Anisotropic 3D elastic full-wavefield inversion to directly estimate elastic properties and its role in interpretation

2021 ◽  
Vol 40 (4) ◽  
pp. 277-286
Author(s):  
Haiyang Wang ◽  
Olivier Burtz ◽  
Partha Routh ◽  
Don Wang ◽  
Jake Violet ◽  
...  
Keyword(s):  
Elastic Properties ◽  
Seismic Data ◽  
Reservoir Characterization ◽  
P Wave ◽  
Quality Estimation ◽  
Amplitude Variation ◽  
Linear Inversion ◽  
Amplitude Variation With Offset ◽  
P Wave Velocity ◽  
Wavefield Inversion

Elastic properties from seismic data are important to determine subsurface hydrocarbon presence and have become increasingly important for detailed reservoir characterization that aids to derisk specific hydrocarbon prospects. Traditional techniques to extract elastic properties from seismic data typically use linear inversion of imaged products (migrated angle stacks). In this research, we attempt to get closer to Tarantola's visionary goal for full-wavefield inversion (FWI) by directly obtaining 3D elastic properties from seismic shot-gather data with limited well information. First, we present a realistic 2D synthetic example to show the need for elastic physics in a strongly elastic medium. Then, a 3D field example from deepwater West Africa is used to validate our workflow, which can be practically used in today's computing architecture. To enable reservoir characterization, we produce elastic products in a cascaded manner and run 3D elastic FWI up to 50 Hz. We demonstrate that reliable and high-resolution P-wave velocity can be retrieved in a strongly elastic setting (i.e., with a class 2 or 2P amplitude variation with offset response) in addition to higher-quality estimation of P-impedance and VP/VS ratio. These parameters can be directly used in interpretation, lithology, and fluid prediction.

Elastic reflectivity vectors and the geometry of intercept-gradient crossplots

2019 ◽  
Vol 38 (10) ◽  
pp. 762-769
Author(s):  
Patrick Connolly
Keyword(s):  
Elastic Property ◽  
Elastic Properties ◽  
Wave Velocity ◽  
Seismic Data ◽  
Measurement Errors ◽  
Rock Physics ◽  
P Wave ◽  
S Wave ◽  
P Wave Velocity ◽  
Well Log Analysis

Reflectivities of elastic properties can be expressed as a sum of the reflectivities of P-wave velocity, S-wave velocity, and density, as can the amplitude-variation-with-offset (AVO) parameters, intercept, gradient, and curvature. This common format allows elastic property reflectivities to be expressed as a sum of AVO parameters. Most AVO studies are conducted using a two-term approximation, so it is helpful to reduce the three-term expressions for elastic reflectivities to two by assuming a relationship between P-wave velocity and density. Reduced to two AVO components, elastic property reflectivities can be represented as vectors on intercept-gradient crossplots. Normalizing the lengths of the vectors allows them to serve as basis vectors such that the position of any point in intercept-gradient space can be inferred directly from changes in elastic properties. This provides a direct link between properties commonly used in rock physics and attributes that can be measured from seismic data. The theory is best exploited by constructing new seismic data sets from combinations of intercept and gradient data at various projection angles. Elastic property reflectivity theory can be transferred to the impedance domain to aid in the analysis of well data to help inform the choice of projection angles. Because of the effects of gradient measurement errors, seismic projection angles are unlikely to be the same as theoretical angles or angles derived from well-log analysis, so seismic data will need to be scanned through a range of angles to find the optimum.

Traveltime and relative geometric spreading approximation in elastic orthorhombic medium

Geophysics ◽  
2020 ◽  
Vol 85 (5) ◽  
pp. C153-C162 ◽  
Author(s):  
Shibo Xu ◽  
Alexey Stovas ◽  
Hitoshi Mikada
Keyword(s):  
Seismic Data ◽  
Real Data ◽  
P Wave ◽  
Form Expression ◽  
Amplitude Variation ◽  
Rational Form ◽  
Amplitude Variation With Offset ◽  
Practical Applications ◽  
Numerical Tests ◽  
Geometric Spreading

Wavefield properties such as traveltime and relative geometric spreading (traveltime derivatives) are highly essential in seismic data processing and can be used in stacking, time-domain migration, and amplitude variation with offset analysis. Due to the complexity of an elastic orthorhombic (ORT) medium, analysis of these properties becomes reasonably difficult, where accurate explicit-form approximations are highly recommended. We have defined the shifted hyperbola form, Taylor series (TS), and the rational form (RF) approximations for P-wave traveltime and relative geometric spreading in an elastic ORT model. Because the parametric form expression for the P-wave vertical slowness in the derivation is too complicated, TS (expansion in offset) is applied to facilitate the derivation of approximate coefficients. The same approximation forms computed in the acoustic ORT model also are derived for comparison. In the numerical tests, three ORT models with parameters obtained from real data are used to test the accuracy of each approximation. The numerical examples yield results in which, apart from the error along the y-axis in ORT model 2 for the relative geometric spreading, the RF approximations all are very accurate for all of the tested models in practical applications.

