Joint inversion of seismic, vertical seismic profiling, and crosswell data — A case study from China

2017 ◽  
Vol 5 (1) ◽  
pp. T107-T119 ◽  
Author(s):  
Hemin Yuan ◽  
De-hua Han ◽  
Hui Li ◽  
Danping Cao
Keyword(s):  
Seismic Data ◽  
Joint Inversion ◽  
Seismic Inversion ◽  
Inversion Method ◽  
A Posteriori ◽  
Frequency Bandwidth ◽  
Surface Reflection ◽  
Seismic Profiling ◽  
Reflection Seismic ◽  
Vertical Seismic Profiling

Three-dimensional poststack and prestack seismic inversion results such as P- and S-impedance are commonly used for reservoir characterization. However, the frequency bandwidth of surface-based reflection seismic surveys usually ranges from 10 to 70 Hz, and these surveys have limited vertical resolution. The frequency bandwidth of vertical seismic profiling (VSP) and crosswell data is much wider than that of surface reflection seismic data, and it can give a detailed illumination of the subsurface around the borehole. We test a joint inversion method that integrated surface reflection seismic, VSP, and crosswell data. To better constrain the inversion results, we further integrate a posteriori information on the reflectivity obtained from petrophysics data into the inversion procedure. The a posteriori distribution we use is a modified-Cauchy distribution obtained from the statistical analysis of petrophysics data. To demonstrate the effectiveness of our algorithm, we applied our inversion strategy to a 2D synthetic model and a real seismic data set, and an uncertainty assessment was also performed. The joint inversion method can detect the thin layers that surface seismic inversion fail to, demonstrating the higher resolution of the method.

scholarly journals Fluid prediction of a deep carbonate reservoir using walkaround 3D-3C vertical seismic profiling data

2019 ◽  
Author(s):  
Haohao Zhang ◽  
Jun Lu ◽  
Benchi Chen ◽  
Xuejun Ma ◽  
Zhidong Cai
Keyword(s):  
Poisson’S Ratio ◽  
Wave Impedance ◽  
Carbonate Reservoir ◽  
P Wave ◽  
Poisson's Ratio ◽  
Inversion Method ◽  
Seismic Profiling ◽  
Tahe Oilfield ◽  
Vertical Seismic Profiling ◽  
Time Migration

Abstract The considerable depth and complicated structure of the Tahe Oilfield in the Tuofutai area of China make it very difficult to delineate its Ordovician carbonate fracture-cavity reservoir. The resolution of conventional ground seismic data is inadequate to satisfy current exploitation requirements. To further improve the understanding of the carbonate fracture-cavity reservoir of the Tahe Oilfield and to provide predictions of reservoir properties that are more accurate, a walkaround 3D-3C vertical seismic profiling (VSP) survey was conducted. First, we preprocessed raw VSP data and developed a method of joint PP- and PSV-wave prestack time migration. In contrast to ground seismic imaging profiles, VSP imaging profiles have a higher resolution and wider spectrum range that provide more detailed strata information. Then, using the joint PP- and PSV-wave prestack inversion method, we obtained the PP- and PSV-wave impedance and Poisson's ratio parameters of the Ordovician carbonate reservoir. Compared with the P-wave impedance of the ground seismic inversion, we found the VSP inversion results had higher accuracy, which enabled clearer identification of the internal characteristics of the carbonate reservoir. Finally, coupled with the Poisson's ratio attribute, we predicted the distribution of favorable reservoirs and interwell connectivity. The prediction results were verified using both logging and production data. The findings of this study demonstrate the applicability of the proposed technical method for the exploration of deep carbonate fracture-cavity reservoirs.

Sensitivity analysis of optimization parameters on cooperative inversion of seismic reflection and gravity data

2020 ◽  
Author(s):  
Maiara Gonçalves ◽  
Emilson Leite
Keyword(s):  
Sensitivity Analysis ◽  
Objective Function ◽  
Seismic Data ◽  
Optimization Methods ◽  
Inversion Method ◽  
Standard Case ◽  
Reflection Seismic ◽  
Gravimetric Data ◽  
Standard Values ◽  
Cooperative Inversion

