Spectral similarity fault enhancement

2016 ◽  
Vol 4 (1) ◽  
pp. SB149-SB159 ◽  
Author(s):  
Dustin T. Dewett ◽  
Alissa A. Henza

Fault interpretation in seismic data is a critical task that must be completed to thoroughly understand the structural history of the subsurface. The development of similarity-based attributes has allowed geoscientists to effectively filter a seismic data set to highlight discontinuities that are often associated with fault systems. Furthermore, there are numerous workflows that provide, to varying degrees, the ability to enhance this seismic attribute family. We have developed a new method, spectral similarity, to improve the similarity enhancement by integrating spectral decomposition, swarm intelligence, magnitude filtering, and orientated smoothing. In addition, the spectral similarity method has the ability to take any seismic attribute (e.g., similarity, curvature, total energy, coherent energy gradient, reflector rotation, etc.), combine it with the benefits of spectral decomposition, and create an accurate enhancement to similarity attributes. The final result is an increase in the quality of the similarity enhancement over previously used methods, and it can be computed entirely in commercial software packages. Specifically, the spectral similarity method provides a more realistic fault dip, reduction of noise, and removal of the discontinuous “stair-step” pattern common to similarity volumes.

2020 ◽  
Vol 11 (1) ◽  
pp. 219
Author(s):  
Jing Zeng ◽  
Alexey Stovas ◽  
Handong Huang ◽  
Lixia Ren ◽  
Tianlei Tang

Paleozoic marine shale gas resources in Southern China present broad prospects for exploration and development. However, previous research has mostly focused on the shale in the Sichuan Basin. The research target of this study is expanded to the Lower Silurian Longmaxi shale outside the Sichuan Basin. A prediction scheme of shale gas reservoirs through the frequency-dependent seismic attribute technology is developed to reduce drilling risks of shale gas related to complex geological structure and low exploration level. Extracting frequency-dependent seismic attribute is inseparable from spectral decomposition technology, whereby the matching pursuit algorithm is commonly used. However, frequency interference in MP results in an erroneous time-frequency (TF) spectrum and affects the accuracy of seismic attribute. Firstly, a novel spectral decomposition technology is proposed to minimize the effect of frequency interference by integrating the MP and the ensemble empirical mode decomposition (EEMD). Synthetic and real data tests indicate that the proposed spectral decomposition technology provides a TF spectrum with higher accuracy and resolution than traditional MP. Then, a seismic fluid mobility attribute, extracted from the post-stack seismic data through the proposed spectral decomposition technology, is applied to characterize the shale reservoirs. The application result indicates that the seismic fluid mobility attribute can describe the spatial distribution of shale gas reservoirs well without well control. Based on the seismic fluid mobility attribute section, we have learned that the shale gas enrich areas are located near the bottom of the Longmaxi Formation. The inverted velocity data are also introduced to further verify the reliability of seismic fluid mobility. Finally, the thickness map of gas-bearing shale reservoirs in the Longmaxi Formation is obtained by combining the seismic fluid mobility attribute with the inverted velocity data, and two favorable exploration areas are suggested by analyzing the thickness, structure, and burial depth. The present work can not only be used to evaluate shale gas resources in the early stage of exploration, but also help to design the landing point and trajectory of directional drilling in the development stage.


1995 ◽  
Vol 35 (1) ◽  
pp. 358 ◽  
Author(s):  
R. Lovibond ◽  
R.J. Suttill ◽  
J.E. Skinner ◽  
A.N. Aburas

