Resolving subtle stratigraphic features using spectral ridges and phase residues

2013 ◽  
Vol 1 (1) ◽  
pp. SA93-SA108 ◽  
Author(s):  
Oswaldo Davogustto ◽  
Marcílio Castro de Matos ◽  
Carlos Cabarcas ◽  
Toan Dao ◽  
Kurt J. Marfurt
Keyword(s):  
Seismic Data ◽  
Thin Layers ◽  
Earth Model ◽  
Well Log ◽  
Anadarko Basin ◽  
Seismic Amplitude ◽  
West Texas ◽  
Amplitude Data ◽  
Using Data ◽  
Extract Information

Seismic interpretation is dependent on the quality and resolution of seismic data. Unfortunately, seismic amplitude data are often insufficient for detailed sequence stratigraphy interpretation. We reviewed a method to derive high-resolution seismic attributes based upon complex continuous wavelet transform pseudodeconvolution (PD) and phase-residue techniques. The PD method is based upon an assumption of a blocky earth model that allowed us to increase the frequency content of seismic data that, for our data, better matched the well log control. The phase-residue technique allowed us to extract information not only from thin layers but also from interference patterns such as unconformities from the seismic amplitude data. Using data from a West Texas carbonate environment, we found out how PD can be used not only to improve the seismic well ties but also to provide sharper sequence terminations. Using data from an Anadarko Basin clastic environment, we discovered how phase residues delineate incised valleys seen on the well logs that are difficult to see on vertical slices through the original seismic amplitude.

Estimating tilted fracture weaknesses from azimuthal differences in seismic amplitude data

Geophysics ◽  
2020 ◽  
Vol 85 (3) ◽  
pp. R135-R146
Author(s):  
Huaizhen Chen ◽  
Tiansheng Chen ◽  
Kristopher A. Innanen
Keyword(s):  
Reflection Coefficient ◽  
Tilt Angle ◽  
Seismic Data ◽  
Fractured Reservoirs ◽  
Transverse Isotropy ◽  
Elastic Response ◽  
Moderate Degree ◽  
Fractured Reservoir ◽  
Seismic Amplitude ◽  
Amplitude Data

Tilted transverse isotropy (TTI) provides a useful model for the elastic response of a medium containing aligned fractures with a symmetry axis oriented obliquely in the vertical and horizontal coordinate directions. Robust methods for determining the TTI properties of a medium from seismic observations to characterize fractures are sought. Azimuthal differencing of seismic amplitude data produces quantities that are particularly sensitive to TTI properties. Based on the linear slip fracture model, we express the TTI stiffness matrix in terms of the normal and tangential fracture weaknesses. Perturbing stiffness parameters to simulate an interface separating an isotropic medium and a TTI medium, we derive a linearized P-to-P reflection coefficient expression in which the influence of tilt angle and fracture weaknesses separately emerge. We formulate a Bayesian inversion approach in which amplitude differences between seismic data along two azimuths, interpreted in terms of the reflection coefficient approximation, are used to determine fracture weaknesses and tilt angle. Tests with simulated data confirm that the unknown parameter vector involving fracture weakness and tilted fracture weaknesses is stably estimated from seismic data containing a moderate degree of additive Gaussian noise. The inversion approach is applied to a field surface seismic data acquired over a fractured reservoir; from it, interpretable tilted fracture weaknesses, consistent with expected reservoir geology, are obtained. We determine that our inversion approach and the established inversion workflow can produce the properties of systems of tilted fractures stably using azimuthal seismic amplitude differences, which may add important information for characterization of fractured reservoirs.

Multispectral coherence

2018 ◽  
Vol 6 (1) ◽  
pp. T61-T69 ◽  
Author(s):  
Fangyu Li ◽  
Jie Qi ◽  
Bin Lyu ◽  
Kurt J. Marfurt
Keyword(s):  
Seismic Data ◽  
Seismic Reflection ◽  
Filter Bank ◽  
Signal To Noise Ratio ◽  
Spectral Component ◽  
Single Image ◽  
Anadarko Basin ◽  
Seismic Amplitude ◽  
Spectral Components ◽  
Structural Boundary