<p>Reflections of seismic waves are strongly distorted by the presence of complex geological structures (e.g. salt bodies) and their vertical resolution is usually of the order of a few tens of meters, imposing limitations in the construction of subsurface models. One way to improve the reliability of such models is to integrate reflection seismic data with other types of geophysical data, such as gravimetric data, since the latter provide an additional link to map geological structures that exhibit density contrasts with respect to their surroundings. In a previous study, we developed a cooperative inversion method of 2D post-stack and migrated reflection seismic data, and gravimetric data. Using that inversion method, we minimize two problems: (1) the problem of the distortion of reflection seismic data due to the presence of complex geological bodies and (2) the problem of the greater ambiguity and the commonly lower resolution of the models obtained only from gravimetric anomalies. The method incorporates a technique to decrease the number of variables and is solved by optimization of the gravity inverse problem, thus reducing computing time. The objective function of cooperative inversion was minimized using three different methods of optimization: (1) simplex, (2) simulated annealing, and (3) genetic algorithm. However, these optimization methods have internal parameters which affect the convergence rate and objective function values. These parameters are usually chosen accordingly to previous references. Although the usage of these standard values is widely accepted, the best values to assure effectiveness and stability of convergence are case-dependent. In the present study, we propose a sensitivity analysis on the internal parameters of the optimization methods for the previously presented cooperative inversion. First, we developed the standard case, which is an inversion performed using all parameters at their standard values. Then, the sensitivity analysis is performed by running multiple inversions, each one with a set of parameters. Each set is obtained by modifying the value of a single parameter either for a lower or for a higher value, keeping all other values at their standard values. The results obtained by each setting are compared to the results of the standard case. The compared results are both the number of evaluations and the final value of the objective function. We then classify parameters accordingly to their relative influence on the optimization processes. The sensitivity analysis provides insight into the best practices to deal with object-based cooperative inversion schemes. The technique was tested using a synthetic model calculated from the Benchmark BP 2004, representing an offshore sedimentary basin containing salt bodies and small hydrocarbons reservoirs.</p>

Accuracy of wavelets, seismic inversion, and thin-bed resolution

2017 ◽  
Vol 5 (4) ◽  
pp. T523-T530
Author(s):  
Ehsan Zabihi Naeini ◽  
Mark Sams
Keyword(s):  
Seismic Data ◽  
Reservoir Characterization ◽  
Low Frequency ◽  
Seismic Inversion ◽  
Inversion Method ◽  
Frequency Content ◽  
Frequency Model ◽  
North West ◽  
The North ◽  
Well Data

Broadband reprocessed seismic data from the North West Shelf of Australia were inverted using wavelets estimated with a conventional approach. The inversion method applied was a facies-based inversion, in which the low-frequency model is a product of the inversion process itself, constrained by facies-dependent input trends, the resultant facies distribution, and the match to the seismic. The results identified the presence of a gas reservoir that had recently been confirmed through drilling. The reservoir is thin, with up to 15 ms of maximum thickness. The bandwidth of the seismic data is approximately 5–70 Hz, and the well data used to extract the wavelet used in the inversion are only 400 ms long. As such, there was little control on the lowest frequencies of the wavelet. Different wavelets were subsequently estimated using a variety of new techniques that attempt to address the limitations of short well-log segments and low-frequency seismic. The revised inversion showed greater gas-sand continuity and an extension of the reservoir at one flank. Noise-free synthetic examples indicate that thin-bed delineation can depend on the accuracy of the low-frequency content of the wavelets used for inversion. Underestimation of the low-frequency contents can result in missing thin beds, whereas underestimation of high frequencies can introduce false thin beds. Therefore, it is very important to correctly capture the full frequency content of the seismic data in terms of the amplitude and phase spectra of the estimated wavelets, which subsequently leads to a more accurate thin-bed reservoir characterization through inversion.

Twelve years of vertical birefringence in nine‐component VSP data

Geophysics ◽  
2001 ◽  
Vol 66 (2) ◽  
pp. 582-597 ◽  
Author(s):  
Donald F. Winterstein ◽  
Gopa S. De ◽  
Mark A. Meadows
Keyword(s):  
Seismic Data ◽  
Azimuthal Anisotropy ◽  
Vertical Shear ◽  
S Wave ◽  
Seismic Profiles ◽  
Surface Reflection ◽  
Vertical Seismic Profiles ◽  
Reflection Seismic ◽  
San Andreas ◽  
Vsp Data

Since 1986, when industry scientists first publicly showed data supporting the presence of azimuthal anisotropy in sedimentary rock, we have studied vertical shear‐wave (S-wave) birefringence in 23 different wells in western North America. The data were from nine‐component vertical seismic profiles (VSPs) supplemented in recent years with data from wireline crossed‐dipole logs. This paper summarizes our results, including birefringence results in tabular form for 54 depth intervals in 19 of those 23 wells. In the Appendix we present our conclusions about how to record VSP data optimally for study of vertical birefringence. We arrived at four principal conclusions about vertical S-wave birefringence. First, birefringence was common but not universal. Second, birefringence ranged from 0–21%, but values larger than 4% occurred only in shallow formations (<1200 m) within 40 km of California’s San Andreas fault. Third, at large scales birefringence tended to be blocky. That is, both the birefringence magnitude and the S-wave polarization azimuth were often consistent over depth intervals of several tens to hundreds of meters but then changed abruptly, sometimes by large amounts. Birefringence in some instances diminished with depth and in others increased with depth, but in almost every case a layer near the surface was more birefringent than the layer immediately below it. Fourth, observed birefringence patterns generally do not encourage use of multicomponent surface reflection seismic data for finding fractured hydrocarbon reservoirs, but they do encourage use of crossed‐dipole logs to examine them. That is, most reservoirs were birefringent, but none we studied showed increased birefringence confined to the reservoir.

