The impact of reservoir scale on amplitude variation with offset

2016 ◽  
Vol 65 (3) ◽  
pp. 736-746 ◽  
Author(s):  
Chao Xu ◽  
Jianxin Wei ◽  
Bangrang Di
2021 ◽  
pp. 1-55
Author(s):  
Arash JafarGandomi

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.


2019 ◽  
Vol 7 (3) ◽  
pp. T581-T593 ◽  
Author(s):  
Mark Sams ◽  
Annushia Annamalai ◽  
Jeremy Gallop

Vertical transverse isotropy (VTI) will affect seismic inversion, but it is not possible to solve for the full set of anisotropic elastic parameters from amplitude variation with offset inversion because there exists an isotropic solution to every VTI problem. We can easily approximate the pseudoisotropic properties that result from the isotropic solution to the anisotropic problem for well-log data. We can then use these well-log properties to provide a low-frequency model for inversion and/or a framework for interpreting either absolute or relative inversion results. This, however, requires prior knowledge of the anisotropic properties, which are often unavailable or poorly constrained. If we ignore anisotropy and assume that the amplitude variations caused by VTI are going to be accounted for by effective wavelets, the inversion results would be in error: The impact of anisotropy is not merely a case of linear scaling of seismic amplitudes for any particular angle range. Ignoring VTI does not affect the prediction of acoustic impedance, but it does affect predictions of [Formula: see text] and density. For realistic values of anisotropy, these errors can be significant, such as predicting oil instead of brine. If the anisotropy of the rocks is known, then we can invert for the true vertical elastic properties using the known anisotropy coefficients through a facies-based inversion. This can produce a more accurate result than solving for pseudoelastic properties, and it can take advantage of the sometimes increased separation of isotropic and anisotropic rocks in the pseudoisotropic elastic domain. Because the effect of anisotropy will vary depending on the strength of the anisotropy and the distribution of the rocks, we strongly recommend forward modeling for each case prior to inversion to understand the potential impact on the study objectives.


Geophysics ◽  
2012 ◽  
Vol 77 (6) ◽  
pp. B295-B306 ◽  
Author(s):  
Alexander Duxbury ◽  
Don White ◽  
Claire Samson ◽  
Stephen A. Hall ◽  
James Wookey ◽  
...  

Cap rock integrity is an essential characteristic of any reservoir to be used for long-term [Formula: see text] storage. Seismic AVOA (amplitude variation with offset and azimuth) techniques have been applied to map HTI anisotropy near the cap rock of the Weyburn field in southeast Saskatchewan, Canada, with the purpose of identifying potential fracture zones that may compromise seal integrity. This analysis, supported by modeling, observes the top of the regional seal (Watrous Formation) to have low levels of HTI anisotropy, whereas the reservoir cap rock (composite Midale Evaporite and Ratcliffe Beds) contains isolated areas of high intensity anisotropy, which may be fracture-related. Properties of the fracture fill and hydraulic conductivity within the inferred fracture zones are not constrained using this technique. The predominant orientations of the observed anisotropy are parallel and normal to the direction of maximum horizontal stress (northeast–southwest) and agree closely with previous fracture studies on core samples from the reservoir. Anisotropy anomalies are observed to correlate spatially with salt dissolution structures in the cap rock and overlying horizons as interpreted from 3D seismic cross sections.


Geophysics ◽  
1995 ◽  
Vol 60 (5) ◽  
pp. 1426-1436 ◽  
Author(s):  
Wojciech Dȩbski ◽  
Albert Tarantola

Seismic amplitude variation with offset data contain information on the elastic parameters of geological layers. As the general solution of the inverse problem consists of a probability over the space of all possible earth models, we look at the probabilities obtained using amplitude variation with offset (AVO) data for different choices of elastic parameters. A proper analysis of the information in the data requires a nontrivial definition of the probability defining the state of total ignorance on different elastic parameters (seismic velocities, Lamé’s parameters, etc.). We conclude that mass density, seismic impedance, and Poisson’s ratio constitute the best resolved parameter set when inverting seismic amplitude variation with offset data.


2021 ◽  
Vol 40 (9) ◽  
pp. 646-654
Author(s):  
Henning Hoeber

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.


2021 ◽  
Vol 40 (10) ◽  
pp. 716-722
Author(s):  
Yangjun (Kevin) Liu ◽  
Michelle Ellis ◽  
Mohamed El-Toukhy ◽  
Jonathan Hernandez

We present a basin-wide rock-physics analysis of reservoir rocks and fluid properties in Campeche Basin. Reservoir data from discovery wells are analyzed in terms of their relationship between P-wave velocity, density, porosity, clay content, Poisson's ratio (PR), and P-impedance (IP). The fluid properties are computed by using in-situ pressure, temperature, American Petroleum Institute gravity, gas-oil ratio, and volume of gas, oil, and water. Oil- and gas-saturated reservoir sands show strong PR anomalies compared to modeled water sand at equivalent depth. This suggests that PR anomalies can be used as a direct hydrocarbon indicator in the Tertiary sands in Campeche Basin. However, false PR anomalies due to residual gas or oil exist and compose about 30% of the total anomalies. The impact of fluid properties on IP and PR is calibrated using more than 30 discovery wells. These calibrated relationships between fluid properties and PR can be used to guide or constrain amplitude variation with offset inversion for better pore fluid discrimination.


