Pre-stack Gathers Research Articles

Rock-physics modeling and pre-stack seismic inversion for the Cambrian superdeep dolomite reservoirs in Tarim Basin, Northwest China

The Cambrian superdeep dolomite in Tarim Basin has great resource potentialities. However, the superdeep dolomite reservoirs have the seismogeological characteristics of deep burial, low porosity and permeability, complex fracture networks and low signal-to-noise, which cannot support the efficient exploration and development of superdeep dolomite reservoir due to restricting the precision of fracture prediction. The fractures and pores compose the main storage spaces of superdeep dolomite reservoir. To better characterize the superior reservoir of superdeep dolomite with complex fracture, we first describe the properties of dolomite using core data, which illustrates that the low-porosity and low-permeability dolomite reservoirs have three tendencies: relatively higher porosity and lower permeability, relatively lower porosity and lower permeability, and relatively lower porosity and higher permeability. The development of porosity is decided by the size of dolomite particle, and when the porosity is greater, the pore type controls the permeability of the reservoir. It is difficult to effectively characterize dolomite with multiple types fractures and pores with the traditional rock physical analysis. Considering the influence of complex pore structures on the elastic parameters of superdeep dolomites, we propose a fracture characterization indicator (FCI) based on Biot theory. We test the FCI using cores and well-logging data, which can quantitatively describe the change of pores in dolomite reservoirs, much better than conventional rock-physics modeling. Meanwhile, the pre-stack seismic gather optimization process is established to employ the combination of denoising and flattening. The density indicator (DI) is proposed due to the poor result of density inversion. The priority distributions of superdeep dolomite reservoirs are revealed through the FCI and DI applied to 3D pre-stack seismic inversions. The results are consistent with those by actual drilling, which confirms that the proposed method can serve as a new way to predict superdeep dolomite reservoirs.

Seismic deconvolution based on SNR-weighted stacking

We propose a seismic deconvolution algorithm based on signal-to-noise ratio (SNR)-weighted stacking. First, we applied the time-frequency analysis to decompose the common midpoint (CMP) or common reflection point (CRP) gather. It is considered that there are differences in noise between different traces in the frequency domain profile. Then, we employ an SNR-weighted stacking strategy in each frequency-domain profile. Finally, we construct the resolution-enhancement amplitude spectrum, apply a linear inversion approach to calculate the overall weights of each frequency-domain profile, perform weighted stacking between the frequency-domain profiles, and obtain the resolution-enhancement post-stack data. The frequency decomposition of the pre-stack gather is efficiently utilized for the primary data of the proposed method. The SNR-weighted stacking adaptively selects the components with high SNR at each frequency. In addition, the resolution-oriented stacking weights are determined by the linear inversion approach. This algorithm can be adaptively weighted by considering the SNR of each frequency component, which can effectively overcome the problem of low SNR in spectral simulation and obtain high-resolution seismic data. The algorithm does not include wavelet extraction and regularization; thus, the resolution-enhancement data is more reliable. Applications to synthetic and field seismic datasets demonstrate that the proposed resolution-enhancement methodology is of great benefit to the succeeding structural interpretation and thin-bed identification.

An integrated workflow for pre-stack gather optimization

Abstract High-quality seismic data contribute to improving the prediction accuracy of complex reservoirs. Currently, there are several methods for enhancing pre-stack gather resolution and signal-to-noise ratio (SNR). Meanwhile, to avoid incorrect seismic interpretation, we must evaluate whether the processed data maintains its original characteristics and reliability. This paper establishes an integrated workflow for optimizing common-reflection-point (CRP) gather that is divided into processing and quality control. Furthermore, we summarize the comprehensive quality control means and explain their specific significance in each step. Data processing includes four parts: gather flattening, SNR enhancement, energy compensation, and resolution improvement. Simultaneously, we use well log data, forward simulation, stack data, and inversion to guarantee the processed data is optimized and keeps its original characteristics. Applications in carbonate reservoir CRP gathers demonstrate that this workflow can comprehensively optimize pre-stack seismic data and improve SNR and resolution. Importantly, the quality controls guarantee results have improved accuracy in reservoir prediction and stronger correlation coefficients with well data.