The Penola Trough is an elongate, Late Jurassic to Early Cretaceous, NW-SE trending half graben filled mainly with synrift sediments of the Crayfish Group. Katnook-1 discovered gas in the basal Eumeralla Formation, but all commercial discoveries have been within the Crayfish Group, particularly the Pretty Hill Formation. Recent improvements in seismic data quality, in conjunction with additional well control, have greatly improved the understanding of the stratigraphy, structure and hydrocarbon prospectivity of the trough. Strati-graphic units within the Pretty Hill Formation are now mappable seismically. The maturity of potential source rocks within these deeper units has been modelled, and the distribution and quality of potential reservoir sands at several levels within the Crayfish Group have been studied using both well and seismic data. Evaluation of the structural history of the trough, the risk of a late carbon dioxide charge to traps, the direct detection of gas using seismic AVO analysis, and the petrophysical ambiguities recorded in wells has resulted in new insights. An important new play has been recognised on the northern flank of the Penola Trough: a gas and oil charge from mature source rocks directly overlying basement into a quartzose sand sequence referred to informally as the Sawpit Sandstone. This play was successfully tested in early 1994 by Wynn-1 which flowed both oil and gas during testing from the Sawpit Sandstone. In mid 1994, Haselgrove-1 discovered commercial quantities of gas in a tilted Pretty Hill Formation fault block adjacent to the Katnook Field. These recent discoveries enhance the prospectivity of the Penola Trough and of the Early Cretaceous sequence in the wider Otway Basin where these sediments are within reach of the drill.


2021 ◽  
Vol 72 ◽  
pp. 1-13
Author(s):  
Chee Meng Choong ◽  
◽  
Manuel Pubellier ◽  
Benjamin Sautter ◽  
Mirza Arshad Beg ◽  
...  

Over two decades, analysis of seismic attributes had been an integral part of seismic reflection interpretation. Seismic attributes are an influential assistance to seismic interpretation, delivering geoscientists with alternative images of structural (faults) and stratigraphic features (channels), which can be utilised as mechanisms to identify prospects, ascertain depositional environment and structural deformation history more rapidly even provide direct hydrocarbon indicators. The additional steps are obligatory to compute and interpret the attributes of faults and channels from seismic images, which are often sensitive to noise due to the characteristically computed as discontinuities of seismic reflections. Furthermore, on a conventional seismic profile or poor quality data, faults and channels are hard to visible. The current research review these geological structures through a case study of 3D seismic data from N-field in the viewpoint of Malay Basin. This study aimed to characterise the structure and stratigraphic features by using seismic attributes on the N-field below seismic resolution. Also, two different methods are proposed to improve seismic reflections, i.e., faults and channels that are hard to see on the conventional 3D data set. The first method, to detect faults in seismic data, which this paper employs the ant tracking attribute as a unique algorithm to be an advanced forwarding that introduces a new tool in the interpretation of fault. The effective implementation of ant tracking can be achieved when the output of other faults sensitive attributes are used as input data. In this work, the seismic data used are carefully conditioned using a signal. Chaos and variance that are sensitive to faults are applied to the seismic data set, and the output from these processes are used as input data that run the ant tracking attribute, which the faults were seen difficult to display on the raw seismic data. Meanwhile, for the second method, spectral decomposition was adopted to deliberate the way its method could be utilised to augment stratigraphic features (channels) of the N-field, where the channel is ultimately considered being one of the largest formations of the petroleum entrapment. The spectral decomposition analysis method is an alternative practice concentrated on processing S-transform that can offer better results. Spectral decomposition has been completed over the Pleistocene channels, and results propose that application of its methods directs to dependable implications. Respective channel in this area stands out more obviously within the specific frequency range. The thinner layer demonstrates higher amplitude reading at a higher frequency, and the thicker channel displays higher amplitude reading at a lower frequency. Implementation of spectral decomposition assists in deciding the channels that were placed within incised valleys and helps in recognising the orientation and the relative thickness of each channel. By doing this, the ant tracking attribute and spectral decomposition approach have generated the details of subsurface geologic features through attributes by obtaining enhanced reflections and channels and sharpened faults, respectively.


2020 ◽  
Vol 39 (10) ◽  
pp. 727-733
Author(s):  
Haibin Di ◽  
Leigh Truelove ◽  
Cen Li ◽  
Aria Abubakar

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.


