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78th EAGE Conference and Exhibition 2016
- Conference date: May 30, 2016 - June 2, 2016
- Location: Online
- Published: 30 May 2016
81 - 100 of 1034 results
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Applications of the Fractional Order Analytic Signal amplitude and Local Wavenumber
More LessSummaryAnalytic expressions for the fractional order anomaly, analytic signal amplitude, and local wavenumber of different magnetic models are derived. These expressions can be integrated with existing source-distance methods and used as part of the semi-automatic interpretation of magnetic anomalies. The order of the fractional order derivatives can be chosen based on the noise levels of the data.
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3D Inversion of Gravity Gradient Data Based on Cokriging to Identify the Dip Angle of a Dipping Dike Model
More LessSummaryWhen we invert gravity gradient data to recover 3D density distributions by cokriging, the dip angle of a dike directly influence the recovered results. Where there is a lack of the prior information about the dip angle, to obtain the reasonable results we present a method to identify the angle. Firstly, keeping the parameters same in cokriging inversion but we introduce some different dip angles by angle scan approach, then according to the prior information, only zero and positive density contrast are chosen. The standard deviations of the residuals between the observed and predicted data change with the angle. And the estimated dip angle of this method is the scan angle corresponding to the minimum standard deviation. In this paper, we choose four typical dipping dike model with the dip angle of 0o, 45o, 90o, 135o. Tzz data was inverted to test the validity of the mothed. All these four dip angles can be estimated correctly. This result make cokriging can be applied in more cases in which even the dip angle is unavailable.
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Identification the Basin Structure Using FHD and SVD - The Case Study in North East Java Basin
Authors F.H. Hisyam, Q.D.T.F. Fiandani and Z.F. Zuhrotul FirdausSummaryResearch has been done in North East Java Basin using gravity method. The data which be processed on this research are obtained from Bureau Gravimétrique International (International Gravimetric Bureau). Initial data processing yields Complete Bouguer Anomaly map which is filtered using Upward Continuation to separate regional and residual anomaly. The residual anomaly data was processed using derivative analysis include First Horizontal Derivative (FHD) and Second Vertical Derivative (SVD). The angle which used in FHD is 135o. Result from this analysis show six fault structures which has NE - SW orientation. The structures are normal fault which associated with half graben. The high area (ridge zone) is shown with high value Residual Bouguer Anomaly (RBA) ranged 6 until 11 mGal. The low area (trough zone) is shown with low value RBA ranged -16 until -8 mGal. These results appropriate with geological data of the research area.
Keyword: FHD, SVD, Geology Structure, North East Java Basin
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Robust Time-domain Migration Velocity Analysis Methods for Initial-model Building in a Full Waveform Tomography Workflow
Authors H.B. Santos, J. Schleicher, A. Novais, A. Kurzmann and T. BohlenSummaryFull-waveform tomography (FWT) is notorious for its strong dependence on the initial model. We present a workflow for the construction of initial velocity-models for FWT methods consisting of automatic time-migration velocity analysis by means of double multi-stack migration, followed by time-to-depth conversion by image-ray wavefront propagation. Evaluation of the converted velocity model as an initial velocity model in an acoustic FWT process indicates the potential of using a combination of these methods to achieve a fully automatic tool for initial-model building in a FWT workflow. Our tests on a modified version of the Marmousi-2 model have shown that correct background velocity information can be successfully extracted from automatic time-domain migration velocity analysis even in media where time-migration cannot provide satisfactory seismic images.
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Hybrid Super Memory Gradient Method Full Waveform Inversion
Authors Y Hu, L.G. Han, v Zhang, L. Bai and T.Z. ZhangSummaryIn this paper, we discussed the Hybrid Super Memory Gradient (HSPM) method for FWI, whereby the Super Memory Gradient (SPM) method and Unconstrained Super Memory Gradient (USPM) method are used for FWI iterations. SPM method uses many gradients information to correct current descent direction, so we can obtain more accurate descent direction. USPM method without Wolfe linear search which can save a lot of computational time. Firstly, at low frequencies, we use USPM method , and then use SPM method to inverse high frequencies information. The numerical examples show that HSPM delivers similar results as those expected with the SPM method, and improved computational efficiency over Conjugate Gradient method.
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Frequency Domain FWI with Angle Domain Wavenumber Filter Using Local Slant Stacking
More LessSummaryThe scale length of velocity perturbations is closely related to the scattering angels of the wave. In the full waveform inversion, waves with different scattering angles can retrieve model parameters of different scale length. We introduce an angle-domain wavenumber filter for frequency domain full waveform inversion. Both source- and receiver-side waves are decomposed into local plane waves using slant-stack method. At each grid point, the scattering angles between the incident and scattering directions are used as the constraint to determine the wavenumber components to be retrieved. Large scattering angles are related to large-scale model perturbations, so by filtering out small scattering angles in the inversion, we can get the large-scale background model. Numerical examples show that when the initial model has large velocity errors and the low-frequency information is missing in the data, the angle-domain filter can largely improve the convergence in the initial iteration stage.
