The use of geologic expression workflows for basin scale reconnaissance: A case study from the Exmouth Subbasin, North Carnarvon Basin, northwestern Australia

2014 ◽  
Vol 2 (1) ◽  
pp. SA163-SA177 ◽  
Author(s):  
N. J. McArdle ◽  
D. Iacopini ◽  
M. A. KunleDare ◽  
G. S. Paton
Keyword(s):  
Seismic Data ◽  
Regional Scale ◽  
Normal Fault ◽  
Seismic Attributes ◽  
Data Sets ◽  
Seismic Attribute ◽  
Data Set ◽  
Attribute Analysis ◽  
Basin Scale ◽  
Northwestern Australia

The focus of this study is to demonstrate how seismic attributes can be used in the interpretation workflow to rapidly obtain a high-resolution view of the geology that is imaged within a seismic data set. To demonstrate the efficacy of seismic attribute analysis to basin scale reconnaissance, we apply a workflow to seismic data sets from the Exmouth Subbasin, northwestern Australia, with the aim of determining the geologic expression of the subsurface. Of specific interest are Barrow Group Jurassic and Cretaceous fluvial and marine sediments, that were faulted during the Jurassic-Cretaceous rifting associated with the breakup of East Gondwana. Regional-scale interpretations are made to develop a tectonostratigraphic context to the investigation. Target-level analyses, focused on features of exploration interest identified using regional reconnaissance, are made to calibrate attribute response and demonstrate the effectiveness of seismic attributes for rapid evaluation of prospectivity in the initial stages of exploration. The main structural episodes are distinguished using dip and azimuth attributes, and faulting is expressed using a combination of edge attributes which are used to create fault trend lineations. We observe three main structural trends: the main northeast–southwest Jurassic-Cretaceous syn-rift primary fault orientation of 48°, a secondary trend of 108°, taken to represent secondary conjugate faulting and a third trend of 100° interpreted as the reactivation of these faults into the postrift sediments. Stratigraphic attributes that respond to amplitude and frequency are used to create reservoir scale geobodies of faulted Macedon turbidites, which in turn are used for detailed tuning sensitivity analysis. The final part of the investigation is of the syn-rift magmatic system responsible for sills and dikes that exploit the normal fault network. These intrusive and extrusive features are important as are potential drilling hazards and can act as baffles to hydrocarbon migration.

scholarly journals Using Seismic Attributes in seismotectonic research: an application to the Norcia's Mw = 6.5 earthquake (30th October 2016) in Central Italy

2019 ◽  
Author(s):  
Maurizio Ercoli ◽  
Emanuele Forte ◽  
Massimiliano Porreca ◽  
Ramon Carbonell ◽  
Cristina Pauselli ◽  
...  
Keyword(s):  
Seismic Reflection ◽  
Central Italy ◽  
Seismic Attributes ◽  
Seismic Attribute ◽  
Data Set ◽  
Epicentral Zone ◽  
Seismic Reflection Data ◽  
Near Surface ◽  
Reflection Data ◽  
Attribute Analysis

Abstract. In seismotectonic studies, seismic reflection data are a powerful tool to unravel the complex deep architecture of active faults. Such tectonic structures are usually mapped at surface through traditional geological surveying whilst seismic reflection data may help to trace their continuation from the near-surface down to hypocentral depth. In this study, we propose the application of the seismic attributes technique, commonly used in seismic reflection exploration by oil industry, to seismotectonic research for the first time. The study area is a geologically complex region of Central Italy, recently struck by a long-lasting seismic sequence including a Mw 6.5 main-shock. A seismic reflection data-set consisting of three vintage seismic profiles, currently the only available across the epicentral zone, constitutes a singular opportunity to attempt a seismic attribute analysis. This analysis resulted in peculiar seismic signatures which generally correlate with the exposed surface geologic features, and also confirming the presence of other debated structures. These results are critical, because provide information also on the relatively deep structural setting, mapping a prominent, high amplitude regional reflector that marks the top basement, interpreted as important rheological boundary. Complex patterns of high-angle discontinuities crossing the reflectors have been also identified. These dipping fabrics are interpreted as the expression of fault zones, belonging to the active normal fault systems responsible for the seismicity of the region. This work demonstrates that seismic attribute analysis, even if used on low-quality vintage 2D data, may contribute to improve the subsurface geological interpretation of areas characterized by high seismic potential.

