Physical modeling of overburden effects

Geophysics ◽  
2007 ◽  
Vol 72 (4) ◽  
pp. T37-T45 ◽  
Author(s):  
Mu Luo ◽  
Mamoru Takanashi ◽  
Kazuo Nakayama ◽  
Teruya Ezaka
Keyword(s):  
Seismic Data ◽  
Physical Modeling ◽  
Wave Reflection ◽  
Seismic Anisotropy ◽  
Middle Layer ◽  
P Wave ◽  
Scale Model ◽  
Reservoir Properties ◽  
P Waves ◽  
High Degree

Reservoir properties can be inferred from the amount of anisotropy estimated from seismic data. Unfortunately, irregularities in the formations above the reservoir unit can mask or overprint the true seismic anisotropy of the reservoir unit. This overburden effect subjects the measured reservoir seismic anisotropy to a high degree of uncertainty. We investigate this overburden effect on P-waves with a three-layer ultrasonic laboratory-scale model whose middle layer contains localized, gas-filled vertical fractures. We analyze the reflection amplitudes and traveltimes of a P-wave reflection event from below the overburden to understand the overburden effect on anisotropy analysis and imaging. Our study shows that steps must be taken to reduce the P-wave overburden effect when significant irregularities occur in the formations above the reservoir unit.

Quartic reflection moveout in a weakly anisotropic dipping layer

Geophysics ◽  
2006 ◽  
Vol 71 (1) ◽  
pp. D1-D13 ◽  
Author(s):  
Vladimir Grechka ◽  
Andrés Pech
Keyword(s):  
General Formula ◽  
Anisotropic Medium ◽  
Seismic Data ◽  
Wave Reflection ◽  
P Wave ◽  
Weak Anisotropy ◽  
Effective Anisotropy ◽  
Isotropic Solid ◽  
Strike Direction

Deviations of P-wave reflection traveltimes from a hyperbola, called the nonhyperbolic or quartic moveout, need to be handled properly while processing long-spread seismic data. As observed nonhyperbolic moveout is usually attributed to the presence of anisotropy, we devote our paper to deriving and analyzing a general formula that describes an azimuthally varying quartic moveout coefficient in a homogeneous, weakly anisotropic medium above a dipping, mildly curved reflector. To obtain the desired expression, we consistently linearize all quantities in small stiffness perturbations from a given isotropic solid. Our result incorporates all known weak-anisotropy approximations of the quartic moveout coefficient and extends them further to triclinic media. By comparing our approximation with nonhyperbolic moveout obtained from the ray-traced reflection traveltimes, we find that the former predicts azimuthal variations of the quartic moveout when its magnitude is less than 20% of the corresponding hyperbolic moveout term. We also study the influence of reflector curvature on nonhyperbolic moveout. It turns out that the curvature produces no quartic moveout in the reflector strike direction, where the anisotropy-induced moveout nonhyperbolicity is usually nonnegligible. Thus, the presence of nonhyperbolic moveout along the reflector strike might indicate effective anisotropy.

Rapid map and inversion of P-SV waves

Geophysics ◽  
1991 ◽  
Vol 56 (6) ◽  
pp. 859-862 ◽  
Author(s):  
Robert R. Stewart
Keyword(s):  
Spatial Resolution ◽  
Seismic Data ◽  
P Wave ◽  
Rock Properties ◽  
Low Velocity ◽  
P Waves ◽  
Near Surface ◽  
Seismic Profiling ◽  
Vertical Seismic Profiling ◽  
And Inversion

Multicomponent seismic recordings are currently being analyzed in an attempt to improve conventional P‐wave sections and to find and use rock properties associated with shear waves (e.g. Dohr, 1985; Danbom and Dominico, 1986). Mode‐converted (P-SV) waves hold a special interest for several reasons: They are generated by conventional P‐wave sources and have only a one‐way travel path as a shear wave through the typically low velocity and attenuative near surface. For a given frequency, they will have a shorter wavelength than the original P wave, and thus offer higher spatial resolution; this has been observed in several vertical seismic profiling (VSP) cases (e.g., Geis et al., 1990). However, for surface seismic data, converted waves are often found to be of lower frequency than P-P waves (e.g., Eaton et al., 1991).

