Limitations on impedance inversion of band‐limited reflection data

Geophysics ◽  
2000 ◽  
Vol 65 (3) ◽  
pp. 951-957 ◽  
Author(s):  
Santi Kumar Ghosh
Keyword(s):  
Seismic Data ◽  
Dominant Frequency ◽  
Seismic Exploration ◽  
Reflection Data ◽  
Homogeneous Half Space ◽  
Impedance Inversion ◽  
White Band ◽  
Full Band ◽  
Band Limited ◽  
Analytical Expressions

A seismic approximate impedance log is often the ultimate output in the sequence of seismic data‐processing steps. In principle, the true acoustic impedance is obtainable from the inversion of full‐band impulse response. Because the seismic data necessarily is band limited, its inversion obviously would produce an approximate impedance log. A question addressed is how the true and reconstructed logs are related and a mathematical relationship between the two is derived without the assumptions required in an existing derivation of the same result. The deductions also include the contribution of an individual seismic frequency in the reconstruction of the impedance and, in particular, a simple formula for the contribution of direct‐current (dc) frequency, which never is recorded but is required to supplement the inversion. Analytical expressions are derived for the reconstructed impedance corresponding to any given frequency band for two cases: a simple discontinuity and a bed sandwiched between two similar half‐spaces. While analyzing the results, some conclusions pertinent to seismic exploration are drawn. A criterion is formulated to decide what should be termed a thin bed within a homogeneous half‐space in the context of a white band of frequencies, in contrast to a single dominant frequency, which is the basis of the Widess criterion.

Instantaneous spectral bandwidth and dominant frequency with applications to seismic reflection data

Geophysics ◽  
1993 ◽  
Vol 58 (3) ◽  
pp. 419-428 ◽  
Author(s):  
Arthur E. Barnes
Keyword(s):  
Instantaneous Frequency ◽  
Seismic Data ◽  
Seismic Reflection ◽  
Power Spectra ◽  
Dominant Frequency ◽  
Center Frequency ◽  
Spectral Bandwidth ◽  
Instantaneous Amplitude ◽  
Seismic Reflection Data ◽  
Reflection Data

Fourier power spectra are often usefully characterized by average measures. In reflection seismology, the important average measures are center frequency, spectral bandwidth, and dominant frequency. These quantities have definitions familiar from probability theory: center frequency is the spectral mean, spectral bandwidth is the standard deviation about that mean, and dominant frequency is the square root of the second moment, which serves as an estimate of the zero‐crossing frequency. These measures suggest counterparts defined with instantaneous power spectra in place of Fourier power spectra, so that they are instantaneous in time though they represent averages in frequency. Intuitively reasonable requirements yield specific forms for these instantaneous quantities that can be computed with familiar complex seismic trace attributes. Instantaneous center frequency is just instantaneous frequency. Instantaneous bandwidth is the absolute value of the derivative of the instantaneous amplitude divided by the instantaneous amplitude. Instantaneous dominant frequency is the square root of the sum of the squares of the instantaneous frequency and instantaneous bandwidth. Instantaneous bandwidth and dominant frequency find employment as additional complex seismic trace attributes in the detailed study of seismic data. Instantaneous bandwidth is observed to be nearly always less than instantaneous frequency; the points where it is larger may mark the onset of distinct wavelets. These attributes, together with instantaneous frequency, are perhaps, of greater use in revealing the time‐varying spectral properties of seismic data. They can help in the search for low frequency shadows or in the analysis of frequency change due to effects of data processing. Instantaneous bandwidth and dominant frequency complement instantaneous frequency and should find wide application in the analysis of seismic reflection data.

Band-limited scattered wavefield reconstruction beneath complex overburdens using the Marchenko method

2021 ◽  
Author(s):  
David Vargas ◽  
Ivan Vasconcelos ◽  
Matteo Ravasi
Keyword(s):  
Seismic Data ◽  
Reservoir Characterization ◽  
Accurate Estimation ◽  
Target Area ◽  
Complex Media ◽  
Depth Level ◽  
Seismic Reflection Data ◽  
Reflection Data ◽  
Band Limited ◽  
Internal Multiples

