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.

Effects of incomplete parameterization on full-wavefield viscoelastic seismic data for petrophysical reservoir properties

Geophysics ◽  
2007 ◽  
Vol 72 (3) ◽  
pp. O9-O17 ◽  
Author(s):  
Upendra K. Tiwari ◽  
George A. McMechan
Keyword(s):  
Seismic Data ◽  
Input Data ◽  
Elastic Model ◽  
Quality Factors ◽  
Noise Levels ◽  
Reservoir Properties ◽  
Estimated Parameters ◽  
Model Parameterization ◽  
The Earth ◽  
Incomplete Model

In inversion of viscoelastic full-wavefield seismic data, the choice of model parameterization influences the uncertainties and biases in estimating seismic and petrophysical parameters. Using an incomplete model parameterization results in solutions in which the effects of missing parameters are attributed erroneously to the parameters that are included. Incompleteness in this context means assuming the earth is elastic rather than viscoelastic. The inclusion of compressional and shear-wave quality factors [Formula: see text] and [Formula: see text] in inversion gives better estimates of reservoir properties than the less complete (elastic) model parameterization. [Formula: see text] and [Formula: see text] are sensitive primarily to fluid types and saturations. The parameter correlations are sensitive also to the model parameterization. As noise increases in the viscoelastic input data, the resolution of the estimated parameters decreases, but the parameter correlations are relatively unaffected by modest noise levels.

scholarly journals Semiglobal viscoacoustic full-waveform inversion

Geophysics ◽  
2019 ◽  
Vol 84 (2) ◽  
pp. R271-R293 ◽  
Author(s):  
Nuno V. da Silva ◽  
Gang Yao ◽  
Michael Warner
Keyword(s):  
Physical Properties ◽  
Wave Velocity ◽  
Seismic Data ◽  
Waveform Inversion ◽  
P Wave ◽  
Full Waveform Inversion ◽  
Data Set ◽  
Intrinsic Attenuation ◽  
Full Waveform ◽  
P Wave Velocity

Full-waveform inversion deals with estimating physical properties of the earth’s subsurface by matching simulated to recorded seismic data. Intrinsic attenuation in the medium leads to the dispersion of propagating waves and the absorption of energy — media with this type of rheology are not perfectly elastic. Accounting for that effect is necessary to simulate wave propagation in realistic geologic media, leading to the need to estimate intrinsic attenuation from the seismic data. That increases the complexity of the constitutive laws leading to additional issues related to the ill-posed nature of the inverse problem. In particular, the joint estimation of several physical properties increases the null space of the parameter space, leading to a larger domain of ambiguity and increasing the number of different models that can equally well explain the data. We have evaluated a method for the joint inversion of velocity and intrinsic attenuation using semiglobal inversion; this combines quantum particle-swarm optimization for the estimation of the intrinsic attenuation with nested gradient-descent iterations for the estimation of the P-wave velocity. This approach takes advantage of the fact that some physical properties, and in particular the intrinsic attenuation, can be represented using a reduced basis, substantially decreasing the dimension of the search space. We determine the feasibility of the method and its robustness to ambiguity with 2D synthetic examples. The 3D inversion of a field data set for a geologic medium with transversely isotropic anisotropy in velocity indicates the feasibility of the method for inverting large-scale real seismic data and improving the data fitting. The principal benefits of the semiglobal multiparameter inversion are the recovery of the intrinsic attenuation from the data and the recovery of the true undispersed infinite-frequency P-wave velocity, while mitigating ambiguity between the estimated parameters.

Elastic impedance parameterization and inversion with Young’s modulus and Poisson’s ratio

Geophysics ◽  
2013 ◽  
Vol 78 (6) ◽  
pp. N35-N42 ◽  
Author(s):  
Zhaoyun Zong ◽  
Xingyao Yin ◽  
Guochen Wu
Keyword(s):  
Parameter Estimation ◽  
Young’S Modulus ◽  
Seismic Data ◽  
Poisson’S Ratio ◽  
Young's Modulus ◽  
Incident Angle ◽  
P Wave ◽  
Poisson's Ratio ◽  
Data Set ◽  
Elastic Impedance

Young’s modulus and Poisson’s ratio are related to quantitative reservoir properties such as porosity, rock strength, mineral and total organic carbon content, and they can be used to infer preferential drilling locations or sweet spots. Conventionally, they are computed and estimated with a rock physics law in terms of P-wave, S-wave impedances/velocities, and density which may be directly inverted with prestack seismic data. However, the density term imbedded in Young’s modulus is difficult to estimate because it is less sensitive to seismic-amplitude variations, and the indirect way can create more uncertainty for the estimation of Young’s modulus and Poisson’s ratio. This study combines the elastic impedance equation in terms of Young’s modulus and Poisson’s ratio and elastic impedance variation with incident angle inversion to produce a stable and direct way to estimate the Young’s modulus and Poisson’s ratio, with no need for density information from prestack seismic data. We initially derive a novel elastic impedance equation in terms of Young’s modulus and Poisson’s ratio. And then, to enhance the estimation stability, we develop the elastic impedance varying with incident angle inversion with damping singular value decomposition (EVA-DSVD) method to estimate the Young’s modulus and Poisson’s ratio. This method is implemented in a two-step inversion: Elastic impedance inversion and parameter estimation. The introduction of a model constraint and DSVD algorithm in parameter estimation renders the EVA-DSVD inversion more stable. Tests on synthetic data show that the Young’s modulus and Poisson’s ratio are still estimated reasonable with moderate noise. A test on a real data set shows that the estimated results are in good agreement with the results of well interpretation.