Seismic coherence is a routine measure of seismic reflection similarity for interpreters seeking structural boundary and discontinuity features that may be not properly highlighted on original amplitude volumes. One mostly wishes to use the broadest band seismic data for interpretation. However, because of thickness tuning effects, spectral components of specific frequencies can highlight features of certain thicknesses with higher signal-to-noise ratio than others. Seismic stratigraphic features (e.g., channels) may be buried in the full-bandwidth data, but can be “lit up” at certain spectral components. For the same reason, coherence attributes computed from spectral voice components (equivalent to a filter bank) also often provide sharper images, with the “best” component being a function of the tuning thickness and the reflector alignment across faults. Although one can corender three coherence images using red-green-blue (RGB) blending, a display of the information contained in more than three volumes in a single image is difficult. We address this problem by combining covariance matrices for each spectral component, adding them together, resulting in a “multispectral” coherence algorithm. The multispectral coherence images provide better images of channel incisement, and they are less noisy than those computed from the full bandwidth data. In addition, multispectral coherence also provides a significant advantage over RGB blended volumes. The information content from unlimited spectral voices can be combined into one volume, which is useful for a posteriori/further processing, such as color corendering display with other related attributes, such as petrophysics parameters plotted against a polychromatic color bar. We develop the value of multispectral coherence by comparing it with the RGB blended volumes and coherence computed from spectrally balanced, full-bandwidth seismic amplitude volume from a megamerge survey acquired over the Red Fork Formation of the Anadarko Basin, Oklahoma.

Techniques and best practices in multiattribute display

2015 ◽  
Vol 3 (1) ◽  
pp. B1-B23 ◽  
Author(s):  
Kurt J. Marfurt
Keyword(s):  
Central Basin ◽  
Seismic Amplitude ◽  
West Texas ◽  
3D Data ◽  
Amplitude Data ◽  
Data Volume ◽  
Similar Images ◽  
True Color ◽  
Central Basin Platform ◽  
Display Technique

All color monitors display images by mixing red, green, and blue (RGB) components. These RGB components can be defined mathematically in terms of hue, lightness, and saturation (HLS) components. A fourth alpha-blending (also called opacity) component provides a means to corender multiple images. Most, but not all, modern commercial interpretation workstation software vendors provide multiattribute display tools using an opacity model. A smaller subset of vendors provide tools to interactively display two or three attributes using HLS, CMY, and RGB color models. I evaluated a technique (or trick) to simulate the HLS color model using monochromatic color bars and only opacity. This same trick only approximates true color blending of RGB or CMY components. There are three basic objectives in choosing which attributes to display together. The first objective is to understand the correlation of one attribute to another, and most commonly, of a given attribute to the original seismic amplitude data. The second objective is to visualize the confidence or relevance of a given attribute by modulating it with a second attribute. The third objective is to provide a more integrated image of the seismic data volume by choosing attributes that are mathematically independent but correlated through the underlying geology. I developed the interpretation value of the HLS display technique on a 3D data volume acquired over the Central Basin Platform of west Texas exhibiting faults, fractures, folds, channels, pinch outs, and karst features. To be a useful “technique,” I need to demonstrate these workflows within a specific package. Although I implemented the workflow in Petrel 2014, similar images can be generated using any software with flexible opacity capabilities. I also developed a short list of attribute combinations that are particularly amenable to corendering in HLS.

Missing log data interpolation and semiautomatic seismic well ties using data matching techniques

2019 ◽  
Vol 7 (2) ◽  
pp. T347-T361 ◽  
Author(s):  
Sean Bader ◽  
Xinming Wu ◽  
Sergey Fomel
Keyword(s):  
Seismic Data ◽  
Local Similarity ◽  
Well Log ◽  
Data Set ◽  
Log Data ◽  
Data Matching ◽  
Using Data ◽  
Depth Relationship ◽  
Matching Techniques ◽  
3D Seismic Data

Relating well-log data, measured in depth, to seismic data, measured in time, typically requires estimating well-log impedance and a time-to-depth relationship using available sonic and density logs. When sonic and density logs are not available, it is challenging to incorporate wells into integrated reservoir studies because the wells cannot be tied to seismic. We have developed a workflow to estimate missing well-log information, automatically tie wells to seismic data, and generate a global well-log property volume using data matching techniques. We first used the local similarity scan to align all logs to constant geologic time and interpolate missing well-log information. Local similarity is then used to tie available wells with seismic data. Finally, log data from each well are interpolated along local seismic structures to generate global log property volumes. We use blind well tests to verify the accuracy of well-log interpolation and seismic well ties. Applying our workflow to a 3D seismic data set with 26 wells achieves consistent and verifiably accurate results.

scholarly journals Application of Artificial Neural Network in seismic reservoir characterization: a case study from Offshore Nile Delta

