Detecting small scale heterogeneities through the application of multifocusing 3D diffraction imaging using pre-existing seismic data

2014 ◽  
Author(s):  
Marianne Rauch-Davies* ◽  
Kostya Deev ◽  
Maria Kachkachev-Shuifer ◽  
Alex Berkovitch
Keyword(s):  
Seismic Data ◽  
Small Scale ◽  
Diffraction Imaging

Diffractivity — Another attribute for the interpretation of seismic data in hard rock environment, a case study

2016 ◽  
Vol 4 (4) ◽  
pp. B23-B32 ◽  
Author(s):  
Mohammad Javad Khoshnavaz ◽  
Andrej Bóna ◽  
Muhammad Shahadat Hossain ◽  
Milovan Urosevic ◽  
Kit Chambers
Keyword(s):  
Seismic Data ◽  
Hard Rock ◽  
Shear Zones ◽  
Primary Objective ◽  
Seismic Exploration ◽  
Image Point ◽  
Small Scale ◽  
Imaging Method ◽  
Data Set ◽  
Diffraction Imaging

The primary objective of seismic exploration in a hard rock environment is the detection of heterogeneities such as fracture zones, small-scale geobodies, intrusions, and steeply dipping structures that are often associated with mineral deposits. Prospecting in such environments using seismic-reflection methods is more challenging than in sedimentary settings due to lack of continuous reflector beds and predominance of steeply dipping hard rock formations. The heterogeneities and “fractal” aspect of hard rock geologic environment produce considerable scattering of the seismic energy in the form of diffracted waves. These scatterers can be traced back to irregular and often “sharp-shaped” mineral bodies, magmatic intrusions, faults, and complex and heterogeneous shear zones. Due to the natural lack of reflectors and abundant number of diffractors, there are only a few case studies of diffraction imaging in hard rock environments. There are almost no theoretical models or field examples of diffraction imaging in prestack domain. We have filled this gap by applying a 3D prestack diffraction imaging method to image point diffractors. We calculated the diffractivity by computing the semblance of seismic data along diffraction traveltime curves in the prestack domain. The performance of the method is evaluated on a synthetic case and a field seismic data set collected over the Kevitsa mineral deposit in northern Finland. The high-resolution results obtained by the application of prestack diffraction imaging suggest that diffractivity is a robust attribute that can be used in addition to other seismic attributes for the interpretation of seismic data in hard rock environment.

Poststack impedance inversion considering the diffractive component of the wavefield

Geophysics ◽  
2020 ◽  
Vol 85 (1) ◽  
pp. R11-R28 ◽  
Author(s):  
Kun Xiang ◽  
Evgeny Landa
Keyword(s):  
Specular Reflection ◽  
Low Frequency ◽  
Velocity Model ◽  
Forward Modeling ◽  
Small Scale ◽  
Fracture Detection ◽  
Frequency Model ◽  
New Approach ◽  
Impedance Inversion ◽  
Diffraction Imaging

Seismic diffraction waveform energy contains important information about small-scale subsurface elements, and it is complementary to specular reflection information about subsurface properties. Diffraction imaging has been used for fault, pinchout, and fracture detection. Very little research, however, has been carried out taking diffraction into account in the impedance inversion. Usually, in the standard inversion scheme, the input is the migrated data and the assumption is taken that the diffraction energy is optimally focused. This assumption is true only for a perfectly known velocity model and accurate true amplitude migration algorithm, which are rare in practice. We have developed a new approach for impedance inversion, which takes into account diffractive components of the total wavefield and uses the unmigrated input data. Forward modeling, designed for impedance inversion, includes the classical specular reflection plus asymptotic diffraction modeling schemes. The output model is composed of impedance perturbation and the low-frequency model. The impedance perturbation is estimated using the Bayesian approach and remapped to the migrated domain by the kinematic ray tracing. Our method is demonstrated using synthetic and field data in comparison with the standard inversion. Results indicate that inversion with taking into account diffraction can improve the acoustic impedance prediction in the vicinity of local reflector discontinuities.

Footstep detection in urban seismic data with a convolutional neural network

2020 ◽  
Vol 39 (9) ◽  
pp. 654-660 ◽  
Author(s):  
Srikanth Jakkampudi ◽  
Junzhu Shen ◽  
Weichen Li ◽  
Ayush Dev ◽  
Tieyuan Zhu ◽  
...  
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Seismic Data ◽  
Earthquake Hazard ◽  
Small Scale ◽  
State University ◽  
Data Set ◽  
Near Surface ◽  
Privacy Concerns ◽  
Seismic Arrays

Seismic data for studying the near surface have historically been extremely sparse in cities, limiting our ability to understand small-scale processes, locate small-scale geohazards, and develop earthquake hazard microzonation at the scale of buildings. In recent years, distributed acoustic sensing (DAS) technology has enabled the use of existing underground telecommunications fibers as dense seismic arrays, requiring little manual labor or energy to maintain. At the Fiber-Optic foR Environmental SEnsEing array under Pennsylvania State University, we detected weak slow-moving signals in pedestrian-only areas of campus. These signals were clear in the 1 to 5 Hz range. We verified that they were caused by footsteps. As part of a broader scheme to remove and obscure these footsteps in the data, we developed a convolutional neural network to detect them automatically. We created a data set of more than 4000 windows of data labeled with or without footsteps for this development process. We describe improvements to the data input and architecture, leading to approximately 84% accuracy on the test data. Performance of the network was better for individual walkers and worse when there were multiple walkers. We believe the privacy concerns of individual walkers are likely to be highest priority. Community buy-in will be required for these technologies to be deployed at a larger scale. Hence, we should continue to proactively develop the tools to ensure city residents are comfortable with all geophysical data that may be acquired.

