Effects of near surface lithology on velocity modelling and time–depth relationships in the Cooper–Eromanga–Lake Eyre Basin

2018 ◽  
Vol 58 (1) ◽  
pp. 321
Author(s):  
Anna Manka ◽  
Glen Buick ◽  
Rob Menpes ◽  
Luke Gardiner ◽  
Cameron Jones ◽  
...  
Keyword(s):  
Seismic Velocity ◽  
Velocity Model ◽  
Petroleum Exploration ◽  
Success Rates ◽  
Near Surface ◽  
Depth Prediction ◽  
Western Flank ◽  
3D Velocity Model ◽  
The Time Domain ◽  
Eromanga Basin

Structural closures on the western flank of the Patchawarra Trough in the Cooper–Eromanga Basin are truly low relief; drilling opportunities regularly target hydrocarbon columns of similar magnitude to the uncertainty of depth prediction. Improving the accuracy and precision of depth prediction will reduce risk for drilling opportunities, and improve drilling success rates. A detailed study of the near surface geology (surface to ~500 m depth) of the western flank of the Patchawarra Trough has been undertaken to better understand the effect of observed geological variations of the near surface on depth prediction at deeper target levels. The stratigraphic interval investigated includes the top of the Eromanga Basin and the entire Lake Eyre Basin, which is sparingly studied and routinely overlooked in the statics and velocity modelling process. This study analysed recently acquired cased-hole sonic logs in conjunction with gamma logs and mudlog data to map out the observed geological variations, and construct a 3D velocity model of the near surface. Variations of layer thickness and seismic velocity were input into Monte Carlo simulations to investigate sensitivities of each formation on two-way travel time and depth prediction. This investigation has found that velocity variations of the Weathered Winton Formation, and thickness variations of the Namba Clastics have the greatest impact on imaging of structures at depth. Independently, these have the potential to completely conceal or create structures in the time domain. Continued efforts in improved understanding of the near surface will subsequently lead to enhanced imaging of structures, which can then be used in the mapping of structural closures in petroleum exploration and development.

scholarly journals Seismic velocity estimation: A deep recurrent neural-network approach

Geophysics ◽  
2019 ◽  
Vol 85 (1) ◽  
pp. U21-U29
Author(s):  
Gabriel Fabien-Ouellet ◽  
Rahul Sarkar
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Recurrent Neural Networks ◽  
Model Building ◽  
Seismic Velocity ◽  
Velocity Model ◽  
Velocity Estimation ◽  
Interval Velocity ◽  
Velocity Model Building ◽  
3D Velocity Model

Applying deep learning to 3D velocity model building remains a challenge due to the sheer volume of data required to train large-scale artificial neural networks. Moreover, little is known about what types of network architectures are appropriate for such a complex task. To ease the development of a deep-learning approach for seismic velocity estimation, we have evaluated a simplified surrogate problem — the estimation of the root-mean-square (rms) and interval velocity in time from common-midpoint gathers — for 1D layered velocity models. We have developed a deep neural network, whose design was inspired by the information flow found in semblance analysis. The network replaces semblance estimation by a representation built with a deep convolutional neural network, and then it performs velocity estimation automatically with recurrent neural networks. The network is trained with synthetic data to identify primary reflection events, rms velocity, and interval velocity. For a synthetic test set containing 1D layered models, we find that rms and interval velocity are accurately estimated, with an error of less than [Formula: see text] for the rms velocity. We apply the neural network to a real 2D marine survey and obtain accurate rms velocity predictions leading to a coherent stacked section, in addition to an estimation of the interval velocity that reproduces the main structures in the stacked section. Our results provide strong evidence that neural networks can estimate velocity from seismic data and that good performance can be achieved on real data even if the training is based on synthetics. The findings for the 1D problem suggest that deep convolutional encoders and recurrent neural networks are promising components of more complex networks that can perform 2D and 3D velocity model building.

scholarly journals An Investigation of Seismic Velocity Variation through a Tectonic Boundaries-Case Study in Central Iraq

2021 ◽  
pp. 2614-2626
Author(s):  
Ahmed S. AL-Banna ◽  
Hassan E. Al-Assady
Keyword(s):  
High Velocity ◽  
Seismic Velocity ◽  
Velocity Model ◽  
Seismic Inversion ◽  
Velocity Variation ◽  
Time Model ◽  
3D Velocity Model ◽  
Western Side ◽  
Well Data ◽  
Seismic Lines

