AVO inversion using pseudoisotropic elastic properties

2021 ◽  
Vol 40 (1) ◽  
pp. 52-59
Author(s):  
Michinori Asaka
Keyword(s):  
Elastic Properties ◽  
Oil And Gas ◽  
Reservoir Characterization ◽  
Elastic Anisotropy ◽  
Data Set ◽  
Amplitude Variation With Offset ◽  
Avo Inversion ◽  
Characterization Study ◽  
Anisotropy Parameters ◽  
Using Data

Amplitude variation with offset (AVO) inversion of an anisotropic data set is a challenging task. Nonnegligible differences in the anisotropy parameters between the various lithologies make the seismic data AVO response completely different from the isotropic synthetic seismogram. In this case, it is difficult to invert for VP/VS and density consistent with well-log data. AVO inversion using pseudoisotropic elastic properties is a practical solution to this problem. Verification of this method was performed using data from an offshore Western Australia field. It was found that wavelet extraction and density inversion are improved significantly by replacing the isotropic elastic properties with the pseudoisotropic properties. Inverted density shows reasonable quality and therefore can be included in the reservoir characterization study. Postinversion analyses can be performed effectively on the pseudoisotropic elastic properties because crossplot analysis shows the increased separation of different lithofacies due to contrasts in anisotropy parameters. This result could have significant implications for other fields, as shale constitutes most of the overburden in conventional oil and gas fields and often shows strong elastic anisotropy.

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.

Amplitude variation with offset inversion using the reflectivity method

Geophysics ◽  
2016 ◽  
Vol 81 (4) ◽  
pp. R185-R195 ◽  
Author(s):  
Hongxing Liu ◽  
Jingye Li ◽  
Xiaohong Chen ◽  
Bo Hou ◽  
Li Chen
Keyword(s):  
Wave Velocity ◽  
P Wave ◽  
Transmission Losses ◽  
Amplitude Variation ◽  
Data Set ◽  
Amplitude Variation With Offset ◽  
Avo Inversion ◽  
Propagation Effects ◽  
Reflectivity Method ◽  
Internal Multiples

Most existing amplitude variation with offset (AVO) inversion methods are based on the Zoeppritz’s equation or its approximations. These methods assume that the amplitude of seismic data depends only on the reflection coefficients, which means that the wave-propagation effects, such as geometric spreading, attenuation, transmission loss, and multiples, have been fully corrected or attenuated before inversion. However, these requirements are very strict and can hardly be satisfied. Under a 1D assumption, reflectivity-method-based inversions are able to handle transmission losses and internal multiples. Applications of these inversions, however, are still time-consuming and complex in computation of differential seismograms. We have evaluated an inversion methodology based on the vectorized reflectivity method, in which the differential seismograms can be calculated from analytical expressions. It is computationally efficient. A modification is implemented to transform the inversion from the intercept time and ray-parameter domain to the angle-gather domain. AVO inversion is always an ill-posed problem. Following a Bayesian approach, the inversion is stabilized by including the correlation of the P-wave velocity, S-wave velocity, and density. Comparing reflectivity-method-based inversion with Zoeppritz-based inversion on a synthetic data and a real data set, we have concluded that reflectivity-method-based inversion is more accurate when the propagation effects of transmission losses and internal multiples are not corrected. Model testing has revealed that the method is robust at high noise levels.

Introduction to this special section: Reservoir characterization Part I

2020 ◽  
Vol 39 (2) ◽  
pp. 82-83
Author(s):  
Ali Tura ◽  
Margarita Corzo
Keyword(s):  
Oil And Gas ◽  
Reservoir Characterization ◽  
Joint Inversion ◽  
Special Section ◽  
Waveform Inversion ◽  
Velocity Model ◽  
Reflection Mode ◽  
Amplitude Variation With Offset ◽  
Zoeppritz Equations ◽  
Full Waveform

In 1980, Aki and Richards published linearized formulations of the Zoeppritz equations from 1919. From then on, many flavors and variations of the P-P reflection mode so-called amplitude variation with offset (AVO) equations have been published and used. Assuming the earth is isotropic, these equations are used day in and day out in the industry for reservoir characterization and to find oil and gas in the subsurface. Some publications have shown that using the P-P and P-S reflections in a joint inversion can increase the accuracy of the inverted parameters. Technically, however, there has been little divergence from the linearized Zoeppritz equations until lately when full-waveform inversion started to gain traction, initially for velocity model estimation and imaging and more recently applied to reservoir characterization.

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.

