scholarly journals Land-Streamer vs. Conventional Seismic Data for High-Resolution Near-Surface Surveys

2022 ◽  
Vol 12 (2) ◽  
pp. 584
Author(s):  
Sherif M. Hanafy
Keyword(s):  
High Resolution ◽  
Seismic Data ◽  
Acquisition Time ◽  
Data Set ◽  
Near Surface ◽  
Seismic Surveys ◽  
Time Frequency ◽  
Lower Accuracy ◽  
Recorded Data ◽  
Local Anomalies

Near-surface high-resolution seismic mapping is very important in many applications such as engineering and environmental. However, the conventional setup of the seismic technique requires planting geophones, connecting cables, and then collecting all equipment after completing the survey, which is time-consuming. In this study, we suggest using a land-streamer setup rather than the conventional setup for fast, accurate, and high-resolution near-surface seismic surveys. Only one field data set is recorded using both the conventional and the land-streamer setups. The recorded data is then compared in terms of time, frequency, wavenumber domains, and acquisition time. Following this, we compared the accuracy of the subsurface mapping of both setups using a synthetic example. The results show that the conventional setup can reach deeper depths but with lower accuracy, where the errors in imaging the local anomalies’ widths and thicknesses are 77% to 145% and 35% to 50%, respectively. The land-streamer setup provides accurate near-surface results but shallower penetration depth, here the errors in the anomalies’ widths and thicknesses are 5% to 12% and 10% to 20%, respectively.

Probing the subsurface karst features using time-frequency decomposition

2016 ◽  
Vol 4 (4) ◽  
pp. T533-T542 ◽  
Author(s):  
Yangkang Chen
Keyword(s):  
High Resolution ◽  
Seismic Data ◽  
Single Frequency ◽  
Frequency Interval ◽  
Data Set ◽  
Time Frequency ◽  
Frequency Decomposition ◽  
Inherent Frequency ◽  
Resolution Mapping ◽  
Resource Exploration

The high-resolution mapping of karst features is of great importance to hydrocarbon discovery and recovery in the resource exploration field. Currently, however, there are few effective methods specifically tailored for such a task. The 3D seismic data can reveal the existence of karsts to some extent, but a precise characterization cannot be obtained. I have developed an effective framework for accurately probing the subsurface karst features using a well-developed time-frequency decomposition algorithm. More specifically, I have introduced a frequency interval analysis approach for obtaining the best karsts detection result using an optimal frequency interval. A high-resolution time-frequency transform was preferred in the proposed framework to capture the inherent frequency components hidden behind the amplitude map. Although the single-frequency slice could not provide a reliable karst depiction result, the summation over the selected frequency interval could obtain a high-resolution and high-fidelity delineation of subsurface karsts. I used a publicly available 3D field seismic data set as an example to indicate the performance of the proposed method.

Regularization and datuming of seismic data by weighted, damped least squares

Geophysics ◽  
2006 ◽  
Vol 71 (5) ◽  
pp. U67-U76 ◽  
Author(s):  
Robert J. Ferguson
Keyword(s):  
Least Squares ◽  
Seismic Data ◽  
Synthetic Data ◽  
Real Data ◽  
Structural Data ◽  
Irregular Sampling ◽  
Data Set ◽  
Near Surface ◽  
Damped Least Squares ◽  
Wavefield Extrapolation

The possibility of improving regularization/datuming of seismic data is investigated by treating wavefield extrapolation as an inversion problem. Weighted, damped least squares is then used to produce the regularized/datumed wavefield. Regularization/datuming is extremely costly because of computing the Hessian, so an efficient approximation is introduced. Approximation is achieved by computing a limited number of diagonals in the operators involved. Real and synthetic data examples demonstrate the utility of this approach. For synthetic data, regularization/datuming is demonstrated for large extrapolation distances using a highly irregular recording array. Without approximation, regularization/datuming returns a regularized wavefield with reduced operator artifacts when compared to a nonregularizing method such as generalized phase shift plus interpolation (PSPI). Approximate regularization/datuming returns a regularized wavefield for approximately two orders of magnitude less in cost; but it is dip limited, though in a controllable way, compared to the full method. The Foothills structural data set, a freely available data set from the Rocky Mountains of Canada, demonstrates application to real data. The data have highly irregular sampling along the shot coordinate, and they suffer from significant near-surface effects. Approximate regularization/datuming returns common receiver data that are superior in appearance compared to conventional datuming.

