Bayesian lithology and fluid prediction from seismic prestack data

Geophysics ◽  
2008 ◽  
Vol 73 (3) ◽  
pp. C13-C21 ◽  
Author(s):  
Arild Buland ◽  
Odd Kolbjørnsen ◽  
Ragnar Hauge ◽  
Øyvind Skjæveland ◽  
Kenneth Duffaut
Keyword(s):  
Seismic Data ◽  
Rock Physics ◽  
Real Data ◽  
Feasibility Analysis ◽  
Bayesian Inversion ◽  
Inversion Method ◽  
Elastic Parameters ◽  
Data Set ◽  
Prior Probabilities ◽  
Simultaneous Inversion

A fast Bayesian inversion method for 3D lithology and fluid prediction from prestack seismic data, and a corresponding feasibility analysis were developed and tested on a real data set. The objective of the inversion is to find the probabilities for different lithology-fluid classes from seismic data and geologic knowledge. The method combines stochastic rock physics relations between the elastic parameters and the different lithology-fluid classes with the results from a fast Bayesian seismic simultaneous inversion from seismic data to elastic parameters. A method for feasibility analysis predicts the expected modification of the prior probabilities to posterior probabilities for the different lithology-fluid classes. The feasibility analysis can be carried out before the seismic data are analyzed. Both the feasibility method and the seismic lithology-fluid probability inversion were applied to a prospect offshore Norway. The analysis improves the probability for gas sand from 0.1 to about 0.2–0.4 with seismic data.

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.

Bayesian time-lapse inversion

Geophysics ◽  
2006 ◽  
Vol 71 (3) ◽  
pp. R43-R48 ◽  
Author(s):  
Arild Buland ◽  
Youness El Ouair
Keyword(s):  
Water Injection ◽  
Rock Physics ◽  
Real Data ◽  
Time Lapse ◽  
Baseline Survey ◽  
Inversion Method ◽  
Data Set ◽  
Uncertainty Calculation ◽  
The Difference ◽  
Fast Inversion

A new, fast inversion approach for time-lapse seismic data is developed where the uncertainty of the inversion results is an integral part of the solution. The inversion method estimates changes in the elastic material properties of a reservoir because of production of hydrocarbons, including uncertainty bounds on these estimates. The changes in elastic properties then can be related to changes in hydrocarbon saturation and reservoir pressure by using rock-physics relations. The inversion operates directly on the difference between a repeat survey and a baseline survey. This is advantageous with respect to the uncertainty calculation, because an estimate of the seismic uncertainty can be obtained directly from the difference data in zones not affected by production. The method is formulated in a Bayesian setting, and the solution is represented by explicit expressions for the posterior expectation and the covariance of the elastic parameter changes. The explicit analytical form of the posterior distribution provides a computationally fast inversion method. Results of the applied approach to a real data set from the Norne field are consistent with the expected effects of water flushing because of water injection.

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.

Stochastic nonlinear inversion of seismic data for the estimation of petroelastic properties using the ensemble smoother and data reparameterization

Geophysics ◽  
2018 ◽  
Vol 83 (3) ◽  
pp. M25-M39 ◽  
Author(s):  
Mingliang Liu ◽  
Dario Grana
Keyword(s):  
Seismic Data ◽  
Reservoir Characterization ◽  
Computational Cost ◽  
Rock Physics ◽  
Inversion Method ◽  
Nonlinear Inversion ◽  
Seismic Velocities ◽  
Reservoir Properties ◽  
Data Set ◽  
Ensemble Smoother

We have developed a new stochastic nonlinear inversion method for seismic reservoir characterization studies to jointly estimate elastic and petrophysical properties and to quantify their uncertainty. Our method aims to estimate multiple reservoir realizations of the entire set of reservoir properties, including seismic velocities, density, porosity, mineralogy, and saturation, by iteratively updating the initial ensemble of models based on the mismatch between their seismic response and the measured seismic data. The initial models are generated using geostatistical methods and the geophysical forward operators include rock-physics relations and a seismic forward model. The optimization is achieved using an iterative ensemble-based algorithm, namely, the ensemble smoother with multiple data assimilation, in which each iteration is based on a Bayesian updating step. The advantages of the proposed method are that it can be applied to nonlinear inverse problems and it can provide an ensemble of solutions from which we can quantify the uncertainty of the model properties of interest. To reduce the computational cost of the inversion, we perform the optimization in a lower dimensional data space reparameterized by singular value decomposition. The proposed methodology is validated on a synthetic case in which the set of petroelastic properties is recovered with satisfactory accuracy. Then, we applied the inversion method to a real seismic data set from the Norne field in the Norwegian Sea.