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Multi-scale Frequency-domain Elastic Full Waveform Inversion Based on Dual-level Parallelism
More LessSummaryThe complexity of the elastic wavefield increases the nonlinearity of inversion. To some extent, multi-scale inversion decreases the nonlinearity of inversion and prevents it from falling into local extremes. A multi-scale strategy based on the simultaneous use of frequency groups and layer stripping method based on damped wave field improves the stability of inversion. A dual-level parallel algorithm is then used to decrease the computational cost and improve practicability. The seismic wave modeling of a single frequency and inversion in a frequency group are computed in parallel by multiple nodes based on MUMPS and MPI. Numerical tests using an overthrust model show that the proposed inversion algorithm can effectively improve the stability and accuracy of inversion by selecting the appropriate inversion frequency and damping factor in low-frequency seismic data.
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An Optimized Correlation-based Full Waveform Inversion
Authors Y. Choi and T. AlkhalifahSummaryThe conventional correlation-based objective function for FWI has a limitation: the desired (accurate) solution is not exactly located at the global minimum (or maximum) since the auto-correlation of the observed wavefield has some energy at non-zero time-lags. We propose two optimized correlation-based objective functions incorporating the auto-correlation term. Including this term in the new objective functions as a reference for the cross-correlation to fit locates the desired solution at the global minimum (or maximum). We derive the gradient expressions of the new objective functions using the adjoint-state method, where only two modelling steps are needed to calculate the gradients. The numerical examples show that FWI based on the new objective functions generate good convergent results, whereas the conventional correlation-based FWI does not.
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Wavelet Filter Based Low-frequency Data Reconstruction for Time Domain Full Waveform Inversion
Authors P. Zhang, L.G. Han, F.J. Zhang and Y. ZhouSummaryThe conventional full waveform inversion (FWI) often uses local optimization algorithm to update velocity model. So the initial model we provide should be good enough to avoid local minimum. Abundant low-frequency information can compensate for the inaccuracy of the initial model and help to avoid cycle-skipping. In this paper, we proposed a wavelet filter based low-frequency data reconstruction method. We extracted the subsurface impulse responses using Fast Iterative Shrinkage-Thresholding Algorithm (FISTA), and convolved the broad-band impulse responses with band-limited low-frequency source wavelets to obtain low-frequency data. The convolution process is equivalent to filtering using low-frequency source wavelets. The accuracy analysis demonstrated that the reconstructed data can meet the requirement of FWI. We proposed a new strategy for multiscale time domain full waveform inversion (TDFWI), which using a series of low-frequency reconstructed data as observed data. One distinct advantage is that the wavelet is accurately known for the reconstructed data, which reduces the uncertainty of FWI. This strategy avoids the effect of source wavelets uncertainty on inversion results, and avoids the simultaneously pre-process of data and wavelets. Numerical example shows that our strategy can avoid cycle-skipping effectively and can converge on a bad initial model.
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Hybrid Frequency Domain Full Waveform Inversion Using Born Sensitivity Kernels
Authors R. Djebbi and T. AlkhalifahSummaryFull Waveform inversion (FWI) using the scattering integral (SI) approach is an explicit formulation of the inversion optimization problem. The inversion equations are straightforward and the dependence on the data residuals and model parameters is clear. However, the biggest limitation with this approach is the huge computational cost for exploration seismology applications. To deal with this issue, we propose a hybrid implementation of the frequency domain FWI using the Born sensitivity kernels. Specifically, we use the sensitivity kernels computed from dynamic ray-tracing to build the gradient. We compute also the truncated Gauss-Newton update direction using the kernels without extra wavefield modeling steps. Considering that in FWI long-to-intermediate wavelengths are updated during the first iterations, using a transmission experiment
we obtain accurate inverted models. The inversion managed to develop the anomaly embedded in the homogeneous background medium. The truncated Gauss-Newton updates helped in the fast convergence. With this approach we managed to reduce the computational cost and the memory requirements. For more complex models, the hybrid inversion method help improving the initial model with little cost compared to conventional SI inversion.
