Fault interpretation from high‐resolution seismic data in the northern Negev, Israel

Geophysics ◽  
1991 ◽  
Vol 56 (7) ◽  
pp. 1064-1070 ◽  
Author(s):  
Ilan Bruner ◽  
Eugeny Landa
Keyword(s):  
High Resolution ◽  
Seismic Data ◽  
Field Data ◽  
Dynamic Properties ◽  
Fault Zones ◽  
Diffracted Waves ◽  
Fault Interpretation ◽  
Low Amplitude ◽  
Seismic Lines ◽  
Sense Reverse

Detection and investigation of fault zones are important tools for tectonic analysis and geological studies. A fault zone inferred on high‐resolution seismic lines has been interpreted using a method of detection of diffracted waves utilizing the main kinematic and dynamic properties of the wavefield. The application of the method to field data from the northern Negev in Israel shows that it provides a good estimate of results and, when used in conjunction with the final stacked data, can give the suspected location of the fault, its sense (reverse or normal), and the amount of “low amplitude” displacement (in an order of the wavelength or even less).

Poststack velocity analysis by separation and imaging of seismic diffractions

Geophysics ◽  
2007 ◽  
Vol 72 (6) ◽  
pp. U89-U94 ◽  
Author(s):  
Sergey Fomel ◽  
Evgeny Landa ◽  
M. Turhan Taner
Keyword(s):  
High Resolution ◽  
Seismic Data ◽  
Field Data ◽  
Small Scale ◽  
Velocity Analysis ◽  
High Resolution Imaging ◽  
Diffracted Waves ◽  
Resolution Imaging ◽  
Seismic Reflections ◽  
Optimal Focusing

Small geologic features manifest themselves in seismic data in the form of diffracted waves, which are fundamentally different from seismic reflections. Using two field-data examples and one synthetic example, we demonstrate the possibility of separating seismic diffractions in the data and imaging them with optimally chosen migration velocities. Our criteria for separating reflection and diffraction events are the smoothness and continuity of local event slopes that correspond to reflection events. For optimal focusing, we develop the local varimax measure. The objectives of this work are velocity analysis implemented in the poststack domain and high-resolution imaging of small-scale heterogeneities. Our examples demonstrate the effectiveness of the proposed method for high-resolution imaging of such geologic features as faults, channels, and salt boundaries.

scholarly journals High-resolution coherency functionals for velocity analysis: An application for subbasalt seismic exploration

Geophysics ◽  
2013 ◽  
Vol 78 (5) ◽  
pp. U53-U63 ◽  
Author(s):  
Andrea Tognarelli ◽  
Eusebio Stucchi ◽  
Alessia Ravasio ◽  
Alfredo Mazzotti
Keyword(s):  
High Resolution ◽  
Seismic Data ◽  
Field Data ◽  
Signal To Noise Ratio ◽  
Synthetic Seismograms ◽  
Seismic Exploration ◽  
Velocity Analysis ◽  
Signal To Noise ◽  
Geologic Setting ◽  
Analytic Signals

We tested the properties of three different coherency functionals for the velocity analysis of seismic data relative to subbasalt exploration. We evaluated the performance of the standard semblance algorithm and two high-resolution coherency functionals based on the use of analytic signals and of the covariance estimation along hyperbolic traveltime trajectories. Approximate knowledge of the wavelet was exploited to design appropriate filters that matched the primary reflections, thereby further improving the ability of the functionals to highlight the events of interest. The tests were carried out on two synthetic seismograms computed on models reproducing the geologic setting of basaltic intrusions and on common midpoint gathers from a 3D survey. Synthetic and field data had a very low signal-to-noise ratio, strong multiple contamination, and weak primary subbasalt signals. The results revealed that high-resolution coherency functionals were more suitable than semblance algorithms to detect primary signals and to distinguish them from multiples and other interfering events. This early discrimination between primaries and multiples could help to target specific signal enhancement and demultiple operations.

An image of the Columbia Plateau from inversion of high‐resolution seismic data

Geophysics ◽  
1994 ◽  
Vol 59 (8) ◽  
pp. 1278-1289 ◽  
Author(s):  
William J. Lutter ◽  
Rufus D. Catchings ◽  
Craig M. Jarchow
Keyword(s):  
High Resolution ◽  
Seismic Data ◽  
Velocity Structure ◽  
Interface Velocity ◽  
Seismic Profile ◽  
Fault Zones ◽  
Reliable Estimate ◽  
Low Velocity ◽  
Depth Of Penetration ◽  
Image Blurring