Accelerating seismic fault and stratigraphy interpretation with deep CNNs: A case study of the Taranaki Basin, New Zealand

2020 ◽  
Vol 39 (10) ◽  
pp. 727-733
Author(s):  
Haibin Di ◽  
Leigh Truelove ◽  
Cen Li ◽  
Aria Abubakar
Keyword(s):  
New Zealand ◽  
Seismic Data ◽  
Reservoir Characterization ◽  
Seismic Survey ◽  
Deep Convolutional Neural Networks ◽  
Seismic Attribute ◽  
Data Set ◽  
Seismic Fault ◽  
Attribute Analysis ◽  
Specific Implementation

Accurate mapping of structural faults and stratigraphic sequences is essential to the success of subsurface interpretation, geologic modeling, reservoir characterization, stress history analysis, and resource recovery estimation. In the past decades, manual interpretation assisted by computational tools — i.e., seismic attribute analysis — has been commonly used to deliver the most reliable seismic interpretation. Because of the dramatic increase in seismic data size, the efficiency of this process is challenged. The process has also become overly time-intensive and subject to bias from seismic interpreters. In this study, we implement deep convolutional neural networks (CNNs) for automating the interpretation of faults and stratigraphies on the Opunake-3D seismic data set over the Taranaki Basin of New Zealand. In general, both the fault and stratigraphy interpretation are formulated as problems of image segmentation, and each workflow integrates two deep CNNs. Their specific implementation varies in the following three aspects. First, the fault detection is binary, whereas the stratigraphy interpretation targets multiple classes depending on the sequences of interest to seismic interpreters. Second, while the fault CNN utilizes only the seismic amplitude for its learning, the stratigraphy CNN additionally utilizes the fault probability to serve as a structural constraint on the near-fault zones. Third and more innovatively, for enhancing the lateral consistency and reducing artifacts of machine prediction, the fault workflow incorporates a component of horizontal fault grouping, while the stratigraphy workflow incorporates a component of feature self-learning of a seismic data set. With seven of 765 inlines and 23 of 2233 crosslines manually annotated, which is only about 1% of the available seismic data, the fault and four sequences are well interpreted throughout the entire seismic survey. The results not only match the seismic images, but more importantly they support the graben structure as documented in the Taranaki Basin.

Delineation of reservoir channels by different seismic attributes and geobody extractions for robust volumetric estimation, Saffron Field, offshore Nile Delta, Egypt

2021 ◽  
Vol 40 (7) ◽  
pp. 484-493
Author(s):  
Doha Monier ◽  
Azza El Rawy ◽  
Abdullah Mahmoud
Keyword(s):  
Seismic Data ◽  
Nile Delta ◽  
Three Dimensional ◽  
Dynamic Test ◽  
Data Interpretation ◽  
Seismic Attributes ◽  
Reservoir Properties ◽  
Root Mean Square Amplitude ◽  
Seismic Attribute ◽  
Attribute Analysis

The Nile Delta Basin is a major gas province. Commercial gas discoveries there have been proven mainly in Pleistocene to Oligocene sediments, and most discoveries are within sandstone reservoirs. Three-dimensional seismic data acquired over the basin have helped greatly in imaging and visualization of stratigraphy and structure, leading to robust understanding of the subsurface. Channel fairways serve as potential reservoir units; hence, mapping channel surfaces and identifying and defining infill lithology is important. Predicting sand distribution and reservoir presence is one of the key tasks as well as one of the key uncertainties in exploration. Integrating state-of-the-art technologies, such as including 3D seismic reflection surveys, seismic attributes, and geobody extractions, can reduce this uncertainty through recognition and accurate mapping of channel features. In this study, seismic attribute analysis, frequency analysis through spectral decomposition (SD), geobodies, and seismic sections have been used to delineate shallow Plio-Pleistocene El Wastani Formation channel fairways within the Saffron Field, offshore Nile Delta, Egypt. This has led to providing more reliable inputs for calculation of volumetrics. Interpretation of the stacked-channels complex through different seismic attributes helped to discriminate between sand-filled and shale-filled channels and in understanding their geometries. Results include more confident delineation of four distinct low-sinuosity channelized features. Petrophysical evaluation conducted on five wells penetrating Saffron reservoirs included electric logs and modular dynamic test data interpretation. The calculated average reservoir properties were used in different volumetric calculation cases. Different approaches were applied to delineate channel geometries that were later used in performing different volumetric cases. These approaches included defining channels from root-mean-square amplitude extractions, SD color-blended frequencies, and geobodies, all calculated from prestack seismic data. The different volumetric cases performed were compared against the latest field volume estimates proven after several years of production in which an area-versus-depth input showed the closest calculated hydrocarbon volumes to the actual proven field volumes.