Oil and gas prediction basing on seismic inversion of elastic properties in Chaoshan depression, south China sea

The marine Mesozoic is widely distributed in the northeastern waters of the South China Sea and is an important field for oil-gas exploration in the South China Sea. The Chaoshan Depression is the largest residual depression in this sea. At a previous well, LF35-1-1, no oil and gas have been discovered with then pre-drilling prediction techniques. Post-drill analysis shows that the physical properties of the Mesozoic reservoir are not favorable there. So, in accurate prediction of the oil-gas reservoirs is necessary. Since the drilling at the LF35-1-1, extensive surveys and studies have been carried out which shows a number of favorable trapping structures. In the middle low bulge of the Chaoshan Depression, the DS-A structures found with potential reservoirs, complete trap structures, and dual source hydrocarbon supply on both sides, making it the most favorable zone for oil-gas accumulation. We apply the state of art prediction techniques for it using pre-stack seismic raw gather. The sensitivity analysis results of reservoir physical properties indicate that the difference in P- wave velocity between sand and mudstone is 500 m/s, the difference in density is 0.02 g/cm3, and the Poisson’s ratio ranges between 0.11 and 0.33. The Mesozoic sandstone reservoirs in the Chaoshan Depression have characteristics of high velocity and low Poisson’s ratio, and the P-wave velocity, density, and Poisson’s ratio are the main sensitive parameters for predicting reservoir and its oil-gas bearing properties. The density inversion, P-wave impedance inversion, and S-wave impedance inversion jointly characterize the “wedge-shaped” sand body in the DS-A structural area, with a maximum thickness of over 400 m and an area of ∼130 km2. The overlap of the sand body contour map and Poisson’s ratio inversion results indicates that the “wedge-shaped” sand body is an oil-gas bearing sand body. It can be concluded that pre-stack elastic parameter inversion is an effective method for reservoir prediction in deep-sea no-well exploration areas. It has the characteristics of high signal-to-noise ratio, strong stability and reliability, and high accuracy, which is conducive to reduce the non-uniqueness and uncertainty of seismic inversion. The inversion results predict that the DS-A structure is an oil-gas bearing structure.

Characterization of natural fractures in tight sandstone reservoirs in Yuanba area, northern Sichuan Basin

Natural fractures are quite important for the high and stable production of tight sandstone gas reservoirs. However, it is commonly difficult to accurately characterize their distribution in tight sandstone gas reservoirs due to the strong heterogeneity. A comprehensive characterization of natural fractures in tight sandstone gas reservoirs of the Xujiahe Formation in the Yuanba area, Sichuan Basin, was carried out by multimethod of core description, log interpretation and seismic prediction. The results show that (1) the natural fractures in the Xujiahe Formation are mainly low-angle fractures, with a few medium- and high-angle fractures. The degree of fracture development is mainly controlled by the distance from the fault, the flexural degree of the strata and the thickness of the rock mechanical layer. (2) The fracture-sensitive seismic attributes such as the preferred maximum likelihood, structure entropy, illuminant-based symmetry and high-precision curvature are taken as the input, and the unsupervised cluster analysis algorithm based on Bayesian probability model is applied to predict the distribution of large-scale fractures at different dip angles; on the basis of narrow azimuthal pre-stack CMP gather optimization, the anisotropy detection technique of Hampson-Russell's ProAZ full CMP gather is used to characterize the distribution of small- and medium-scale fractures, and the predicted fracture development intensity matches the fracture interpretation results of the imaging logs by more than 85%. Moreover, the predicted fracture orientation is basically consistent with that of the imaging loggings. (3) The fault-genesis fractures of the Xujiahe Formation are mainly distributed near the fault on the southeast flank of the Jiulongshan anticline, and are distributed in a narrow strip in NE direction. The fold-genesis fractures are mainly developed in the Xu 3rd Member, and are located in the axis of the Jiulongshan anticline and its southeast flank where the strata are strongly flexed. This study provides a solid foundation for the development of tight sandstone gas reservoirs and extends the approaches for the accurate characterization of fractures.

Inversion-based pre-stack gather flattening by exploiting temporal sparsity

This paper addresses the problem of flattening the events on pre-stack seismic gathers. Undesirable non-flat events induced by inaccurate normal moveout and static correction inevitably degrade the reliability of reservoir prediction. The typical methods based on dynamic time warping (DTW) are sample-by-sample procedures, distorting the seismic waveforms resulting from the locally non-sensible matchings. We observe that the multichannel reflectivity gathers are inherently temporally sparse and spatially correlated impulse sequences and can be aligned precisely. Hence, we propose an inversion-based gather flattening method based on sparse representation (SR) and DTW, which can substantially reduce waveform distortions and pathological alignments. A novel SR algorithm, iteratively reweighted L1−2-L1-norm minimization (IR-L1−2-L1), is proposed for improved robustness to outliers and better handling of highly coherent dictionaries. Given a dictionary constructed with a seismic wavelet as the basis function, we can invert the reflectivity patterns of seismic gathers via IR-L1−2-L1. The obtained multichannel offset-dependent reflectivity traces, rather than the seismic seismograms, are flattened by an improved alignment algorithm: smooth shape dynamic time warping (SSDTW), which enhances DTW by a few structural modifications to the prototype. Finally, the flat gathers can be reconstructed by the matrix multiplication of the dictionary and reflectivity gathers. Both synthetic and practical applications indicate that our algorithm yields more flat events and improved lateral continuity while separating random noise and outliers.