Regularization and datuming of seismic data by weighted, damped least squares

Geophysics ◽  
2006 ◽  
Vol 71 (5) ◽  
pp. U67-U76 ◽  
Author(s):  
Robert J. Ferguson
Keyword(s):  
Least Squares ◽  
Seismic Data ◽  
Synthetic Data ◽  
Real Data ◽  
Structural Data ◽  
Irregular Sampling ◽  
Data Set ◽  
Near Surface ◽  
Damped Least Squares ◽  
Wavefield Extrapolation

The possibility of improving regularization/datuming of seismic data is investigated by treating wavefield extrapolation as an inversion problem. Weighted, damped least squares is then used to produce the regularized/datumed wavefield. Regularization/datuming is extremely costly because of computing the Hessian, so an efficient approximation is introduced. Approximation is achieved by computing a limited number of diagonals in the operators involved. Real and synthetic data examples demonstrate the utility of this approach. For synthetic data, regularization/datuming is demonstrated for large extrapolation distances using a highly irregular recording array. Without approximation, regularization/datuming returns a regularized wavefield with reduced operator artifacts when compared to a nonregularizing method such as generalized phase shift plus interpolation (PSPI). Approximate regularization/datuming returns a regularized wavefield for approximately two orders of magnitude less in cost; but it is dip limited, though in a controllable way, compared to the full method. The Foothills structural data set, a freely available data set from the Rocky Mountains of Canada, demonstrates application to real data. The data have highly irregular sampling along the shot coordinate, and they suffer from significant near-surface effects. Approximate regularization/datuming returns common receiver data that are superior in appearance compared to conventional datuming.

Porosity estimation based on rock skeleton general formula and comprehensive pore structure parameter – An application to a tight-sand reservoir

2021 ◽  
pp. 1-59
Author(s):  
Kai Lin ◽  
Xilei He ◽  
Bo Zhang ◽  
Xiaotao Wen ◽  
Zhenhua He ◽  
...  
Keyword(s):  
Aspect Ratio ◽  
Pore Structure ◽  
Seismic Data ◽  
Rock Physics ◽  
Structure Parameters ◽  
Pore Structure Parameter ◽  
Elastic Parameters ◽  
Physics Model ◽  
Rock Physics Model ◽  
Porosity Estimation

Most of current 3D reservoir’s porosity estimation methods are based on analyzing the elastic parameters inverted from seismic data. It is well-known that elastic parameters vary with pore structure parameters such as pore aspect ratio, consolidate coefficient, critical porosity, etc. Thus, we may obtain inaccurate 3D porosity estimation if the chosen rock physics model fails properly address the effects of pore structure parameters on the elastic parameters. However, most of current rock physics models only consider one pore structure parameter such as pore aspect ratio or consolidation coefficient. To consider the effect of multiple pore structure parameters on the elastic parameters, we propose a comprehensive pore structure (CPS) parameter set that is generalized from the current popular rock physics models. The new CPS set is based on the first order approximation of current rock physics models that consider the effect of pore aspect ratio on elastic parameters. The new CPS set can accurately simulate the behavior of current rock physics models that consider the effect of pore structure parameters on elastic parameters. To demonstrate the effectiveness of proposed parameters in porosity estimation, we use a theoretical model to demonstrate that the proposed CPS parameter set properly addresses the effect of pore aspect ratio on elastic parameters such as velocity and porosity. Then, we obtain a 3D porosity estimation for a tight sand reservoir by applying it seismic data. We also predict the porosity of the tight sand reservoir by using neural network algorithm and a rock physics model that is commonly used in porosity estimation. The comparison demonstrates that predicted porosity has higher correlation with the porosity logs at the blind well locations.

scholarly journals Estimates of European emissions of methyl chloroform using a Bayesian inversion method

2014 ◽  
Vol 14 (18) ◽  
pp. 9755-9770 ◽  
Author(s):  
M. Maione ◽  
F. Graziosi ◽  
J. Arduini ◽  
F. Furlani ◽  
U. Giostra ◽  
...  
Keyword(s):  
Point Source ◽  
High Frequency ◽  
Stratospheric Ozone ◽  
Montreal Protocol ◽  
Source Analysis ◽  
Bayesian Inversion ◽  
Inversion Method ◽  
Data Set ◽  
Methyl Chloroform

Abstract. Methyl chloroform (MCF) is a man-made chlorinated solvent contributing to the destruction of stratospheric ozone and is controlled under the "Montreal Protocol on Substances that Deplete the Ozone Layer" and its amendments, which called for its phase-out in 1996 in developed countries and 2015 in developing countries. Long-term, high-frequency observations of MCF carried out at three European sites show a constant decline in the background mixing ratios of MCF. However, we observe persistent non-negligible mixing ratio enhancements of MCF in pollution episodes, suggesting unexpectedly high ongoing emissions in Europe. In order to identify the source regions and to give an estimate of the magnitude of such emissions, we have used a Bayesian inversion method and a point source analysis, based on high-frequency long-term observations at the three European sites. The inversion identified southeastern France (SEF) as a region with enhanced MCF emissions. This estimate was confirmed by the point source analysis. We performed this analysis using an 11-year data set, from January 2002 to December 2012. Overall, emissions estimated for the European study domain decreased nearly exponentially from 1.1 Gg yr−1 in 2002 to 0.32 Gg yr−1 in 2012, of which the estimated emissions from the SEF region accounted for 0.49 Gg yr−1 in 2002 and 0.20 Gg yr−1 in 2012. The European estimates are a significant fraction of the total semi-hemisphere (30–90° N) emissions, contributing a minimum of 9.8% in 2004 and a maximum of 33.7% in 2011, of which on average 50% are from the SEF region. On the global scale, the SEF region is thus responsible for a minimum of 2.6% (in 2003) and a maximum of 10.3% (in 2009) of the global MCF emissions.