We use a method of traveltime inversion of high‐resolution seismic data to provide the first reliable images of internal details of the Columbia River Basalt Group (CRBG), the subsurface basalt/sediment interface, and the deeper sediment/basement interface. Velocity structure within the basalts, delineated on the order of 1 km horizontally and 0.2 km vertically, is constrained to within ±0.1 km/s for most of the seismic profile. Over 5000 observed traveltimes fit our model with an rms error of 0.018 s. The maximum depth of penetration of the basalt diving waves (truncated by underlying low‐velocity sediments) provides a reliable estimate of the depth to the base of the basalt, which agrees with well‐log measurements to within 0.05 km (165 ft). We use image blurring, calculated from the resolution matrix, to estimate the aspect ratio of imaged velocity anomaly widths to true widths for velocity features within the basalt. From our calculations of image blurring, we interpret low velocity zones (LVZ) within the basalts at Boylston Mountain and the Whiskey Dick anticline to have widths of 4.5 and 3 km, respectively, within the upper 1.5 km of the model. At greater depth, the widths of these imaged LVZs thin to approximately 2 km or less. We interpret these linear, subparallel, low‐velocity zones imaged adjacent to anticlines of the Yakima Fold Belt to be brecciated fault zones. These fault zones dip to the south at angles between 15 to 45 degrees.

Enhancing resolution of nonstationary seismic data by molecular-Gabor transform

Geophysics ◽  
2013 ◽  
Vol 78 (1) ◽  
pp. V31-V41 ◽  
Author(s):  
Lingling Wang ◽  
Jinghuai Gao ◽  
Wei Zhao ◽  
Xiudi Jiang
Keyword(s):  
High Resolution ◽  
Seismic Data ◽  
Field Data ◽  
Optimization Problem ◽  
Gabor Transform ◽  
Frequency Bandwidth ◽  
Time Frequency ◽  
Text Model ◽  
Amplitude Compensation

We propose an adaptive spectrum-broadening method (ASBM) to improve the resolution of nonstationary seismic data. This method assumes that a seismic trace can be split into segments, each of which can be considered as approximately stationary. We construct a set of specific windows, called molecular-Gabor (MG) windows, by solving an optimization problem, such that the seismic trace in each of the MG windows is stationary. A time-frequency (t-f) transform, called MG transform, can be obtained from a MG frame constructed using the MG windows. For a seismic trace, we first transform it into the t-f domain, then spectrum-broadening and/or amplitude compensation are performed in each of the MG windows. Subsequently, a high-resolution version of the nonstationary seismic trace will be obtained after the inverse MG transform. Applications of this method to synthetic and field data show that the ASBM works well for a general earth [Formula: see text]-model that varies with traveltime. It can restore the attenuated energy and expand the frequency bandwidth of a nonstationary seismic trace effectively. One significant advantage of our method is that it automatically estimates all the parameters that are optimal for each trace.

Common-azimuth seismic data fault analysis using residual UNet

2020 ◽  
Vol 8 (3) ◽  
pp. SM25-SM37 ◽  
Author(s):  
Naihao Liu ◽  
Tao He ◽  
Yajun Tian ◽  
Bangyu Wu ◽  
Jinghuai Gao ◽  
...  
Keyword(s):  
Seismic Data ◽  
Field Data ◽  
Synthetic Data ◽  
Detection Algorithm ◽  
Fault Analysis ◽  
Seismic Structure ◽  
Validation Data ◽  
Seismic Fault ◽  
Key Steps ◽  
Fault Interpretation

Seismic fault interpretation is one of the key steps for seismic structure interpretation, which is a time-consuming task and strongly depends on the experience of the interpreter. Aiming to automate fault interpretation, we have considered it as an image segmentation issue and adopt a solution using a residual UNet (ResUNet), which introduces residual units to UNet. Using the ResUNet model, we develop a fault-versus-azimuth analysis based on offset vector tile data, which, as common-azimuth seismic data, provide more detailed and useful information for interpreting seismic faults. To avoid manual efforts for picking training labels and the inaccuracy introduced by different interpreters, we use synthetic seismic data with a random number of faults with different locations and throws as the training and validation data sets. ResUNet is finally trained using only synthetic data and tested on field data. Field data applications show that the proposed fault-detection algorithm using ResUNet can predict seismic faults more accurately than coherence- and UNet-based approaches. Moreover, geologic fault interpretation results computed using common-azimuth data exhibit higher lateral resolution than those computed using poststack seismic data.

scholarly journals High-resolution reservoir characterization using deep learning-aided elastic full-waveform inversion: The North Sea field data example

Geophysics ◽  
2020 ◽  
Vol 85 (4) ◽  
pp. WA137-WA146
Author(s):  
Zhen-dong Zhang ◽  
Tariq Alkhalifah
Keyword(s):  
Deep Learning ◽  
High Resolution ◽  
North Sea ◽  
Seismic Data ◽  
Field Data ◽  
Reservoir Characterization ◽  
Waveform Inversion ◽  
Oil Field ◽  
Full Waveform Inversion ◽  
Full Waveform