RESERVOIR CHARACTERIZATION USING SIMULTANEOUS INVERSION TO DELINEATE HYDROCARBON RESERVOIR

Reservoir characterization analysis has been carried out for identifying lithology and Àuid content on TalangAkarFormation in South Sumatra Basin. Robust method that being used in this study is the simultaneous inversion which uses pre-stack gather and well log data from Puja A and Puja B. Elastic parameters resulted from simultaneous inversion are P Impedance, S Impedance and V / V ratio. Lambda-Rho parameter (lr) and Mu-Rho (mr) derived from P impedance (I ) and S impedance (I ). Lambda-Rho is sensitive to Àuid content while Mu-Rho to lithology. Area of interest in this study is Talang Akar Formation as reservoir which contains gas with Lambda-Rho (lr) between 5-15 (GPa*g/cc) and Mu-Rho (mr) 35-45 (GPa*g/cc). The ratio of P wave (Vp) and S wave (Vs) can be used as an indicator to determine Àuid saturation. Gas saturated rock has value of Vp / Vs lower than the water saturated rock. In this study, the ratio of Vp / Vs is 1.5-1.7 for gas saturated rock

Inversion-Based Pre-Stack Gather Flattening by Exploiting Temporal Sparsity

Inversion-Based Pre-Stack Gather Flattening by Exploiting Temporal Sparsity

Automatic Velocity Picking Using a Multi-Information Fusion Deep Semantic Segmentation Network

Velocity picking, a critical step in seismic data processing, has been studied for decades. Although manual picking can produce accurate normal moveout (NMO) velocities from the velocity spectra of prestack gathers, it is time-consuming and becomes infeasible with the emergence of large amount of seismic data. Numerous automatic velocity picking methods have thus been developed. In recent years, deep learning (DL) methods have produced good results on the seismic data with medium and high signal-to-noise ratios (SNR). Unfortunately, it still lacks a picking method to automatically generate accurate velocities in the situations of low SNR. In this paper, we propose a multi-information fusion network (MIFN) to estimate stacking velocity from the fusion information of velocity spectra and stack gather segments (SGS). In particular, we transform the velocity picking problem into a semantic segmentation problem based on the velocity spectrum images. Meanwhile, the information provided by SGS is used as a prior in the network to assist segmentation. The experimental results on two field datasets show that the picking results of MIFN are stable and accurate for the scenarios with medium and high SNR, and it also performs well in low SNR scenarios.

Study on the Velocity Analysis Method of Low SNR Seismic Data

When the signal to noise ratio of seismic data is very low, velocity spectrum focusing will be poor., the velocity model obtained by conventional velocity analysis methods is not accurate enough, which results in inaccurate migration. For the low signal noise ratio (SNR) data, this paper proposes to use partial Common Reflection Surface (CRS) stack to build CRS gathers, making full use of all of the reflection information of the first Fresnel zone, and improves the signal to noise ratio of pre-stack gathers by increasing the number of folds. In consideration of the CRS parameters of the zero-offset rays emitted angle and normal wave front curvature radius are searched on zero offset profile, we use ellipse evolving stacking to improve the zero offset section quality, in order to improve the reliability of CRS parameters. After CRS gathers are obtained, we use principal component analysis (PCA) approach to do velocity analysis, which improves the noise immunity of velocity analysis. Models and actual data results demonstrate the effectiveness of this method.