Simultaneous inversion of prestack seismic data for rock properties using simulated annealing

Geophysics ◽  
2002 ◽  
Vol 67 (6) ◽  
pp. 1877-1885 ◽  
Author(s):  
Xin‐Quan Ma
Keyword(s):  
Simulated Annealing ◽  
Seismic Data ◽  
Low Frequency ◽  
Optimization Procedure ◽  
P Wave ◽  
Rock Properties ◽  
Inversion Method ◽  
Inversion Algorithm ◽  
Simultaneous Inversion ◽  
Reflection Seismic

A new prestack inversion algorithm has been developed to simultaneously estimate acoustic and shear impedances from P‐wave reflection seismic data. The algorithm uses a global optimization procedure in the form of simulated annealing. The goal of optimization is to find a global minimum of the objective function, which includes the misfit between synthetic and observed prestack seismic data. During the iterative inversion process, the acoustic and shear impedance models are randomly perturbed, and the synthetic seismic data are calculated and compared with the observed seismic data. To increase stability, constraints have been built into the inversion algorithm, using the low‐frequency impedance and background Vs/Vp models. The inversion method has been successfully applied to synthetic and field data examples to produce acoustic and shear impedances comparable to log data of similar bandwidth. The estimated acoustic and shear impedances can be combined to derive other elastic parameters, which may be used for identifying of lithology and fluid content of reservoirs.

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).

Probabilistic petrophysical-properties estimation integrating statistical rock physics with seismic inversion

Geophysics ◽  
2010 ◽  
Vol 75 (3) ◽  
pp. O21-O37 ◽  
Author(s):  
Dario Grana ◽  
Ernesto Della Rossa
Keyword(s):  
Seismic Data ◽  
Measurement Errors ◽  
Rock Physics ◽  
Seismic Inversion ◽  
Joint Estimation ◽  
Physical Models ◽  
Inversion Method ◽  
Petrophysical Properties ◽  
Reservoir Properties ◽  
Statistical Rock Physics

A joint estimation of petrophysical properties is proposed that combines statistical rock physics and Bayesian seismic inversion. Because elastic attributes are correlated with petrophysical variables (effective porosity, clay content, and water saturation) and this physical link is associated with uncertainties, the petrophysical-properties estimation from seismic data can be seen as a Bayesian inversion problem. The purpose of this work was to develop a strategy for estimating the probability distributions of petrophysical parameters and litho-fluid classes from seismics. Estimation of reservoir properties and the associated uncertainty was performed in three steps: linearized seismic inversion to estimate the probabilities of elastic parameters, probabilistic upscaling to include the scale-changes effect, and petrophysical inversion to estimate the probabilities of petrophysical variables andlitho-fluid classes. Rock-physics equations provide the linkbetween reservoir properties and velocities, and linearized seismic modeling connects velocities and density to seismic amplitude. A full Bayesian approach was adopted to propagate uncertainty from seismics to petrophysics in an integrated framework that takes into account different sources of uncertainty: heterogeneity of the real data, approximation of physical models, measurement errors, and scale changes. The method has been tested, as a feasibility step, on real well data and synthetic seismic data to show reliable propagation of the uncertainty through the three different steps and to compare two statistical approaches: parametric and nonparametric. Application to a real reservoir study (including data from two wells and partially stacked seismic volumes) has provided as a main result the probability densities of petrophysical properties and litho-fluid classes. It demonstrated the applicability of the proposed inversion method.

Reflectivity decomposition: Theory and application

2021 ◽  
pp. 1-57
Author(s):  
Chen Liang ◽  
John Castagna ◽  
Marcelo Benabentos
Keyword(s):  
Seismic Data ◽  
Seismic Inversion ◽  
Well Logs ◽  
Reflection Coefficients ◽  
3D Seismic ◽  
Decomposition Theory ◽  
Midland Basin ◽  
Reflection Seismic ◽  
Sparse Inversion ◽  
Reflectivity Inversion

Sparse reflectivity inversion of processed reflection seismic data is intended to produce reflection coefficients that represent boundaries between geological layers. However, the objective function for sparse inversion is usually dominated by large reflection coefficients which may result in unstable inversion for weak events, especially those interfering with strong reflections. We propose that any seismogram can be decomposed according to the characteristics of the inverted reflection coefficients which can be sorted and subset by magnitude, sign, and sequence, and new seismic traces can be created from only reflection coefficients that pass sorting criteria. We call this process reflectivity decomposition. For example, original inverted reflection coefficients can be decomposed by magnitude, large ones removed, the remaining reflection coefficients reconvolved with the wavelet, and this residual reinverted, thereby stabilizing inversions for the remaining weak events. As compared with inverting an original seismic trace, subtle impedance variations occurring in the vicinity of nearby strong reflections can be better revealed and characterized when only the events caused by small reflection coefficients are passed and reinverted. When we apply reflectivity decomposition to a 3D seismic dataset in the Midland Basin, seismic inversion for weak events is stabilized such that previously obscured porous intervals in the original inversion, can be detected and mapped, with good correlation to actual well logs.

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