Computation of dry-rock VP/VS ratio, fluid property factor, and density estimation from amplitude-variation-with-offset inversion

Geophysics ◽  
2018 ◽  
Vol 83 (6) ◽  
pp. R669-R679 ◽  
Author(s):  
Gang Chen ◽  
Xiaojun Wang ◽  
Baocheng Wu ◽  
Hongyan Qi ◽  
Muming Xia
Keyword(s):  
Reservoir Characterization ◽  
Synthetic Data ◽  
Pore Fluid ◽  
Inversion Method ◽  
S Wave ◽  
Amplitude Variation ◽  
Amplitude Variation With Offset ◽  
Fluid Identification ◽  
Fluid Property ◽  
Avo Inversion

Estimating the fluid property factor and density from amplitude-variation-with-offset (AVO) inversion is important for fluid identification and reservoir characterization. The fluid property factor can distinguish pore fluid in the reservoir and the density estimate aids in evaluating reservoir characteristics. However, if the scaling factor of the fluid property factor (the dry-rock [Formula: see text] ratio) is chosen inappropriately, the fluid property factor is not only related to the pore fluid, but it also contains a contribution from the rock skeleton. On the other hand, even if the angle gathers include large angles (offsets), a three-parameter AVO inversion struggles to estimate an accurate density term without additional constraints. Thus, we have developed an equation to compute the dry-rock [Formula: see text] ratio using only the P- and S-wave velocities and density of the saturated rock from well-logging data. This decouples the fluid property factor from lithology. We also developed a new inversion method to estimate the fluid property factor and density parameters, which takes full advantage of the high stability of a two-parameter AVO inversion. By testing on a portion of the Marmousi 2 model, we find that the fluid property factor calculated by the dry-rock [Formula: see text] ratio obtained by our method relates to the pore-fluid property. Simultaneously, we test the AVO inversion method for estimating the fluid property factor and density parameters on synthetic data and analyze the feasibility and stability of the inversion. A field-data example indicates that the fluid property factor obtained by our method distinguishes the oil-charged sand channels and the water-wet sand channel from the well logs.

Effective elastic properties of solid clays

Geophysics ◽  
2001 ◽  
Vol 66 (2) ◽  
pp. 428-440 ◽  
Author(s):  
Zhijing (Zee) Wang ◽  
Hui Wang ◽  
Michael E. Cates
Keyword(s):  
Clay Minerals ◽  
Elastic Properties ◽  
Reservoir Characterization ◽  
Seismic Exploration ◽  
Data Set ◽  
Effective Elastic Properties ◽  
Seismic Properties ◽  
Sonic Log ◽  
Log Interpretation ◽  
Composite Samples

Clay minerals are perhaps the most abundant materials in the earth’s upper crust. As such, their elastic properties are extremely important in seismic exploration, seismic reservoir characterization, and sonic‐log interpretation. Because little exists in the literature on elastic properties of clays, we have designed a method of measuring effective elastic properties of solid clays (clays without pores). In this method, clay minerals are mixed with a material with known elastic properties to make composite samples. Elastic properties of these clay minerals are then inverted from the measured elastic properties of the composite samples using the weighted Hashin‐Shtrikman average. Using this method, we have measured 66 samples of 16 types of clays. In this paper, we present a comprehensive data set of elastic properties of solid clays that commonly occur in, or are related to, petroleum reservoirs. Although uncertainties (up to 10%) exist, the data set reported here is by far the most comprehensive set of elastic properties in the literature. These data can be used potentially in modeling the seismic properties of clay‐bearing rocks.

scholarly journals Data Model and Application of Pipeline Integrity Management

2021 ◽  
Vol 329 ◽  
pp. 01036
Author(s):  
Bingtao Dai
Keyword(s):  
Data Model ◽  
Oil And Gas ◽  
Spatial Information ◽  
Social Economy ◽  
Gas Pipeline ◽  
Data Set ◽  
Development Status ◽  
Integrity Management ◽  
Using Data ◽  
Stable Development

Data is an important foundation and premise to ensure pipeline integrity management. Using data model to manage and utilize data is the key to implement pipeline integrity management, which can not only ensure the safety of oil and gas transportation, but also promote the stable development of China's social economy. Based on this, this paper deeply analyzes the development status of oil and gas pipeline integrity management data model, and makes an in-depth exploration on the establishment and application of oil and gas pipeline integrity data model by comparing various data models, combined with the current situation of oil and gas pipeline integrity management, and with the help of the advantages of apdm model, such as data set division and spatial information management.

Seismic petrophysics workflow applied to Delaware Basin

2020 ◽  
Vol 8 (2) ◽  
pp. T349-T363
Author(s):  
Yoryenys Del Moro ◽  
Venkatesh Anantharamu ◽  
Lev Vernik ◽  
Alfonso Quaglia ◽  
Eduardo Carrillo
Keyword(s):  
Elastic Properties ◽  
Reservoir Characterization ◽  
Weighted Average ◽  
Rock Physics ◽  
Seismic Inversion ◽  
Source Rocks ◽  
Amplitude Variation With Offset ◽  
Geomechanical Properties ◽  
Delaware Basin ◽  
Seismic Amplitudes

