On the value of 3D seismic amplitude data to reduce uncertainty in the forecast of reservoir production

2006 ◽  
Vol 50 (3-4) ◽  
pp. 269-284 ◽  
Author(s):  
Omar J. Varela ◽  
Carlos Torres-Verdín ◽  
Larry W. Lake
Keyword(s):  
3D Seismic ◽  
Seismic Amplitude ◽  
Amplitude Data

Seismic attributes and structural interpretation—it takes two to tango...

2012 ◽  
Vol 52 (1) ◽  
pp. 437 ◽  
Author(s):  
Guillaume Backé ◽  
Ernest Swierczek ◽  
Justin MacDonald ◽  
Adam Bailey ◽  
David Tassone ◽  
...  
Keyword(s):  
Structural Information ◽  
Median Filter ◽  
Seismic Attributes ◽  
3D Seismic ◽  
Seismic Amplitude ◽  
The North ◽  
Amplitude Data ◽  
Fracture Models ◽  
Processing Techniques

In this paper, different 3D seismic attributes calculated to improve the accuracy and robustness of structural interpretations in several energy-rich Australian basins are compared. Detailed and precise fault and fracture maps are crucial not only for initial petroleum play assessment, but also for fault seal analysis and reservoir integrity studies. Robust fault and fracture models are also needed to improve the design of reservoir simulation programs and to manage the long-term containment of gas in geological formations. Different attributes (including coherency, dip-steered similarity, dip-steered median filter, dip-steered variance, apparent dip, and dip-steered most-positive and most-negative curvatures) from an array of 3D seismic datasets to better image structural fabrics, such as normal and different fractures patterns, in the North Perth, Cooper, Ceduna, Otway and Gippsland basins have been calculated. The results provide a remarkable improvement in the quality and precision of structural maps using this multi-attribute mapping workflow by comparison with more conventional maps produced, solely using seismic amplitude data. The key to the successful application of multi-attribute structural analysis, however, remains with the ability of the interpreter to identify meaningful structural information from a large volume of data. Thus, the structural expertise of the interpreter remains as the cornerstone to making geological sense of the various seismic processing techniques available.

Unsupervised machine learning using 3D seismic data applied to reservoir evaluation and rock type identification

2021 ◽  
pp. 1-69
Author(s):  
Marwa Hussein ◽  
Robert R. Stewart ◽  
Deborah Sacrey ◽  
Jonny Wu ◽  
Rajas Athale
Keyword(s):  
Machine Learning ◽  
Seismic Data ◽  
Rock Type ◽  
Seismic Attributes ◽  
Reservoir Quality ◽  
3D Seismic ◽  
Reservoir Properties ◽  
Unsupervised Machine Learning ◽  
Amplitude Data ◽  
3D Seismic Data

Net reservoir discrimination and rock type identification play vital roles in determining reservoir quality, distribution, and identification of stratigraphic baffles for optimizing drilling plans and economic petroleum recovery. Although it is challenging to discriminate small changes in reservoir properties or identify thin stratigraphic barriers below seismic resolution from conventional seismic amplitude data, we have found that seismic attributes aid in defining the reservoir architecture, properties, and stratigraphic baffles. However, analyzing numerous individual attributes is a time-consuming process and may have limitations for revealing small petrophysical changes within a reservoir. Using the Maui 3D seismic data acquired in offshore Taranaki Basin, New Zealand, we generate typical instantaneous and spectral decomposition seismic attributes that are sensitive to lithologic variations and changes in reservoir properties. Using the most common petrophysical and rock typing classification methods, the rock quality and heterogeneity of the C1 Sand reservoir are studied for four wells located within the 3D seismic volume. We find that integrating the geologic content of a combination of eight spectral instantaneous attribute volumes using an unsupervised machine-learning algorithm (self-organizing maps [SOMs]) results in a classification volume that can highlight reservoir distribution and identify stratigraphic baffles by correlating the SOM clusters with discrete net reservoir and flow-unit logs. We find that SOM classification of natural clusters of multiattribute samples in the attribute space is sensitive to subtle changes within the reservoir’s petrophysical properties. We find that SOM clusters appear to be more sensitive to porosity variations compared with lithologic changes within the reservoir. Thus, this method helps us to understand reservoir quality and heterogeneity in addition to illuminating thin reservoirs and stratigraphic baffles.

REDUCING RESOURCE UNCERTAINTY USING SEISMIC AMPLITUDE ANALYSIS ON THE SOUTHERN RANKIN TREND, NORTHWEST AUSTRALIA

1999 ◽  
Vol 39 (1) ◽  
pp. 128 ◽  
Author(s):  
D. Sibley ◽  
F. Herkenhoff ◽  
D. Criddle ◽  
M. McLerie
Keyword(s):  
Seismic Attributes ◽  
3D Seismic ◽  
Amplitude Analysis ◽  
Seismic Amplitude ◽  
Amplitude Versus Offset ◽  
Minimum Number ◽  
Gas Fields ◽  
Resource Uncertainty