Investigation of fluid effects on seismic responses through a physical modeling experiment

2020 ◽  
pp. 1-38
Author(s):  
Chao Xu ◽  
Pinbo Ding ◽  
Bangrang Di ◽  
Jianxin Wei
Keyword(s):  
Seismic Data ◽  
Physical Modeling ◽  
Seismic Velocity ◽  
Water Saturation ◽  
P Wave ◽  
Seismic Velocities ◽  
Seismic Responses ◽  
Modeling Experiment ◽  
Seismic Reflections ◽  
Tight Rocks

We investigated fluid effects on seismic responses using seismic data from a physical modeling experiment. Eight cubic samples with cavities quantitatively filled with air, oil, and water and sixteen non-fluid samples were set within a physical model. Both pre-stack and post-stack seismic responses of the samples were analyzed to quantitatively investigate the fluid effect on the seismic response. It was indicated that fluids could cause detectable changes in both pre-stack and post-stack seismic responses for tight rocks. At first, fluids filled within samples caused changes in pre-stack seismic responses. Visible differences could be detected between angle gathers of the samples filled with air, oil, and water. For the base reflections, the amplitudes at large angles of the air-filled and oil-filed samples are obviously stronger than those of the water-filled sample. In addition, the presence of fluids within samples led to significant changes in post-stack seismic reflections. For samples with similar P-wave impedances to the background, we found strong seismic reflections for the fluid samples and weak or even no reflections for the non-fluid samples. There was notable interference between the top and base reflections for the fluid samples while there was none for the non-fluid samples. Seismic velocities were estimated using the two-way travel times between the top and base reflections. The estimated seismic velocity gently declined with increasing water saturation until 90%. When the water saturation was more than 90%, the seismic velocity showed a steep increase.

A skeptic's view of VVAz and AVAz

2020 ◽  
Vol 39 (2) ◽  
pp. 128-134 ◽  
Author(s):  
Norbert Van De Coevering ◽  
Klaas Koster ◽  
Rob Holt
Keyword(s):  
Phase Ii ◽  
Seismic Data ◽  
Wave Mode ◽  
P Wave ◽  
Noise Levels ◽  
Reservoir Properties ◽  
Data Set ◽  
Lower Amplitude ◽  
Software Note ◽  
Dense Sampling

We have applied a modern amplitude- and azimuth-preserving seismic data processing workflow to the SEG Advanced Modeling Program (SEAM) Phase II Barrett classic data set — an orthorhombic synthetic seismic model that has extremely dense sampling of all azimuths and offsets. We analyze the resulting prestack depth-migrated offset vector tiles with a variety of methods and software. Note that we only analyze the P-P wave mode, which is the focus of our study. We demonstrate that observed azimuthal changes cannot be correlated with the model's reservoir properties. We have made the migrated data available through SEAM. Compared to modeled data, real onshore seismic data have significantly lower amplitude fidelity, higher noise levels, and more uncertainty in the migration velocity field used for processing. Since we are unable to relate the anisotropy measured from the fully sampled clean SEAM Phase II Barrett synthetic seismic data to the model's known anisotropy, we conclude that it is highly unlikely that azimuthal variations observed on real onshore seismic data will be predictive of reservoir fracture properties.

Data-driven Prestack Waveform Inversion Using Genetic Algorithm- Methodology and Examples

2021 ◽  
pp. 1-97
Author(s):  
Lingxiao Jia ◽  
Subhashis Mallick ◽  
Cheng Wang
Keyword(s):  
Genetic Algorithm ◽  
Seismic Data ◽  
Waveform Inversion ◽  
Seismic Inversion ◽  
P Wave ◽  
Data Driven ◽  
Initial Model ◽  
Reservoir Properties ◽  
Well Control ◽  
Seismic Waveform

The choice of an initial model for seismic waveform inversion is important. In matured exploration areas with adequate well control, we can generate a suitable initial model using well information. However, in new areas where well control is sparse or unavailable, such an initial model is compromised and/or biased by the regions with more well controls. Even in matured exploration areas, if we use time-lapse seismic data to predict dynamic reservoir properties, an initial model, that we obtain from the existing preproduction wells could be incorrect. In this work, we outline a new methodology and workflow for a nonlinear prestack isotropic elastic waveform inversion. We call this method a data driven inversion, meaning that we derive the initial model entirely from the seismic data without using any well information. By assuming a locally horizonal stratification for every common midpoint and starting from the interval P-wave velocity, estimated entirely from seismic data, our method generates pseudo wells by running a two-pass one-dimensional isotropic elastic prestack waveform inversion that uses the reflectivity method for forward modeling and genetic algorithm for optimization. We then use the estimated pseudo wells to build the initial model for seismic inversion. By applying this methodology to real seismic data from two different geological settings, we demonstrate the usefulness of our method. We believe that our new method is potentially applicable for subsurface characterization in areas where well information is sparse or unavailable. Additional research is however necessary to improve the compute-efficiency of the methodology.