      A 3D velocity model was created by using stacking velocity of 9 seismic lines and average velocity of 6 wells drilled in Iraq. The model was achieved by creating a time model to 25 surfaces with an interval time between each two successive surfaces of about 100 msec.  The summation time of all surfaces reached about 2400 msec, that was adopted according to West Kifl-1 well, which penetrated to a depth of 6000 m, representing the deepest well in the study area. The seismic lines and well data were converted to build a 3D cube time model and the velocity was spread on the model. The seismic inversion modeling of the elastic properties of the horizon and well data was applied to achieve a corrected velocity cube. Then, the velocity cube was converted to a time model and, finally, a corrected 3D depth model was obtained. This model shows that the western side of the study area, which is a part of the stable shelf, is characterized by relatively low thickness and high velocity layers. While the eastern side of the study area, which is a part of the Mesopotamian, is characterized by high thickness and low velocity of the Cretaceous succession. The Abu Jir fault is considered as a boundary between the stable and unstable shelves in Iraq, situated at the extreme west part of the study area. The area of relatively high velocity gradient is considered as the limit of the western side of the Mesopotamian basin. This area extends from Najaf-Karbala axis in the west to the Euphrates River in the east. It is found that the 3D stacking velocity model can be used to obtain good results concerning the tectonic boundary.  

scholarly journals Characterization of seasonal glacial seismicity from a single-station on-ice record at Holtedahlfonna, Svalbard

2019 ◽  
Vol 60 (79) ◽  
pp. 23-36 ◽  
Author(s):  
Andreas Köhler ◽  
Valerie Maupin ◽  
Christopher Nuth ◽  
Ward van Pelt
Keyword(s):  
Seismic Velocity ◽  
Temporal Distribution ◽  
Velocity Model ◽  
Ice Dynamics ◽  
Near Surface ◽  
Waveform Modeling ◽  
Single Station ◽  
Glacier Runoff ◽  
Fast Flow ◽  
Seismic Background

ABSTRACTGlacial seismicity provides important insights into glacier dynamic processes. We study the temporal distribution of cryogenic seismic signals (icequakes) at Holtedahlfonna, Svalbard, between April and August 2016 using a single three-component sensor. We investigate sources of observed icequakes using polarization analysis and waveform modeling. Processes responsible for five icequake categories are suggested, incorporating observations of previous studies into our interpretation. We infer that the most dominant icequake type is generated by surface crevasse opening through hydrofracturing. Secondly, bursts of high-frequency signals are presumably caused by repeated near-surface crevassing due to high strain rates during glacier fast-flow episodes. Furthermore, signals related to resonance in water-filled cracks, fracturing or settling events in dry firn or snow before the melt season, and processes at the glacier bed are observed. Amplitude of seismic background noise is clearly related to glacier runoff. We process ambient seismic noise to invert horizontal-to-vertical spectral ratios for a sub-surface seismic velocity model used to model icequake signals. Our study shows that a single seismic sensor provides useful information about seasonal ice dynamics in case deployment of a network is not feasible.

scholarly journals A P-wave velocity model of the upper crust of the Sannio region (Southern Apennines, Italy)

1998 ◽  
Vol 41 (4) ◽  
Author(s):  
G. Iannaccone ◽  
L. Improta ◽  
P. Capuano ◽  
A. Zollo ◽  
G. Biella ◽  
...  
Keyword(s):  
Wave Velocity ◽  
Seismic Velocity ◽  
Carbonate Platform ◽  
Velocity Model ◽  
P Wave ◽  
Seismic Velocities ◽  
Upper Crust ◽  
Near Surface ◽  
P Wave Velocity ◽  
Apulia Platform