Petrophysical analysis of unconventional plays that are comprised of organic mudrock needs detailed data QC and preparation to optimize the results of quantitative interpretation. This includes accurate computation of mineral volumes, total organic carbon (TOC), porosity, and saturations. We used TOC estimation to aid the process of determining the best pay zones for development of such reservoirs. TOC was calculated as a weighted average of Passey’s (empirical) and the bulk density-based (theoretical) methods. In organic mudrock reservoirs, the computed TOC log was used as an input to compute porosity and calibrate rock-physics models (RPMs), which are needed for understanding the potential of source rocks or finding sweet spots and their contribution to the amplitude variation with offset (AVO) changes in the seismic data. Using calibrated RPM templates, we found that TOC is driving the elastic property variations in the Avalon Formation. We determined the layering and rock fabric anisotropy using empirical relationships or modeled in the rock property characterization process because reflectivity effects are often seen in the observed seismic used for well tie and wavelet estimation. A Class IV AVO response was seen at the top of the Avalon Formation, which is typical of an unconventional reservoir. We then performed solid organic matter (TOC) substitution to account for variability of elastic properties and their contrasts as expressed in seismic amplitudes. To complete the characterization of the intervals of interest, we used conventional seismic petrophysical methods in the workflow and found that the main driver modifying the elastic properties for the Avalon shales was TOC; this conclusion serves as a foundation in integrated seismic inversion that may target lithofacies, TOC, and geomechanical properties. Seismic reservoir characterization results are critical in constraining landing zones and trajectories of the horizontal wells. The final interpretation may be used to rank targets, optimize drilling campaigns, and ultimately improve production.

3D structural-orientation vector guided autotracking for weak seismic reflections: A new tool for shale reservoir visualization and interpretation

2018 ◽  
Vol 6 (4) ◽  
pp. SN47-SN56 ◽  
Author(s):  
Haibin Di ◽  
Dengliang Gao ◽  
Ghassan AlRegib
Keyword(s):  
Oil And Gas ◽  
Reservoir Characterization ◽  
Signal To Noise Ratio ◽  
Estimation Algorithm ◽  
3D Seismic ◽  
Data Set ◽  
Structural Orientation ◽  
Weak Reflection ◽  
Orientation Vector ◽  
Shale Reservoirs

Recognizing and tracking weak reflections, which are characterized by low amplitude, low signal-to-noise ratio, and low degree of lateral continuity, is a long-time issue in 3D seismic interpretation and reservoir characterization. The problem is particularly acute with unconventional, fractured shale reservoirs, in which the impedance contrast is low and/or reservoir beds are below the tuning thickness. To improve the performance of interpreting weak reflections associated with shale reservoirs, we have developed a new workflow for weak-reflection tracking guided by a robust structural-orientation vector (SOV) estimation algorithm. The new SOV-guided auto-tracking workflow first uses the reflection orientation at the seed location as a constraint to project the most-likely locations in the neighboring traces, and then locally adjust them to maximally match the target reflection. We verify our workflow through application to a test seismic data set that is typical of routine 3D seismic surveys over shale oil and gas fields. The results demonstrate the improved quality of the resulting horizons compared with the traditional autotracking algorithms. We conclude that this new SOV-guided autotracking workflow can be used to enhance the performance and effectiveness of weak reflection mapping, which should have important implications for improved shale reservoirs visualization and characterization.

scholarly journals Inversion for Geofluid Discrimination Based on Poroelasticity and AVO Inversion

Geofluids ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-17
Author(s):  
Lingqian Wang ◽  
Hui Zhou ◽  
Bo Yu ◽  
Yanxin Zhou ◽  
Wenling Liu ◽  
...  
Keyword(s):  
Bulk Modulus ◽  
Reservoir Characterization ◽  
Approximate Equation ◽  
Deterministic Models ◽  
Amplitude Variation With Offset ◽  
Avo Inversion ◽  
Empirical Relations ◽  
Seismic Records ◽  
The One ◽  
Mixed Fluid

Geofluid discrimination plays an important role in reservoir characterization and prospect identification. Compared with other fluid indicators, the effective pore-fluid bulk modulus is more sensitive to the property of fluid contained in reservoirs. We combine the empirical relations with deterministic models to form a new kind of linearized relationship between the mixed fluid/rock term and the fluid modulus. On the one hand, the linearized relationship can decouple the fluid bulk modulus from the mixed fluid/rock term; on the other hand, the decoupled terms are more stable especially in low-porosity situations compared with previous approaches. In terms of the new linearized equation of the fluid modulus, we derive a novel linearized amplitude variation with offset (AVO) approximation to avoid the complicated nonlinear relationship between the fluid modulus and the reflectivity series. Convoluting this linearized AVO approximation with seismic wavelets, the forward modeling is constructed to combine the prestack seismic records with the fluid modulus. Meanwhile, we introduce the Bayesian inference with multivariable Cauchy prior to the fluid modulus inversion for a stable and high-resolution solution. Model examples demonstrate the accuracy of the proposed linearized AVO approximation compared with the exact Zoeppritz equation and Aki-Richards approximate equation. The synthetic and field data tests illustrate the accuracy and feasibility of the proposed fluid modulus inversion approach for geofluid discrimination.

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