Identification of polygonal faulting from legacy 3D seismic data in vintage Gulf of Mexico data using seismic attributes

2021 ◽  
pp. 1-17
Author(s):  
Karen M. Leopoldino Oliveira ◽  
Heather Bedle ◽  
Karelia La Marca Molina
Keyword(s):  
Seismic Data ◽  
Seismic Attributes ◽  
Fault System ◽  
3D Seismic ◽  
Seismic Attribute ◽  
Variable Amplitude ◽  
Attribute Analysis ◽  
Amplitude Data ◽  
3D Seismic Data ◽  
Polygonal Fault

We analyzed a 1991 3D seismic data located offshore Florida and applied seismic attribute analysis to identify geological structures. Initially, the seismic data appears to have a high signal-to-noise-ratio, being of an older vintage of quality, and appears to reveal variable amplitude subparallel horizons. Additional geophysical analysis, including seismic attribute analysis, reveals that the data has excessive denoising, and that the continuous features are actually a network of polygonal faults. The polygonal faults were identified in two tiers using variance, curvature, dip magnitude, and dip azimuth seismic attributes. Inline and crossline sections show continuous reflectors with a noisy appearance, where the polygonal faults are suppressed. In the variance time slices, the polygonal fault system forms a complex network that is not clearly imaged in the seismic amplitude data. The patterns of polygonal fault systems in this legacy dataset are compared to more recently acquired 3D seismic data from Australia and New Zealand. It is relevant to emphasize the importance of seismic attribute analysis to improve accuracy of interpretations, and also to not dismiss older seismic data that has low accurate imaging, as the variable amplitude subparallel horizons might have a geologic origin.

Seismic attributes — A historical perspective

Geophysics ◽  
2005 ◽  
Vol 70 (5) ◽  
pp. 3SO-28SO ◽  
Author(s):  
Satinder Chopra ◽  
Kurt J. Marfurt
Keyword(s):  
Seismic Data ◽  
Quantitative Measure ◽  
Seismic Attributes ◽  
Seismic Attribute ◽  
Black And White ◽  
Interval Velocity ◽  
Reflection Seismic ◽  
Color Displays ◽  
Attribute Analysis ◽  
Other Information

A seismic attribute is a quantitative measure of a seismic characteristic of interest. Analysis of attributes has been integral to reflection seismic interpretation since the 1930s when geophysicists started to pick traveltimes to coherent reflections on seismic field records. There are now more than 50 distinct seismic attributes calculated from seismic data and applied to the interpretation of geologic structure, stratigraphy, and rock/pore fluid properties. The evolution of seismic attributes is closely linked to advances in computer technology. As examples, the advent of digital recording in the 1960s produced improved measurements of seismic amplitude and pointed out the correlation between hydrocarbon pore fluids and strong amplitudes (“bright spots”). The introduction of color printers in the early 1970s allowed color displays of reflection strength, frequency, phase, and interval velocity to be overlain routinely on black-and-white seismic records. Interpretation workstations in the 1980s provided interpreters with the ability to interact quickly with data to change scales and colors and to easily integrate seismic traces with other information such as well logs. Today, very powerful computer workstations capable of integrating large volumes of diverse data and calculating numerous seismic attributes are a routine tool used by seismic interpreters seeking geologic and reservoir engineering information from seismic data. In this review paper celebrating the 75th anniversary of the Society of Exploration Geophysicists, we reconstruct the key historical events that have lead to modern seismic attribute analysis.

