as coherence images of salt domes, result in a salt-and-pepper classification. Application of 3D Kuwahara median filters smooths the interior attribute response and sharpens the contrast between neighboring facies, thereby preconditioning the attribute volumes for subsequent clustering. In our workflow, the interpreter manually painted n target facies using traditional interpretation techniques, resulting in attribute training data for each facies. Candidate attribute...

Improving the quality of prestack inversion by prestack data conditioning

AbstractPrestack seismic inversion techniques provide valuable information of rock properties, lithology, and fluid content for reservoir characterization. The confidence of inverted results increases with increasing incident angle of seismic gathers. The most accurate result of simultaneous prestack inversion of P-wave seismic data is P-impedance. S-impedance estimation becomes reliable with incident angles approaching 30°, whereas density evaluation becomes reliable with incident angles approaching 45°. As the offset increases, we often encounter “hockey sticks” and severe stretch at large offsets. Hockey sticks and stretch not only lower the seismic resolution but also hinder long offset prestack seismic inversion analysis. The inverted results are also affected by the random noises present in the prestack gathers. We developed a three-step workflow to perform data conditioning prior to simultaneous prestack inversion. First, we mitigated the hockey sticks by using an automatic nonhyperbolic velocity a...

Noise suppression of time-migrated gathers using prestack structure-oriented filtering

AbstractPrestack seismic analysis provides information on rock properties, lithology, fluid content, and the orientation and intensity of anisotropy. However, such analysis demands high-quality seismic data. Unfortunately, noise is always present in seismic data even after careful processing. Noise in the prestack gathers may not only contaminate the seismic image, thereby lowering the quality of seismic interpretation, but it may also bias the seismic prestack inversion for rock properties, such as acoustic- and shear-impedance estimation. Common postmigration data conditioning includes running window median and Radon filters that are applied to the flattened common reflection point gathers. We have combined filters across the offset and azimuth with edge-preserving filters along the structure to construct a true “5D” filter that preserves amplitude, thereby preconditioning the data for subsequent quantitative analysis. We have evaluated our workflow by applying it to a prestack seismic volume acquired o...

Quantifying the significance of coherence anomalies

AbstractSemblance and other coherence measures are routinely used in seismic processing, such as velocity spectra analysis, in seismic interpretation to estimate volumetric dip and to delineate geologic boundaries, and in poststack and prestack data conditioning such as edge-preserving structure-oriented filtering. Although interpreters readily understand the significance of outliers for such measures as seismic amplitude being described by a Gaussian (or normal) distribution, and root-mean-square amplitude by a log-normal distribution, the measurement significance of a given coherence of poststack seismic data is much more difficult to grasp. We have followed early work on the significance of events seen in semblance-based velocity spectra, and we used an F-statistic to quantify the significance of coherence measures at each voxel. The accuracy and resolution of these measures depended on the bandwidth of the data, the signal-to-noise ratio (S/N), and the size of the spatial and temporal analysis windows...

Value of nonstationary wavelet spectral balancing in mapping a faulted fluvial system, Bohai Gulf, China

AbstractSeismic data with enhanced resolution allow interpreters to effectively delineate and interpret architectural components of stratigraphically thin geologic features. We used a recently developed time-frequency domain deconvolution method to spectrally balance nonstationary seismic data. The method was based on polynomial fitting of seismic wavelet magnitude spectra. The deconvolution increased the spectral bandwidth but did not amplify random noise. We compared our new spectral modeling algorithm with existing time-variant spectral-whitening and inverse Q-filtering algorithms using a 3D offshore survey acquired over Bohai Gulf, China. We mapped these improvements spatially using a suite of 3D volumetric coherence, energy, curvature, and frequency attributes. The resulting images displayed improved lateral resolution of channel edges and fault edges with few, if any artifacts associated with amplification of random noise.