Reservoir property prediction using abductive networks

Geophysics ◽  
2010 ◽  
Vol 75 (1) ◽  
pp. P1-P9 ◽  
Author(s):  
Osama A. Ahmed ◽  
Radwan E. Abdel-Aal ◽  
Husam AlMustafa
Keyword(s):  
Statistical Methods ◽  
Seismic Data ◽  
Polynomial Regression ◽  
Seismic Attributes ◽  
Oil Field ◽  
Attribute Selection ◽  
Reservoir Properties ◽  
Seismic Amplitude ◽  
Porosity Logs ◽  
High Degree

Statistical methods, such as linear regression and neural networks, are commonly used to predict reservoir properties from seismic attributes. However, a huge number of attributes can be extracted from seismic data and an efficient method for selecting an attribute subset with the highest correlation to the property being predicted is essential. Most statistical methods, however, lack an optimized approach for this attribute selection. We propose to predict reservoir properties from seismic attributes using abductive networks, which use iterated polynomial regression to derive high-degree polynomial predictors. The abductive networks simultaneously select the most relevant attributes and construct an optimal nonlinear predictor. We applied the approach to predict porosity from seismic data of an area within the 'Uthmaniyah portion of the Ghawar oil field, Saudi Arabia. The data consisted of normal seismic amplitude, acoustic impedance, 16 other seismic attributes, and porosity logs from seven wells located in the study area. Out of 27 attributes, the abductive network selected only the best two to six attributes and produced a more accurate and robust porosity prediction than using the more common neural-network predictors. In addition, the proposed method requires no effort in choosing the attribute subset or tweaking their parameters.

Imaging structures below dipping TI media

Geophysics ◽  
1999 ◽  
Vol 64 (4) ◽  
pp. 1239-1246 ◽  
Author(s):  
Robert W. Vestrum ◽  
Don C. Lawton ◽  
Ron Schmid
Keyword(s):  
Seismic Data ◽  
Seismic Anisotropy ◽  
Rocky Mountain ◽  
Transversely Isotropic ◽  
Velocity Model ◽  
P Wave ◽  
Depth Imaging ◽  
Depth Migration ◽  
Kirchhoff Depth Migration ◽  
Ti Media

Seismic anisotropy in dipping shales causes imaging and positioning problems for underlying structures. We developed an anisotropic depth‐migration approach for P-wave seismic data in transversely isotropic (TI) media with a tilted axis of symmetry normal to bedding. We added anisotropic and dip parameters to the depth‐imaging velocity model and used prestack depth‐migrated image gathers in a diagnostic manner to refine the anisotropic velocity model. The apparent position of structures below dipping anisotropic overburden changes considerably between isotropic and anisotropic migrations. The ray‐tracing algorithm used in a 2-D prestack Kirchhoff depth migration was modified to calculate traveltimes in the presence of TI media with a tilted symmetry axis. The resulting anisotropic depth‐migration algorithm was applied to physical‐model seismic data and field seismic data from the Canadian Rocky Mountain Thrust and Fold Belt. The anisotropic depth migrations offer significant improvements in positioning and reflector continuity over those obtained using isotropic algorithms.

Weak-anisotropy moveout approximations for P-waves in homogeneous TOR layers

Geophysics ◽  
2017 ◽  
Vol 82 (4) ◽  
pp. WA23-WA32 ◽  
Author(s):  
Véronique Farra ◽  
Ivan Pšenčík
Keyword(s):  
Wave Reflection ◽  
P Wave ◽  
Homogeneous Layer ◽  
Orthorhombic Symmetry ◽  
Euler Angles ◽  
Weak Anisotropy ◽  
P Waves ◽  
Anisotropy Parameters ◽  
Dip Angle

We have developed approximate P-wave reflection moveout formulas for a homogeneous layer of orthorhombic symmetry overlying a horizontal or dipping reflector. The symmetry planes of an orthorhombic medium in the layer can be arbitrarily oriented. The formulas are based on the weak-anisotropy approximation. Thus, their accuracy depends not only on the strength of anisotropy, but also on the deviations of the phase and ray velocities. Nevertheless, the performed tests indicate that for P-wave anisotropy of approximately 25%, the maximum relative traveltime errors of the formulas do not exceed 3%. The formulas are expressed in terms of six P-wave weak-anisotropy parameters and three Euler angles specifying the orientation of the symmetry planes of the orthorhombic medium. In the case of a dipping reflector, the formulas also depend on the apparent dip angle of the reflector.

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