Joint inversion of logging-while-drilling multipole acoustic data to determine P- and S-wave velocities in unconsolidated slow formations

Geophysics ◽  
2016 ◽  
Vol 81 (5) ◽  
pp. D553-D560 ◽  
Author(s):  
Yuan-Da Su ◽  
Can Jiang ◽  
Chun-Xi Zhuang ◽  
Song Xu ◽  
Xiao-Ming Tang
Keyword(s):  
Data Processing ◽  
Joint Inversion ◽  
P Wave ◽  
Inversion Method ◽  
Dispersion Characteristics ◽  
S Wave ◽  
Data Set ◽  
Acoustic Data ◽  
Wave Velocities ◽  
Logging While Drilling

We have developed a joint inversion method for logging-while-drilling (LWD) multipole acoustic data processing to simultaneously determine the formation of P- and S-wave velocities. The presence of the LWD tool strongly influences the dispersion characteristics of quadrupole and monopole leaky-P-waves, especially in unconsolidated slow formations. We have verified that an equivalent-tool theory can be adequately used to model the LWD multipole wave dispersion characteristics and can therefore be used to do forward modeling for the inversion. A major advantage of jointly inverting the multipole data sets, as compared with separately inverting each individual data set, is the reduction of uncertainties in the estimated formation of P- and S-wave velocities. We have applied the method to field data processing. The results found that the method not only corrected the dispersion effect in the quadrupole and leaky-P-wave data but also simultaneously obtained the formation of P- and S-wave velocities.

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.

Joint inversion of logging-while-drilling multipole acoustic data to determine formation shear-wave transverse isotropy

Geophysics ◽  
2020 ◽  
Vol 85 (4) ◽  
pp. D121-D132
Author(s):  
Yang-Hu Li ◽  
Song Xu ◽  
Can Jiang ◽  
Yuan-Da Su ◽  
Xiao-Ming Tang
Keyword(s):  
Shear Wave ◽  
Joint Inversion ◽  
Transverse Isotropy ◽  
Synthetic Data ◽  
Flexural Wave ◽  
Inversion Method ◽  
S Wave ◽  
Acoustic Data ◽  
Wave Data ◽  
Logging While Drilling

Seismic-wave anisotropy has long been an important topic in the exploration and development of unconventional reservoirs, especially in shales, which are commonly characterized as transversely isotropic ([TI] or vertical TI [VTI]) media. At present, the shear-wave (S-wave) TI properties have mainly been determined from monopole Stoneley- or dipole flexural-wave measurements in wireline acoustic logging, but the feasibility of those obtained from logging-while-drilling (LWD) acoustic data needs to be established. We have developed a joint inversion method for simultaneously determining formation S-wave transverse isotropy and vertical velocity from LWD multipole acoustic data. Our theoretical analysis shows that the presence of anisotropy strongly influences LWD Stoneley- and quadrupole-wave dispersion characteristics. Although the monopole Stoneley and quadrupole waves are sensitive to the formation S-wave TI parameters, they suffer from the typical nonuniqueness problem when using the individual-wave data to invert parameters alone. Thus, the respective dispersion data can be jointly used to estimate the formation S-wave TI properties. By the joint inversion, the nonuniqueness problem in the parameter inversion can also be effectively alleviated. The feasibility of the method has been verified by the processing results of theoretical synthetic data and field LWD acoustic-wave data. Therefore, the result offers an effective method for evaluating VTI formation anisotropy from acoustic LWD data.

scholarly journals Quadri-joint inversion: Method and application to the Big Sky 9C 3D data set in northern Montana

2018 ◽  
Vol 6 (4) ◽  
pp. SN101-SN118 ◽  
Author(s):  
Vincent Clochard ◽  
Bryan C. DeVault ◽  
David Bowen ◽  
Nicolas Delépine ◽  
Kanokkarn Wangkawong
Keyword(s):  
Reservoir Characterization ◽  
Joint Inversion ◽  
Wave Impedance ◽  
P Wave ◽  
Seismic Survey ◽  
Time Shift ◽  
Inversion Method ◽  
S Wave ◽  
Data Set ◽  
Long Term Storage

The Kevin Dome [Formula: see text] storage project, located in northern Montana, attempted to characterize the Duperow Formation as a potential long-term storage zone for injected [Formula: see text]. A multicomponent (9C) seismic survey was acquired for the Big Sky Carbon Sequestration Partnership over a portion of the Kevin Dome using P- and S-wave sources. Prestack migrated PP, PS, SH, and SV data sets were generated. We then applied several stratigraphic inversion workflows using one or several kinds of seismic wavefield at the same time resulting in joint inversions of each data set. The aim of our study is to demonstrate the benefits of doing quadri-joint inversion of PP-, PS-, SH-, and SV-wavefields for the recovery of the elastic earth parameters, especially the S-wave impedance and density. These are crucial parameters because they can help determine lithology and porefill in the reservoir characterization workflow. Because the inversion workflow always uses the original seismic data recorded in its own time domain, it is necessary to compute registration laws between PP-PS-, PP-SH-, and PP-SV-wavefields using a time shift computation procedure (warping) based on inverted S-wave impedances from inversion of a single wavefield. This generated a significant improvement over methods that rely on attempting to match trace waveforms that may have a different phase, frequency content, and polarity. Finally, we wanted to investigate the reliability of the quadri-joint inversion results in the Bakken/Banff Formations, which have less lateral geologic variation than the underlying Duperow target. This interval shares many of the geophysical characterization challenges common to shale reservoirs in other North American basins. We computed geomechanical parameters, such as Poisson’s ratio and Young’s modulus, which are a proxy for brittleness. Comparison of these results with independent laboratory measurements in the Bakken interval demonstrates the superiority of the quadri-joint inversion method to the traditional inversion using P-wave data only.

