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

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.

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Simultaneous inversion of PP and PS seismic data

Geophysics ◽

10.1190/1.2194533 ◽

2006 ◽

Vol 71 (3) ◽

pp. R1-R10 ◽

Cited By ~ 51

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.

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TitleApplication of M4C P-wave and S-wave Joint Inversion in Shallow Reservoir Identification

10.2523/iptc-21465-ms ◽

2021 ◽

Author(s):

Sian Zhu ◽

Hongtao Chen ◽

Yongjun Hu ◽

Feng Yang ◽

Yubin Feng

Keyword(s):

Wave Velocity ◽

Oil And Gas ◽

Joint Inversion ◽

Wave Impedance ◽

P Wave ◽

Seismic Survey ◽

Bohai Bay ◽

S Wave ◽

Bohai Bay Basin ◽

Gas Reservoirs

Abstract The genetic mechanism of shallow gas reservoirs is complex, which is usually characterized by shallow burial depth, multiple types, low reserves and wide distribution, so that the inversion based on P-wave data alone may be ambiguous. For shallow reservoir with large lateral variation, it is hard to accurately predict oil and water distribution by conventional P-wave prestack inversion. Marine four-component (M4C) P-wave and S-wave joint inversion can solve the problem effectively. M4C seismic survey collects P-wave and S-wave seismic data. An initial model can be established based on fine structural interpretation of P-wave and S-wave data and S-wave compression pattern matching. It lays a good foundation for subsequent P-wave and S-wave joint inversion. Based on the P-wave seismic record equation proposed by Fatti et al., a seismic record equation from poststack P-wave and S-wave joint inversion was derived according to the relationship among reflection coefficient, P-wave impedance, S-wave impedance and density, then important lithologic parameters (P-wave impedance, S-wave impedance and density) were calculated, and finally the ratio of P-wave velocity to S-wave velocity which is more sensitive to oil and gas was obtained. According to the ratio of P-wave velocity to S-wave velocity, the oil and gas distribution was predicted in shallow Bohai Bay Basin. Application has proven that the inversion can well reflect the fluid distribution, and the coincidence between the inversion results and the drilling data is up to 85%.M4C seismic survey was conducted for the first time to the shallow oil and gas reservoirs with rapid lateral variation in the Bohai Bay Basin, and collected raw P-wave and S-wave seismic data. Based on the data, the precision and reliability of P-wave and S-wave joint inversion was improved. The results provided strong technical support to the reserves and production increase in the Bohai Bay Basin.

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

Geophysics ◽

10.1190/geo2016-0133.1 ◽

2016 ◽

Vol 81 (5) ◽

pp. D553-D560 ◽

Cited By ~ 4

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.

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Bayesian linearized AVO inversion

Geophysics ◽

10.1190/1.1543206 ◽

2003 ◽

Vol 68 (1) ◽

pp. 185-198 ◽

Cited By ~ 450

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.

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Inversion and interpretation of a 3D seismic data set from the Ouachita Mountains, Oklahoma

Geophysics ◽

10.1190/1.3073005 ◽

2009 ◽

Vol 74 (2) ◽

pp. B37-B45 ◽

Cited By ~ 3

Author(s):

Abuduwali Aibaidula ◽

George McMechan

Keyword(s):

Seismic Data ◽

Acoustic Impedance ◽

3D Visualization ◽

Wave Impedance ◽

P Wave ◽

3D Seismic ◽

S Wave ◽

Ouachita Mountains ◽

Data Set ◽

3D Seismic Data

Acoustic impedance inversion (AI) and simultaneous angle-dependent inversion (SADI) of a 3D seismic data set characterize reservoirs of Mississippian Morrowan age in the triangle zone of the frontal Ouachita Mountains, Oklahoma. Acoustic impedance of the near-angle seismic data images the 3D spatial distributions of Wapanucka limestone and Cromwell sandstone. Lamé [Formula: see text] ([Formula: see text] and [Formula: see text]) and [Formula: see text] sections are derived from the P-wave and S-wave impedance ([Formula: see text] and [Formula: see text]) sections produced by the SADI. Lithology is identified from the gamma logs and [Formula: see text]. The [Formula: see text], [Formula: see text], and [Formula: see text] are interpreted in terms of a hydrocarbon distribution pattern. The [Formula: see text] is used to identify high [Formula: see text] regions that are consistent with high sand/shale ratio. The estimated impedances and derived Lamé parameter sections are consistent with the interpretation that parts of the Wapanucka limestone and Cromwell sandstone contain potential gas reservoirs in fault-bounded compartments. The Cromwell sandstone contains the main inferred reservoirs; the two largest of these are each [Formula: see text] in pore volume. The inversion results also explain the observed low production in previous wells because those did not sample the best compartments. We propose a single new well location that would penetrate both reservoirs; 3D visualization facilitates this recommendation.

