A depth variant seismic wavelet extraction method for inversion of poststack depth-domain seismic data

Geophysics ◽  
2018 ◽  
Vol 83 (6) ◽  
pp. R569-R579 ◽  
Author(s):  
Rui Zhang ◽  
Zhiwen Deng
Keyword(s):  
Seismic Data ◽  
Extraction Method ◽  
Reservoir Characterization ◽  
Real Data ◽  
Velocity Model ◽  
Seismic Inversion ◽  
Data Depth ◽  
Spectral Variation ◽  
Seismic Wavelet ◽  
The Time Domain

Prestack depth seismic imaging is increasingly being used in industry, which has also led to an increasing need for its inversion results, such as acoustic impedance (AI), for reservoir characterization. Conventional seismic inversion methods for reservoir characterization are usually implemented in the time domain. A depth-time conversion would be required before inversion of depth-domain seismic data, which would depend on an accurate velocity model and a fine time-depth conversion algorithm. Thus, it could be beneficial that we can directly invert the depth migrated seismic data. Depth-domain seismic data could indicate a strong nonstationarity, such as spectral variation, which makes it difficult to use a constant wavelet for direct inversion in depth. To address this issue, we have developed a new wavelet extraction method by using a depth-wavenumber decomposition technique, which can generate depth variant wavelets to accommodate the nonstationarity of the depth-domain seismic data. The synthetic and real data applications have been used to test the effectiveness of our method. The directly inverted depth-domain AI indicates a good correlation with well-log data and a strong potential for reservoir characterization.

Relative acoustic impedance from wavelet transform

2014 ◽  
Vol 2 (1) ◽  
pp. SA107-SA118 ◽  
Author(s):  
Marcílio Castro de Matos ◽  
Rodrigo Penna ◽  
Paulo Johann ◽  
Kurt Marfurt
Keyword(s):  
Wavelet Transform ◽  
Continuous Wavelet Transform ◽  
Seismic Data ◽  
Acoustic Impedance ◽  
Real Data ◽  
Velocity Model ◽  
Continuous Wavelet ◽  
Reconstruction Process ◽  
Seismic Wavelet ◽  
Morlet Continuous Wavelet Transform

Most deconvolution algorithms try to transform the seismic wavelet into spikes by designing inverse filters that remove an estimated seismic wavelet from seismic data. We assume that seismic trace subtle discontinuities are associated with acoustic impedance contrasts and can be characterized by wavelet transform spectral ridges, also called modulus maxima lines (WTMML), allowing us to improve seismic resolution by using the wavelet transform. Specifically, we apply the complex Morlet continuous wavelet transform (CWT) to each seismic trace and compute the WTMMLs. Then, we reconstruct the seismic trace with the inverse continuous wavelet transform from the computed WTMMLs with a broader band complex Morlet wavelet than that used in the forward CWT. Because the reconstruction process preserves amplitude and phase along different scales, or frequencies, the result looks like a deconvolution method. Considering this high-resolution seismic representation as a reflectivity approximation, we estimate the relative acoustic impedance (RAI) by filtering and trace integrating it. Conventional deconvolution algorithms assume the seismic wavelet to be stochastic, while the CWT is implicitly time varying such that it can be applied to both depth and time-domain data. Using synthetic and real seismic data, we evaluated the effectiveness of the methodology on detecting seismic events associated with acoustic impedance changes. In the real data examples, time and in-depth RAI results, show good correlation with real P-impedance band-pass data computed using more rigorous commercial inversion software packages that require well logs and low-frequency velocity model information.

Depth-domain seismic reflectivity inversion with compressed sensing technique

2017 ◽  
Vol 5 (1) ◽  
pp. T1-T9 ◽  
Author(s):  
Rui Zhang ◽  
Kui Zhang ◽  
Jude E. Alekhue
Keyword(s):  
Compressed Sensing ◽  
Time Domain ◽  
Seismic Data ◽  
Reservoir Characterization ◽  
Synthetic Data ◽  
Seismic Inversion ◽  
Inversion Method ◽  
Depth Migration ◽  
Band Limited ◽  
The Time Domain

More and more seismic surveys produce 3D seismic images in the depth domain by using prestack depth migration methods, which can present a direct subsurface structure in the depth domain rather than in the time domain. This leads to the increasing need for applications of seismic inversion on the depth-imaged seismic data for reservoir characterization. To address this issue, we have developed a depth-domain seismic inversion method by using the compressed sensing technique with output of reflectivity and band-limited impedance without conversion to the time domain. The formulations of the seismic inversion in the depth domain are similar to time-domain methods, but they implement all the elements in depth domain, for example, a depth-domain seismic well tie. The developed method was first tested on synthetic data, showing great improvement of the resolution on inverted reflectivity. We later applied the method on a depth-migrated field data with well-log data validated, showing a great fit between them and also improved resolution on the inversion results, which demonstrates the feasibility and reliability of the proposed method on depth-domain seismic data.