2021 ◽  
Author(s):  
Adel Othman ◽  
Mohamed Fathy ◽  
Islam A. Mohamed
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Seismic Data ◽  
Reservoir Characterization ◽  
Nile Delta ◽  
Reservoir Properties ◽  
Seismic Amplitude ◽  
Inversion Methods ◽  
Amplitude Data ◽  
Seismic Reservoir

AbstractThe Prediction of the reservoir characteristics from seismic amplitude data is a main challenge. Especially in the Nile Delta Basin, where the subsurface geology is complex and the reservoirs are highly heterogeneous. Modern seismic reservoir characterization methodologies are spanning around attributes analysis, deterministic and stochastic inversion methods, Amplitude Variation with Offset (AVO) interpretations, and stack rotations. These methodologies proved good outcomes in detecting the gas sand reservoirs and quantifying the reservoir properties. However, when the pre-stack seismic data is not available, most of the AVO-related inversion methods cannot be implemented. Moreover, there is no direct link between the seismic amplitude data and most of the reservoir properties, such as hydrocarbon saturation, many assumptions are imbedded and the results are questionable. Application of Artificial Neural Network (ANN) algorithms to predict the reservoir characteristics is a new emerging trend. The main advantage of the ANN algorithm over the other seismic reservoir characterization methodologies is the ability to build nonlinear relationships between the petrophysical logs and seismic data. Hence, it can be used to predict various reservoir properties in a 3D space with a reasonable amount of accuracy. We implemented the ANN method on the Sequoia gas field, Offshore Nile Delta, to predict the reservoir petrophysical properties from the seismic amplitude data. The chosen algorithm was the Probabilistic Neural Network (PNN). One well was kept apart from the analysis and used later as blind quality control to test the results.

Application of Fault Detection Using Ant-Tracking Algorithm: Daqing Oilfield Example

2012 ◽  
Vol 459 ◽  
pp. 406-410
Author(s):  
Gang Zhou ◽  
Wei Bing Lei ◽  
Jin Huan Zhang
Keyword(s):  
Fault Detection ◽  
Tracking Algorithm ◽  
Oil Reservoirs ◽  
Well Log ◽  
Powerful Method ◽  
Seismic Amplitude ◽  
Amplitude Data ◽  
Fault Interpretation

The traditional manual fault interpretation is time consuming. A powerful method for rapidly obtaining detailed fault and fracture interpretation from seismic amplitude data was proposed. It can remarkably save time during the fault interpretation task. Moreover, it can easily detect some minor faults that can not be traced manually. This method has been applied to one of Chinese oil reservoirs. The resulting interpretation, in conjunction with fracture information derived from well log measurements are illustrated.

Addressing artifacts in PP-PS registration prior to performing joint impedance inversion

2020 ◽  
Vol 39 (1) ◽  
pp. 47-52
Author(s):  
Satinder Chopra ◽  
Ritesh Kumar Sharma
Keyword(s):  
Seismic Data ◽  
The United States ◽  
Synthetic Seismograms ◽  
Data Sets ◽  
Well Log ◽  
Data Set ◽  
Anadarko Basin ◽  
Matching Process ◽  
Impedance Inversion ◽  
Integrated Interpretation

Multicomponent seismic data analysis enhances confidence in interpretation by providing mode-converted PS data for imaging the subsurface. Integrated interpretation of PP and PS data begins with the identification of reflections corresponding to similar geologic events on both data sets. This identification is accomplished by carrying out well-log correlation through the generation of PP and PS synthetic seismograms. There are a few issues associated with the approach. One of the issues is that PS data have lower resolution than PP data. This presents difficulties in the correlation of equivalent reflection events on both data sets. Even if few consistent horizons are tracked, the horizon-matching process introduces artifacts on the PS data mapped in PP time. In this paper, we elaborate on such challenges with a data set from the Anadarko Basin in the United States. We then propose a novel workflow to address the challenges.