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

Geophysics ◽

10.1190/geo2013-0212.1 ◽

2014 ◽

Vol 79 (4) ◽

pp. EN49-EN59 ◽

Cited By ~ 14

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).

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Simultaneous inversion for model geometry and elastic parameters

Geophysics ◽

10.1190/1.1444514 ◽

1999 ◽

Vol 64 (1) ◽

pp. 182-190 ◽

Cited By ~ 24

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.

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Seismic simultaneous inversion using a multidamped subspace method

Geophysics ◽

10.1190/geo2018-0470.1 ◽

2019 ◽

Vol 85 (1) ◽

pp. R1-R10 ◽

Cited By ~ 4

Author(s):

Jinyue Liu ◽

Yanghua Wang

Keyword(s):

Fourier Coefficients ◽

Hessian Matrix ◽

Wave Impedance ◽

Seismic Inversion ◽

P Wave ◽

Inversion Method ◽

Subspace Method ◽

S Wave ◽

Elastic Parameters ◽

Simultaneous Inversion

Seismic inversion of amplitude variation with offset (AVO) plays a key role in seismic interpretation and reservoir characterization. The AVO inversion should be a simultaneous inversion that inverts for three elastic parameters simultaneously: the P-wave impedance, S-wave impedance, and density. Using only seismic P-wave reflection data with a limited source-receiver offset range, the AVO simultaneous inversion can obtain two elastic parameters reliably, but it is difficult to invert for the third parameter, usually the density term. To address this difficulty in the AVO simultaneous inversion, we used a subspace inversion method in which we partitioned the elastic parameters into different subspaces. We parameterized each single elastic parameter with a truncated Fourier series and inverted for the Fourier coefficients. Because the Fourier coefficients of different wavenumber components have different sensitivities, we grouped the Fourier coefficients of low-, medium-, and high-wavenumber components into different subspaces. We further assigned different damping factors to the Hessian matrix corresponding to different wavenumber components within each subspace. This inversion scheme is referred to as a multidamped subspace method. Synthetic and field seismic data examples confirmed that the AVO simultaneous inversion with this multidamped subspace method is capable of producing reliable estimation of the three elastic parameters simultaneously.

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Seismic impedance inversion and interpretation of a gas carbonate reservoir in the Alberta Foothills, western Canada

Geophysics ◽

10.1190/1.1620619 ◽

2003 ◽

Vol 68 (5) ◽

pp. 1460-1469 ◽

Cited By ~ 16

Author(s):

Gislain B. Madiba ◽

George A. McMechan

Keyword(s):

Rocky Mountain ◽

Wave Impedance ◽

Carbonate Reservoir ◽

P Wave ◽

Western Canada ◽

S Wave ◽

Data Set ◽

Water Saturated ◽

Gas Potential ◽

Elastic Impedance

Acoustic and simultaneous elastic impedance inversions of a 2D land seismic data set are performed to characterize a carbonate reservoir of Mississippian age in the Turner Valley Formation, in the Rocky Mountain foothills of western Canada. The inversions produce P‐wave and S‐wave impedance sections (Ip and Is, respectively), from which Lamé parameter × density (λρ and μρ) sections are derived. The Ip data provide a separation between the clastics and carbonates. The μρ data provide an estimate of porosity distribution within the dolomitized limestone target. Deviations from baseline curves for water‐saturated carbonates, of λρ versus porosity, λ/μ versus porosity, and Is versus Ip, are interpreted as indicators of gas potential. These indicators all provide similar spatial patterns of areas of high gas potential and are consistent with the gas occurence observed in a well.

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

10.5194/egusphere-egu21-9470 ◽

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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