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Multiscale Adaptive Full Waveform Inversion Based on the Wavelet Transform
Authors L. Bai, L.G. Han, F.J. Zhang, P. Zhang and Y. HuSummaryThe conventional full waveform inversion (FWI) is often suffered from the cycle skipping problem. In order to solve this problem, we introduced the wavelet transform to the FWI, and combined with the least squares filter in the wavelet domain. It can effectively reduce the influence of the cycle skipping problem in the inversion procedure, and improve the stability of the FWI. The least square filter has the higher accuracy in the wavelet domain than in the time domain. By using this feature we can narrow the phase difference between the predicted data and observed data, and construct a new objective function to make the inversion procedure steadily converge to the global minimum. Meanwhile, due to the multiscale characteristic of the wavelet transform, the data can be divided into different frequency bands. We could run the FWI in a multiscale way. The results from the synthetic example demonstrates that the multiscale adaptive FWI based on the wavelet transform is much less dependent on the initial model and low-frequency data. The method can also effectively reduce the cycle skipping problem and more robust than the conventional FWI.
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The Comparison between Full-stack Data and Pure P-wave Data on Deeply Buried Ordovician Paleokarst Reservoir Prediction
More LessSummaryThe present burial depth of the paleokarst reservoirs in the Tarim Basin is greater than 5000m, which premises rigorous demands for the data quality for accurate predictions. Although routinely used for reservoir prediction, the conventional full-stack data are often contaminated by the AV O (amplitude versus offset) effects no matter how much signal to noise ratio degree can be enhanced via stacking. This contamination usually changes with different geological deposits, and could reach an inappropriate and unacceptable level for the deeply buried carbonate reservoir in the Tarim Basin. In this paper, the pure P-wave data theoretically inverted through AVO effects removal are employed to improve the reservoir prediction, which are illustrated by the comparisons with that of the conventional full-stack data for the four classical AVO models and the field data in the ZG8 area, Tarim Basin. The dominant frequency has been improved for 8 Hz from 15 to 23 Hz in the target Yingshan formation, Ordovician through AVO effects removal, and the reflection events of the pure P-wave data are obviously more continuous comparing with that of the full-stack data. The fake potential reservoir caused by AVO effects in the northeast area has been removed, while the integral delineation of paleokarst reservoirs have been significantly improved with a higher fitness with the oil-testing results, which are more beneficial for later on exploration. The pure P-wave data inversion is in essence an important complement to current processing strategy.
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Flow Detection Using Well Seismic Data
Authors J.L.O. Mari and G. PorelSummaryThe aquifer studied, 20 to 130 m in depth, consists of tight karstic carbonates. 3D seismic survey revealed three high-porosity, presumably-water-productive, layers. Ambient seismic noise and VSP data have been recorded in 11 wells in order to evaluate the potential of the well seismic method to detect karstic bodies and flows, the results being compared with full waveform acoustic data, BHTV logs and flow measurements.
The paper describes the methodology developed to detect flow using both ambient noise measurement and conversion of P-wave into Stoneley waves, observed on VSP data recorded with hydrophone sensor. An attribute, named VSP flow index, has been calculated to detect both karstic levels and flows. Concerning the karstic level detection, the results obtained on 11 wells are compared with full waveform acoustic data and confirmed by BHTV logging data and at a large scale by seismic data (3D seismic). The results obtained are consistent. The VSP data have also been compared with PLT data. An attempt to obtain a VSP flow detector has been done. The conclusions of the study show that ambient noise analysis and conversion of P- body waves into Stoneley waves can be fruitfully used to detect productive levels and flow circulation.
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Well Controlling Multi-trace Seismic Deconvolution Technology
More LessSummaryConventional deconvolution methods in reducing band-limited wavelet interference often cause lateral instability of the estimated reflectivity or impedance. In addition, conventional deconvolution processing ignores the spatial relationship between traces. Spatial regularization technique can solve the problems to some extent, but there is still lack of recovery of low frequency and high frequency and ill posed problems. In this paper, based on spatial regularization, we induced logging data and proposed wells controlling multi-trace deconvolution method. A synthetic data example and a field data example are adopted to illustrate the method effectively. After processing, the seismic data resolution is improved significantly and its spatial continuity keeps well. The result has good match with low-pass filtering of logging data. The method can provide high resolution seismic data for thin reservoir prediction.
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Multi-scale Fracture Prediction Using P-wave Data - A Case Study
More LessSummaryFracture prediction is very difficult when characterizing unconventional hydrocarbon reservoirs, especially for reservoirs with different fracture scale sizes. Here, we present an integrated workflow combined with poststack and prestack seismic attributes to distinguish between fractures of different scale, which is used in a case study from a basin in China. We classify fracture scales into three categories: macro-scale, meso-scale and micro-scale. In this case study, we used poststack seismic attributes to predict the macro-scale fractures, and utilized prestack seismic inversion to determine the meso-scale fractures. Micro-scale fracture prediction is out of the range of this study. We combined the prediction results with the superimposed images of faults, verified the corresponding relation between meso-scale fractures and faults, and finally comprehensively analyzed the fracture development of the target horizon. The integrated prediction result indicates that the structure of the target horizon is mainly controlled by several major faults and meso-scale fractures are distributed along the fault zones.
