LEAST‐SQUARES INVERSE FILTERING AND WAVELET DECONVOLUTION

Geophysics ◽  
1977 ◽  
Vol 42 (7) ◽  
pp. 1369-1383 ◽  
Author(s):  
A. J. Berkhout
Keyword(s):  
Seismic Data ◽  
Broad Band ◽  
Detailed Comparison ◽  
Inverse Filtering ◽  
Borehole Data ◽  
Seismic Wavelet ◽  
Phase Property ◽  
Seismic Sections ◽  
Phase Spectra ◽  
Zero Phase

Detailed comparison between borehole data and seismic data has taught that, in general, conventional seismic inverse filtering is not effective enough to produce desirable deconvolution results, i.e., seismic sections with broad‐band zero‐phase wavelets. Application of conventional seismic reverse filters has the advantage that very little information is needed from the user. However, as is shown in this paper, the phase spectra of these filters may be seriously in error, even if the seismic wavelet has the minimum‐phase property. In wavelet deconvolution the phase spectrum of the filter is correct, provided a good estimate of the seismic wavelet is available. In this paper, wavelet deconvolution is compared with Wiener filtering. The main conclusions are illustrated by examples.

Sensitivity of the dispersion correction to Q error

Geophysics ◽  
1997 ◽  
Vol 62 (1) ◽  
pp. 288-290 ◽  
Author(s):  
Richard E. Duren ◽  
E. Clark Trantham
Keyword(s):  
Amplitude Spectrum ◽  
Careful Attention ◽  
Dispersion Correction ◽  
Event Time ◽  
Seismic Wavelet ◽  
Reflection Time ◽  
Seismic Image ◽  
Time Zones ◽  
Seismic Sections ◽  
Zero Phase

A controlled‐phase acquisition and processing methodology for our company has been described by Trantham (1994). He pointed out that it is careful attention to wavelet phase that leads to improved well ties and a more geologically accurate seismic image. In addition, we prefer zero‐phase wavelets on our seismic sections. For a given amplitude spectrum they have the simplest shape and the highest peak; further, the peak occurs at the reflection time of the event. This alignment is important since the seismic wavelet generally broadens with increasing depth with a zero‐phase wavelet remaining symmetrical about the event time. Our experience has been that a true zero‐phase section can be tied over the entire length of a synthetic trace without having to slide the synthetic trace to tie different time zones.

Could the processed seismic wavelet be simpler than we think?

Geophysics ◽  
1991 ◽  
Vol 56 (5) ◽  
pp. 681-690 ◽  
Author(s):  
N. S. Neidell
Keyword(s):  
Unit Circle ◽  
Frequency Distribution ◽  
Amplitude Spectrum ◽  
Root Structure ◽  
Symmetric Form ◽  
Central Frequency ◽  
Seismic Wavelet ◽  
Phase Property ◽  
Short Piece ◽  
Zero Phase

J. P. Lindsey, (1988) in a clearly written short piece, opens an old question which concerns the analytic properties of seismic wavelets. This well conceived study concludes that most of the roots of a seismic wavelet as expressed by its z transform representation lie on or are very near the unit circle. The present discussion does not seek to characterize the form of all seismic wavelets, but only many if not most of those which have been processed with deconvolutions or “inversion” type operators to have reduced length, broadened bandwidth, and some desirable phase property. For such wavelets, despite the diversity by which they are obtained, remarkably simple operations having very few parameters can be extremely effective. As a case in point, constant‐phase rotations appear to carry such wavelets to zero‐phase symmetric form to a very good approximation. I start with empirical attributes which appear to characterize most processed seismic wavelets. Such wavelets tend to be of 40–100 ms duration with a smooth and unimodal amplitude spectrum of “peak” or “central” frequency between 15 and 30 Hz. The amplitude spectrum itself is further largely concentrated at frequencies between 5 and 55 Hz. A z transform root structure having essentially all of its roots only on the unit circle and on the real axis seems able to characterize all of the observed attributes rather well. This structure will be termed the band‐limiting root approximation (BLRA) and describes the attributes I seek to explain which are not as readily understood from alternative descriptions of the wavelets. Since the class of wavelets we address is obtained by a variety of means, and because the differences in character are at best subtle according to interpretive criteria, my justification is heuristic. The BLRA wavelet structure can be represented with remarkably few parameters (typically fewer than five). Of these few parameters, two relate to the frequency distribution. Such a formalism should be exceptionally useful for designing seismic techniques which seek to extract interpretive information based on properties of the wavelet.