Seismic well tie by aligning impedance log with inverted impedance from seismic data

2020 ◽  
Vol 8 (4) ◽  
pp. T917-T925
Author(s):  
Bo Zhang ◽  
Yahua Yang ◽  
Yong Pan ◽  
Hao Wu ◽  
Danping Cao
Keyword(s):  
Seismic Data ◽  
Dynamic Time Warping ◽  
Real Data ◽  
Seismic Inversion ◽  
Synthetic Seismogram ◽  
Well Logs ◽  
Time Warping ◽  
Seismic Wavelet ◽  
Dynamic Time ◽  
Depth Relationship

The accuracy of seismic inversion is affected by the seismic wavelet and time-depth relationship generated by the process of the seismic well tie. The seismic well tie is implemented by comparing the synthetic seismogram computed from well logs and the poststack seismogram at or nearby the borehole location. However, precise waveform matching between the synthetic seismogram and the seismic trace does not guarantee an accurate tie between the elastic properties contained represented by the seismic data and well logs. We have performed the seismic well tie using the impedance log and the impedance inverted from poststack seismic data. We use an improved dynamic time warping to align the impedance log and impedance inverted from seismic data. Our workflow is similar to the current procedure of the seismic well tie except that the matching is implemented between the impedance log and the inverted impedance. The current seismic well-tie converges if there is no visible changes for the wavelets and time-depth relationship in the previous and current tying loops. Similarly, our seismic well tie converges if there are no visible changes for the wavelets, inverted impedance, and time-depth relationship in the previous and current tying loops. The real data example illustrates that more accurate inverted impedance is obtained by using the new wavelet and time-depth relationship.

Migration velocity analysis based on focusing diffractions generated using the CRS wavefront attributes: Application to real land data

Geophysics ◽  
2021 ◽  
pp. 1-50
Author(s):  
German Garabito ◽  
José Silas dos Santos Silva ◽  
Williams Lima
Keyword(s):  
Time Domain ◽  
Real Data ◽  
Normal Incidence ◽  
Velocity Model ◽  
Migration Velocity ◽  
Velocity Analysis ◽  
Velocity Models ◽  
Time Migration ◽  
Migration Velocity Analysis ◽  
The Time Domain

In land seismic data processing, the prestack time migration (PSTM) image remains the standard imaging output, but a reliable migrated image of the subsurface depends on the accuracy of the migration velocity model. We have adopted two new algorithms for time-domain migration velocity analysis based on wavefield attributes of the common-reflection-surface (CRS) stack method. These attributes, extracted from multicoverage data, were successfully applied to build the velocity model in the depth domain through tomographic inversion of the normal-incidence-point (NIP) wave. However, there is no practical and reliable method for determining an accurate and geologically consistent time-migration velocity model from these CRS attributes. We introduce an interactive method to determine the migration velocity model in the time domain based on the application of NIP wave attributes and the CRS stacking operator for diffractions, to generate synthetic diffractions on the reflection events of the zero-offset (ZO) CRS stacked section. In the ZO data with diffractions, the poststack time migration (post-STM) is applied with a set of constant velocities, and the migration velocities are then selected through a focusing analysis of the simulated diffractions. We also introduce an algorithm to automatically calculate the migration velocity model from the CRS attributes picked for the main reflection events in the ZO data. We determine the precision of our diffraction focusing velocity analysis and the automatic velocity calculation algorithms using two synthetic models. We also applied them to real 2D land data with low quality and low fold to estimate the time-domain migration velocity model. The velocity models obtained through our methods were validated by applying them in the Kirchhoff PSTM of real data, in which the velocity model from the diffraction focusing analysis provided significant improvements in the quality of the migrated image compared to the legacy image and to the migrated image obtained using the automatically calculated velocity model.