Sparse spectral attributes to detect hydrocarbons: A case study from deep dolomite reservoirs

2019 ◽  
Vol 7 (3) ◽  
pp. T701-T711
Author(s):  
Jianhu Gao ◽  
Bingyang Liu ◽  
Shengjun Li ◽  
Hongqiu Wang
Keyword(s):  
Seismic Data ◽  
Signal To Noise Ratio ◽  
Low Frequency ◽  
Spectral Amplitude ◽  
Data Set ◽  
Frequency Spectra ◽  
Hydrocarbon Production ◽  
Hydrocarbon Detection ◽  
Time Frequency ◽  
Gas Bearing

Hydrocarbon detection is always one of the most critical sections in geophysical exploration, which plays an important role in subsequent hydrocarbon production. However, due to the low signal-to-noise ratio and weak reflection amplitude of deep seismic data, some conventional methods do not always provide favorable hydrocarbon prediction results. The interesting dolomite reservoirs in Central Sichuan are buried over an average depth of 4500 m, and the dolomite rocks have a low porosity below approximately 4%, which is measured by well-logging data. Furthermore, the dominant system of pores and fractures as well as strong heterogeneity along the lateral and vertical directions lead to some difficulties in describing the reservoir distribution. Spectral decomposition (SD) has become successful in illuminating subsurface features and can also be used to identify potential hydrocarbon reservoirs by detecting low-frequency shadows. However, the current applications for hydrocarbon detection always suffer from low resolution for thin reservoirs, probably due to the influence of the window function and without a prior constraint. To address this issue, we developed sparse inverse SD (SISD) based on the wavelet transform, which involves a sparse constraint of time-frequency spectra. We focus on investigating the applications of sparse spectral attributes derived from SISD to deep marine dolomite hydrocarbon detection from a 3D real seismic data set with an area of approximately [Formula: see text]. We predict and evaluate gas-bearing zones in two target reservoir segments by analyzing and comparing the spectral amplitude responses of relatively high- and low-frequency components. The predicted results indicate that most favorable gas-bearing areas are located near the northeast fault zone in the upper reservoir segment and at the relatively high structural positions in the lower reservoir segment, which are in good agreement with the gas-testing results of three wells in the study area.

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.

scholarly journals Fennec dust forecast intercomparison over the Sahara in June 2011

2016 ◽  
Vol 16 (11) ◽  
pp. 6977-6995 ◽  
Author(s):  
Jean-Pierre Chaboureau ◽  
Cyrille Flamant ◽  
Thibaut Dauhut ◽  
Cécile Kocha ◽  
Jean-Philippe Lafore ◽  
...  
Keyword(s):  
High Resolution ◽  
Surface Wind ◽  
Dust Emission ◽  
Airborne Lidar ◽  
Data Sets ◽  
Density Currents ◽  
Data Set ◽  
Near Surface ◽  
Western Sahara ◽  
Deep Well

Abstract. In the framework of the Fennec international programme, a field campaign was conducted in June 2011 over the western Sahara. It led to the first observational data set ever obtained that documents the dynamics, thermodynamics and composition of the Saharan atmospheric boundary layer (SABL) under the influence of the heat low. In support to the aircraft operation, four dust forecasts were run daily at low and high resolutions with convection-parameterizing and convection-permitting models, respectively. The unique airborne and ground-based data sets allowed the first ever intercomparison of dust forecasts over the western Sahara. At monthly scale, large aerosol optical depths (AODs) were forecast over the Sahara, a feature observed by satellite retrievals but with different magnitudes. The AOD intensity was correctly predicted by the high-resolution models, while it was underestimated by the low-resolution models. This was partly because of the generation of strong near-surface wind associated with thunderstorm-related density currents that could only be reproduced by models representing convection explicitly. Such models yield emissions mainly in the afternoon that dominate the total emission over the western fringes of the Adrar des Iforas and the Aïr Mountains in the high-resolution forecasts. Over the western Sahara, where the harmattan contributes up to 80 % of dust emission, all the models were successful in forecasting the deep well-mixed SABL. Some of them, however, missed the large near-surface dust concentration generated by density currents and low-level winds. This feature, observed repeatedly by the airborne lidar, was partly forecast by one high-resolution model only.

Fluid dynamics at the base of hydrate-bearing sediments at the Vestnesa Ridge inferred from 5 years of high-resolution 4D seismic surveying

2020 ◽  
Author(s):  
Malin Waage ◽  
Stefan Bünz ◽  
Kate Waghorn ◽  
Sunny Singhorha ◽  
Pavel Serov
Keyword(s):  
High Resolution ◽  
Gas Hydrate ◽  
Seismic Data ◽  
Time Lapse ◽  
Stability Zone ◽  
Seismic Surveys ◽  
Free Gas ◽  
4D Seismic ◽  
Hydrate Bearing Sediments ◽  
Hydrate Stability