Nonstationary phase estimation using regularized local kurtosis maximization

Geophysics ◽  
2009 ◽  
Vol 74 (6) ◽  
pp. A75-A80 ◽  
Author(s):  
Mirko van der Baan ◽  
Sergey Fomel
Keyword(s):  
Statistical Estimation ◽  
Phase Estimation ◽  
Time Varying ◽  
Seismic Wavelet ◽  
Optimization Framework ◽  
Phase Rotation ◽  
Seismic Sections ◽  
The Stability ◽  
Kurtosis Maximization ◽  
Zero Phase

Phase mismatches sometimes occur between final processed seismic sections and zero-phase synthetics based on well logs — despite best efforts for controlled-phase acquisition and processing. Statistical estimation of the phase of a seismic wavelet is feasible using kurtosis maximization by constant-phase rotation, even if the phase is nonstationary. We cast the phase-estimation problem into an optimization framework to improve the stability of an earlier method based on a piecewise-stationarity assumption. After estimation, we achieve space-and-time-varying zero-phasing by phase rotation.

Ghosting and marine signature deconvolution: A prerequisite for detailed seismic interpretation

Geophysics ◽  
1983 ◽  
Vol 48 (11) ◽  
pp. 1468-1485 ◽  
Author(s):  
Dushan B. Jovanovich ◽  
Roger D. Sumner ◽  
Sharon L. Akins‐Easterlin
Keyword(s):  
Gulf Coast ◽  
Seismic Line ◽  
Near Surface ◽  
Seismic Wavelet ◽  
Phase Errors ◽  
Air Gun ◽  
Statistical Hypotheses ◽  
Seismic Sections ◽  
Sonic Logs ◽  
Zero Phase

Detailed lithologic interpretation of seismic sections and/or pseudo‐sonic logs generated from seismic data requires that the seismic trace can be modeled as a reflection series convolved with a zero‐phase broadband wavelet. Ghosting and marine signature deconvolution processing is a prerequisite for assuring that the seismic wavelet on a marine CDP section will be zero phase. A deterministic approach to deconvolution is centered around the concept of abandoning the purely statistical method of wavelet estimation and actually measuring the seismic wavelet. A proper signature recording for marine data is, therefore, a crucial component of deterministic deconvolution. Another important element in the deterministic deconvolution sequence is the application of a deghosting filter to remove near‐surface reflections. Proper application of a deghosting filter significantly improves the correlation between log synthetics and the seismic trace. It has been found that statistical deconvolution schemes, because of the number of statistical hypotheses required to produce a deconvolution filter, produce residual wavelets that are highly variable in character and whose average phases cover the entire phase spectrum, modulo 2π. Examples of a Gulf Coast marine line which was shot with Aquapulse™, air gun, and Maxipulse™ sources by the RV Hollis Hedberg are presented to demonstrate the differences between statistical and deterministic deconvolution processing sequences. It will be shown, using sonic logs from wells adjacent to the seismic line, that the deterministic deconvolution sections for all three sources are close to zero phase while the statistical deconvolution sections have residual average phase errors between 180 and 270 degrees. The deterministic deconvolution sections have a high degree of correlation among themselves and to the wells adjacent to the line, while the statistical deconvolution sections correlate poorly to each other and to the wells. Synthetic seismograms and their impedance logs, and the seismic sections and their corresponding pseudo‐sonic logs, are used to demonstrate how deconvolution influences lithologic interpretation. ™Western Geophysics Co.

scholarly journals Pitfalls and limitations in seismic attribute interpretation of tectonic features

2015 ◽  
Vol 3 (1) ◽  
pp. SB5-SB15 ◽  
Author(s):  
Kurt J. Marfurt ◽  
Tiago M. Alves
Keyword(s):  
Seismic Data ◽  
Seismic Attributes ◽  
Seismic Attribute ◽  
3D Data ◽  
Amplitude Data ◽  
Seismic Sections ◽  
Push Down ◽  
Data Coherence ◽  
Level Of Experience ◽  
Tectonic Features