<p>Structural imaging beneath complex overburdens, such as sub-salt or sub-basalt, typically characterized by high-impedance contrasts represents a major challenge for state-of-the-art seismic methods. Reconstructing complex geological structures in the vicinity of and below salt bodies is challenging not only due to uneven, single-sided illumination of the target area but also because of the imperfect removal of surface and internal multiples from the recorded data, as required by traditional migration algorithms. In such tectonic setups, most of the downgoing seismic wavefield is reflected toward the surface when interacting with the overburden's top layer. Similarly, the sub-salt upcoming energy is backscattered at the salt's base. Consequently, the actual energy illuminating the sub-salt reflectors, recorded at the surface, is around the noise level. In diapiric trap systems, conventional seismic extrapolation techniques do not guarantee sufficient quality to reduce exploration and production risks; likewise, seismic-based reservoir characterization and monitoring are also compromised. In this regard, accurate wavefield extrapolation techniques based on the Marchenko method may open up new ways to exploit seismic data.</p><p>The Marchenko redatuming technique retrieves reliable full-wavefield information in the presence of geologic intrusions, which can be subsequently used to produce artefact-free images by naturally including all orders of multiples present in seismic reflection data. To achieve such a goal, the method relies on the estimation of focusing operators allowing the synthesis of virtual surveys at a given depth level. Still, current Marchenko implementations do not fully incorporate available subsurface models with sharp contrasts, due to the requirements regarding the initialization of the focusing functions. Most importantly, in complex media, even a fairly accurate estimation of a direct wave as a proxy for the required initial focusing functions may not be enough to guarantee sufficiently accurate wavefield reconstruction.</p><p>In this talk, we will discuss a scattering-based Marchenko redatuming framework which improves the redatuming of seismic surface data in highly complex media when compared to other Marchenko-based schemes. This extended version is designed to accommodate for band-limited, multi-component, and possibly unevenly sampled seismic data, which contain both free-surface and internal multiples, whilst requiring minimum pre-processing steps. The performance of our scattering Marchenko method will be evaluated using a comprehensive set of numerical tests on a complex 2D subsalt model.</p>

Data-driven multichannel seismic impedance inversion with anisotropic total variation regularization

2018 ◽  
Vol 26 (2) ◽  
pp. 229-241 ◽  
Author(s):  
Dehua Wang ◽  
Jinghuai Gao ◽  
Hongan Zhou
Keyword(s):  
Total Variation ◽  
Seismic Data ◽  
Reservoir Characterization ◽  
Data Driven ◽  
Total Variation Regularization ◽  
Split Bregman ◽  
Seismic Reflection Data ◽  
Reflection Data ◽  
Impedance Inversion ◽  
Anisotropic Total Variation

AbstractAcoustic impedance (AI) inversion is a desirable tool to extract rock-physical properties from recorded seismic data. It plays an important role in seismic interpretation and reservoir characterization. When one of recursive inversion schemes is employed to obtain the AI, the spatial coherency of the estimated reflectivity section may be damaged through the trace-by-trace processing. Meanwhile, the results are sensitive to noise in the data or inaccuracies in the generated reflectivity function. To overcome the above disadvantages, in this paper, we propose a data-driven inversion scheme to directly invert the AI from seismic reflection data. We first explain in principle that the anisotropic total variation (ATV) regularization is more suitable for inverting the impedance with sharp interfaces than the total variation (TV) regularization, and then establish the nonlinear objective function of the AI model by using anisotropic total variation (ATV) regularization. Next, we solve the nonlinear impedance inversion problem via the alternating split Bregman iterative algorithm. Finally, we illustrate the performance of the proposed method and its robustness to noise with synthetic and real seismic data examples by comparing with the conventional methods.

Broadband seismic data — The importance of low frequencies

Geophysics ◽  
2013 ◽  
Vol 78 (2) ◽  
pp. WA3-WA14 ◽  
Author(s):  
Fons ten Kroode ◽  
Steffen Bergler ◽  
Cees Corsten ◽  
Jan Willem de Maag ◽  
Floris Strijbos ◽  
...  
Keyword(s):  
Research And Development ◽  
Experimental Evidence ◽  
Case Studies ◽  
Seismic Data ◽  
Seismic Reflection ◽  
Low Frequencies ◽  
Seismic Reflection Data ◽  
Reflection Data ◽  
Enhanced Resolution ◽  
Impedance Inversion

We considered the importance of low frequencies in seismic reflection data for enhanced resolution, better penetration, and waveform and impedance inversion. We reviewed various theoretical arguments underlining why adding low frequencies may be beneficial and provided experimental evidence for the improvements by several case studies with recently acquired broadband data. We discussed where research and development efforts in the industry with respect to low frequencies should be focusing.