Between 1973 and 1996 West Australian Petroleum Pty Limited (WAPET) discovered five major gas fields on the southern Rankin Trend including Spar, West Tryal Rocks, Gorgon, Chrysaor, and Dionysus (collectively termed the Greater Gorgon Resource). Recent discoveries at Chrysaor and Dionysus emphasise the role of subtle 3D seismic attributes in finding hydrocarbons and defining reserves with a minimum number of wells.The Gorgon, Chrysaor, and Dionysus fields were covered by 3D seismic data shot in 1991 and 1995, which led WAPET to discover Chrysaor and later Dionysus. Subsequent to the 3D acquisitions, field reservoirs have been correlated with anomalous seismic events (seismic amplitude and amplitude versus offset) that conform to depth structure. Follow-up work has shown that combining these 3D seismic attributes improves the prediction of wet sands, gas sands, and other lithologies.The resulting understanding and confidence provided by this 3D seismic has driven an aggressive exploration program and defined field reserves at a high confidence level. Results include the recent award of permit area WA-267-P to WAPET and the ongoing studies to begin development of the Greater Gorgon Resource.

Noise suppression in 2D and 3D seismic data with data-driven sifting algorithms

Geophysics ◽  
2019 ◽  
Vol 85 (1) ◽  
pp. V1-V10
Author(s):  
Julián L. Gómez ◽  
Danilo R. Velis ◽  
Juan I. Sabbione
Keyword(s):  
Seismic Data ◽  
Noise Suppression ◽  
Department Of Energy ◽  
Time Slice ◽  
3D Seismic ◽  
Coherent Noise ◽  
Data Set ◽  
Amplitude Data ◽  
3D Volume ◽  
2D And 3D

We have developed an empirical-mode decomposition (EMD) algorithm for effective suppression of random and coherent noise in 2D and 3D seismic amplitude data. Unlike other EMD-based methods for seismic data processing, our approach does not involve the time direction in the computation of the signal envelopes needed for the iterative sifting process. Instead, we apply the sifting algorithm spatially in the inline-crossline plane. At each time slice, we calculate the upper and lower signal envelopes by means of a filter whose length is adapted dynamically at each sifting iteration according to the spatial distribution of the extrema. The denoising of a 3D volume is achieved by removing the most oscillating modes of each time slice from the noisy data. We determine the performance of the algorithm by using three public-domain poststack field data sets: one 2D line of the well-known Alaska 2D data set, available from the US Geological Survey; a subset of the Penobscot 3D volume acquired offshore by the Nova Scotia Department of Energy, Canada; and a subset of the Stratton 3D land data from South Texas, available from the Bureau of Economic Geology at the University of Texas at Austin. The results indicate that random and coherent noise, such as footprint signatures, can be mitigated satisfactorily, enhancing the reflectors with negligible signal leakage in most cases. Our method, called empirical-mode filtering (EMF), yields improved results compared to other 2D and 3D techniques, such as [Formula: see text] EMD filter, [Formula: see text] deconvolution, and [Formula: see text]-[Formula: see text]-[Formula: see text] adaptive prediction filtering. EMF exploits the flexibility of EMD on seismic data and is presented as an efficient and easy-to-apply alternative for denoising seismic data with mild to moderate structural complexity.

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.

Amplitude and frequency anomalies in regional 3D seismic data surrounding the Mallik 5L-38 research site, Mackenzie Delta, Northwest Territories, Canada

Geophysics ◽  
2006 ◽  
Vol 71 (6) ◽  
pp. B183-B191 ◽  
Author(s):  
M. Riedel ◽  
G. Bellefleur ◽  
S. R. Dallimore ◽  
A. Taylor ◽  
J. F. Wright
Keyword(s):  
Northwest Territories ◽  
Gas Hydrate ◽  
Seismic Data ◽  
Ratio Method ◽  
Unfrozen Water ◽  
3D Seismic ◽  
Mackenzie Delta ◽  
Data Set ◽  
Seismic Amplitude ◽  
3D Seismic Data

Amplitude and frequency anomalies associated with lakes and drainage systems were observed in a 3D seismic data set acquired in the Mallik area, Mackenzie Delta, Northwest Territories, Canada. The site is characterized by large gas hydrate deposits inferred from well-log analyses and coring. Regional interpretation of the gas hydrate occurrences is mainly based on seismic amplitude anomalies, such as brightening or blanking of seismic energy. Thus, the scope of this research is to understand the nature of the amplitude behavior in the seismic data. We have therefore analyzed the 3D seismic data to define areas with amplitude reduction due to contamination from lakes and channels and to distinguish them from areas where amplitude blanking may be a geologic signal. We have used the spectral ratio method to define attenuation (Q) over different areas in the 3D volume and subsequently applied Q-compensation to attenuate lateral variations ofdispersive absorption. Underneath larger lakes, seismic amplitude is reduced and the frequency content is reduced to [Formula: see text], which is half the original bandwidth. Traces with source-receiver pairs located inside of lakes show an attenuation factor Q of [Formula: see text], approximately half of that obtained for source-receiver pairs situated on deep, continuous permafrost outside of lakes. Deeper reflections occasionally identified underneath lakes show low-velocity-related pull-down. The vertical extent of the washout zones is enhanced by acquisition with limited offsets and from processing parameters such as harsh mute functions to reduce noise from surface waves. The strong attenuation and seismic pull-down may indicate the presence of unfrozen water in deeper lakes and unfrozen pore water within the sediments underlying the lakes. Thus, the blanking underneath lakes is not necessarily related to gas migration or other in situ changes in physical properties potentially associated with the presence of gas hydrate.

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