A statistical methodology for deriving reservoir properties from seismic data

Geophysics ◽  
1995 ◽  
Vol 60 (5) ◽  
pp. 1437-1450 ◽  
Author(s):  
Frédérique Fournier ◽  
Jean‐François Derain
Keyword(s):  
Seismic Data ◽  
Large Scale ◽  
Seismic Attributes ◽  
Seismic Facies ◽  
Reservoir Properties ◽  
Data Set ◽  
Analysis Technique ◽  
Seismic Facies Analysis ◽  
Statistical Relationships

The use of seismic data to better constrain the reservoir model between wells has become an important goal for seismic interpretation. We propose a methodology for deriving soft geologic information from seismic data and discuss its application through a case study in offshore Congo. The methodology combines seismic facies analysis and statistical calibration techniques applied to seismic attributes characterizing the traces at the reservoir level. We built statistical relationships between seismic attributes and reservoir properties from a calibration population consisting of wells and their adjacent traces. The correlation studies are based on the canonical correlation analysis technique, while the statistical model comes from a multivariate regression between the canonical seismic variables and the reservoir properties, whenever they are predictable. In the case study, we predicted estimates and associated uncertainties on the lithofacies thicknesses cumulated over the reservoir interval from the seismic information. We carried out a seismic facies identification and compared the geological prediction results in the cases of a calibration on the whole data set and a calibration done independently on the traces (and wells) related to each seismic facies. The later approach produces a significant improvement in the geological estimation from the seismic information, mainly because the large scale geological variations (and associated seismic ones) over the field can be accounted for.

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.

Simultaneous inversion of PP and PS seismic data

Geophysics ◽  
2006 ◽  
Vol 71 (3) ◽  
pp. R1-R10 ◽  
Author(s):  
Helene Hafslund Veire ◽  
Martin Landrø
Keyword(s):  
Seismic Data ◽  
Reservoir Characterization ◽  
Model Building ◽  
Joint Inversion ◽  
P Wave ◽  
Inversion Method ◽  
System Of Equations ◽  
S Wave ◽  
Data Set ◽  
Simultaneous Inversion

Elastic parameters derived from seismic data are valuable input for reservoir characterization because they can be related to lithology and fluid content of the reservoir through empirical relationships. The relationship between physical properties of rocks and fluids and P-wave seismic data is nonunique. This leads to large uncertainties in reservoir models derived from P-wave seismic data. Because S- waves do not propagate through fluids, the combined use of P-and S-wave seismic data might increase our ability to derive fluid and lithology effects from seismic data, reducing the uncertainty in reservoir characterization and thereby improving 3D reservoir model-building. We present a joint inversion method for PP and PS seismic data by solving approximated linear expressions of PP and PS reflection coefficients simultaneously using a least-squares estimation algorithm. The resulting system of equations is solved by singular-value decomposition (SVD). By combining the two independent measurements (PP and PS seismic data), we stabilize the system of equations for PP and PS seismic data separately, leading to more robust parameter estimation. The method does not require any knowledge of PP and PS wavelets. We tested the stability of this joint inversion method on a 1D synthetic data set. We also applied the methodology to North Sea multicomponent field data to identify sand layers in a shallow formation. The identified sand layers from our inverted sections are consistent with observations from nearby well logs.

The structural architecture of the Whataroa Valley at the Alpine Fault (New Zealand) from first-arrival tomography and reflection imaging using an extended 3D VSP survey

2020 ◽  
Author(s):  
Vera Lay ◽  
Stefan Buske ◽  
Sascha Barbara Bodenburg ◽  
Franz Kleine ◽  
John Townend ◽  
...  
Keyword(s):  
New Zealand ◽  
Seismic Data ◽  
Average Velocity ◽  
Velocity Model ◽  
P Wave ◽  
3D Seismic ◽  
Data Set ◽  
Alpine Fault ◽  
P Wave Velocity ◽  
First Arrival