Recognizing tide- and wave-dominated compound deltaic clinothems in the rock record

Geology ◽  
2020 ◽  
Vol 48 (12) ◽  
pp. 1149-1153
Author(s):  
Yang Peng ◽  
Cornel Olariu ◽  
Ronald J. Steel
Keyword(s):  
Seismic Data ◽  
Three Dimensional ◽  
Gravity Flow ◽  
Small Scale ◽  
Sedimentary Record ◽  
Sediment Gravity Flow ◽  
Rock Record ◽  
Storm Wave ◽  
Tidal Deposits

Abstract Many modern deltas exhibit a compound geometry that consists of a shoreline clinoform and a larger subaqueous clinoform connected through a subaqueous platform. Despite the ubiquity of compound clinoforms in modern deltas, very few examples have been documented from the ancient sedimentary record. We present recognition criteria for shelf compound-clinoform systems in both tide- and wave-dominated deltas by integration of ancient and modern examples from multiple types of data. The compound clinothem can be identified by using a combination of: (1) the three-dimensional (3-D) configuration identified in bathymetric or seismic data, (2) bipartite stacked regressive units, consisting of a lower muddy coarsening-to-fining-upward (CUFU) or coarsening-upward (CU) unit (30–100 m thick) and an overlying sandier CU unit (5–30 m thick) (together they represent the subaqueous and shoreline clinoform pair), and (3) distinct facies described herein, though both types of delta have highly bioturbated mudstone and siltstone bottomsets. Tide-dominated deltas have muddy foresets with tidal scours containing tidal rhythmites or inclined heterolithic strata in the subaqueous clinothem overlain by river and tidal deposits of the shoreline clinothem. Wave-dominated deltas show mainly wave-enhanced sediment-gravity-flow (WSGF) beds and some thin hummocky/swaley cross-stratified (HCS/SCS) sandstones toward the top in the subaqueous muddy foreset, and upward-thickening HCS/SCS and trough/planar cross-bedded sandstones interbedded with siltstones in the shoreline clinothem. The subaqueous platform, which links the clinoform couplet, shows evidence of frequent tidal or wave reworking and redeposition. The platform in tide-dominated deltas is characterized by tide-generated heterolithic strata (e.g., bidirectional current-rippled and cross-stratified sandstones, spring and neap tidal bundles, tidal rhythmites) with occasional storm-wave–influenced strata. In contrast, the wave-dominated platform comprises small-scale swales with scours and mud clasts and some WSGF deposits. The proposed criteria can aid in the recognition of compound deltaic clinothems in other basins, particularly those with limited amounts and/or types of data.

Diffraction imaging of ground-penetrating radar data

Geophysics ◽  
2019 ◽  
Vol 84 (3) ◽  
pp. H1-H12 ◽  
Author(s):  
Hemin Yuan ◽  
Mahboubeh Montazeri ◽  
Majken C. Looms ◽  
Lars Nielsen
Keyword(s):  
Ground Penetrating Radar ◽  
Field Data ◽  
Velocity Structure ◽  
Velocity Estimation ◽  
Small Scale ◽  
Imaging Method ◽  
Surface Reflection ◽  
Diffraction Imaging ◽  
Saturated Media ◽  
Ground Penetrating

Diffractions caused by, e.g., faults, fractures, and small-scale heterogeneity localized near the surface are often used in ground-penetrating radar (GPR) reflection studies to constrain the subsurface velocity distribution using simple hyperbola fitting. Interference with reflected energy makes the identification of diffractions difficult. We have tailored and applied a diffraction imaging method to improve imaging for surface reflection GPR data. Based on a plane-wave destruction algorithm, the method can separate reflections from diffractions. Thereby, a better identification of diffractions facilitates an improved determination of GPR wave velocities and an optimized migration result. We determined the potential of this approach using synthetic and field data, and, for the field study, we also compare the estimated velocity structure with crosshole GPR results. For the field data example, we find that the velocity structure estimated using the diffraction-based process correlates well with results from crosshole GPR velocity estimation. Such improved velocity estimation may have important implications for using surface reflection GPR to map, e.g., porosity for fully saturated media or soil moisture changes in partially saturated media because these physical properties depend on the dielectric permittivity and thereby also the GPR wave velocity.

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.

Diffraction images and their attributes based on asymmetric summation: real data application

2020 ◽  
Author(s):  
Maxim I. Protasov ◽  
◽  
Vladimir A. Tcheverda ◽  
Valery V. Shilikov ◽  
◽  
...  
Keyword(s):  
Seismic Data ◽  
Real Data ◽  
Data Sets ◽  
Data Application ◽  
Diffraction Imaging

The paper deals with a 3D diffraction imaging with the subsequent diffraction attribute calculation. The imaging is based on an asymmetric summation of seismic data and provides three diffraction attributes: structural diffraction attribute, point diffraction attribute, an azimuth of structural diffraction. These attributes provide differentiating fractured and cavernous objects and to determine the fractures orientations. Approbation of the approach was provided on several real data sets.

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