Energies ◽  
2020 ◽  
Vol 13 (22) ◽  
pp. 6036
Author(s):  
Anna Łaba-Biel ◽  
Anna Kwietniak ◽  
Andrzej Urbaniec

An integrated geological and geophysical approach is presented for the recognition of unconventional targets in the Miocene formations of the Carpathian Foredeep, southern Poland. The subject of the analysis is an unconventional reservoir built of interlayered packets of sandstone, mudstone and claystone, called a “heterogeneous sequence”. This type of sequence acts as both a reservoir and as source rock for hydrocarbons and it consists of layers of insignificant thickness, below the resolution of seismic data. The interpretation of such a sequence has rarely been based on seismic stratigraphy analysis; however, such an approach is proposed here. The subject of interpretation is high-quality seismic data of high resolution that enable detailed depositional analysis. The reconstruction of the depositional history was possible due to the analysis of flattened chronostratigraphic horizons (Wheeler diagram). The identification of depositional positions in a sedimentary basin was the first step for the indication of potential target areas. These areas were also subject to seismic attribute analysis (sweetness) and spectral decomposition. The seismic attribute results positively verified the previously proposed prospects. The results obtained demonstrate that the interpretation of the Miocene sediments in the Carpathian Foredeep should take into account the depositional history reconstruction and paleogeographical analysis.


2020 ◽  
Vol 223 (3) ◽  
pp. 1888-1898
Author(s):  
Kirill Gadylshin ◽  
Ilya Silvestrov ◽  
Andrey Bakulin

SUMMARY We propose an advanced version of non-linear beamforming assisted by artificial intelligence (NLBF-AI) that includes additional steps of encoding and interpolating of wavefront attributes using inpainting with deep neural network (DNN). Inpainting can efficiently and accurately fill the holes in waveform attributes caused by acquisition geometry gaps and data quality issues. Inpainting with DNN delivers excellent quality of interpolation with the negligible computational effort and performs particularly well for a challenging case of irregular holes where other interpolation methods struggle. Since conventional brute-force attribute estimation is very costly, we can further intentionally create additional holes or masks to restrict expensive conventional estimation to a smaller subvolume and obtain missing attributes with cost-effective inpainting. Using a marine seismic data set with ocean bottom nodes, we show that inpainting can reliably recover wavefront attributes even with masked areas reaching 50–75 per cent. We validate the quality of the results by comparing attributes and enhanced data from NLBF-AI and conventional NLBF using full-density data without decimation.


Author(s):  
Caroline SCHAAL ◽  
Henri-Georges Naton

By analyzing the mechanisms that govern the interactions between environmental factors and ecosystems, paleoecology refines our knowledge of the mechanisms that are structuring plant communities, helping us to understand the complexity of past environments. While undertaking palaeoecological analyses, it is necessary to analyze and to understand the taphonomic phenomena influencing plant macrofossil assemblages. Indeed, the evaluation of under- and over-representation of taxa makes it possible to judge the interest and quality of the retained data set as a source of paleo-ecological information. The French National Centre for Archaeological Research (CNRA) recommends "refining taphonomic modelling in different aspects: accumulation and modification processes by biological agents, natural ageing processes of taphocenoses" (National Research Programming 2016, p. 35). The inability to reconstruct the diagenetic history of sedimentary layers can sometimes lead to erroneous palaeoecological interpretations. Like all archaeological documents, macrofossil plant assemblages come to us distorted by the taphonomic processes involved in the formation of sediment layers. The study of waterlogged plant macrofossils preserved in the wet sediments of an oxbow lake of the river Meuse (Autrecourt-et-Pourron, Ardennes, France) aims to analyze these taphonomic processes. This archaeobotanical study focusing on a river wall dated to the Preboreal period (11.7 ̵ 10.7 ka BP) allows establishing a taphonomic reference frame. We applied a correspondence analysis to establish links between criteria preservation and the analyzed sediment samples. We observed differences in preservation conditions depending on the stratigraphy and nature of the sediments. Before conducting archaeobotanical studies in natural contexts, an assessment of the taphonomic state of the retrieved plant macrofossils is highly recommended.