Oriented pre-stack inverse Q filtering for resolution enhancements of seismic data

SUMMARY Seismic attenuation is one of the main factors responsible for degradation of the resolution of seismic data. During seismic wave propagation in attenuation medium, the energy of signal components seriously decreases, especially those with higher frequencies. The seismic attenuation and resolution reduction are generally compensated for with inverse Q filtering in the frequency or time domain. However, the implementation of pre-stack inverse Q filtering is challenging because the traveltime in each layer is not easy to obtain for the pre-stack seismic gather, unless the accurate velocity model is known. In this study, we propose an inverse Q filtering method for the pre-stack seismic gather that uses the local slope and warped mapping to determine the propagation path, and Taylor-expansion-based division is used to stabilize the inversion. The local slope can determine the reflection events with the same ray path, and the inverse warped mapping can transform the attenuation factor from the ${t_0} - p$ (zero-offset traveltime to ray parameter) domain to the $t - x$ (traveltime and offset) domain. The attenuation factor in the ${t_0} - p$ domain is easy to calculate because the traveltimes and Q values in each layer are known. The proposed oriented pre-stack inverse Q filtering method is velocity-independent and suitable for a depth varying Q model. The synthetic and real data examples demonstrated that the method can effectively correct the attenuation and dispersion of seismic waves, and can obtain pre-stack seismic gathers with high resolution.

Pre-stack gather optimization technology based on an improved bidimensional empirical mode decomposition method

This study proposes a pre-stack gather optimization technique based on the improved BEMD (bidimensional empirical mode decomposition) method with high stability and adaptability. An original gather signal was decomposed into different components with varying characteristics by the BEMD method, which combines morphological extremum point extraction and the bicubic spline interpolation method to obtain different-scale component signals. Then, wavelet threshold orthogonal filter was used to process the components, which correspond to noise, mostly in small-scale domain. Finally, correlation weighting reconstruction was performed on each component. The weight coefficient is determined according to the relationship between each component of the amplitude-preserving superposition gather and the original gather-preserving superposition gather. The testes on the data from Northeast Sichuan confirm that the method can optimize the pre-stack gather steadily and efficiently. The comparison of the AVO analysis results before and after optimization shows that the method is effective and feasible, which lays a good foundation for a prediction method based on pre-stack data.

A physical modelling study of the reservoir scale effect on amplitude variation with incidence angle

Abstract The 3D pre-stack seismic data from a physical modeling experiment were employed to investigate the effect of reservoir scales on AVO (amplitude variation with offset or incidence angle). Eight cuboid samples simulating cavernous reservoirs with different widths and the same thickness and elastic parameters were set within a 3D model. 3D seismic data acquisition and processing were conducted. To get the AVO responses of the samples with different widths, trough amplitudes corresponding to the sample tops at different incidence angles were extracted from the pre-stack angle gathers. Amplitude calibration for transducer radiation patterns was conducted on the extracted amplitudes at different angles. AVO analysis was conducted to quantitatively demonstrate the effect of sample scales on AVO characteristics. The effect of sample width was weak when the width was less than 60 m, which was 3/5 of the wavelength. When the width was larger than 60 m, both AVO intercept and gradient gradually increased with the sample width. The AVO gradient peaked at 150 m, which was 1.5 times the wavelength. Cross-plot analysis of AVO intercept and gradient showed the samples were aligned in a straight line when the sample width was less than twice the seismic wavelength. The result in this study partially verified the conclusions of reservoir scale effect on AVO responses drawn from previous numerical modelling studies. For a heterogeneous rectangular reservoir, the effect of reservoir scales on AVO responses could potentially be used to quantitatively estimate reservoir scale.

FK-filter and radon transform methods comparative study on 2D pre-stack migration gather of Kangean Waters data

The main problem in marine seismic exploration are multiples. Multiple is coherent noise appeared by the difference of impedance between water and seabed layer which is lead to secondary reflection wave acts as new reflector source point. Multiple appearance in seismic cross section can cause misinterpretation so multiple attenuation is required. Both F-K Filter and Radon Transform methods can be used to attenuate multiple by isolating signal and noise data. Both methods have similarity in domain transform, F-K Filter transforms offset (x) - time (t) domain to frequency (f) - wavenumber (K) and Radon Transform operates in τ-ρ domain to separate moveout between signal and noise. Both mehods are applied on 2D marine seismic data on Kangean waters shallow depth 200-500 meter. Radon Transform shows better result on attenuating multiple compare to F-K Filter on migrated cross section line L09 and L16. Multiple attenuation increases signal to ratio (SNR) of both line L09 and L16 which lead to more accurate in interpretation.

Remove the moveout of azimuth anisotropy based on difference

In order to improve the imaging quality of seismic profile, a new method based on difference is proposed to eliminate the azimuthal moveout. Test results shows that the resolution of the model and real data have been improved significantly in both the prestack gather and the stack profile. The new method proposed is valid and implemented simply.