scholarly journals Time-Lapse Seismic Monitoring of Onshore Reservoirs in Niger Delta, Field ‘K’ as a Case Study

2017 ◽  
Vol 1 (1) ◽  
pp. 23-27 ◽  
Author(s):  
A. Ogbamikhumi ◽  
T. Tralagba ◽  
E. E. Osagiede
Keyword(s):  
Seismic Data ◽  
Acoustic Impedance ◽  
Niger Delta ◽  
Rock Physics ◽  
Time Lapse ◽  
Seismic Survey ◽  
Impedance Change ◽  
Data Set ◽  
Reservoir Fluid ◽  
4D Seismic

Field ‘K’ is a mature field in the coastal swamp onshore Niger delta, which has been producing since 1960. As a huge producing field with some potential for further sustainable production, field monitoring is therefore important in the identification of areas of unproduced hydrocarbon. This can be achieved by comparing production data with the corresponding changes in acoustic impedance observed in the maps generated from base survey (initial 3D seismic) and monitor seismic survey (4D seismic) across the field. This will enable the 4D seismic data set to be used for mapping reservoir details such as advancing water front and un-swept zones. The availability of good quality onshore time-lapse seismic data for Field ‘K’ acquired in 1987 and 2002 provided the opportunity to evaluate the effect of changes in reservoir fluid saturations on time-lapse amplitudes. Rock physics modelling and fluid substitution studies on well logs were carried out, and acoustic impedance change in the reservoir was estimated to be in the range of 0.25% to about 8%. Changes in reservoir fluid saturations were confirmed with time-lapse amplitudes within the crest area of the reservoir structure where reservoir porosity is 0.25%. In this paper, we demonstrated the use of repeat Seismic to delineate swept zones and areas hit with water override in a producing onshore reservoir.

Common-focus point-based target-oriented imaging approach for continuous seismic reservoir monitoring

Geophysics ◽  
2018 ◽  
Vol 83 (4) ◽  
pp. M41-M48 ◽  
Author(s):  
Hongwei Liu ◽  
Mustafa Naser Al-Ali
Keyword(s):  
Seismic Data ◽  
Rock Physics ◽  
Time Lapse ◽  
Velocity Estimation ◽  
Estimation Methods ◽  
Data Sets ◽  
Data Set ◽  
Velocity Models ◽  
Reservoir Monitoring ◽  
Focus Point

The ideal approach for continuous reservoir monitoring allows generation of fast and accurate images to cope with the massive data sets acquired for such a task. Conventionally, rigorous depth-oriented velocity-estimation methods are performed to produce sufficiently accurate velocity models. Unlike the traditional way, the target-oriented imaging technology based on the common-focus point (CFP) theory can be an alternative for continuous reservoir monitoring. The solution is based on a robust data-driven iterative operator updating strategy without deriving a detailed velocity model. The same focusing operator is applied on successive 3D seismic data sets for the first time to generate efficient and accurate 4D target-oriented seismic stacked images from time-lapse field seismic data sets acquired in a [Formula: see text] injection project in Saudi Arabia. Using the focusing operator, target-oriented prestack angle domain common-image gathers (ADCIGs) could be derived to perform amplitude-versus-angle analysis. To preserve the amplitude information in the ADCIGs, an amplitude-balancing factor is applied by embedding a synthetic data set using the real acquisition geometry to remove the geometry imprint artifact. Applying the CFP-based target-oriented imaging to time-lapse data sets revealed changes at the reservoir level in the poststack and prestack time-lapse signals, which is consistent with the [Formula: see text] injection history and rock physics.

Seismic resolution enhancement in shale-oil reservoirs

Geophysics ◽  
2018 ◽  
Vol 83 (5) ◽  
pp. B281-B287 ◽  
Author(s):  
Xiwu Liu ◽  
Fengxia Gao ◽  
Yuanyin Zhang ◽  
Ying Rao ◽  
Yanghua Wang
Keyword(s):  
Seismic Data ◽  
Resolution Enhancement ◽  
Oil Reservoirs ◽  
Inversion Method ◽  
Shale Oil ◽  
Data Set ◽  
Extension Method ◽  
Seismic Resolution ◽  
Full Band ◽  
Shale Oil Reservoirs

We developed a case study of seismic resolution enhancement for shale-oil reservoirs in the Q Depression, China, featured by rhythmic bedding. We proposed an innovative method for resolution enhancement, called the full-band extension method. We implemented this method in three consecutive steps: wavelet extraction, filter construction, and data filtering. First, we extracted a constant-phase wavelet from the entire seismic data set. Then, we constructed the full-band extension filter in the frequency domain using the least-squares inversion method. Finally, we applied the band extension filter to the entire seismic data set. We determined that this full-band extension method, with a stretched frequency band from 7–70 to 2–90 Hz, may significantly enhance 3D seismic resolution and distinguish reflection events of rhythmite groups in shale-oil reservoirs.

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