This paper describes the results of a seismic refraction profile conducted in October 1992 in the Sannio region, Southern Italy, to obtain a detailed P-wave velocity model of the upper crust. The profile, 75 km long, extended parallel to the Apenninic chain in a region frequently damaged in historical time by strong earthquakes. Six shots were fired at five sites and recorded by a number of seismic stations ranging from 41 to 71 with a spacing of 1-2 km along the recording line. We used a two-dimensional raytracing technique to model travel times and amplitudes of first and second arrivals. The obtained P-wave velocity model has a shallow structure with strong lateral variations in the southern portion of the profile. Near surface sediments of the Tertiary age are characterized by seismic velocities in the 3.0-4.1 km/s range. In the northern part of the profile these deposits overlie a layer with a velocity of 4.8 km/s that has been interpreted as a Mesozoic sedimentary succession. A high velocity body, corresponding to the limestones of the Western Carbonate Platform with a velocity of 6 km/s, characterizes the southernmost part of the profile at shallow depths. At a depth of about 4 km the model becomes laterally homogeneous showing a continuous layer with a thickness in the 3-4 km range and a velocity of 6 km/s corresponding to the Meso-Cenozoic limestone succession of the Apulia Carbonate Platform. This platform appears to be layered, as indicated by an increase in seismic velocity from 6 to 6.7 km/s at depths in the 6-8 km range, that has been interpreted as a lithological transition from limestones to Triassic dolomites and anhydrites of the Burano formation. A lower P-wave velocity of about 5.0-5.5 km/s is hypothesized at the bottom of the Apulia Platform at depths ranging from 10 km down to 12.5 km; these low velocities could be related to Permo-Triassic siliciclastic deposits of the Verrucano sequence drilled at the bottom of the Apulia Platform in the Apulia Foreland.

Acquisition/Processing

2021 ◽  
Vol 40 (6) ◽  
pp. 460-463
Author(s):  
Lionel J. Woog ◽  
Anthony Vassiliou ◽  
Rodney Stromberg
Keyword(s):  
Model Building ◽  
Seismic Velocity ◽  
Signal To Noise Ratio ◽  
Velocity Model ◽  
High Signal ◽  
Processing Unit ◽  
High Quality ◽  
Near Surface ◽  
Velocity Model Building ◽  
Static Corrections

In seismic data processing, static corrections for near-surface velocities are derived from first-break picking. The quality of the static corrections is paramount to developing an accurate shallow velocity model, a model that in turn greatly impacts the subsequent seismic processing steps. Because even small errors in first-break picking can greatly impact the seismic velocity model building, it is necessary to pick high-quality traveltimes. Whereas various artificial intelligence-based methods have been proposed to automate the process for data with medium to high signal-to-noise ratio (S/N), these methods are not applicable to low-S/N data, which still require intensive labor from skilled operators. We successfully replace 160 hours of skilled human work with 10 hours of processing by a single NVIDIA Quadro P6000 graphical processing unit by reducing the number of human picks from the usual 5%–10% to 0.19% of available gathers. High-quality inferred picks are generated by convolutional neural network-based machine learning trained from the human picks.

An application of full-waveform inversion to land data using the pseudo-Hessian matrix

2016 ◽  
Vol 4 (4) ◽  
pp. T627-T635
Author(s):  
Yikang Zheng ◽  
Wei Zhang ◽  
Yibo Wang ◽  
Qingfeng Xue ◽  
Xu Chang
Keyword(s):  
Hessian Matrix ◽  
Waveform Inversion ◽  
Computational Cost ◽  
Velocity Model ◽  
Surface Velocity ◽  
Full Waveform Inversion ◽  
Data Set ◽  
Near Surface ◽  
Full Waveform ◽  
The Time Domain

Full-waveform inversion (FWI) is used to estimate the near-surface velocity field by minimizing the difference between synthetic and observed data iteratively. We apply this method to a data set collected on land. A multiscale strategy is used to overcome the local minima problem and the cycle-skipping phenomenon. Another obstacle in this application is the slow convergence rate. The inverse Hessian can enhance the poorly blurred gradient in FWI, but obtaining the full Hessian matrix needs intensive computation cost; thus, we have developed an efficient method aimed at the pseudo-Hessian in the time domain. The gradient in our FWI workflow is preconditioned with the obtained pseudo-Hessian and a synthetic example verifies its effectiveness in reducing computational cost. We then apply the workflow on the land data set, and the inverted velocity model is better resolved compared with traveltime tomography. The image and angle gathers we get from the inversion result indicate more detailed information of subsurface structures, which will contribute to the subsequent seismic interpretation.