Fracture-porosity inversion from P-wave AVOA data along 2D seismic lines: An example from the Austin Chalk of southeast Texas

Geophysics ◽  
2007 ◽  
Vol 72 (1) ◽  
pp. B1-B7 ◽  
Author(s):  
Abdullatif A. Al-Shuhail
Keyword(s):  
Aspect Ratio ◽  
Wave Velocity ◽  
P Wave ◽  
S Wave ◽  
Amplitude Variation ◽  
Fracture Porosity ◽  
Amplitude Variation With Offset ◽  
P Wave Velocity ◽  
Austin Chalk ◽  
Southeast Texas

Vertical aligned fractures can significantly enhance the horizontal permeability of a tight reservoir. Therefore, it is important to know the fracture porosity and direction in order to develop the reservoir efficiently. P-wave AVOA (amplitude variation with offset and azimuth) can be used to determine these fracture parameters. In this study, I present a method for inverting the fracture porosity from 2D P-wave seismic data. The method is based on a modeling result that shows that the anisotropic AVO (amplitude variation with offset) gradient is negative and linearly dependent on the fracture porosity in a gas-saturated reservoir, whereas the gradient is positive and linearly dependent on the fracture porosity in a liquid-saturated reservoir. This assumption is accurate as long as the crack aspect ratio is less than 0.1 and the ratio of the P-wave velocity to the S-wave velocity is greater than 1.8 — two conditions that are satisfied in most naturally fractured reservoirs. The inversion then uses the fracture strike, the crack aspect ratio, and the ratio of the P-wave velocity to the S-wave velocity to invert the fracture porosity from the anisotropic AVO gradient after inferring the fluid type from the sign of the anisotropic AVO gradient. When I applied this method to a seismic line from the oil-saturated zone of the fractured Austin Chalk of southeast Texas, I found that the inversion gave a median fracture porosity of 0.21%, which is within the fracture-porosity range commonly measured in cores from the Austin Chalk.

Constrained nonlinear amplitude variation with offset inversion using Zoeppritz equations

Geophysics ◽  
2018 ◽  
Vol 83 (3) ◽  
pp. R245-R255 ◽  
Author(s):  
Ali Gholami ◽  
Hossein S. Aghamiry ◽  
Mostafa Abbasi
Keyword(s):  
Nonlinear Equations ◽  
Wave Velocity ◽  
Seismic Data ◽  
P Wave ◽  
Simultaneous Estimation ◽  
Model Parameters ◽  
Amplitude Variation ◽  
Amplitude Variation With Offset ◽  
Zoeppritz Equations ◽  
Avo Inversion

The inversion of prestack seismic data using amplitude variation with offset (AVO) has received increased attention in the past few decades because of its key role in estimating reservoir properties. AVO is mainly governed by the Zoeppritz equations, but traditional inversion techniques are based on various linear or quasilinear approximations to these nonlinear equations. We have developed an efficient algorithm for nonlinear AVO inversion of precritical reflections using the exact Zoeppritz equations in multichannel and multi-interface form for simultaneous estimation of the P-wave velocity, S-wave velocity, and density. The total variation constraint is used to overcome the ill-posedness while solving the forward nonlinear model and to preserve the sharpness of the interfaces in the parameter space. The optimization is based on a combination of Levenberg’s algorithm and the split Bregman iterative scheme, in which we have to refine the data and model parameters at each iteration. We refine the data via the original nonlinear equations, but we use the traditional cost-effective linearized AVO inversion to construct the Jacobian matrix and update the model. Numerical experiments show that this new iterative procedure is convergent and converges to a solution of the nonlinear problem. We determine the performance and optimality of our nonlinear inversion algorithm with various simulated and field seismic data sets.