Measurement of the shear slowness of slow formations from monopole logging-while-drilling sonic logs

Geophysics ◽  
2019 ◽  
Vol 85 (1) ◽  
pp. D45-D52
Author(s):  
Yuanda Su ◽  
Xinding Fang ◽  
Xiaoming Tang
Keyword(s):  
Numerical Modeling ◽  
Wave Velocity ◽  
Fluid Velocity ◽  
S Wave ◽  
Data Set ◽  
Acoustic Logging ◽  
Wave Velocities ◽  
Logging While Drilling ◽  
Sonic Logs ◽  
Refracted Waves

Acoustic logging-while-drilling (LWD) is used to measure formation velocity/slowness during drilling. In a fast formation, in which the S-wave velocity is higher than the borehole-fluid velocity, monopole logging can be used to obtain P- and S-wave velocities by measuring the corresponding refracted waves. In a slow formation, in which the S-wave velocity is less than the borehole-fluid velocity, because the fully refracted S-wave is missing, quadrupole logging has been developed and used for S-wave slowness measurement. A recent study based on numerical modeling implies that monopole LWD can generate a detectable transmitted S-wave in a slow formation. This nondispersive transmitted S-wave propagates at the formation S-wave velocity and thus can be used for measuring the S-wave slowness of a slow formation. We evaluate a field example to demonstrate the applicability of monopole LWD in determining the S-wave slowness of slow formations. We compare the S-wave slowness extracted from a monopole LWD data set acquired in a slow formation and the result derived from the quadrupole data recorded in the same logging run. The results indicated that the S-wave slowness can be reliably determined from monopole LWD sonic data in fairly slow formations. However, we found that the monopole approach is not applicable to very slow formations because the transmitted S-wave becomes too weak to detect when the formation S-wave slowness is much higher than the borehole-fluid slowness.

Bayesian linearized AVO inversion

Geophysics ◽  
2003 ◽  
Vol 68 (1) ◽  
pp. 185-198 ◽  
Author(s):  
Arild Buland ◽  
Henning Omre
Keyword(s):  
Wave Velocity ◽  
Posterior Distribution ◽  
Acoustic Impedance ◽  
Velocity Ratio ◽  
P Wave ◽  
Inversion Method ◽  
Inversion Algorithm ◽  
S Wave ◽  
Data Set ◽  
Avo Inversion

A new linearized AVO inversion technique is developed in a Bayesian framework. The objective is to obtain posterior distributions for P‐wave velocity, S‐wave velocity, and density. Distributions for other elastic parameters can also be assessed—for example, acoustic impedance, shear impedance, and P‐wave to S‐wave velocity ratio. The inversion algorithm is based on the convolutional model and a linearized weak contrast approximation of the Zoeppritz equation. The solution is represented by a Gaussian posterior distribution with explicit expressions for the posterior expectation and covariance; hence, exact prediction intervals for the inverted parameters can be computed under the specified model. The explicit analytical form of the posterior distribution provides a computationally fast inversion method. Tests on synthetic data show that all inverted parameters were almost perfectly retrieved when the noise approached zero. With realistic noise levels, acoustic impedance was the best determined parameter, while the inversion provided practically no information about the density. The inversion algorithm has also been tested on a real 3‐D data set from the Sleipner field. The results show good agreement with well logs, but the uncertainty is high.

Joint inversion of Rayleigh-wave dispersion and P-wave refraction data for laterally varying layered models

Geophysics ◽  
2014 ◽  
Vol 79 (4) ◽  
pp. EN49-EN59 ◽  
Author(s):  
Daniele Boiero ◽  
Laura Valentina Socco
Keyword(s):  
Rayleigh Wave ◽  
Joint Inversion ◽  
A Priori ◽  
P Wave ◽  
Inversion Method ◽  
Model Parameters ◽  
Data Set ◽  
Wave Refraction ◽  
Velocity Models ◽  
Refraction Data

We implemented a joint inversion method to build P- and S-wave velocity models from Rayleigh-wave and P-wave refraction data, specifically designed to deal with laterally varying layered environments. A priori information available over the site and any physical law to link model parameters can be also incorporated. We tested and applied the algorithm behind the method. The results from a field data set revealed advantages with respect to individual surface-wave analysis (SWA) and body wave tomography (BWT). The algorithm imposed internal consistency for all the model parameters relaxing the required a priori assumptions (i.e., Poisson’s ratio level of confidence in SWA) and the inherent limitations of the two methods (i.e., velocity decreases for BWT).