Coherence attribute applications on seismic data in various guises — Part 1

2018 ◽  
Vol 6 (3) ◽  
pp. T521-T529 ◽  
Author(s):  
Satinder Chopra ◽  
Kurt J. Marfurt
Keyword(s):  
Seismic Data ◽  
Added Value ◽  
Karst Collapse ◽  
Additional Information ◽  
Seismic Amplitude ◽  
Input Amplitude ◽  
Amplitude Data ◽  
Decomposition Procedure ◽  
Band Spectra ◽  
Definition Of

The iconic coherence attribute is very useful for imaging geologic features such as faults, deltas, submarine canyons, karst collapse, mass-transport complexes, and more. In addition to its preconditioning, the interpretation of discrete stratigraphic features on seismic data is also limited by its bandwidth, where in general the data with higher bandwidth yield crisper features than data with lower bandwidth. Some form of spectral balancing applied to the seismic amplitude data can help in achieving such an objective so that coherence run on spectrally balanced seismic data yields a better definition of the geologic features of interest. The quality of the generated coherence attribute is also dependent in part on the algorithm used for its computation. In the eigenstructure decomposition procedure for coherence computation, spectral balancing equalizes each contribution to the covariance matrix, and thus it yields crisper features on coherence displays. There are other ways to modify the spectrum of the input data in addition to simple spectral balancing, including the amplitude-volume technique, taking the derivative of the input amplitude, spectral bluing, and thin-bed spectral inversion. We compare some of these techniques, and show their added value in seismic interpretation, which forms part of the more elaborate exercise that we had carried out. In other work, we discuss how different spectral components derived from the input seismic data allow interpretation of different scales of discontinuities, what additional information is provided by coherence computed from narrow band spectra, and the different ways to integrate them.

scholarly journals Fluid‐property discrimination with AVO: A Biot‐Gassmann perspective

Geophysics ◽  
2003 ◽  
Vol 68 (1) ◽  
pp. 29-39 ◽  
Author(s):  
Brian H. Russell ◽  
Ken Hedlin ◽  
Fred J. Hilterman ◽  
Lawrence R. Lines
Keyword(s):  
Seismic Data ◽  
Rock Physics ◽  
Well Log ◽  
Eastern Canada ◽  
Shallow Gas ◽  
Shear Moduli ◽  
Seismic Amplitude ◽  
Amplitude Inversion ◽  
Avo Inversion ◽  
Fluid Factor

This analysis draws together basic rock physics, amplitude variations with offset (AVO), and seismic amplitude inversion to discuss how fluid‐factor discrimination can be performed using prestack seismic data. From both Biot and Gassmann theories for porous, fluid‐saturated rocks, a general formula is first derived for fluid‐factor discrimination given that both the P and S impedances are available. In essence, the two impedances are transformed so that they better differentiate between the fluid and rock matrix of the porous medium. This formula provides a more sensitive discriminator of the pore‐fluid saturant than the acoustic impedance and is especially applicable in hard‐rock environments. The formulation can be expressed with either the Lamé constants and density, or the bulk and shear moduli and density. Numerical and well‐log examples illustrate the applicability of this approach. AVO inversion results are then incorporated to show how this method can be implemented using prestack seismic data. Finally, a shallow gas‐sand example from Alberta and a well‐log example from eastern Canada are shown to illustrate the technique.

scholarly journals Use of Seismic Spectral Decomposition, Phase, and Relative Geologic Age as Attributes to Improve Quantitative Porosity Prediction in the Daqing Field, China

2021 ◽  
Vol 11 (17) ◽  
pp. 8034
Author(s):  
David Mora Calderon ◽  
John P. Castagna ◽  
Ramses Meza ◽  
Shumin Chen ◽  
Renqi Jiang
Keyword(s):  
Seismic Data ◽  
Spectral Decomposition ◽  
Reservoir Characterization ◽  
Effective Porosity ◽  
Thin Layers ◽  
Rock Properties ◽  
Seismic Amplitude ◽  
Attribute Analysis ◽  
Stratigraphic Position ◽  
Phase Amplitude

The high production potential of the Daqing oilfield in China is recognized for seismically thin sand bodies that usually are not resolved with conventional seismic data. The present study assesses the usefulness of applying seismic multi-attribute analysis to bandwidth extended data in resolving and making inferences about these thin layers. In thin layers, tuning can obscure relationships between seismic amplitude and rock properties. In such cases, the seismic phase varies with the layer impedance and may hence aid in reservoir characterization. A seismically derived relative geologic age may also be a useful attribute in predicting rock properties because it helps define the stratigraphic position of a layer. When utilized in multi-attribute analysis in the Daqing field, spectral decomposition amplitude, phase, and a relative geological age attribute to improved prediction of well log effective porosity from seismic data and are preferentially selected by stepwise regression. The study follows standard methodology by implementing seismic multi-attribute analysis and discusses the improvement of applying it to bandwidth extended data. This will include a combination of attributes such as relative geologic age, phase, amplitude, and the magnitude components of spectrally decomposed data.

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