<p>The transition from gas hydrate to gas-bearing sediments at the base of the hydrate stability zone (BHSZ) is commonly identified on seismic data as a bottom-simulating reflection (BSR). At this boundary, phase transitions driven by thermal effects, pressure alternations, and gas and water flux exist. Sedimentation, erosion, subsidence, uplift, variations in bottom water temperature or heat flow cause changes in marine gas hydrate stability leading to expansion or reduction of gas hydrate accumulations and associated free gas accumulations. Pressure build-up in gas accumulations trapped beneath the hydrate layer may eventually lead to fracturing of hydrate-bearing sediments that enables advection of fluids into the hydrate layer and potentially seabed seepage. Depletion of gas along zones of weakness creates hydraulic gradients in the free gas zone where gas is forced to migrate along the lower hydrate boundary towards these weakness zones. However, due to lack of “real time” data, the magnitude and timescales of processes at the gas hydrate – gas contact zone remains largely unknown. Here we show results of high resolution 4D seismic surveys at a prominent Arctic gas hydrate accumulation – Vestnesa ridge - capturing dynamics of the gas hydrate and free gas accumulations over 5 years. The 4D time-lapse seismic method has the potential to identify and monitor fluid movement in the subsurface over certain time intervals. Although conventional 4D seismic has a long history of application to monitor fluid changes in petroleum reservoirs, high-resolution seismic data (20-300 Hz) as a tool for 4D fluid monitoring of natural geological processes has been recently identified.<br><br>Our 4D data set consists of four high-resolution P-Cable 3D seismic surveys acquired between 2012 and 2017 in the eastern segment of Vestnesa Ridge. Vestnesa Ridge has an active fluid and gas hydrate system in a contourite drift setting near the Knipovich Ridge offshore W-Svalbard. Large gas flares, ~800 m tall rise from seafloor pockmarks (~700 m diameter) at the ridge axis. Beneath the pockmarks, gas chimneys pierce the hydrate stability zone, and a strong, widespread BSR occurs at depth of 160-180 m bsf. 4D seismic datasets reveal changes in subsurface fluid distribution near the BHSZ on Vestnesa Ridge. In particular, the amplitude along the BSR reflection appears to change across surveys. Disappearance of bright reflections suggest that gas-rich fluids have escaped the free gas zone and possibly migrated into the hydrate stability zone and contributed to a gas hydrate accumulation, or alternatively, migrated laterally along the BSR. Appearance of bright reflection might also indicate lateral migration, ongoing microbial or thermogenic gas supply or be related to other phase transitions. We document that faults, chimneys and lithology constrain these anomalies imposing yet another control on vertical and lateral gas migration and accumulation. These time-lapse differences suggest that (1) we can resolve fluid changes on a year-year timescale in this natural seepage system using high-resolution P-Cable data and (2) that fluids accumulate at, migrate to and migrate from the BHSZ over the same time scale.</p>

Near-surface full-waveform inversion in a transmission surface-consistent scheme

Geophysics ◽  
2020 ◽  
pp. 1-57
Author(s):  
Daniele Colombo ◽  
Ernesto Sandoval ◽  
Diego Rovetta ◽  
Apostolos Kontakis
Keyword(s):  
High Resolution ◽  
Seismic Data ◽  
Waveform Inversion ◽  
Surface Velocity ◽  
Full Waveform Inversion ◽  
Velocity Mapping ◽  
Signal To Noise ◽  
Near Surface ◽  
Velocity Modeling ◽  
Full Waveform

Land seismic velocity modeling is a difficult task largely related to the description of the near surface complexities. Full waveform inversion is the method of choice for achieving high-resolution velocity mapping but its application to land seismic data faces difficulties related to complex physics, unknown and spatially varying source signatures, and low signal-to-noise ratio in the data. Large parameter variations occur in the near surface at various scales causing severe kinematic and dynamic distortions of the recorded wavefield. Some of the parameters can be incorporated in the inversion model while others, due to sub-resolution dimensions or unmodeled physics, need to be corrected through data preconditioning; a topic not well described for land data full waveform inversion applications. We have developed novel algorithms and workflows for surface-consistent data preconditioning utilizing the transmitted portion of the wavefield, signal-to-noise enhancement by generation of CMP-based virtual super shot gathers, and robust 1.5D Laplace-Fourier full waveform inversion. Our surface-consistent scheme solves residual kinematic corrections and amplitude anomalies via scalar compensation or deconvolution of the near surface response. Signal-to-noise enhancement is obtained through the statistical evaluation of volumetric prestack responses at the CMP position, or virtual super (shot) gathers. These are inverted via a novel 1.5D acoustic Laplace-Fourier full waveform inversion scheme using the Helmholtz wave equation and Hankel domain forward modeling. Inversion is performed with nonlinear conjugate gradients. The method is applied to a complex structure-controlled wadi area exhibiting faults, dissolution, collapse, and subsidence where the high resolution FWI velocity modeling helps clarifying the geological interpretation. The developed algorithms and automated workflows provide an effective solution for massive full waveform inversion of land seismic data that can be embedded in typical near surface velocity analysis procedures.

Predictive removal of scattered noise

Geophysics ◽  
2006 ◽  
Vol 71 (2) ◽  
pp. V41-V49 ◽  
Author(s):  
Gérard C. Herman ◽  
Colin Perkins
Keyword(s):  
Mathematical Model ◽  
Wave Propagation ◽  
Surface Wave ◽  
Seismic Data ◽  
Coherent Noise ◽  
Data Set ◽  
Near Surface ◽  
Unique Data ◽  
Surface Wave Propagation ◽  
Petroleum Development

Land seismic data can be severely contaminated with coherent noise. We discuss a deterministic technique to predict and remove scattered coherent noise from land seismic data based on a mathematical model of near-surface wave propagation. We test the method on a unique data set recorded by Petroleum Development of Oman in the Qarn Alam area (with shots and receivers on the same grid), and we conclude that it effectively reduces scattered noise without smearing reflection energy.

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