Seismic attributes are routinely used to accelerate and quantify the interpretation of tectonic features in 3D seismic data. Coherence (or variance) cubes delineate the edges of megablocks and faulted strata, curvature delineates folds and flexures, while spectral components delineate lateral changes in thickness and lithology. Seismic attributes are at their best in extracting subtle and easy to overlook features on high-quality seismic data. However, seismic attributes can also exacerbate otherwise subtle effects such as acquisition footprint and velocity pull-up/push-down, as well as small processing and velocity errors in seismic imaging. As a result, the chance that an interpreter will suffer a pitfall is inversely proportional to his or her experience. Interpreters with a history of making conventional maps from vertical seismic sections will have previously encountered problems associated with acquisition, processing, and imaging. Because they know that attributes are a direct measure of the seismic amplitude data, they are not surprised that such attributes “accurately” represent these familiar errors. Less experienced interpreters may encounter these errors for the first time. Regardless of their level of experience, all interpreters are faced with increasingly larger seismic data volumes in which seismic attributes become valuable tools that aid in mapping and communicating geologic features of interest to their colleagues. In terms of attributes, structural pitfalls fall into two general categories: false structures due to seismic noise and processing errors including velocity pull-up/push-down due to lateral variations in the overburden and errors made in attribute computation by not accounting for structural dip. We evaluate these errors using 3D data volumes and find areas where present-day attributes do not provide the images we want.

On the Processing of Non-Rectangularly Sampled Multi-Dimensional Geophysical Data

1991 ◽  
Vol 02 (01) ◽  
pp. 223-226
Author(s):  
VIRGIL BARDAN
Keyword(s):  
Seismic Data ◽  
Geophysical Data ◽  
Seismic Sections

In this paper the processing of triangularly sampled 2-D seismic data is illustrated by examples of synthetic and field seismic sections.

Using Logging and Seismic Data to Identify Boundaries Between Different OWC Units in a Deepwater Carbonate Reservoirs

2021 ◽  
Author(s):  
Kangxu Ren ◽  
Junfeng Zhao ◽  
Jian Zhao ◽  
Xilong Sun
Keyword(s):  
Seismic Data ◽  
Carbonate Rocks ◽  
Carbonate Reservoir ◽  
Carbonate Reservoirs ◽  
Sedimentary Process ◽  
Core Samples ◽  
Tight Carbonate ◽  
Porosity And Permeability ◽  
Seismic Sections ◽  
Parameters Inversion

Abstract At least three very different oil-water contacts (OWC) encountered in the deepwater, huge anticline, pre-salt carbonate reservoirs of X oilfield, Santos Basin, Brazil. The boundaries identification between different OWC units was very important to help calculating the reserves in place, which was the core factor for the development campaign. Based on analysis of wells pressure interference testing data, and interpretation of tight intervals in boreholes, predicating the pre-salt distribution of igneous rocks, intrusion baked aureoles, the silicification and the high GR carbonate rocks, the viewpoint of boundaries developed between different OWC sub-units in the lower parts of this complex carbonate reservoirs had been better understood. Core samples, logging curves, including conventional logging and other special types such as NMR, UBI and ECS, as well as the multi-parameters inversion seismic data, were adopted to confirm the tight intervals in boreholes and to predicate the possible divided boundaries between wells. In the X oilfield, hundreds of meters pre-salt carbonate reservoir had been confirmed to be laterally connected, i.e., the connected intervals including almost the whole Barra Velha Formation and/or the main parts of the Itapema Formation. However, in the middle and/or the lower sections of pre-salt target layers, the situation changed because there developed many complicated tight bodies, which were formed by intrusive diabase dykes and/or sills and the tight carbonate rocks. Many pre-salt inner-layers diabases in X oilfield had very low porosity and permeability. The tight carbonate rocks mostly developed either during early sedimentary process or by latter intrusion metamorphism and/or silicification. Tight bodies were firstly identified in drilled wells with the help of core samples and logging curves. Then, the continuous boundary were discerned on inversion seismic sections marked by wells. This paper showed the idea of coupling the different OWC units in a deepwater pre-salt carbonate play with complicated tight bodies. With the marking of wells, spatial distributions of tight layers were successfully discerned and predicated on inversion seismic sections.