Mesozoic tectonostratigraphic evolution of the North Carnarvon Basin unlocked using regional 3D seismic

2016 ◽  
Vol 56 (2) ◽  
pp. 564
Author(s):  
Daniel Bishop ◽  
Megan Halbert ◽  
Katherine Welbourn ◽  
Ben Boterhoven ◽  
Stacey Mansfield ◽  
...  
Keyword(s):  
Seismic Data ◽  
Regional Scale ◽  
Depositional Environments ◽  
Single Channels ◽  
Data Sets ◽  
3D Seismic ◽  
The North ◽  
Basin Scale ◽  
3D Seismic Data ◽  
Carnarvon Basin

Interpretation of regional scale merged 3D seismic data sets covering the North Carnarvon Basin has for the first time enabled a detailed description of Mesozoic stratigraphic and structural features on a basin scale. Isoproportional slicing of the data enables direct interpretation of Triassic depositional environments, including contrasting low-stand and high-stand fluvial channel complexes, marginal marine clastic systems and reef complexes. Channels vary dramatically between sinuous-straight single channels within low net:gross floodplain successions, to broad channel belts within relatively high net:gross fluvial successions. The latter can be traced from the inboard part of the basin to the outer areas of the Exmouth Plateau. 3D visualisation and interpretation has demonstrated the huge variety of structural styles that are present, including basement-involved extensional faults, detached listric fault complexes, polygonal faults, and regional scale vertical strike-slip faults with flower structures. Fault trends include north–south, north–northeast to south–southwest, and northeast–southwest, with deformation events occurring mainly between the Rhaetian and Valanginian. Extensional and compressional deformation has created multiple horsts, three-way fault closures, fold belts and associated four-way anticlinal traps. Wrench tectonics may also explain pock-mark trains with the interpreted transfer of over-pressure from Triassic to Early Cretaceous levels. The use of regional scale merged 3D seismic data sets is now shedding light on tectonostratigraphic features on a basin scale that were previously unrecognised or enigmatic on 2D seismic or local 3D seismic data sets.

Delineation of Carbonate Buildups Using Advanced Seismic Attributes, NW Sirte Basin, Libya

2021 ◽  
pp. 159-168
Author(s):  
Muneer Abdalla
Keyword(s):  
Seismic Data ◽  
Carbonate Platform ◽  
Median Filter ◽  
Random Noise ◽  
Seismic Attributes ◽  
Small Scale ◽  
Seismic Attribute ◽  
Attribute Analysis ◽  
Data Conditioning ◽  
Sirte Basin

The Paleocene reservoir formations of the Northwest Sirte Basin in North-central, Libya contains chaotic and mound-shaped seismic geometries that may have an impact on the performance of the reservoirs. It is crucial to characterize and interpret these complex geometries for future field development. Therefore, this study was utilized numerous seismic attributes to characterize and enhance the interpretation of the chaotic and mounded geometries. Data conditioning represented by spectral whitening and median filter was first applied to enhance the quality of the seismic data and remove random noise resulted from data acquisition and processing. It provided high-resolution seismic data and better-displayed edges and sedimentological features. Variance, root mean square (RMS), curvature, and envelope attributes were computed from the post-stack 3D seismic data to better visualize and interpret the chaotic and mound-like seismic geometries. Based on the seismic attribute analysis, the chaotic facies were interpreted as barrier reefs forming the margins of an isolated carbonate platform, whereas the small-scale mound-shaped facies was interpreted as patch reefs developed on the platform interior. Data conditioning methods and seismic attribute analysis that were applied to the 3-D seismic data have effectively improved the detection and interpretation of the chaotic and mounded facies in the study area. Keywords: Carbonate buildup, data conditioning, seismic attributes, Sirte Basin, Libya

scholarly journals Pitfalls and limitations in seismic attribute interpretation of tectonic features

2015 ◽  
Vol 3 (1) ◽  
pp. SB5-SB15 ◽  
Author(s):  
Kurt J. Marfurt ◽  
Tiago M. Alves
Keyword(s):  
Seismic Data ◽  
Seismic Attributes ◽  
Seismic Attribute ◽  
3D Data ◽  
Amplitude Data ◽  
Seismic Sections ◽  
Push Down ◽  
Data Coherence ◽  
Level Of Experience ◽  
Tectonic Features