Applications of median filtering to deconvolution, pulse estimation, and statistical editing of seismic data

Geophysics ◽  
1983 ◽  
Vol 48 (12) ◽  
pp. 1598-1610 ◽  
Author(s):  
J. Bee Bednar
Keyword(s):  
Seismic Data ◽  
Empirical Studies ◽  
Synthetic Data ◽  
Real Data ◽  
Weighted Averaging ◽  
Seismic Exploration ◽  
Median Filtering ◽  
Spectral Window ◽  
Reflection Data ◽  
Traditional Processing

Seismic exploration problems frequently require analysis of noisy data. Traditional processing removes or reduces noise effects by linear statistical filtering. This filtering process can be viewed as a weighted averaging with coefficients chosen to enhance the data information content. When the signal and noise components occupy separate spectral windows, or when the statistical properties of the noise are sufficiently understood, linear statistical filtering is an effective tool for data enhancement. When the noise properties are not well understood, or when the noise and signal occupy the same spectral window, linear or weighted averaging performs poorly as a signal enhancement process. One must look for alternative procedures to extract the desired information. As a nonlinear operation which is statistically similar to averaging, median filtering represents one potential alternative. This paper investigates the application of median filtering to several seismic data enhancement problems. A methodology for using median filtering as one step in cepstral deconvolution or seismic signature estimation is presented. The median filtering process is applied to statistical editing of acoustic impedance data and the removal of noise bursts from reflection data. The most surprising conclusion obtained from the empirical studies on synthetic data is that, in high‐noise situations, cepstral‐based median filtering appears to perform exceptionally well as a deconvolver but poorly as a signature estimator. For real data, the process is stable and, to the extent that the data follow the convolutional model, does a reasonable job at both pulse estimation and deconvolution.

Root‐mean‐square velocities and recovery of the acoustic impedance

Geophysics ◽  
1984 ◽  
Vol 49 (10) ◽  
pp. 1653-1663 ◽  
Author(s):  
D. W. Oldenburg ◽  
S. Levy ◽  
K. Stinson
Keyword(s):  
Seismic Data ◽  
Acoustic Impedance ◽  
Velocity Structure ◽  
Low Frequency ◽  
Full Band ◽  
Impedance Profile ◽  
Band Limited ◽  
Point Velocity ◽  
Velocity Constraints ◽  
Additional Point

The loss of low‐frequency information in reflection seismograms causes serious difficulties when attempting to generate a full‐band impedance profile. Information about the low‐frequency velocity structure is available from rms (stacking velocities). We show how rms velocities can be inverted with additional point velocity constraints (if they are available) to construct either smooth or blocky velocity structures. Backus‐Gilbert averages of the constructed velocity are then autoregressive solutions for recovering a full band reflectivity from band‐limited seismograms. Our final result is therefore a full‐band acoustic impedance which is consistent with the seismic data section, stacking velocities, and available point constraints.

scholarly journals Deblending by direct inversion

Geophysics ◽  
2012 ◽  
Vol 77 (3) ◽  
pp. A9-A12 ◽  
Author(s):  
Kees Wapenaar ◽  
Joost van der Neut ◽  
Jan Thorbecke
Keyword(s):  
Inverse Problem ◽  
Seismic Data ◽  
Iterative Procedure ◽  
Inversion Process ◽  
Direct Inversion ◽  
Source Data ◽  
Band Limited ◽  
Blended Data ◽  
Simultaneous Source ◽  
Additional Constraints

Deblending of simultaneous-source data is usually considered to be an underdetermined inverse problem, which can be solved by an iterative procedure, assuming additional constraints like sparsity and coherency. By exploiting the fact that seismic data are spatially band-limited, deblending of densely sampled sources can be carried out as a direct inversion process without imposing these constraints. We applied the method with numerically modeled data and it suppressed the crosstalk well, when the blended data consisted of responses to adjacent, densely sampled sources.

Potentially Large Subsurface Gas Hydrate Bodies in the Mexican Ridges, Southwestern Gulf of Mexico

2021 ◽  
pp. 1-29
Author(s):  
Papia Nandi ◽  
Patrick Fulton ◽  
James Dale
Keyword(s):  
Gulf Of Mexico ◽  
Gas Hydrate ◽  
Seismic Data ◽  
Poor Quality ◽  
Reflection Point ◽  
Seismic Reflection Data ◽  
Reflection Data ◽  
High Impedance ◽  
Acoustic Velocities ◽  
Seismic Images