2016 ◽  
Vol 56 (2) ◽  
pp. 577
Author(s):  
Irina Borissova ◽  
Chris Southby ◽  
George Bernardel ◽  
Jennifer Totterdell ◽  
Robbie Morris ◽  
...  

In 2014–15 Geoscience Australia acquired 3,300 km of deep 2D seismic data over the northern part of the Houtman Sub-basin (Perth Basin). Prior to this survey, this area had a very sparse coverage of 2D seismic data with 50–70 km line spacing in the north and an industry grid with 20 km line spacing in the south. Initial interpretation of the available data has shown that the structural style, major sequences, and potential source rocks in this area are similar to those in the southern Houtman and Abrolhos sub-basins. The major difference between these depocentres, however, is in the volume and distribution of volcanic and intrusive igneous rocks. The northern part of the Houtman Sub-basin is adjacent to the Wallaby Plateau Large Igneous Province (LIP). The Wallaby Plateau and the Wallaby Saddle, which borders the western flank of the Houtman Sub-basin, had active volcanism from the Valanginian to at least the end of the Barremian. Volcanic successions significantly reduce the quality of seismic imaging at depth, making it difficult to ascertain the underlying thickness, geometry and structure of the sedimentary basin. The new 2D seismic dataset across the northern Houtman Sub-basin provides an opportunity for improved mapping of the structure and stratigraphy of the pre-breakup succession, assessment of petroleum prospectivity, and examination of the role of volcanism in the thermal history of this frontier basin.


Geophysics ◽  
2007 ◽  
Vol 72 (4) ◽  
pp. V79-V86 ◽  
Author(s):  
Kurang Mehta ◽  
Andrey Bakulin ◽  
Jonathan Sheiman ◽  
Rodney Calvert ◽  
Roel Snieder

The virtual source method has recently been proposed to image and monitor below complex and time-varying overburden. The method requires surface shooting recorded at downhole receivers placed below the distorting or changing part of the overburden. Redatuming with the measured Green’s function allows the reconstruction of a complete downhole survey as if the sources were also buried at the receiver locations. There are still some challenges that need to be addressed in the virtual source method, such as limited acquisition aperture and energy coming from the overburden. We demonstrate that up-down wavefield separation can substantially improve the quality of virtual source data. First, it allows us to eliminate artifacts associated with the limited acquisition aperture typically used in practice. Second, it allows us to reconstruct a new optimized response in the absence of downgoing reflections and multiples from the overburden. These improvements are illustrated on a synthetic data set of a complex layered model modeled after the Fahud field in Oman, and on ocean-bottom seismic data acquired in the Mars field in the deepwater Gulf of Mexico.


2019 ◽  
Vol 7 (2) ◽  
pp. T383-T408 ◽  
Author(s):  
Francisco J. Bataller ◽  
Neil McDougall ◽  
Andrea Moscariello

Ancient glacial sediments form major hydrocarbon plays in several parts of the world; most notably, North Africa, Latin America, and the Middle East. We have described a methodology for reconstructing broad-scale paleogeographies in just such a depositional system, using an extensive subsurface data set from the uppermost Ordovician glacial sediments of the Murzuq Basin of southwest Libya. Our workflow begins with the analysis of a large, high-quality 3D seismic data set, to understand the frequency content. Subsequently, optimum frequency bands are extracted, after applying spectral decomposition, and then recombined into an R (red) G (green) B (blue) blended cube. This volume is then treated as an image within which paleomorphological features can be distinguished and compared with modern glacial analogs. Mapping at different depths (time slices) of these features is then tied, by integration with core and image-log sedimentology, to specific depositional environments defined within the framework of a facies scheme developed using the well data and published outcrop studies. These depositional environments are extrapolated into areas with little or no well data using the spectral decomposition as a framework, always taking into account the significant difference in vertical resolution between the seismic data set and core-scale descriptions. The result of this methodology is a set of calibrated maps, at three different time depths (two-way time travel), indicating paleogeographic reconstructions of the glacial depositional environments in the study area and the evolution through time (at different depths/time slices 2D + 1) of these glacial settings.


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