Seismic-to-well tie of a field of the Nigerian Delta

2021 ◽  
Vol 19 (3) ◽  
pp. 125-138
Author(s):  
S. Inichinbia ◽  
A.L. Ahmed
Keyword(s):  
Seismic Data ◽  
Processing Parameters ◽  
Seismic Inversion ◽  
Seismic Wavelet ◽  
Statistical Measures ◽  
Convolution Model ◽  
Data Driven Approach ◽  
Well Data ◽  
Seismic Reflectors ◽  
Matching Techniques

This paper presents a rigorous but pragmatic and data driven approach to the science of making seismic-to-well ties. This pragmatic  approach is consistent with the interpreter’s desire to correlate geology to seismic information by the use of the convolution model,  together with least squares matching techniques and statistical measures of fit and accuracy to match the seismic data to the well data. Three wells available on the field provided a chance to estimate the wavelet (both in terms of shape and timing) directly from the seismic and also to ascertain the level of confidence that should be placed in the wavelet. The reflections were interpreted clearly as hard sand at H1000 and soft sand at H4000. A synthetic seismogram was constructed and matched to a real seismic trace and features from the well are correlated to the seismic data. The prime concept in constructing the synthetic is the convolution model, which represents a seismic reflection signal as a sequence of interfering reflection pulses of different amplitudes and polarity but all of the same shape. This pulse shape is the seismic wavelet which is formally, the reflection waveform returned by an isolated reflector of unit strength at the target  depth. The wavelets are near zero phase. The goal and the idea behind these seismic-to-well ties was to obtain information on the sediments, calibration of seismic processing parameters, correlation of formation tops and seismic reflectors, and the derivation of a  wavelet for seismic inversion among others. Three seismic-to-well ties were done using three partial angle stacks and basically two formation tops were correlated. Keywords: seismic, well logs, tie, synthetics, angle stacks, correlation,

Applications of quantitative prestack seismic analysis to unconventional resource play characterization in the Permian/Delaware Basin

2019 ◽  
Vol 38 (2) ◽  
pp. 106-115 ◽  
Author(s):  
Phuong Hoang ◽  
Arcangelo Sena ◽  
Benjamin Lascaud
Keyword(s):  
Hydraulic Fracturing ◽  
Seismic Data ◽  
Reservoir Characterization ◽  
Seismic Analysis ◽  
Seismic Inversion ◽  
Reservoir Properties ◽  
Yield Attributes ◽  
Horizontal Drilling ◽  
Delaware Basin ◽  
Unconventional Resource

The characterization of shale plays involves an understanding of tectonic history, geologic settings, reservoir properties, and the in-situ stresses of the potential producing zones in the subsurface. The associated hydrocarbons are generally recovered by horizontal drilling and hydraulic fracturing. Historically, seismic data have been used mainly for structural interpretation of the shale reservoirs. A primary benefit of surface seismic has been the ability to locate and avoid drilling into shallow carbonate karsting zones, salt structures, and basement-related major faults which adversely affect the ability to drill and complete the well effectively. More recent advances in prestack seismic data analysis yield attributes that appear to be correlated to formation lithology, rock strength, and stress fields. From these, we may infer preferential drilling locations or sweet spots. Knowledge and proper utilization of these attributes may prove valuable in the optimization of drilling and completion activities. In recent years, geophysical data have played an increasing role in supporting well planning, hydraulic fracturing, well stacking, and spacing. We have implemented an integrated workflow combining prestack seismic inversion and multiattribute analysis, microseismic data, well-log data, and geologic modeling to demonstrate key applications of quantitative seismic analysis utilized in developing ConocoPhillips' acreage in the Delaware Basin located in Texas. These applications range from reservoir characterization to well planning/execution, stacking/spacing optimization, and saltwater disposal. We show that multidisciplinary technology integration is the key for success in unconventional play exploration and development.

2-D continuation operators and their applications

Geophysics ◽  
1996 ◽  
Vol 61 (6) ◽  
pp. 1846-1858 ◽  
Author(s):  
Claudio Bagaini ◽  
Umberto Spagnolini
Keyword(s):  
Seismic Data ◽  
Real Data ◽  
Integral Form ◽  
Amplitude Distribution ◽  
Velocity Model ◽  
Velocity Analysis ◽  
Seismic Data Processing ◽  
Analysis Method ◽  
Standard Tool ◽  
Zero Offset

Continuation to zero offset [better known as dip moveout (DMO)] is a standard tool for seismic data processing. In this paper, the concept of DMO is extended by introducing a set of operators: the continuation operators. These operators, which are implemented in integral form with a defined amplitude distribution, perform the mapping between common shot or common offset gathers for a given velocity model. The application of the shot continuation operator for dip‐independent velocity analysis allows a direct implementation in the acquisition domain by exploiting the comparison between real data and data continued in the shot domain. Shot and offset continuation allow the restoration of missing shot or missing offset by using a velocity model provided by common shot velocity analysis or another dip‐independent velocity analysis method.