As rising ocean temperatures can destabilize gas hydrate, identifying and characterizing large shallow hydrate bodies is increasingly important in order to understand their hazard potential. In the southwestern Gulf of Mexico, reanalysis of 3D seismic reflection data reveals evidence for the presence of six potentially large gas hydrate bodies located at shallow depths below the seafloor. We originally interpreted these bodies as salt, as they share common visual characteristics on seismic data with shallow allochthonous salt bodies, including high-impedance boundaries and homogenous interiors with very little acoustic reflectivity. However, when seismic images are constructed using acoustic velocities associated with salt, the resulting images were of poor quality containing excessive moveout in common reflection point (CRP) offset image gathers. Further investigation reveals that using lower-valued acoustic velocities results in higher quality images with little or no moveout. We believe that these lower acoustic values are representative of gas hydrate and not of salt. Directly underneath these bodies lies a zone of poor reflectivity, which is both typical and expected under hydrate. Observations of gas in a nearby well, other indicators of hydrate in the vicinity, and regional geologic context, all support the interpretation that these large bodies are composed of hydrate. The total equivalent volume of gas within these bodies is estimated to potentially be as large as 1.5 gigatons or 10.5 TCF, considering uncertainty for estimates of porosity and saturation, comparable to the entire proven natural gas reserves of Trinidad and Tobago in 2019.

Marchenko multiple elimination and full wavefield migration in a resonant pinch-out model

Geophysics ◽  
2021 ◽  
pp. 1-59
Author(s):  
Evert Slob ◽  
Lele Zhang ◽  
Eric Verschuur
Keyword(s):  
Constant Velocity ◽  
Local Minimum ◽  
Velocity Model ◽  
Dominant Frequency ◽  
Data Sampling ◽  
Multiple Reflections ◽  
Linear Inversion ◽  
Acoustic Reflection ◽  
Reflection Data ◽  
Multiple Elimination

Marchenko multiple elimination schemes are able to attenuate all internal multiple reflections in acoustic reflection data. These can be implemented with and without compensation for two-way transmission effects in the resulting primary reflection dataset. The methods are fully automated and run without human intervention, but require the data to be properly sampled and pre-processed. Even when several primary reflections are invisible in the data because they are masked by overlapping primaries, such as in the resonant wedge model, all missing primary reflections are restored and recovered with the proper amplitudes. Investigating the amplitudes in the primary reflections after multiple elimination with and without compensation for transmission effects shows that transmission effects are properly accounted for in a constant velocity model. When the layer thickness is one quarter of the wavelength at the dominant frequency of the source wavelet, the methods cease to work properly. Full wavefield migration relies on a velocity model and runs a non-linear inversion to obtain a reflectivity model which results in the migration image. The primary reflections that are masked by interference with multiples in the resonant wedge model, are not recovered. In this case, minimizing the data misfit function leads to the incorrect reflector model even though the data fit is optimal. This method has much lower demands on data sampling than the multiple elimination schemes, but is prone to get stuck in a local minimum even when the correct velocity model is available. A hybrid method that exploits the strengths of each of these methods could be worth investigating.

Deepwater reservoir prediction using broadband seismic-driven impedance inversion and seismic sedimentology in the South China Sea

2018 ◽  
Vol 6 (4) ◽  
pp. SO17-SO29 ◽  
Author(s):  
Yaneng Luo ◽  
Handong Huang ◽  
Yadi Yang ◽  
Qixin Li ◽  
Sheng Zhang ◽  
...  
Keyword(s):  
South China Sea ◽  
South China ◽  
Seismic Data ◽  
Seismic Velocity ◽  
The South China Sea ◽  
Hydrocarbon Exploration ◽  
The South ◽  
Low Frequencies ◽  
China Sea ◽  
Impedance Inversion

In recent years, many important discoveries have been made in the marine deepwater hydrocarbon exploration in the South China Sea, which indicates the huge exploration potential of this area. However, the seismic prediction of deepwater reservoirs is very challenging because of the complex sedimentation, the ghost problem, and the low exploration level with sparse wells in deepwater areas. Conventional impedance inversion methods interpolate the low frequencies from well-log data with the constraints of interpreted horizons to fill in the frequency gap between the seismic velocity and seismic data and thereby recover the absolute impedance values that may be inaccurate and cause biased inversion results if wells are sparse and geology is complex. The variable-depth streamer seismic data contain the missing low frequencies and provide a new opportunity to remove the need to estimate the low-frequency components from well-log data. Therefore, we first developed a broadband seismic-driven impedance inversion approach using the seismic velocity as initial low-frequency model based on the Bayesian framework. The synthetic data example demonstrates that our broadband impedance inversion approach is of high resolution and it can automatically balance between the inversion resolution and stability. Then, we perform seismic sedimentology stratal slices on the broadband seismic data to analyze the depositional evolution history of the deepwater reservoirs. Finally, we combine the broadband amplitude stratal slices with the impedance inversion results to comprehensively predict the distribution of deepwater reservoirs. Real data application results in the South China Sea verify the feasibility and effectiveness of our method, which can provide a guidance for the future deepwater hydrocarbon exploration in this area.

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