Geophysics ◽  
2020 ◽  
Vol 85 (2) ◽  
pp. V201-V221 ◽  
Author(s):  
Mehdi Aharchaou ◽  
Erik Neumann

Broadband preprocessing has become widely used for marine towed-streamer seismic data. In the standard workflow, far-field source designature, receiver and source-side deghosting, and redatuming to mean sea level are applied in sequence, with amplitude compensation for background [Formula: see text] delayed until the imaging or postmigration stages. Thus, each step is likely to generate its own artifacts, quality checking can be time-consuming, and broadband data are only obtained late in this chained workflow. We have developed a unified method for broadband preprocessing — called integrated broadband preprocessing (IBP) — which enables the joint application of all the above listed steps early in the processing sequence. The amplitude, phase, and amplitude-variation-with-offset fidelity of IBP are demonstrated on pressure data from the shallow, deep, and slanted streamers. The integration allows greater sparsity to emerge in the representation of seismic data, conferring clear benefits over the sequential application. Moreover, time sparsity, full dimensionality, and early amplitude [Formula: see text] compensation all have an impact on broadband data quality, in terms of reduced ringing artifacts, improved wavelet integrity at large crossline angles, and fewer residual high-frequency multiples.


2020 ◽  
Vol 8 (1) ◽  
pp. SA25-SA33
Author(s):  
Ellen Xiaoxia Xu ◽  
Yu Jin ◽  
Sarah Coyle ◽  
Dileep Tiwary ◽  
Henry Posamentier ◽  
...  

Seismic amplitude has played a critical role in the exploration and exploitation of hydrocarbon in West Africa. Class 3 and 2 amplitude variation with offset (AVO) was extensively used as a direct hydrocarbon indicator and reservoir prediction tool in Neogene assets. As exploration advanced to deeper targets with class 1 AVO seismic character, the usage of seismic amplitude for reservoir presence and quality prediction became challenged. To overcome this obstacle, (1) we used seismic geomorphology to infer reservoir presence and precisely target geophysical analysis on reservoir prone intervals, (2) we applied rigorous prestack data preparation to ensure the accuracy and precision of AVO simultaneous inversion for reservoir quality prediction, and (3) we used lateral statistic method to sum up AVO behavior in regions of contrasts to infer reservoir quality changes. We have evaluated a case study in which the use of the above three techniques resulted in confident prediction of reservoir presence and quality. Our results reduced the uncertainty around the biggest risk element in reservoir among the source, charge, and trap mechanism in the prospecting area. This work ultimately made a significant contribution toward a confident resource booking.


Geophysics ◽  
2017 ◽  
Vol 82 (5) ◽  
pp. W31-W45 ◽  
Author(s):  
Necati Gülünay

The old technology [Formula: see text]-[Formula: see text] deconvolution stands for [Formula: see text]-[Formula: see text] domain prediction filtering. Early versions of it are known to create signal leakage during their application. There have been recent papers in geophysical publications comparing [Formula: see text]-[Formula: see text] deconvolution results with the new technologies being proposed. These comparisons will be most effective if the best existing [Formula: see text]-[Formula: see text] deconvolution algorithms are used. This paper describes common [Formula: see text]-[Formula: see text] deconvolution algorithms and studies signal leakage occurring during their application on simple models, which will hopefully provide a benchmark for the readers in choosing [Formula: see text]-[Formula: see text] algorithms for comparison. The [Formula: see text]-[Formula: see text] deconvolution algorithms can be classified by their use of data which lead to transient or transient-free matrices and hence windowed or nonwindowed autocorrelations, respectively. They can also be classified by the direction they are predicting: forward design and apply; forward design and apply followed by backward design and apply; forward design and apply followed by application of a conjugated forward filter in the backward direction; and simultaneously forward and backward design and apply, which is known as noncausal filter design. All of the algorithm types mentioned above are tested, and the results of their analysis are provided in this paper on noise free and noisy synthetic data sets: a single dipping event, a single dipping event with a simple amplitude variation with offset, and three dipping events. Finally, the results of applying the selected algorithms on field data are provided.


Geophysics ◽  
2001 ◽  
Vol 66 (6) ◽  
pp. 1864-1876 ◽  
Author(s):  
Tad M. Smith ◽  
Carl H. Sondergeld

Exploration programs in deepwater Tertiary basins (e.g., the Gulf of Mexico) typically rely on bright‐spot and amplitude variation with offset (AVO) technology to help identify oil‐ and gas‐charged sands. The reliance on these attributes, along with the high cost of exploration programs in deepwater environments, has driven the need to examine the limitations of these technologies and to build robust models for the conditions under which AVO is useful as a fluid and/or lithology indicator. We build subregional AVO background trends for both brine‐ and gas‐saturated sands from several wells from the eastern deepwater Gulf of Mexico. These trends are built from the depth dependencies of velocities and densities for both shale and sands (brine saturated). Simple models of AVO gradient and intercept are constructed as a function of depth below the mud line. Sand and shale properties show little velocity contrast, justifying the interpretation of these data in the context of linearized AVO models. In addition to the in‐situ brine response, the response to gas is also calculated. These trend models indicate that the AVO response is suppressed (although still positive) below a depth of approximately 10 000 ft below the mud line. Even optimistic porosity modeling (sand porosity >30°) does not substantially change this conclusion. An important corollary is that the absence of a strong AVO anomaly at these deeper depths cannot be used with confidence when ruling out hydrocarbon presence. This observation also highlights the need to crossplot attributes to best predict hydrocarbon presence. Velocity data collected as part of this study are also used to generate a local shear velocity estimator for sands and shale. These shear estimators are similar in form to other published estimators, but minor differences in coefficients may become important in AVO modeling.


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