A reality check on full-wave inversion applied to land seismic data for near-surface modeling

2022 ◽  
Vol 41 (1) ◽  
pp. 40-46
Author(s):  
Öz Yilmaz ◽  
Kai Gao ◽  
Milos Delic ◽  
Jianghai Xia ◽  
Lianjie Huang ◽  
...  
Keyword(s):  
Wave Velocity ◽  
Seismic Data ◽  
Surface Modeling ◽  
P Wave ◽  
Borehole Data ◽  
Near Surface ◽  
Traveltime Tomography ◽  
Wave Inversion ◽  
Full Wave ◽  
Elastic Inversion

We evaluate the performance of traveltime tomography and full-wave inversion (FWI) for near-surface modeling using the data from a shallow seismic field experiment. Eight boreholes up to 20-m depth have been drilled along the seismic line traverse to verify the accuracy of the P-wave velocity-depth model estimated by seismic inversion. The velocity-depth model of the soil column estimated by traveltime tomography is in good agreement with the borehole data. We used the traveltime tomography model as an initial model and performed FWI. Full-wave acoustic and elastic inversions, however, have failed to converge to a velocity-depth model that desirably should be a high-resolution version of the model estimated by traveltime tomography. Moreover, there are significant discrepancies between the estimated models and the borehole data. It is understandable why full-wave acoustic inversion would fail — land seismic data inherently are elastic wavefields. The question is: Why does full-wave elastic inversion also fail? The strategy to prevent full-wave elastic inversion of vertical-component geophone data trapped in a local minimum that results in a physically implausible near-surface model may be cascaded inversion. Specifically, we perform traveltime tomography to estimate a P-wave velocity-depth model for the near-surface and Rayleigh-wave inversion to estimate an S-wave velocity-depth model for the near-surface, then use the resulting pairs of models as the initial models for the subsequent full-wave elastic inversion. Nonetheless, as demonstrated by the field data example here, the elastic-wave inversion yields a near-surface solution that still is not in agreement with the borehole data. Here, we investigate the limitations of FWI applied to land seismic data for near-surface modeling.

Seismic solutions utilizing existing in-mine infrastructure for mineral exploration: A case study from Maseve platinum mine, South Africa

2022 ◽  
Vol 41 (1) ◽  
pp. 54-61
Author(s):  
Moyagabo K. Rapetsoa ◽  
Musa S. D. Manzi ◽  
Mpofana Sihoyiya ◽  
Michael Westgate ◽  
Phumlani Kubeka ◽  
...  
Keyword(s):  
South Africa ◽  
Seismic Data ◽  
Mineral Exploration ◽  
Ground Surface ◽  
Seismic Survey ◽  
Noisy Environment ◽  
Borehole Data ◽  
Passive Seismic ◽  
Below Ground

We demonstrate the application of seismic methods using in-mine infrastructure such as exploration tunnels to image platinum deposits and geologic structures using different acquisition configurations. In 2020, seismic experiments were conducted underground at the Maseve platinum mine in the Bushveld Complex of South Africa. These seismic experiments were part of the Advanced Orebody Knowledge project titled “Developing technologies that will be used to obtain information ahead of the mine face.” In these experiments, we recorded active and passive seismic data using surface nodal arrays and an in-mine seismic land streamer. We focus on analyzing only the in-mine active seismic portion of the survey. The tunnel seismic survey consisted of seven 2D profiles in exploration tunnels, located approximately 550 m below ground surface and a few meters above known platinum deposits. A careful data-processing approach was adopted to enhance high-quality reflections and suppress infrastructure-generated noise. Despite challenges presented by the in-mine noisy environment, we successfully imaged the platinum deposits with the aid of borehole data and geologic models. The results open opportunities to adapt surface-based geophysical instruments to address challenging in-mine environments for mineral exploration.

Determination of crustal thickness from spectral behavior of SH waves

1969 ◽  
Vol 59 (3) ◽  
pp. 1247-1258
Author(s):  
Abou-Bakr K. Ibrahim
Keyword(s):  
Amplitude Spectrum ◽  
Body Waves ◽  
Multiple Reflections ◽  
Matrix Formulation ◽  
Sh Waves ◽  
Crustal Model ◽  
Amplitude Spectra ◽  
Phase Spectra ◽  
Zero Phase

abstract The amplitude spectrum obtained from Haskell's matrix formulation for body waves travelling through a horizontally layered crustal model shows a sequence of minima and maxima. It is known that multiple reflections within the crustal layers produce constructive and destructive interferences, which are shown as maxima and minima in the amplitude spectrum. Analysis of the minima in the amplitude spectra, which correspond to zero phase in the phase spectra, enables us to determine the thickness of the crust, provided the ratio of wave velocity in the crust to velocity under the Moho is known.

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