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Karst Carbonate Reservoir Identification Using Frequency-dependent AVO Inversion in Tarim Basin, China
More LessSummaryThe dominate storage spaces of karst carbonate reservoir in Hadexun area, Tarim basin are dissolved pores and cavities. The influence of multi-stage structure movement makes the fluid discrimination difficult. Therefore, how to further recognise the fluid type in such reservoir is the key point. Unlike conventional post-stack methods have difficulties in fluid identification, AVOF inversion algorithm utilize P-wave dispersion property reflected by fluid to discriminate its type. Thus greatly improve the accuracy of oil exploration. In this paper, the AVOF inversion method is applied on 3D field seismic data in Hadexun area to solve the problem of fluid discrimination in karst reservoir. Field data application demonstrates that reservoirs filled up with water and hydrocarbon can be effectively separated by inverted P-wave dispersion. To be more important, by analyzing the inversion result and fault distribution, we successfully divided the faults into two groups, which are water-contained and hydrocarbon filled. In sum, the encouraging result of AVOF inversion provided robust information in karst reservoir characterization and fluid distribution, which directly offer key data for well optimization and deployment.
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Seismic Facies Characterization of the Realgrunnen Subgroup in the Wider Hoop Area, Barents Sea
Authors W. Athmer, M. Etchebes, E. Stueland, S.C. Robertson, H.G. Borgos, B.A. Tjostheim, L. Sonneland and J.R. GranliSummaryA seismic facies characterization of the Late Triassic Fruholmen Formation and the Jurassic Stø Formation —both hydrocarbon-bearing reservoir units within the Realgrunnen Subgroup in the Barents Sea—was performed to better understand reservoir facies distributions and variations in the wider Hoop area. Depositional features such as fluvial channels and associated elements were highlighted using (1) RMS amplitude maps draped onto stratal slices, and (2) colour-blended images obtained from partial reconstructions of the seismic volume reflection spectrum (VRS). Depositional thickness variations were investigated using isochore maps, and information obtained from regional well data was considered for the analysis. The study indicates a fluvial-dominated depositional system for the mid- to upper-Fruholmen Formation, and a shallow-marine environment for the overlying Stø Formation. Differences in facies thickness distributions are attributed to morphological changes that constrain the depositional environment and are related to paleo-topography, and fault activity before and during deposition of the reservoir section.
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High Precise Time-frequency Analysis Technology in Hydrocarbon Detection of the Ultra-deep Carbonate Rocks in Tarimbasin
By Q.N. DangSummaryWe present results from a case study being performed in the Ordovician ultra-deep(6500m-8100m) carbonate rocks of TB area in Tarim basin that utilizes the high precise WVD (Wigner Ville distribution) time-frequency technology to detect hydrocarbon of Ordovician carbonate rocks. Through suppressing the cross-term of WVD based on the technique of two weight window function, we obtain the high quality frequency spectrum imaging which preserves low frequency. This technology can not only characterize the boundary of the “string” of carbonate cave-fracture, but also detect the hydrocarbon in the “string”. Two sets of hydrocarbon detection criterion have been built about karst reservoir in buried hill and in interlayer. The results of hydrocarbon detection are compared with several drilled wells to confirm the validity of this technology.
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Influence of Seismic and Velocity Uncertainties on Reservoir Volume
Authors D.T. Odinsson, N. Cardozo and L. SchulteSummaryUncertainty estimation is a well-known concept in geology that can lead to re-evaluation of important development decisions if properly assessed. This study evaluates structural uncertainty through the set-up of “scenarios”. For each parameter of the structural model a low case, base case and high case are defined. The combination of these cases results in numerous structural models that deliver a distribution of the bulk volume. A generally acknowledged way of handling the large number of models coming from the different combinations of the model parameters is experimental design.
This study shows that uncertainties in seismic picks and consequently in reservoir thickness have a large impact on the gross-volume. The reservoir structural geometry controls the influence of fault uncertainty on the reservoir volume. The well velocities used for domain conversion are quite accurate but sparsely sampled and therefore also subject to uncertainty. In addition, the geologic complexity may have a dramatic influence on the uncertainty of the depth conversion. The assessment of seismic and velocity uncertainties was applied to the structural model to estimate the reservoir volume uncertainty. The results confirm that structural uncertainty is a major contributor to the hydrocarbon volume uncertainty.
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Altering the Relaxation Modulus of Crude Oil Using Pulsated Magnetic Field
By D. PandeySummaryThe aim of this technical paper is to present the idea through an experiment that magnetic field can be used as an alternative tool to change the relaxation modulus of crude oil and thus improving its transportation efficiency. During the experiment, it was found that the contact angle between crude oil and sensor probe was influenced by magnetic treatment which resulted in the prevention of wax sticking on the sensor probe. From the experiment it was confirmed that the field can also be used to prevent the wax accumulation.
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