Seismic attributes are routinely used to accelerate and quantify the interpretation of tectonic features in 3D seismic data. Coherence (or variance) cubes delineate the edges of megablocks and faulted strata, curvature delineates folds and flexures, while spectral components delineate lateral changes in thickness and lithology. Seismic attributes are at their best in extracting subtle and easy to overlook features on high-quality seismic data. However, seismic attributes can also exacerbate otherwise subtle effects such as acquisition footprint and velocity pull-up/push-down, as well as small processing and velocity errors in seismic imaging. As a result, the chance that an interpreter will suffer a pitfall is inversely proportional to his or her experience. Interpreters with a history of making conventional maps from vertical seismic sections will have previously encountered problems associated with acquisition, processing, and imaging. Because they know that attributes are a direct measure of the seismic amplitude data, they are not surprised that such attributes “accurately” represent these familiar errors. Less experienced interpreters may encounter these errors for the first time. Regardless of their level of experience, all interpreters are faced with increasingly larger seismic data volumes in which seismic attributes become valuable tools that aid in mapping and communicating geologic features of interest to their colleagues. In terms of attributes, structural pitfalls fall into two general categories: false structures due to seismic noise and processing errors including velocity pull-up/push-down due to lateral variations in the overburden and errors made in attribute computation by not accounting for structural dip. We evaluate these errors using 3D data volumes and find areas where present-day attributes do not provide the images we want.

Predict Channel Sand Body Distribution Characteristics of South Eighth District Based on RMS Amplitude Attributes & Frequency Division

2013 ◽  
Vol 734-737 ◽  
pp. 404-407 ◽  
Author(s):  
Yu Shuang Hu ◽  
Si Miao Zhu
Keyword(s):  
Seismic Data ◽  
Physical Property ◽  
Sedimentary Facies ◽  
Distribution Area ◽  
Frequency Division ◽  
Root Mean Square Amplitude ◽  
Seismic Attribute ◽  
Body Distribution ◽  
Attribute Analysis ◽  
Sand Body

A big tendency in oil industry is underestimating the heterogeneity of the reservoir and overestimating the connectivity, which results in overly optimistic estimates of the capacity. With the development of seismic attributes, we could pick up hidden reservoir lithology and physical property information from the actual seismic data, strengthen seismic data application in actual work, to ensure the objectivity of the results. In this paper, the channel sand body distribution in south eighth district of oilfield Saertu is predicted through seismic data root-mean-square amplitude and frequency division to identify sand body boundaries, predict the distribution area channel sand body characteristics successfully, which consistent with the sedimentary facies distribution. The result proves that seismic attribute analysis has good practicability in channel sand body prediction and sedimentary facies description.

Sparse reflectivity inversion for nonstationary seismic data with surface-related multiples: Numerical and field-data experiments

Geophysics ◽  
2017 ◽  
Vol 82 (3) ◽  
pp. R199-R217 ◽  
Author(s):  
Xintao Chai ◽  
Shangxu Wang ◽  
Genyang Tang
Keyword(s):  
Seismic Data ◽  
Resolution Enhancement ◽  
Synthetic Data ◽  
Data Sets ◽  
Data Set ◽  
Anelastic Attenuation ◽  
Seismic Resolution ◽  
Text Filtering ◽  
The Stability ◽  
Reflectivity Inversion

Seismic data are nonstationary due to subsurface anelastic attenuation and dispersion effects. These effects, also referred to as the earth’s [Formula: see text]-filtering effects, can diminish seismic resolution. We previously developed a method of nonstationary sparse reflectivity inversion (NSRI) for resolution enhancement, which avoids the intrinsic instability associated with inverse [Formula: see text] filtering and generates superior [Formula: see text] compensation results. Applying NSRI to data sets that contain multiples (addressing surface-related multiples only) requires a demultiple preprocessing step because NSRI cannot distinguish primaries from multiples and will treat them as interference convolved with incorrect [Formula: see text] values. However, multiples contain information about subsurface properties. To use information carried by multiples, with the feedback model and NSRI theory, we adapt NSRI to the context of nonstationary seismic data with surface-related multiples. Consequently, not only are the benefits of NSRI (e.g., circumventing the intrinsic instability associated with inverse [Formula: see text] filtering) extended, but also multiples are considered. Our method is limited to be a 1D implementation. Theoretical and numerical analyses verify that given a wavelet, the input [Formula: see text] values primarily affect the inverted reflectivities and exert little effect on the estimated multiples; i.e., multiple estimation need not consider [Formula: see text] filtering effects explicitly. However, there are benefits for NSRI considering multiples. The periodicity and amplitude of the multiples imply the position of the reflectivities and amplitude of the wavelet. Multiples assist in overcoming scaling and shifting ambiguities of conventional problems in which multiples are not considered. Experiments using a 1D algorithm on a synthetic data set, the publicly available Pluto 1.5 data set, and a marine data set support the aforementioned findings and reveal the stability, capabilities, and limitations of the proposed method.

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