Pitfalls in the seismic interpretation of fault shadow events — Vicksburg formation of south Texas

2015 ◽  
Vol 3 (1) ◽  
pp. SB17-SB22 ◽  
Author(s):  
Richard C. Bain
Keyword(s):  
Seismic Data ◽  
Seismic Velocity ◽  
Velocity Model ◽  
South Texas ◽  
Velocity Anomaly ◽  
3D Velocity Model ◽  
Production Wells ◽  
Hidalgo County ◽  
Velocity Changes ◽  
Depositional Units

Reliance on prestack time-migrated seismic data to define structural highs without incorporating all subsurface data and without taking into account the regional and local lateral depositional trends may result in dry holes or poorly positioned production wells due to local velocity changes, which are usually caused by some depositional or structural phenomenon. Tying check-shot control to depositional units may reveal those phenomena and permit assumptions to be made about velocities in areas beyond check-shot control points. We discovered a significant gas accumulation in an area surrounded by dry holes and marginal wells in the Vicksburg Formation in McAllen Ranch Field, Hidalgo County, Texas, by treating a seismic velocity anomaly as a geologic problem and by simple application of arithmetic and geometry to a 3D velocity model. Due to the effects of the anomaly, seismic data displayed in time gave no indication of the existence of a 325 ha (800 ac), 150 BCFG anticlinal structure. A subsurface model that accounted for the velocity anomaly was able to predict its extent and severity by readily identifiable thickness changes in the anomalous units. The resulting discovery yielded a sevenfold increase in field production within a two-year time span.

scholarly journals First arrival Q tomography based on an adjoint-state method

2020 ◽  
Author(s):  
Xinwei Huang ◽  
Zhenbo Guo ◽  
Huawei Zhou ◽  
Yubo Yue
Keyword(s):  
Time Domain ◽  
Spectral Ratio ◽  
Velocity Model ◽  
Similarity Coefficients ◽  
Tomographic Inversion ◽  
Near Surface ◽  
Adjoint State ◽  
Q Tomography ◽  
First Arrival ◽  
The Time Domain

Abstract Under the assumption of invariant ray path in a weakly dissipative (high quality factor Q) subsurface medium, a tomographic inversion approach composed of two cascading applications of first arrival traveltime and Q tomography is proposed for compensating amplitude loss caused by near-surface anomalies, such as unconsolidated soils or the overburden gas cloud. To improve the computational efficiency, these two related tomography methods were adopted with an adjoint-state technique. First, arrival traveltime tomography will be performed to provide an inverted velocity model as one of the inputs for the following first arrival Q tomography. Then, the synthetic first break generated by the inverted velocity model will be used as a stable guidance of accessing the scopes of first arrival waveforms in the time domain where the potential attenuated time information is contained. The attenuated time will be estimated through a logarithmic spectral ratio linear regression corresponding to frequency-dependent propagation responses of different wave types. All these estimated attenuated times will be applied with reference signals to generate synthetic attenuated seismic data in the time domain, and their discrepancies with real data will be evaluated using similarity coefficients. The ones with larger values will be selected as optimal attenuated time inputs for the following Q tomographic inversion. Examples of both synthetic and field data reveal the feasibility and potential of this method.

Velocity rays for heterogeneous anisotropic media: Theory and implementation

Geophysics ◽  
2006 ◽  
Vol 71 (5) ◽  
pp. T117-T127 ◽  
Author(s):  
Einar Iversen
Keyword(s):  
Model Updating ◽  
Seismic Velocity ◽  
Velocity Model ◽  
Media Theory ◽  
First Order ◽  
Velocity Models ◽  
Model Independent ◽  
Upper Level ◽  
The Time Domain ◽  
Seismic Images

The surface of equal two-way time referred to as the isochron is a fundamental concept in seismic imaging. The shape of an isochron depends on the source and receiver locations, on the wave type, and on the parameters constituting the seismic velocity model. A perturbation of a parameter of the velocity model forces the isochron points to move along trajectories called velocity rays, with the selected model parameter as the variable along the rays. Based on earlier work describing first-order approximations to velocity rays, I develop a general theory for velocity rays valid for 3D heterogeneous and anisotropic velocity models. By this theory, velocity rays can be obtained in a way similar to the way conventional rays are computed by numeric integration of a system of ordinary differential equations (ODEs). The process is organized with ODE solvers on two levels, where the upper level is model independent. The lower level includes conventional one-way kinematic and dynamic tracing of source and receiver rays, as well as calculation of ray perturbation quantities. Accurate velocity rays are expected to be useful for perturbation of reflectors mapped from the time domain to the depth domain, for remigration of seismic images in the depth domain, and for velocity model updating.

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