AVO analysis for high amplitude anomalies using 2D pre-stack seismic data

Amplitude variation with offset (AVO) analysis is an 1 efficient tool for hydrocarbon detection and identification of elastic rock properties and fluid types. It has been applied in the present study using reprocessed pre-stack 2D seismic data (1992, Caulerpa) from north-west of the Bonaparte Basin, Australia. The AVO response along the 2D pre-stack seismic data in the Laminaria High NW shelf of Australia was also investigated. Three hypotheses were suggested to investigate the AVO behaviour of the amplitude anomalies in which three different factors; fluid substitution, porosity and thickness (Wedge model) were tested. The AVO models with the synthetic gathers were analysed using log information to find which of these is the controlling parameter on the AVO analysis. AVO cross plots from the real pre-stack seismic data reveal AVO class IV (showing a negative intercept decreasing with offset). This result matches our modelled result of fluid substitution for the seismic synthetics. It is concluded that fluid substitution is the controlling parameter on the AVO analysis and therefore, the high amplitude anomaly on the seabed and the target horizon 9 is the result of changing the fluid content and the lithology along the target horizons. While changing the porosity has little effect on the amplitude variation with offset within the AVO cross plot. Finally, results from the wedge models show that a small change of thickness causes a change in the amplitude; however, this change in thickness gives a different AVO characteristic and a mismatch with the AVO result of the real 2D pre-stack seismic data. Therefore, a constant thin layer with changing fluids is more likely to be the cause of the high amplitude anomalies.

The vertical image projection method for migration stretch compensation

True amplitude inversion is often carried out without taking into account migration distortions to the wavelet. Seismic migration leaves a dip-dependent effect on the wavelet that can cause significant inaccuracies in the inverted impedances obtained from conventional inversion approaches based on 1D vertical convolutional modelling. Neglecting this effect causes misleading inversion results and leakage of dipping noise and migration artifacts from higher frequency bands to the lower frequencies. I have observed that despite dip-dependency of this effect, low-dip and flat events may also suffer if they are contaminated with cross-cutting noise, steep migration artifacts, and smiles. In this paper I propose an efficient, effective and reversible data pre-conditioning approach that accounts for dip-dependency of the wavelet and is applied to migrated images prior to inversion. My proposed method consists of integrating data with respect to the total wavenumber followed by the differentiation with respect to the vertical wavenumber. This process is equivalent to applying a deterministic dip-consistent pre-conditioning that projects the data from the total wavenumber to the vertical wavenumber axis. This preconditioning can be applied to both pre- and post-stack data as well as to amplitude variation with offset (AVO) attributes such as intercept and gradient before inversion. The vertical image projection methodology that I propose here reduces the impact of migration artifacts such as cross-cutting noise and migration smiles and improves inverted impedances in both synthetic and real data examples. In particular I show that neglecting the proposed pre-conditioning leads to anomalously higher impedance values along the steeply dipping structures.

Amplitude variation with offset analysis of nonbright spots for gas channel identification: A case study from the western Sichuan Basin, China

The Shaximiao Formation in the Zhongjiang Gas Field of the Sichuan Basin was initially a high-productivity gas field with the bright spot channel as the vital exploration target. With further development, gas wells were obtained in some nonbright spot areas, which caused interpreters to pay great attention to the channels with nonbright spot abnormal amplitudes. We have developed a method to delineate nonbright spot channels from the complicated sand-mudstone contact relationship. First, we classified sandstone into types I, IIa, IIb, and III, depending on the responses of the amplitude variation with offset from the drilled data, to produce a forward model. We the explain why the hidden channel cannot be identified using the full-angle stack seismic data based on this model. Afterward, we put forward a difference, between the synthetic seismogram responses of bright and nonbright channels, in creating seismic-to-well ties for nonbright channels. This difference from bright channels is that the synthetic data’s wave peak is not corresponding to the peak of the real seismic data. The wave trough has the same situation. Finally, we used far-angle stack seismic data to calculate coherent energy and instantaneous spectral attributes (the latter produced for red-green-blue blending) to identify the hidden channel. We observed that parts of the channel are more clearly visible in the far-angle stack than in the full-angle stack data. In the latter situation, we cannot describe the geometric shape of the channel elaborately. The Shaximiao Formation example is a relatively effective analog for nonbright spot plays compared with elsewhere.

Pressure fluctuation study in the stages of a multistage pump at best efficiency points under various operating speeds

The interaction between the rotor and stator is a major source of high amplitude pressure fluctuation and flow-induced vibration in multistage centrifugal pumps. The pressure fluctuation is detrimental to the reliable operation of pumps. The sensitivity of vibration is severe if the number of stages is more. In the present experimental study, a vertical multistage centrifugal submersible pump is used to measure the pressure fluctuation level at Best Efficiency Points (BEP) and to determine the influence of stage and operating speed on pressure fluctuation. For this purpose, pressure fluctuation signals were captured at the delivery side of the pump at BEP at various speed settings. The characteristics of pressure fluctuation at BEP at various operating speeds were studied with the help of spectra, i.e., in the frequency domain. The amplitude variation of pressure fluctuation with harmonics of vane passing frequency at stages were studied. Results have indicated that variation of pressure fluctuation with stage and speed exhibited a non-linear variation. In addition, such a pressure fluctuation study will be helpful to modify the design to obtain a uniform pressure distribution in the stages of a multistage pump.

Model misspecification and bias in the least-squares algorithm: Implications for linearized isotropic AVO

When inversions use incorrectly specified models, the estimated least-squares model parameters are biased. Their expected values are not the true underlying quantitative parameters being estimated. This means the least-squares model parameters cannot be compared to the equivalent values from forward modeling. In addition, the bias propagates into other quantities, such as elastic reflectivities in amplitude variation with offset (AVO) analysis. I give an outline of the framework to analyze bias, provided by the theory of omitted variable bias (OVB). I use OVB to calculate exactly the bias due to model misspecification in linearized isotropic two-term AVO. The resulting equations can be used to forward model unbiased AVO quantities, using the least-squares fit results, the weights given by OVB analysis, and the omitted variables. I show how uncertainty due to bias propagates into derived quantities, such as the χ-angle and elastic reflectivity expressions. The result can be used to build tables of unique relative rock property relationships for any AVO model, which replace the unbiased, forward-model results.

The SEAM Barrett model: strengths and weaknesses

The SEAM Barrett model was designed to model typical land basins found in the North American mid-continent that host unconventional reservoirs, such as fractured shale reservoirs. This model was used recently in several studies to assess whether shale bodies could be resolved using azimuthal 3D P-P reflection seismic data. In one study it was claimed that near-surface complexity prevents the identification of the shale bodies using azimuthal analysis and concluded that VVAz (Velocity Variation with Azimuth) and AVAz (Amplitude Variation with Azimuth) are not worth running in the Permian basin. However, another study by different authors applied a different seismic processing sequence to successfully resolve the reservoir geobodies and showed promising AVAz and VVAz results. This paper focuses on the SEAM Barrett model itself. Despite some advantages, the limitations of the Barrett model prevent conclusions to be drawn about the usefulness of VVAz and AVAz to characterize fractured reservoirs in other situations, such as the Permian Basin.