Methods for source rock identification on seismic data: An example from the Tanezzuft Formation (Tunisia)

Source rocks occurrence, extension and quality in the subsurface are usually characterized directly from well data. Seismic characterization is however becoming an emerging technique for extending source rock properties beyond well locations and an effective tool for mapping their lateral and vertical heterogeneities. The Tanezzuft Formation in Tunisia, an extremely organic-rich source rock, was used as a test for applying and comparing different seismic methods aimed at organic-rich sequences characterization. The data used consist of a 2D seismic line shot in the northern flank of the Ghadames Basin (Tunisia), pre-stack gathers extracted from an inline of a 3D survey and four wells with a complete set of wireline and petrophysical logs. Impedance inversion, AVO and seismic attributes were computed on the seismic lines and compared to well data. Impedance inversion together with a rock physics model of the formation generated a quantitative estimate of total organic carbon (TOC) content in the studied 2D seismic line. AVO analysis showed a Class IV and a Base Class IV response for the upper and lower reflectors delimiting the organic-rich interval respectively. Seismic attributes analyzed the formation by exploiting its high impedance contrast and intrinsic anelastic attenuation. The three methods here discussed showed coherent results both when compared each other and when compared with the well data and the regional geological model. In particular, AVO and seismic attribute analysis are methods that can be applied without the need of well information, and are then feasible methods for the investigation of source rock properties in undrilled basins.

Numerical simulation of bubble plumes and an analysis of their seismic attributes

To study the bubble plume’s seismic response characteristics, the model of a plume water body has been built in this article using the bubble-contained medium acoustic velocity model and the stochastic medium theory based on an analysis of both the acoustic characteristics of a bubble-contained water body and the actual features of a plume. The finite difference method is used for forward modelling, and the single-shot seismic record exhibits the characteristics of a scattered wave field generated by a plume. A meaningful conclusion is obtained by extracting seismic attributes from the pre-stack shot gather record of a plume. The values of the amplitude-related seismic attributes increase greatly as the bubble content goes up, and changes in bubble radius will not cause seismic attributes to change, which is primarily observed because the bubble content has a strong impact on the plume’s acoustic velocity, while the bubble radius has a weak impact on the acoustic velocity. The above conclusion provides a theoretical reference for identifying hydrate plumes using seismic methods and contributes to further study on hydrate decomposition and migration, as well as on distribution of the methane bubble in seawater.

Target-oriented data conditioning for prestack inversion in an unconventional reservoir: A Canadian case study

Target-oriented data conditioning is a key part of any reservoir characterization workflow. Data conditioning is used to optimize the match between the synthetic data, used in the prestack inversion, and the real data. When this is done correctly, the accuracy and confidence of inversion results may be greatly improved. This is proved on prestack seismic inversion results from a resource play in Canada. The flow is broken down into prestack gather conditioning, which improves the signal-to-noise and gather flatness, and poststack conditioning, which further improves the coherency prior to applying spectral balancing. As a final key step, spatially variant amplitude balancing is used to calibrate the angle stacks to the expected background trend from the well synthetics. The combination of all steps is demonstrated via [Formula: see text] and mu-rho versus lambda-rho crossplots, between the inverted results and the well measurements, to provide a significant improvement on the resolution and accuracy of the final prestack inversion.

Prediction of tectonically deformed coal based on lithologic seismic information

Owing to the differences in physical properties between tectonically deformed coal (TDC) and primary coal, lithologic seismic inversion methods were adopted to identify the coal structure type, including probabilistic neural network (PNN) inversion, elastic impedance (EI) inversion and simultaneous inversion methods. Based on poststack and prestack gathers, the inversion methods were applied to calculate lithologic seismic information, which included porosity, acoustic impedance, elastic impedance, λ×ρ and μ×ρ data. The inversion results were then analysed to evaluate the development potential of TDC. The research showed that the lithology inversion results, which indicated the potential zone of development areas of the coal, were all basically identical and a comprehensive prediction factor (the linear lithologic information combination) was proposed to effectively predict the development potential. Therefore, the prediction of TDC by lithologic seismic information could provide a scientific basis for both coal mining safety and the development potential of large-scale coalbed methane resources.

Imaging complexity in the Earth - Case studies with optimised ray tomography

SUMMARY In the past 10 years, the resolution of tomographic solutions has seen a continuous increase because of evolving sophistication in methodologies and technology. A vital issue in the data domain is accuracy and density of residual move-out picks that are used to derive tomographic velocity-model updates. A new automated method allows for precise tracking of accurate residual move-out on pre-stack depth-migrated gathers and consequently the fast determination of dense, high quality travel time residuals for seismic tomography. The determination of small-scale anomalies ultimately leads to flatter pre-stack depth-migrated gathers and consequently better-focused structural images.