Simultaneous inversion for model geometry and elastic parameters

Geophysics ◽  
1999 ◽  
Vol 64 (1) ◽  
pp. 182-190 ◽  
Author(s):  
Yanghua Wang
Keyword(s):  
Joint Inversion ◽  
Real Data ◽  
Structural Effect ◽  
P Wave ◽  
Inversion Method ◽  
S Wave ◽  
Elastic Parameters ◽  
Simultaneous Inversion ◽  
Avo Analysis ◽  
The North

Both traveltimes and amplitudes in reflection seismology are used jointly in an inversion to simultaneously invert for the interface geometry and the elastic parameters at the reflectors. The inverse problem has different physical dimensions in both data and model spaces. Practical approaches are proposed to tackle the dimensional difficulties. In using the joint inversion, which may properly take care of the structural effect, one potentially improves the estimates of the subsurface elastic parameters in the traditional analysis of amplitude variation with offset (AVO). Analysis of the elastic parameters estimated, using the ratio of s-wave to P-wave velocity contrasts and the deviation of this parameter from a normal background trend, promises to have application in AVO analysis. The inversion method is demonstrated by application to real data from the North Sea.

Using measured velocity to estimate gas hydrates concentration

Geophysics ◽  
2003 ◽  
Vol 68 (3) ◽  
pp. 884-891 ◽  
Author(s):  
David B. Reister
Keyword(s):  
Lower Bound ◽  
Good Method ◽  
Quadratic Functions ◽  
P Wave ◽  
Upper And Lower Bounds ◽  
Well Log ◽  
S Wave ◽  
Data Set ◽  
Measured Velocity ◽  
Wave Velocities

A new method for using measured P‐wave and S‐wave velocities to estimate gas hydrate concentration uses the Hashin‐Shtrikman (HS) lower bound to provide both an upper and lower bound for mixtures of water and hydrate in unconsolidated marine sediments. The method parameterizes the region between the upper and lower bounds by using two upper bounds: HS and Voigt. Well log measurements of resistivity and the Archie equation are used to calculate hydrate concentration, and quadratic functions that relate the hydrate parameters to the hydrate concentration are estimated. For this data set, neither resistivity nor velocity provide a good method for detecting values of hydrate concentration that are less than 20%.

Joint inversion of receiver functions and apparent incidence angles to investigate the crustal structure of Mars

2021 ◽  
Author(s):  
Rakshit Joshi ◽  
Brigitte Knapmeyer-Endrun ◽  
Klaus Mosegaard ◽  
Felix Bissig ◽  
Amir Khan ◽  
...  
Keyword(s):  
Wave Velocity ◽  
Crustal Structure ◽  
Joint Inversion ◽  
Landing Site ◽  
Crustal Thickness ◽  
Receiver Functions ◽  
P Wave ◽  
S Wave ◽  
Data Set ◽  
Insight Mission

<p>Since InSight (the Interior Exploration using Geodesy and Heat Transport) landed 26 months ago and deployed an ultra sensitive broadband seismometer(SEIS) on the surface of Mars, around 500 seismic events of diverse variety have been detected, making it possible to directly analyze the subsurface properties of Mars for the very first time. One of the primary goals of the mission is to retrieve the crustal structure below the landing site. Current estimates differ by more than 100% for the average crustal thickness. Since data from orbital gravity measurementsprovide information on relative variations of crustal thickness but not absolute values, this landing site measurement could serve as a tie point to retrieve global crustal structure models. To do so, we propose using a joint inversion of receiver functions and apparent incidence angles, which contain information on absolute S-wave velocities of the subsurface. Since receiver function inversions suffer from a velocity depth trade-off, we in addition exploit a simple relation which defines apparent S-wave velocity as a function of observed apparent P-wave incidence angles to constrain the parameter space. Finally we use the Neighbourhood Algorithm for the inversion of a suitable joint objective function. The resulting ensemble of models is then used to derive the full uncertainty estimates for each model parameter. Before its application on data from InSight mission, we successfully tested the method on Mars synthetics and terrestrial data from various geological settings using both single and multiple events. Using the same method, we have previously been able to constrain the S-wave velocity and depth for the first inter-crustal layer of Mars between 1.7 to 2.1 km/s and 8 to 11 km, respectively. Here we present the results of applying this technique on our selected data set from the InSight mission. Results show that the data can be explained equally well by models with 2 or 3 crustal layers with constant velocities. Due to the limited data set it is difficult to resolve the ambiguity of this bi-modal solution. We therefore investigate information theoretic statistical tests as a model selection criteria and discuss their relevance and implications in seismological framework.</p><div></div><div></div><div></div>

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