<p>The Alpine Fault along the West Coast of the South Island (New Zealand) is a major plate boundary that is expected to rupture in the next 50 years, likely as a magnitude 8 earthquake. The Deep Fault Drilling Project (DFDP) aims to deliver insight into the geological structure of this fault zone and its evolution by drilling and sampling the Alpine Fault at depth.  </p><p>Here we present results from a 3D seismic survey around the DFDP-2 drill site in the Whataroa Valley where the drillhole penetrated almost down to the fault surface. Within the glacial valley, we collected 3D seismic data to constrain valley structures that were obscured in previous 2D seismic data. The new data consist of a 3D extended vertical seismic profiling (VSP) survey using three-component receivers and a fibre optic cable in the DFDP-2B borehole as well as a variety of receivers at the surface.</p><p>The data set enables us to derive a reliable 3D P-wave velocity model by first-arrival travel time tomography. We identify a 100-460 m thick sediment layer (average velocity 2200±400 m/s) above the basement (average velocity 4200±500 m/s). Particularly on the western valley side, a region of high velocities steeply rises to the surface and mimics the topography. We interpret this to be the infilled flank of the glacial valley that has been eroded into the basement. In general, the 3D structures implied by the velocity model on the upthrown (Pacific Plate) side of the Alpine Fault correlate well with the surface topography and borehole findings.</p><p>A reliable velocity model is not only valuable by itself but it is also required as input for prestack depth migration (PSDM). We performed PSDM with a part of the 3D data set to derive a structural image of the subsurface within the Whataroa Valley. The top of the basement identified in the P-wave velocity model coincides well with reflectors in the migrated images so that we can analyse the geometry of the basement in detail.</p>

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.

Reservoir properties prediction integrating controlled-source electromagnetic, prestack seismic, and well-log data using a rock-physics framework: Case study in the Hoop Area, Barents Sea, Norway

2017 ◽  
Vol 5 (2) ◽  
pp. SE43-SE60 ◽  
Author(s):  
Pedro Alvarez ◽  
Amanda Alvarez ◽  
Lucy MacGregor ◽  
Francisco Bolivar ◽  
Robert Keirstead ◽  
...  
Keyword(s):  
Seismic Data ◽  
Barents Sea ◽  
Rock Physics ◽  
Positive Outcome ◽  
Rock Properties ◽  
Integrated Analysis ◽  
Reservoir Properties ◽  
Data Set ◽  
Controlled Source ◽  
Rotation Scheme

We have developed an example from the Hoop Area of the Barents Sea showing a sequential quantitative integration approach to integrate seismic and controlled-source electromagnetic (CSEM) attributes using a rock-physics framework. The example illustrates a workflow to address the challenges of multiphysics and multiscale data integration for reservoir characterization purposes. A data set consisting of 2D GeoStreamer seismic and towed streamer electromagnetic data that were acquired concurrently in 2015 by PGS provide the surface geophysical measurements that we used. Two wells in the area — Wisting Central (7324/8-1) and Wisting Alternative (7324/7-1S) — provide calibration for the rock-physics modeling and the quantitative integrated analysis. In the first stage of the analysis, we invert prestack seismic and CSEM data separately for impedance and anisotropic resistivity, respectively. We then apply the multi-attribute rotation scheme (MARS) to estimate rock properties from seismic data. This analysis verified that the seismic data alone cannot distinguish between commercial and noncommercial hydrocarbon saturation. Therefore, in the final stage of the analysis, we invert the seismic and CSEM-derived properties within a rock-physics framework. The inclusion of the CSEM-derived resistivity information within the inversion approach allows for the separation of these two possible scenarios. Results reveal excellent correlation with known well outcomes. The integration of seismic, CSEM, and well data predicts very high hydrocarbon saturations at Wisting Central and no significant saturation at Wisting Alternative, consistent with the findings of each well. Two further wells were drilled in the area and used as blind tests in this case: The slightly lower saturation predicted at Hanssen (7324/7-2) is related to 3D effects in the CSEM data, but the positive outcome of the well is correctly predicted. At Bjaaland (7324/8-2), although the seismic indications are good, the integrated interpretation result predicts correctly that this well was unsuccessful.

Interpretation of fractures and stress anisotropy in Marcellus Shale using multicomponent seismic data

2014 ◽  
Vol 2 (2) ◽  
pp. SE105-SE115 ◽  
Author(s):  
Mehdi E. Far ◽  
Bob Hardage
Keyword(s):  
Seismic Data ◽  
Marcellus Shale ◽  
P Wave ◽  
Accurate Information ◽  
Amplitude Analysis ◽  
Data Set ◽  
Regional Stress ◽  
Stress Anisotropy ◽  
Multicomponent Seismic ◽  
Principal Directions

Using a data set from the Marcellus Shale, we evaluated the advantages of multicomponent seismic data for fracture and anisotropy studies over conventional P-wave data. Using traveltime and amplitude analysis on pre- and poststack seismic data, we concluded that PS-waves can provide more accurate information about the location, orientation, and intensity of natural fractures and stress anisotropy than P-waves. Our analysis indicated that regional stress was the main cause of velocity anisotropy. Amplitude variation with offset and azimuth appeared to be more useful for fracture studies, whereas traveltime variations (especially PS-waves) provided a better indication of regional stress orientations. Principal directions for amplitudes and traveltimes of PP- and PS-waves were different. Misalignment of PP- and PS-waves principal directions suggested that the simplest, most realistic anisotropy model for the fractured Marcellus is monoclinic symmetry.

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