Prestack waveform inversion of three-dimensional seismic data — An example from the Rock Springs Uplift, Wyoming, USA

Geophysics ◽  
2017 ◽  
Vol 82 (1) ◽  
pp. B1-B12 ◽  
Author(s):  
Josiane Pafeng ◽  
Subhashis Mallick ◽  
Hema Sharma
Keyword(s):  
Seismic Data ◽  
Reservoir Characterization ◽  
Waveform Inversion ◽  
Three Dimensional ◽  
Seismic Inversion ◽  
Amplitude Variation ◽  
Amplitude Variation With Offset ◽  
Seismic Waveform ◽  
Rock Springs Uplift ◽  
Rock Springs

Applying seismic inversion to estimate subsurface elastic earth properties for reservoir characterization is a challenge in exploration seismology. In recent years, waveform-based seismic inversions have gained popularity, but due to high computational costs, their applications are limited, and amplitude-variation-with-offset/angle inversion is still the current state-of-the-art. We have developed a genetic-algorithm-based prestack seismic waveform inversion methodology. By parallelizing at multiple levels and assuming a locally 1D structure such that forward computation of wave equation synthetics is computationally efficient, this method is capable of inverting 3D prestack seismic data on parallel computers. Applying this inversion to a real prestack seismic data volume from the Rock Springs Uplift (RSU) located in Wyoming, USA, we determined that our method is capable of inverting the data in a reasonable runtime and producing much higher quality results than amplitude-variation-with-offset/angle inversion. Because the primary purpose for seismic data acquisition at the RSU was to characterize the subsurface for potential targets for carbon dioxide sequestration, we also identified and analyzed some potential primary and secondary storage formations and their associated sealing lithologies from our inversion results.

Coupling in amplitude variation with offset and the Wiggins approximation

Geophysics ◽  
2013 ◽  
Vol 78 (4) ◽  
pp. N21-N33 ◽  
Author(s):  
Kristopher A. Innanen
Keyword(s):  
Wave Reflection ◽  
Elastic Parameter ◽  
P Wave ◽  
Converted Wave ◽  
Amplitude Variation ◽  
Amplitude Variation With Offset ◽  
Zoeppritz Equations ◽  
P Wave Velocity ◽  
Higher Order Corrections

Linear amplitude-variation-with-offset (AVO) approximations, which experience a reduction in accuracy as elastic parameter contrasts become large, may be adjusted with second- and higher-order corrections. Corrective terms can be expressed in many ways, but they only serve a meaningful purpose if they provide the same qualitative interpretability as did the linearization. Some aspects of nonlinear AVO can be understood, quantitatively and qualitatively, in terms of coupling — the interdependence of elastic parameter contrasts amongst themselves in their determination of reflection strengths. Coupling, for instance, explains the weak but nonnegligible dependence of the converted wave reflection coefficient on the lower half-space P-wave velocity. This fact can be exposed by expanding the solutions of the Zoeppritz equations in a particular hierarchy of series. Also explainable through this approach is the mathematical importance of what is sometimes referred to as the “Wiggins approximation,” under which [Formula: see text]. This special number is seen to coincide with a full decoupling of density contrasts from [Formula: see text] and [Formula: see text] contrasts at the second order. The decoupling persists across several variations of the nonlinear AVO approximations, including both expressions in terms of the relative changes [Formula: see text], [Formula: see text], and [Formula: see text], and expressions in terms of single-parameter reflectivities.

Seismic reservoir characterization of a class-1 amplitude variation with offset turbiditic system located offshore Cote d’Ivoire, West Africa

2018 ◽  
Vol 6 (2) ◽  
pp. SD115-SD128
Author(s):  
Pedro Alvarez ◽  
William Marin ◽  
Juan Berrizbeitia ◽  
Paola Newton ◽  
Michael Barrett ◽  
...  
Keyword(s):  
West Africa ◽  
Seismic Data ◽  
Reservoir Characterization ◽  
Rock Physics ◽  
Rock Properties ◽  
Well Log ◽  
Amplitude Variation ◽  
Amplitude Variation With Offset ◽  
Fluid Content ◽  
Class 1

We have evaluated a case study, in which a class-1 amplitude variation with offset (AVO) turbiditic system located offshore Cote d’Ivoire, West Africa, is characterized in terms of rock properties (lithology, porosity, and fluid content) and stratigraphic elements using well-log and prestack seismic data. The methodology applied involves (1) the conditioning and modeling of well-log data to several plausible geologic scenarios at the prospect location, (2) the conditioning and inversion of prestack seismic data for P- and S-wave impedance estimation, and (3) the quantitative estimation of rock property volumes and their geologic interpretation. The approaches used for the quantitative interpretation of these rock properties were the multiattribute rotation scheme for lithology and porosity characterization and a Bayesian lithofluid facies classification (statistical rock physics) for a probabilistic evaluation of fluid content. The result indicates how the application and integration of these different AVO- and rock-physics-based reservoir characterization workflows help us to understand key geologic stratigraphic elements of the architecture of the turbidite system and its static petrophysical characteristics (e.g., lithology, porosity, and net sand thickness). Furthermore, we found out how to quantify and interpret the risk related to the probability of finding hydrocarbon in a class-1 AVO setting using seismically derived elastic attributes, which are characterized by having a small level of sensitivity to changes in fluid saturation.