Reservoir characterization is an essential component of oil and gas production, as well as exploration. Classic reservoir characterization algorithms, deterministic and stochastic, are typically based on stacked images and rely on simplifications and approximations to the subsurface (e.g., assuming linearized reflection coefficients). Elastic full-waveform inversion (FWI), which aims to match the waveforms of prestack seismic data, potentially provides more accurate high-resolution reservoir characterization from seismic data. However, FWI can easily fail to characterize deep-buried reservoirs due to illumination limitations. We have developed a deep learning-aided elastic FWI strategy using observed seismic data and available well logs in the target area. Five facies are extracted from the well and then connected to the inverted P- and S-wave velocities using trained neural networks, which correspond to the subsurface facies distribution. Such a distribution is further converted to the desired reservoir-related parameters such as velocities and anisotropy parameters using a weighted summation. Finally, we update these estimated parameters by matching the resulting simulated wavefields to the observed seismic data, which corresponds to another round of elastic FWI aided by the a priori knowledge gained from the predictions of machine learning. A North Sea field data example, the Volve Oil Field data set, indicates that the use of facies as prior knowledge helps resolve the deep-buried reservoir target better than the use of only seismic data.

Investigation on the tectonic significance of Izmir, Uzunada Fault Zones and other tectonic elements in the Gulf of Izmir, western Turkey, using high resolution seismic data

2017 ◽  
Vol 83 ◽  
pp. 73-83 ◽  
Author(s):  
Suleyman Coskun ◽  
Derman Dondurur ◽  
Gunay Cifci ◽  
Attila Aydemir ◽  
Talip Gungor ◽  
...  
Keyword(s):  
High Resolution ◽  
Seismic Data ◽  
Fault Zones ◽  
Western Turkey ◽  
Tectonic Significance

New form of Transmission Cross Coefficient for High-Resolution Imaging

1990 ◽  
Vol 48 (1) ◽  
pp. 60-61
Author(s):  
Kazuo Ishizuka
Keyword(s):  
Electron Microscope ◽  
High Resolution ◽  
Transmission Function ◽  
Incident Beam ◽  
Optical Microscope ◽  
Strong Interactions ◽  
Small Range ◽  
Specimen Thickness ◽  
Beam Direction ◽  
Diffracted Waves

It is well known that taking into account spacial and temporal coherency of illumination as well as the wave aberration is important to interpret an image of a high-resolution electron microscope (HREM). This occues, because coherency of incident electrons restricts transmission of image information. Due to its large spherical and chromatic aberrations, the electron microscope requires higher coherency than the optical microscope. On an application of HREM for a strong scattering object, we have to estimate the contribution of the interference between the diffracted waves on an image formation. The contribution of each pair of diffracted waves may be properly represented by the transmission cross coefficients (TCC) between these waves. In this report, we will show an improved form of the TCC including second order derivatives, and compare it with the first order TCC.In the electron microscope the specimen is illuminated by quasi monochromatic electrons having a small range of illumination directions. Thus, the image intensity for each energy and each incident direction should be summed to give an intensity to be observed. However, this is a time consuming process, if the ranges of incident energy and/or illumination direction are large. To avoid this difficulty, we can use the TCC by assuming that a transmission function of the specimen does not depend on the incident beam direction. This is not always true, because dynamical scattering is important owing to strong interactions of electrons with the specimen. However, in the case of HREM, both the specimen thickness and the illumination angle should be small. Therefore we may neglect the dependency of the transmission function on the incident beam direction.

Nucleosome dynamics

2006 ◽  
Vol 73 ◽  
pp. 109-119 ◽  
Author(s):  
Chris Stockdale ◽  
Michael Bruno ◽  
Helder Ferreira ◽  
Elisa Garcia-Wilson ◽  
Nicola Wiechens ◽  
...  
Keyword(s):  
High Resolution ◽  
Chromatin Structure ◽  
Current Knowledge ◽  
Dynamic Properties ◽  
Structure And Dynamics ◽  
Nucleosome Dynamics ◽  
Sharp Focus ◽  
Recent Advances ◽  
Insight Into ◽  
Chromatin Structure And Dynamics

In the 30 years since the discovery of the nucleosome, our picture of it has come into sharp focus. The recent high-resolution structures have provided a wealth of insight into the function of the nucleosome, but they are inherently static. Our current knowledge of how nucleosomes can be reconfigured dynamically is at a much earlier stage. Here, recent advances in the understanding of chromatin structure and dynamics are highlighted. The ways in which different modes of nucleosome reconfiguration are likely to influence each other are discussed, and some of the factors likely to regulate the dynamic properties of nucleosomes are considered.

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