Reservoir Prediction Under Control of Sedimentary Facies

2017 ◽  
Vol 25 (03) ◽  
pp. 1750022
Author(s):  
Xiuwei Yang ◽  
Peimin Zhu
Keyword(s):  
Seismic Data ◽  
Low Frequency ◽  
Prediction Method ◽  
Rock Physics ◽  
Real Data ◽  
Sedimentary Facies ◽  
Seismic Inversion ◽  
Rock Properties ◽  
Reservoir Prediction ◽  
Frequency Model

Acoustic impedance (AI) from seismic inversion can indicate rock properties and can be used, when combined with rock physics, to predict reservoir parameters, such as porosity. Solutions to seismic inversion problem are almost nonunique due to the limited bandwidth of seismic data. Additional constraints from well log data and geology are needed to arrive at a reasonable solution. In this paper, sedimentary facies is used to reduce the uncertainty in inversion and rock physics modeling; the results not only agree with seismic data, but also conform to geology. A reservoir prediction method, which incorporates seismic data, well logs, rock physics and sedimentary facies, is proposed. AI was first derived by constrained sparse spike inversion (CSSI) using a sedimentary facies dependent low-frequency model, and then was transformed to reservoir parameters by sequential simulation, statistical rock physics and [Formula: see text]-model. Two numerical experiments using synthetic model and real data indicated that the sedimentary facies information may help to obtain a more reasonable prediction.

High-resolution reservoir characterization by an acoustic impedance inversion of a Tertiary deltaic clinoform system in the North Sea

Geophysics ◽  
2010 ◽  
Vol 75 (6) ◽  
pp. O57-O67 ◽  
Author(s):  
Daria Tetyukhina ◽  
Lucas J. van Vliet ◽  
Stefan M. Luthi ◽  
Kees Wapenaar
Keyword(s):  
North Sea ◽  
Seismic Data ◽  
Reservoir Characterization ◽  
Structural Information ◽  
Sampling Rate ◽  
Seismic Inversion ◽  
Acoustic Properties ◽  
The North ◽  
The North Sea ◽  
Well Data

Fluvio-deltaic sedimentary systems are of great interest for explorationists because they can form prolific hydrocarbon plays. However, they are also among the most complex and heterogeneous ones encountered in the subsurface, and potential reservoir units are often close to or below seismic resolution. For seismic inversion, it is therefore important to integrate the seismic data with higher resolution constraints obtained from well logs, whereby not only the acoustic properties are used but also the detailed layering characteristics. We have applied two inversion approaches for poststack, time-migrated seismic data to a clinoform sequence in the North Sea. Both methods are recursive trace-based techniques that use well data as a priori constraints but differ in the way they incorporate structural information. One method uses a discrete layer model from the well that is propagated laterally along the clinoform layers, which are modeled as sigmoids. The second method uses a constant sampling rate from the well data and uses horizontal and vertical regularization parameters for lateral propagation. The first method has a low level of parameterization embedded in a geologic framework and is computationally fast. The second method has a much higher degree of parameterization but is flexible enough to detect deviations in the geologic settings of the reservoir; however, there is no explicit geologic significance and the method is computationally much less efficient. Forward seismic modeling of the two inversion results indicates a good match of both methods with the actual seismic data.

Accuracy of wavelets, seismic inversion, and thin-bed resolution

2017 ◽  
Vol 5 (4) ◽  
pp. T523-T530
Author(s):  
Ehsan Zabihi Naeini ◽  
Mark Sams
Keyword(s):  
Seismic Data ◽  
Reservoir Characterization ◽  
Low Frequency ◽  
Seismic Inversion ◽  
Inversion Method ◽  
Frequency Content ◽  
Frequency Model ◽  
North West ◽  
The North ◽  
Well Data

Broadband reprocessed seismic data from the North West Shelf of Australia were inverted using wavelets estimated with a conventional approach. The inversion method applied was a facies-based inversion, in which the low-frequency model is a product of the inversion process itself, constrained by facies-dependent input trends, the resultant facies distribution, and the match to the seismic. The results identified the presence of a gas reservoir that had recently been confirmed through drilling. The reservoir is thin, with up to 15 ms of maximum thickness. The bandwidth of the seismic data is approximately 5–70 Hz, and the well data used to extract the wavelet used in the inversion are only 400 ms long. As such, there was little control on the lowest frequencies of the wavelet. Different wavelets were subsequently estimated using a variety of new techniques that attempt to address the limitations of short well-log segments and low-frequency seismic. The revised inversion showed greater gas-sand continuity and an extension of the reservoir at one flank. Noise-free synthetic examples indicate that thin-bed delineation can depend on the accuracy of the low-frequency content of the wavelets used for inversion. Underestimation of the low-frequency contents can result in missing thin beds, whereas underestimation of high frequencies can introduce false thin beds. Therefore, it is very important to correctly capture the full frequency content of the seismic data in terms of the amplitude and phase spectra of the estimated wavelets, which subsequently leads to a more accurate thin-bed reservoir characterization through inversion.

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