Interpretation of AVO anomalies

Geophysics ◽  
2010 ◽  
Vol 75 (5) ◽  
pp. 75A3-75A13 ◽  
Author(s):  
Douglas J. Foster ◽  
Robert G. Keys ◽  
F. David Lane
Keyword(s):  
Wave Velocity ◽  
Seismic Data ◽  
P Wave ◽  
Rock Properties ◽  
Light Hydrocarbons ◽  
S Wave ◽  
Amplitude Variation With Offset ◽  
P Wave Velocity ◽  
Fluid Properties ◽  
Porosity Changes

We investigate the effects of changes in rock and fluid properties on amplitude-variation-with-offset (AVO) responses. In the slope-intercept domain, reflections from wet sands and shales fall on or near a trend that we call the fluid line. Reflections from the top of sands containing gas or light hydrocarbons fall on a trend approximately parallel to the fluid line; reflections from the base of gas sands fall on a parallel trend on the opposing side of the fluid line. The polarity standard of the seismic data dictates whether these reflections from the top of hydrocarbon-bearing sands are below or above the fluid line. Typically, rock properties of sands and shales differ, and therefore reflections from sand/shale interfaces are also displaced from the fluid line. The distance of these trends from the fluid line depends upon the contrast of the ratio of P-wave velocity [Formula: see text] and S-wave velocity [Formula: see text]. This ratio is a function of pore-fluid compressibility and implies that distance from the fluid line increases with increasing compressibility. Reflections from wet sands are closer to the fluid line than hydrocarbon-related reflections. Porosity changes affect acoustic impedance but do not significantly impact the [Formula: see text] contrast. As a result, porosity changes move the AVO response along trends approximately parallel to the fluid line. These observations are useful for interpreting AVO anomalies in terms of fluids, lithology, and porosity.

scholarly journals No mafic layer in 80 km thick Tibetan crust

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Gaochun Wang ◽  
Hans Thybo ◽  
Irina M. Artemieva
Keyword(s):  
Seismic Data ◽  
P Wave ◽  
Indian Plate ◽  
Low Velocity ◽  
Crustal Earthquakes ◽  
Tectonic Processes ◽  
P Wave Velocity ◽  
Juvenile Crust ◽  
Mafic Lower Crust ◽  
Thick Crust

AbstractAll models of the magmatic and plate tectonic processes that create continental crust predict the presence of a mafic lower crust. Earlier proposed crustal doubling in Tibet and the Himalayas by underthrusting of the Indian plate requires the presence of a mafic layer with high seismic P-wave velocity (Vp > 7.0 km/s) above the Moho. Our new seismic data demonstrates that some of the thickest crust on Earth in the middle Lhasa Terrane has exceptionally low velocity (Vp < 6.7 km/s) throughout the whole 80 km thick crust. Observed deep crustal earthquakes throughout the crustal column and thick lithosphere from seismic tomography imply low temperature crust. Therefore, the whole crust must consist of felsic rocks as any mafic layer would have high velocity unless the temperature of the crust were high. Our results form basis for alternative models for the formation of extremely thick juvenile crust with predominantly felsic composition in continental collision zones.

Anisotropic correction of sonic logs in wells with large relative dip

Geophysics ◽  
2008 ◽  
Vol 73 (1) ◽  
pp. E1-E5 ◽  
Author(s):  
Lev Vernik
Keyword(s):  
Reservoir Characterization ◽  
Low Frequency ◽  
P Wave ◽  
Amplitude Variation With Offset ◽  
Seismic Amplitude ◽  
Avo Inversion ◽  
Pore Pressure Prediction ◽  
Siliciclastic Rocks ◽  
Dip Angle ◽  
Sonic Logs

Seismic reservoir characterization and pore-pressure prediction projects rely heavily on the accuracy and consistency of sonic logs. Sonic data acquisition in wells with large relative dip is known to suffer from anisotropic effects related to microanisotropy of shales and thin-bed laminations of sand, silt, and shale. Nonetheless, if anisotropy parameters can be related to shale content [Formula: see text] in siliciclastic rocks, then I show that it is straightforward to compute the anisotropy correction to both compressional and shear logs using [Formula: see text] and the formation relative dip angle. The resulting rotated P-wave sonic logs can be used to enhance time-depth ties, velocity to effective stress transforms, and low-frequency models necessary for prestack seismic amplitude variation with offset (AVO) inversion.

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